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खण्ड ‘A’ SECTION ‘ A A AAA
1.(a) मान लीजिए R R RRR तत्समक अवयव सहित एक पूर्णांकीय प्रांत है । दर्शाइए कि R [ x ] R [ x ] R[x]R[x]R[x] में कोई भी एवक R R RRR में एक एकक है।
Let R R RRR be an integral domain with unit element. Show that any unit in R [ x ] R [ x ] R[x]R[x]R[x] is a unit in R R RRR.
Answer:

Introduction

In this problem, we are dealing with the concept of units in the context of integral domains and polynomial rings. Specifically, we are given an integral domain R R RRR with a unit element and are asked to prove that any unit in R [ x ] R [ x ] R[x]R[x]R[x] (the polynomial ring over R R RRR) must also be a unit in R R RRR.

Definitions

  • Integral Domain: An integral domain is a commutative ring R R RRR with a multiplicative identity (unit element) such that the product of any two non-zero elements is non-zero.
  • Unit in a Ring: An element a a aaa in a ring R R RRR is called a unit if there exists an element b b bbb in R R RRR such that a b = b a = 1 a b = b a = 1 a*b=b*a=1a \cdot b = b \cdot a = 1ab=ba=1, where 1 1 111 is the multiplicative identity in R R RRR.
  • Polynomial Ring R [ x ] R [ x ] R[x]R[x]R[x]: The set of all polynomials with coefficients in R R RRR.

Work/Calculations

Step 1: Assume f ( x ) f ( x ) f(x)f(x)f(x) is a Unit in R [ x ] R [ x ] R[x]R[x]R[x]

Let’s assume that f ( x ) f ( x ) f(x)f(x)f(x) is a unit in R [ x ] R [ x ] R[x]R[x]R[x]. This means there exists a polynomial g ( x ) g ( x ) g(x)g(x)g(x) in R [ x ] R [ x ] R[x]R[x]R[x] such that:
f ( x ) g ( x ) = 1 f ( x ) g ( x ) = 1 f(x)*g(x)=1f(x) \cdot g(x) = 1f(x)g(x)=1

Step 2: Examine the Degrees of f ( x ) f ( x ) f(x)f(x)f(x) and g ( x ) g ( x ) g(x)g(x)g(x)

The degree of the polynomial f ( x ) g ( x ) f ( x ) g ( x ) f(x)*g(x)f(x) \cdot g(x)f(x)g(x) is the sum of the degrees of f ( x ) f ( x ) f(x)f(x)f(x) and g ( x ) g ( x ) g(x)g(x)g(x). Since f ( x ) g ( x ) = 1 f ( x ) g ( x ) = 1 f(x)*g(x)=1f(x) \cdot g(x) = 1f(x)g(x)=1, a constant polynomial, the degree of f ( x ) g ( x ) f ( x ) g ( x ) f(x)*g(x)f(x) \cdot g(x)f(x)g(x) is 0.
Let deg ( f ( x ) ) = m deg ( f ( x ) ) = m “deg”(f(x))=m\text{deg}(f(x)) = mdeg(f(x))=m and deg ( g ( x ) ) = n deg ( g ( x ) ) = n “deg”(g(x))=n\text{deg}(g(x)) = ndeg(g(x))=n.
deg ( f ( x ) g ( x ) ) = m + n = 0 deg ( f ( x ) g ( x ) ) = m + n = 0 “deg”(f(x)*g(x))=m+n=0\text{deg}(f(x) \cdot g(x)) = m + n = 0deg(f(x)g(x))=m+n=0

Step 3: Conclude m = n = 0 m = n = 0 m=n=0m = n = 0m=n=0

Since m + n = 0 m + n = 0 m+n=0m + n = 0m+n=0 and m , n 0 m , n 0 m,n >= 0m, n \geq 0m,n0, it must be the case that m = n = 0 m = n = 0 m=n=0m = n = 0m=n=0.

Step 4: Show f ( x ) f ( x ) f(x)f(x)f(x) is a Unit in R R RRR

Since m = 0 m = 0 m=0m = 0m=0, f ( x ) f ( x ) f(x)f(x)f(x) is a constant polynomial, say f ( x ) = a f ( x ) = a f(x)=af(x) = af(x)=a, where a a aaa is in R R RRR. Similarly, g ( x ) = b g ( x ) = b g(x)=bg(x) = bg(x)=b, where b b bbb is in R R RRR.
From f ( x ) g ( x ) = 1 f ( x ) g ( x ) = 1 f(x)*g(x)=1f(x) \cdot g(x) = 1f(x)g(x)=1, we have a b = 1 a b = 1 a*b=1a \cdot b = 1ab=1.
This shows that a a aaa is a unit in R R RRR, as a b = 1 a b = 1 a*b=1a \cdot b = 1ab=1.

Conclusion

We have shown that if f ( x ) f ( x ) f(x)f(x)f(x) is a unit in R [ x ] R [ x ] R[x]R[x]R[x], then it must be a constant polynomial and also a unit in R R RRR. Therefore, any unit in R [ x ] R [ x ] R[x]R[x]R[x] is a unit in R R RRR.
1.(b) असमिका : π 2 9 < π 6 π 2 x sin x d x < 2 π 2 9 π 2 9 < π 6 π 2 x sin x d x < 2 π 2 9 (pi^(2))/(9) < int_((pi)/(6))^((pi)/(2))(x)/(sin x)dx < (2pi^(2))/(9)\frac{\pi^2}{9}<\int_{\frac{\pi}{6}}^{\frac{\pi}{2}} \frac{x}{\sin x} d x<\frac{2 \pi^2}{9}π29<π6π2xsinxdx<2π29 को सिद्ध कीजिए ।
Prove the inequality : π 2 9 < π 6 π 2 x sin x d x < 2 π 2 9 π 2 9 < π 6 π 2 x sin x d x < 2 π 2 9 (pi^(2))/(9) < int_((pi)/(6))^((pi)/(2))(x)/(sin x)dx < (2pi^(2))/(9)\frac{\pi^2}{9}<\int_{\frac{\pi}{6}}^{\frac{\pi}{2}} \frac{x}{\sin x} d x<\frac{2 \pi^2}{9}π29<π6π2xsinxdx<2π29,
Answer:
Introduction:
We have the inequality:
1 1 sin x 2 for all x [ π 6 , π 2 ] . 1 1 sin x 2  for all  x π 6 , π 2 1 <= (1)/(sin x) <= 2″ for all “x in[(pi)/(6),(pi)/(2)]”. “1 \leq \frac{1}{\sin x} \leq 2 \text { for all } x \in\left[\frac{\pi}{6}, \frac{\pi}{2}\right] \text {. }11sinx2 for all x[π6,π2]
Multiply by x x xxx
Therefore, it follows that:
x x sin x 2 x for all x [ π 6 , π 2 ] x x sin x 2 x  for all  x π 6 , π 2 x <= (x)/(sin x) <= 2x” for all “x in[(pi)/(6),(pi)/(2)]x \leq \frac{x}{\sin x} \leq 2x \text { for all } x \in\left[\frac{\pi}{6}, \frac{\pi}{2}\right]xxsinx2x for all x[π6,π2]
Step 1: Defining f ( x ) f ( x ) f(x)f(x)f(x):
Let’s define a function f ( x ) = x sin x f ( x ) = x sin x f(x)=(x)/(sin x)f(x)=\frac{x}{\sin x}f(x)=xsinx.
Step 2: Defining ϕ ( x ) ϕ ( x ) phi(x)\phi(x)ϕ(x) and ψ ( x ) ψ ( x ) psi(x)\psi(x)ψ(x):
We define two more functions as follows:
ϕ ( x ) = x ψ ( x ) = 2 x , x [ π / 6 , π / 2 ] ϕ ( x ) = x ψ ( x ) = 2 x , x [ π / 6 , π / 2 ] {:[phi(x)=x],[psi(x)=2x”,”quad x in[pi//6″,”pi//2]]:}\begin{aligned} & \phi(x)=x \\ & \psi(x)=2x, \quad x \in[\pi / 6, \pi / 2] \end{aligned}ϕ(x)=xψ(x)=2x,x[π/6,π/2]
Step 3: Boundedness and Integrability:
Both f f fff and ϕ ϕ phi\phiϕ are bounded and integrable on [ π / 6 , π / 2 ] [ π / 6 , π / 2 ] [pi//6,pi//2][\pi / 6, \pi / 2][π/6,π/2], and f ( x ) ϕ ( x ) f ( x ) ϕ ( x ) f(x) >= phi(x)f(x) \geq \phi(x)f(x)ϕ(x) for all x [ π / 6 , π / 2 ] x [ π / 6 , π / 2 ] x in[pi//6,pi//2]x \in[\pi / 6, \pi / 2]x[π/6,π/2].
Step 4: Continuity at π / 3 π / 3 pi//3\pi / 3π/3:
Furthermore, f f fff and ϕ ϕ phi\phiϕ are both continuous at x = π / 3 x = π / 3 x=pi//3x = \pi / 3x=π/3, and f ( π / 3 ) > ϕ ( π / 3 ) f ( π / 3 ) > ϕ ( π / 3 ) f(pi//3) > phi(pi//3)f(\pi / 3)>\phi(\pi / 3)f(π/3)>ϕ(π/3).
Step 5: Integral Comparison:
Hence, we can compare the integrals:
π / 6 π / 2 f ( x ) d x > π / 6 π / 2 ϕ ( x ) d x = π / 6 π / 2 x d x = π 2 9 π / 6 π / 2 f ( x ) d x > π / 6 π / 2 ϕ ( x ) d x = π / 6 π / 2 x d x = π 2 9 {:[int_(pi//6)^(pi//2)f(x)dx > int_(pi//6)^(pi//2)phi(x)dx],[=int_(pi//6)^(pi//2)xdx],[=(pi^(2))/(9)]:}\begin{aligned} & \int_{\pi / 6}^{\pi / 2} f(x) d x>\int_{\pi / 6}^{\pi / 2} \phi(x) d x \\ & =\int_{\pi / 6}^{\pi / 2} x d x \\ & =\frac{\pi^2}{9} \end{aligned}π/6π/2f(x)dx>π/6π/2ϕ(x)dx=π/6π/2xdx=π29
Step 6: Comparing with ψ ψ psi\psiψ:
Similarly, we have:
π / 6 π / 2 f ( x ) d x < π / 6 π / 2 ψ ( x ) d x = 2 π / 6 π / 2 x d x = 2 π 2 9 π / 6 π / 2 f ( x ) d x < π / 6 π / 2 ψ ( x ) d x = 2 π / 6 π / 2 x d x = 2 π 2 9 {:[int_(pi//6)^(pi//2)f(x)dx < int_(pi//6)^(pi//2)psi(x)dx],[=2int_(pi//6)^(pi//2)xdx],[=(2pi^(2))/(9)]:}\begin{aligned} \int_{\pi / 6}^{\pi / 2} f(x) d x & <\int_{\pi / 6}^{\pi / 2} \psi(x) d x \\ & =2 \int_{\pi / 6}^{\pi / 2} x d x \\ & =\frac{2 \pi^2}{9} \end{aligned}π/6π/2f(x)dx<π/6π/2ψ(x)dx=2π/6π/2xdx=2π29
Conclusion:
Consequently, we can conclude that:
π 2 9 < π / 6 π / 2 x sin x d x < 2 π 2 9 π 2 9 < π / 6 π / 2 x sin x d x < 2 π 2 9 (pi^(2))/(9) < int_(pi//6)^(pi//2)(x)/(sin x)dx < (2pi^(2))/(9)\frac{\pi^2}{9}<\int_{\pi / 6}^{\pi / 2} \frac{x}{\sin x} d x<\frac{2 \pi^2}{9}π29<π/6π/2xsinxdx<2π29
1.(c) सिद्ध कीजिए कि फलन : u ( x , y ) = ( x 1 ) 3 3 x y 2 + 3 y 2 u ( x , y ) = ( x 1 ) 3 3 x y 2 + 3 y 2 u(x,y)=(x-1)^(3)-3xy^(2)+3y^(2)u(x, y)=(x-1)^3-3 x y^2+3 y^2u(x,y)=(x1)33xy2+3y2 प्रसंवादी है और इसके प्रसंबादी संयुग्मी को और संगत विश्लेषिक फलन f ( z ) f ( z ) f(z)f(z)f(z) को, z z zzz के ल्प में ज्ञात कीजिए ।
Prove that the function: u ( x , y ) = ( x 1 ) 3 3 x y 2 + 3 y 2 u ( x , y ) = ( x 1 ) 3 3 x y 2 + 3 y 2 u(x,y)=(x-1)^(3)-3xy^(2)+3y^(2)u(x, y)=(x-1)^3-3 x y^2+3 y^2u(x,y)=(x1)33xy2+3y2 is harmonic and find its harmonic conjugate and the corresponding analytic function f ( z ) f ( z ) f(z)f(z)f(z) in terms of z z zzz.
Answer:
Introduction:
In this problem, we are tasked with proving that the function u ( x , y ) = ( x 1 ) 3 3 x y 2 + 3 y 2 u ( x , y ) = ( x 1 ) 3 3 x y 2 + 3 y 2 u(x,y)=(x-1)^(3)-3xy^(2)+3y^(2)u(x, y) = (x-1)^3 – 3xy^2 + 3y^2u(x,y)=(x1)33xy2+3y2 is harmonic. Furthermore, we need to find its harmonic conjugate and express the corresponding analytic function f ( z ) f ( z ) f(z)f(z)f(z) in terms of z z zzz.
Step 1: Verification of Harmonicity:
To begin, we need to determine whether the given function u ( x , y ) u ( x , y ) u(x,y)u(x, y)u(x,y) is harmonic. We calculate its partial derivatives with respect to x x xxx and y y yyy:
u x = 3 ( x 1 ) 2 3 y 2 2 u x 2 = 6 ( x 1 ) u y = 6 x y + 6 y 2 u y 2 = 6 ( x 1 ) u x = 3 ( x 1 ) 2 3 y 2 2 u x 2 = 6 ( x 1 ) u y = 6 x y + 6 y 2 u y 2 = 6 ( x 1 ) {:[(del u)/(del x)=3(x-1)^(2)-3y^(2)],[(del^(2)u)/(delx^(2))=6(x-1)],[(del u)/(del y)=-6xy+6y],[(del^(2)u)/(dely^(2))=-6(x-1)]:}\begin{align*} \frac{\partial u}{\partial x} &= 3(x-1)^2 – 3y^2 \\ \frac{\partial^2 u}{\partial x^2} &= 6(x-1) \\ \frac{\partial u}{\partial y} &= -6xy + 6y \\ \frac{\partial^2 u}{\partial y^2} &= -6(x-1) \end{align*}ux=3(x1)23y22ux2=6(x1)uy=6xy+6y2uy2=6(x1)
We notice that 2 u x 2 + 2 u y 2 = 6 ( x 1 ) 6 ( x 1 ) = 0 2 u x 2 + 2 u y 2 = 6 ( x 1 ) 6 ( x 1 ) = 0 (del^(2)u)/(delx^(2))+(del^(2)u)/(dely^(2))=6(x-1)-6(x-1)=0\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2} = 6(x-1) – 6(x-1) = 02ux2+2uy2=6(x1)6(x1)=0. This confirms that u u uuu is a harmonic function.
Step 2: Harmonic Conjugate and Analytic Function f ( z ) f ( z ) f(z)f(z)f(z):
Next, we aim to find the harmonic conjugate of u u uuu and express the corresponding analytic function f ( z ) f ( z ) f(z)f(z)f(z) in terms of z z zzz.
We recognize that u ( x , y ) u ( x , y ) u(x,y)u(x, y)u(x,y) is the real part of the analytic function f ( z ) f ( z ) f(z)f(z)f(z), where f ( z ) = u ( x , y ) + i v ( x , y ) f ( z ) = u ( x , y ) + i v ( x , y ) f(z)=u(x,y)+iv(x,y)f(z) = u(x, y) + iv(x, y)f(z)=u(x,y)+iv(x,y).
We utilize the Cauchy-Riemann equations, which state that u x = v y u x = v y u_(x)=v_(y)u_x = v_yux=vy and u y = v x u y = v x u_(y)=-v_(x)u_y = -v_xuy=vx, to determine the imaginary part v ( x , y ) v ( x , y ) v(x,y)v(x, y)v(x,y) of f ( z ) f ( z ) f(z)f(z)f(z):
v x = u y = u y = ( 6 x y + 6 y ) = 6 x y 6 y v ( x , y ) = ( 6 x y 6 y ) d y = 3 x 2 y 6 x y + f 1 ( y ) v x = u y = u y = ( 6 x y + 6 y ) = 6 x y 6 y v ( x , y ) = ( 6 x y 6 y ) d y = 3 x 2 y 6 x y + f 1 ( y ) {:[v_(x)=-u_(y)=-(del u)/(del y)=-(-6xy+6y)=6xy-6y],[v(x”,”y)=int(6xy-6y)dy=3x^(2)y-6xy+f_(1)(y)]:}\begin{align*} v_x &= -u_y = -\frac{\partial u}{\partial y} = -(-6xy + 6y) = 6xy – 6y \\ v(x, y) &= \int (6xy – 6y) \, dy = 3x^2y – 6xy + f_1(y) \end{align*}vx=uy=uy=(6xy+6y)=6xy6yv(x,y)=(6xy6y)dy=3x2y6xy+f1(y)
Here, f 1 ( y ) f 1 ( y ) f_(1)(y)f_1(y)f1(y) is an arbitrary function of y y yyy.
Now, we differentiate v ( x , y ) v ( x , y ) v(x,y)v(x, y)v(x,y) with respect to y y yyy to find f 1 ( y ) f 1 ( y ) f_(1)(y)f_1(y)f1(y):
v y = 3 x 2 6 x + f 1 ( y ) u x = 3 x 2 6 x + f 1 ( y ) (by the Cauchy-Riemann equations) 3 ( x 1 ) 2 3 y 2 = 3 x 2 6 x + f 1 ( y ) f 1 ( y ) = 3 3 y 2 f 1 ( y ) = 3 y y 3 + C (where C is an arbitrary constant) v y = 3 x 2 6 x + f 1 ( y ) u x = 3 x 2 6 x + f 1 ( y ) (by the Cauchy-Riemann equations) 3 ( x 1 ) 2 3 y 2 = 3 x 2 6 x + f 1 ( y ) f 1 ( y ) = 3 3 y 2 f 1 ( y ) = 3 y y 3 + C (where  C  is an arbitrary constant) {:[(del v)/(del y)=3x^(2)-6x+f_(1)^(‘)(y)],[=>(del u)/(del x)=3x^(2)-6x+f_(1)^(‘)(y)quad(by the Cauchy-Riemann equations)],[3(x-1)^(2)-3y^(2)=3x^(2)-6x+f_(1)^(‘)(y)],[f_(1)^(‘)(y)=3-3y^(2)],[f_(1)(y)=3y-y^(3)+C quad(where C” is an arbitrary constant)”]:}\begin{align*} \frac{\partial v}{\partial y} &= 3x^2 – 6x + f_1′(y) \\ \Rightarrow \frac{\partial u}{\partial x} &= 3x^2 – 6x + f_1′(y) \quad \text{(by the Cauchy-Riemann equations)} \\ 3(x-1)^2 – 3y^2 &= 3x^2 – 6x + f_1′(y) \\ f_1′(y) &= 3 – 3y^2 \\ f_1(y) &= 3y – y^3 + C \quad \text{(where \(C\) is an arbitrary constant)} \end{align*}vy=3x26x+f1(y)ux=3x26x+f1(y)(by the Cauchy-Riemann equations)3(x1)23y2=3x26x+f1(y)f1(y)=33y2f1(y)=3yy3+C(where C is an arbitrary constant)
Thus, the imaginary part v ( x , y ) v ( x , y ) v(x,y)v(x, y)v(x,y) is given by v ( x , y ) = 3 x 2 y 6 x y + 3 y y 3 + C v ( x , y ) = 3 x 2 y 6 x y + 3 y y 3 + C v(x,y)=3x^(2)y-6xy+3y-y^(3)+Cv(x, y) = 3x^2y – 6xy + 3y – y^3 + Cv(x,y)=3x2y6xy+3yy3+C.
Step 3: Expressing f ( z ) f ( z ) f(z)f(z)f(z) in terms of z z zzz:
f ( z ) = ϕ 1 ( z , 0 ) i ϕ 2 ( z , 0 ) f ( z ) = 3 ( z 1 ) 2 3 ( 0 ) 2 i [ 6 z ( 0 ) + 6 ( 0 ) ] f ( z ) = 3 ( z 1 ) 2 f ( z ) = ( z 1 ) 3 + C f ( z ) = ϕ 1 ( z , 0 ) i ϕ 2 ( z , 0 ) f ( z ) = 3 ( z 1 ) 2 3 ( 0 ) 2 i [ 6 z ( 0 ) + 6 ( 0 ) ] f ( z ) = 3 ( z 1 ) 2 f ( z ) = ( z 1 ) 3 + C {:[f^(‘)(z)=phi_(1)(z”,”0)-iphi_(2)(z”,”0)],[f^(‘)(z)=3(z-1)^(2)-3(0)^(2)-i[6*z*(0)+6(0)]],[f^(‘)(z)=3(z-1)^(2)],[:.quadf(z)=(z-1)^(3)+C]:}\begin{aligned} f^{\prime}(z) & =\phi_1(z, 0)-i \phi_2(z, 0) \\ f^{\prime}(z) & =3(z-1)^2-3(0)^2-i[6 \cdot z \cdot(0)+6(0)] \\ f^{\prime}(z) & =3(z-1)^2 \\ \therefore \quad & f(z)=(z-1)^3+C \end{aligned}f(z)=ϕ1(z,0)iϕ2(z,0)f(z)=3(z1)23(0)2i[6z(0)+6(0)]f(z)=3(z1)2f(z)=(z1)3+C
Finally, we express the analytic function f ( z ) f ( z ) f(z)f(z)f(z) in terms of z z zzz. We use the result that f ( z ) = ( z 1 ) 3 + C f ( z ) = ( z 1 ) 3 + C f(z)=(z-1)^(3)+Cf(z) = (z-1)^3 + Cf(z)=(z1)3+C
Conclusion:
In conclusion, the given function u ( x , y ) u ( x , y ) u(x,y)u(x, y)u(x,y) is confirmed to be harmonic. We have found its harmonic conjugate, v ( x , y ) v ( x , y ) v(x,y)v(x, y)v(x,y), and expressed the corresponding analytic function f ( z ) f ( z ) f(z)f(z)f(z) as f ( z ) = ( z 1 ) 3 + C f ( z ) = ( z 1 ) 3 + C f(z)=(z-1)^(3)+Cf(z) = (z-1)^3 + Cf(z)=(z1)3+C, where C C CCC is an arbitrary constant.
1.(d) p ( > 0 ) p ( > 0 ) p( > 0)p(>0)p(>0) का वह परास ज्ञात कीजिए, जिसके लिए श्रेणी:
1 ( 1 + a ) p 1 ( 2 + a ) p + 1 ( 3 + a ) p , a > 0 1 ( 1 + a ) p 1 ( 2 + a ) p + 1 ( 3 + a ) p , a > 0 (1)/((1+a)^(p))-(1)/((2+a)^(p))+(1)/((3+a)^(p))-dots,a > 0\frac{1}{(1+a)^p}-\frac{1}{(2+a)^p}+\frac{1}{(3+a)^p}-\ldots, a>01(1+a)p1(2+a)p+1(3+a)p,a>0
(i) निरपेक्षतः अभिसारी तथा (ii) सापेक्ष अभिसारी है ।
Find the range of p ( > 0 ) p ( > 0 ) p( > 0)p(>0)p(>0) for which the series: 1 ( 1 + a ) p 1 ( 2 + a ) p + 1 ( 3 + a ) p , a > 0 1 ( 1 + a ) p 1 ( 2 + a ) p + 1 ( 3 + a ) p , a > 0 (1)/((1+a)^(p))-(1)/((2+a)^(p))+(1)/((3+a)^(p))-dots,a > 0\frac{1}{(1+a)^p}-\frac{1}{(2+a)^p}+\frac{1}{(3+a)^p}-\ldots, a>01(1+a)p1(2+a)p+1(3+a)p,a>0, is
(i) absolutely convergent and (ii) conditionally convergent.
Answer:
Introduction:
We are tasked with finding the range of p ( > 0 ) p ( > 0 ) p( > 0)p(>0)p(>0) for which the series given by:
1 ( 1 + a ) p 1 ( 2 + a ) p + 1 ( 3 + a ) p , where a > 0 1 ( 1 + a ) p 1 ( 2 + a ) p + 1 ( 3 + a ) p ,  where  a > 0 (1)/((1+a)^(p))-(1)/((2+a)^(p))+(1)/((3+a)^(p))-dots,” where “a > 0\frac{1}{(1+a)^p}-\frac{1}{(2+a)^p}+\frac{1}{(3+a)^p}-\ldots, \text{ where } a>01(1+a)p1(2+a)p+1(3+a)p, where a>0
converges absolutely and conditionally. To do this, we will use various convergence tests and mathematical techniques.
Step 1: Definition of v n v n v_(n)v_nvn and ω n ω n omega _(n)\omega_nωn:
Let u n u n sumu_(n)\sum u_nun be the given series, and define a new series v n v n v_(n)v_nvn as follows:
v n = 1 ( n + a ) p v n = 1 ( n + a ) p v_(n)=(1)/((n+a)^(p))v_n = \frac{1}{(n+a)^p}vn=1(n+a)p
Additionally, define ω n ω n omega _(n)\omega_nωn as:
ω n = 1 n p ω n = 1 n p omega _(n)=(1)/(n^(p))\omega_n = \frac{1}{n^p}ωn=1np
Step 2: Checking Convergence of v n v n sumv_(n)\sum v_nvn for p > 1 p > 1 p > 1p>1p>1:
By comparing v n v n v_(n)v_nvn with ω n ω n omega _(n)\omega_nωn, we find that:
lim n v n ω n = 1 lim n v n ω n = 1 lim_(n rarr oo)(v_(n))/(omega _(n))=1\lim_{n\to\infty} \frac{v_n}{\omega_n} = 1limnvnωn=1
Using the comparison test, we conclude that v n v n sumv_(n)\sum v_nvn is convergent when p > 1 p > 1 p > 1p>1p>1.
Step 3: Case 1 – Absolute Convergence for P > 1 P > 1 P > 1P > 1P>1:
u n u n sumu_(n)\sum u_nun is an alternating series and | u n | u n sum|u_(n)|\sum\left|u_n\right||un| is convergent. Therefore, u n u n sumu_(n)\sum u_nun is absolutely convergent.
Step 4: Case 2 – Conditional Convergence for 0 < p 1 0 < p 1 0 < p <= 10<p \leq 10<p1:
When 0 < p 1 0 < p 1 0 < p <= 10<p \leq 10<p1, the sequence { v n } { v n } {v_(n)}\{v_n\}{vn} is a monotone decreasing sequence of positive real numbers with lim v n = 0 lim v n = 0 limv_(n)=0\lim v_n = 0limvn=0. By Leibniz’s test, ( 1 ) n + 1 v n ( 1 ) n + 1 v n sum(-1)^(n+1)v_(n)\sum (-1)^{n+1} v_n(1)n+1vn, which is equivalent to u n u n sumu_(n)\sum u_nun, is convergent.
Since | u n | u n sum|u_(n)|\sum\left|u_n\right||un| is divergent in this case, u n u n sumu_(n)\sum u_nun is conditionally convergent.
Step 5: Decomposition of u n u n u_(n)u_nun into P n P n P_(n)P_nPn and q n q n q_(n)q_nqn:
Let Σ u n Σ u n Sigmau_(n)\Sigma u_nΣun be a series of positive real numbers. We can decompose it into two new series:
P n = { u n if u n > 0 0 if u n 0 q n = { 0 if u n 0 u n if u n < 0 P n = u n if  u n > 0 0 if  u n 0 q n = 0 if  u n 0 u n if  u n < 0 {:[P_(n)={[u_(n),”if “u_(n) > 0],[0,”if “u_(n) <= 0]:}],[q_(n)={[0,”if “u_(n) >= 0],[u_(n),”if “u_(n) < 0]:}]:}\begin{align*} P_n &= \begin{cases} u_n & \text{if } u_n > 0 \\ 0 & \text{if } u_n \leq 0 \end{cases} \\ q_n &= \begin{cases} 0 & \text{if } u_n \geq 0 \\ u_n & \text{if } u_n < 0 \end{cases} \end{align*}Pn={unif un>00if un0qn={0if un0unif un<0
Conclusion:
In summary, the given series u n u n sumu_(n)\sum u_nun is absolutely convergent when P > 1 P > 1 P > 1P > 1P>1, and it is conditionally convergent when 0 < p 1 0 < p 1 0 < p <= 10<p \leq 10<p1. This analysis provides a comprehensive understanding of the convergence behavior of the series for different values of p p ppp in the specified range.
1.(e) एक कृषि फर्म के पास 180 टन नाइट्रोजन उर्बरक, 250 टन फॉस्फेट तथा 220 टन पोटाश है । फ़र्म इन पदार्थों के क्रमशः 3 : 3 : 4 3 : 3 : 4 3:3:43: 3: 43:3:4 के अनुपात में मिश्रण को 1500 रुपये प्रति टन के मुनाफे से तथा 2 : 4 : 2 2 : 4 : 2 2:4:22: 4: 22:4:2 के अनुपात में मिश्रण को 1200 रुपये प्रति टन के मुनाफे से बेच पायेगी। एक रैखिक-प्रोग्रामन समस्या प्रस्तुत कीजिए, जो यह दर्शाए कि अधिकतम मुनाफा प्राप्त करने के लिए, इन मिश्रणों की कितने टन मात्रा तैयार की जानी चाहिए।
An agricultural firm has 180 tons of nitrogen fertilizer, 250 tons of phosphate and 220 tons of potash. It will be able to sell a mixture of these substances in their respective ratio 3 : 3 : 4 3 : 3 : 4 3:3:43: 3: 43:3:4 at a profit of Rs. 1500 per ton and a mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22: 4: 22:4:2 at a profit of Rs. 1200 per ton. Pose a linear programming problem to show how many tons of these two mixtures should be prepared to obtain the maximum profit.
Answer:
To formulate a Linear Programming (LP) problem, we need to define the decision variables, the objective function, and the constraints.

Decision Variables

Let:
  • x x xxx be the number of tons of the mixture in the ratio 3 : 3 : 4 3 : 3 : 4 3:3:43:3:43:3:4 to be prepared.
  • y y yyy be the number of tons of the mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22:4:22:4:2 to be prepared.

Objective Function

The firm wants to maximize its profit. The profit for the mixture in the ratio 3 : 3 : 4 3 : 3 : 4 3:3:43:3:43:3:4 is Rs. 1500 per ton, and for the mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22:4:22:4:2, it is Rs. 1200 per ton. So, the objective function to maximize is:
P = 1500 x + 1200 y P = 1500 x + 1200 y P=1500 x+1200 yP = 1500x + 1200yP=1500x+1200y

Constraints

The firm has limited amounts of nitrogen fertilizer, phosphate, and potash, so we need to set up constraints based on the availability of these substances.
Certainly! Here is the corrected version with x x xxx and y y yyy replaced by x 1 x 1 x_(1)x_1x1 and x 2 x 2 x_(2)x_2x2:

Nitrogen Fertilizer Constraint

For the mixture in the ratio 3 : 3 : 4 3 : 3 : 4 3:3:43:3:43:3:4, 3 parts out of 10 are nitrogen fertilizer. So, for every ton of this mixture, 3 10 3 10 (3)/(10)\frac{3}{10}310 tons of nitrogen fertilizer are used. Similarly, for the mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22:4:22:4:2, 2 parts out of 8 are nitrogen fertilizer, i.e., 2 8 = 1 4 2 8 = 1 4 (2)/(8)=(1)/(4)\frac{2}{8} = \frac{1}{4}28=14 tons of nitrogen fertilizer per ton of mixture. The firm has 180 tons of nitrogen fertilizer available, so:
3 10 x 1 + 1 4 x 2 180 3 10 x 1 + 1 4 x 2 180 (3)/(10)x_(1)+(1)/(4)x_(2) <= 180\frac{3}{10}x_1 + \frac{1}{4}x_2 \leq 180310x1+14x2180
6 x 1 + 5 x 2 3600 6 x 1 + 5 x 2 3600 6x_(1)+5x_(2) <= 36006x_1 + 5x_2 \leq 36006x1+5x23600

Phosphate Constraint

For the mixture in the ratio 3 : 3 : 4 3 : 3 : 4 3:3:43:3:43:3:4, 3 parts out of 10 are phosphate. So, for every ton of this mixture, 3 10 3 10 (3)/(10)\frac{3}{10}310 tons of phosphate are used. For the mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22:4:22:4:2, 4 parts out of 8 are phosphate, i.e., 4 8 = 1 2 4 8 = 1 2 (4)/(8)=(1)/(2)\frac{4}{8} = \frac{1}{2}48=12 tons of phosphate per ton of mixture. The firm has 250 tons of phosphate available, so:
3 10 x 1 + 1 2 x 2 250 3 10 x 1 + 1 2 x 2 250 (3)/(10)x_(1)+(1)/(2)x_(2) <= 250\frac{3}{10}x_1 + \frac{1}{2}x_2 \leq 250310x1+12x2250
3 x 1 + 5 x 2 2500 3 x 1 + 5 x 2 2500 3x_(1)+5x_(2) <= 25003x_1 + 5x_2 \leq 25003x1+5x22500

Potash Constraint

For the mixture in the ratio 3 : 3 : 4 3 : 3 : 4 3:3:43:3:43:3:4, 4 parts out of 10 are potash. So, for every ton of this mixture, 4 10 4 10 (4)/(10)\frac{4}{10}410 tons of potash are used. For the mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22:4:22:4:2, 2 parts out of 8 are potash, i.e., 2 8 = 1 4 2 8 = 1 4 (2)/(8)=(1)/(4)\frac{2}{8} = \frac{1}{4}28=14 tons of potash per ton of mixture. The firm has 220 tons of potash available, so:
4 10 x 1 + 1 4 x 2 220 4 10 x 1 + 1 4 x 2 220 (4)/(10)x_(1)+(1)/(4)x_(2) <= 220\frac{4}{10}x_1 + \frac{1}{4}x_2 \leq 220410x1+14x2220
8 x 1 + 5 x 2 4400 8 x 1 + 5 x 2 4400 8x_(1)+5x_(2) <= 44008x_1 + 5x_2 \leq 44008x1+5x24400

Non-negativity Constraint

The number of tons of the mixtures cannot be negative:
x 1 0 x 1 0 x_(1) >= 0x_1 \geq 0x10
x 2 0 x 2 0 x_(2) >= 0x_2 \geq 0x20

Linear Programming Problem

To summarize, the Linear Programming problem is as follows:

Maximize

Z = 1500 x 1 + 1200 x 2 Z = 1500 x 1 + 1200 x 2 Z=1500x_(1)+1200x_(2)Z = 1500x_1 + 1200x_2Z=1500x1+1200x2

Subject to

6 x 1 + 5 x 2 3600 3 x 1 + 5 x 2 2500 8 x 1 + 5 x 2 4400 x 1 , x 2 0 6 x 1 + 5 x 2 3600 3 x 1 + 5 x 2 2500 8 x 1 + 5 x 2 4400 x 1 , x 2 0 {:[6x_(1)+5x_(2) <= 3600],[3x_(1)+5x_(2) <= 2500],[8x_(1)+5x_(2) <= 4400],[x_(1)”,”x_(2) >= 0]:}\begin{aligned} & 6x_1 + 5x_2 \leq 3600 \\ & 3x_1 + 5x_2 \leq 2500 \\ & 8x_1 + 5x_2 \leq 4400 \\ & x_1, x_2 \geq 0 \end{aligned}6x1+5x236003x1+5x225008x1+5x24400x1,x20
Now, let’s solve this Linear Programming problem.
The problem is converted to canonical form by adding slack, surplus and artificial variables as appropiate
  1. As the constraint-1 is of type ‘ <=\leq ‘ we should add slack variable S 1 S 1 S_(1)S_1S1
  2. As the constraint-2 is of type ‘ <=\leq ‘ we should add slack variable S 2 S 2 S_(2)S_2S2
  3. As the constraint-3 is of type ‘ <=\leq ‘ we should add slack variable S 3 S 3 S_(3)S_3S3
After introducing slack variables
Max Z = 1500 x 1 + 1200 x 2 + 0 S 1 + 0 S 2 + 0 S 3 Max Z = 1500 x 1 + 1200 x 2 + 0 S 1 + 0 S 2 + 0 S 3 Max Z=1500x_(1)+1200x_(2)+0S_(1)+0S_(2)+0S_(3)\operatorname{Max} Z=1500 x_1+1200 x_2+0 S_1+0 S_2+0 S_3MaxZ=1500x1+1200x2+0S1+0S2+0S3
subject to
6 x 1 + 5 x 2 + S 1 = 3600 3 x 1 + 5 x 2 + S 2 = 2500 8 x 1 + 5 x 2 + S 3 = 4400 6 x 1 + 5 x 2 + S 1 = 3600 3 x 1 + 5 x 2 + S 2 = 2500 8 x 1 + 5 x 2 + S 3 = 4400 {:[6x_(1)+5x_(2)+S_(1)=3600],[3x_(1)+5x_(2)+S_(2)=2500],[8x_(1)+5x_(2)+S_(3)=4400]:}\begin{aligned} 6 x_1+5 x_2+S_1 & =3600 \\ 3 x_1+5 x_2+S_2 & =2500 \\ 8 x_1+5 x_2+S_3 & =4400 \end{aligned}6x1+5x2+S1=36003x1+5x2+S2=25008x1+5x2+S3=4400
and x 1 , x 2 , S 1 , S 2 , S 3 0 x 1 , x 2 , S 1 , S 2 , S 3 0 x_(1),x_(2),S_(1),S_(2),S_(3) >= 0x_1, x_2, S_1, S_2, S_3 \geq 0x1,x2,S1,S2,S30
Iteration-1 C j 1500 1200 0 0 0 B C B X B x 1 x 2 S 1 S 2 S 3 X B x 1 S 1 S 2 0 2500 3 5 0 1 0 2500 3 = 833.3333 S 3 0 4400 ( 8 ) 5 0 0 1 4400 8 = 550 Z = 0 Z j 0 0 0 0 0 C j Z j 1500 1200 0 0 0  Iteration-1  C j 1500 1200 0 0 0 B C B X B x 1 x 2 S 1 S 2 S 3 X B x 1 S 1 S 2 0 2500 3 5 0 1 0 2500 3 = 833.3333 S 3 0 4400 ( 8 ) 5 0 0 1 4400 8 = 550 Z = 0 Z j 0 0 0 0 0 C j Z j 1500 1200 0 0 0 {:[” Iteration-1 “,,C_(j),1500,1200,0,0,0,],[B,C_(B),X_(B),x_(1),x_(2),S_(1),S_(2),S_(3),{:[(X_(B))/(x_(1))],[S_(1)]:}],[S_(2),0,2500,3,5,0,1,0,(2500)/(3)=833.3333],[S_(3),0,4400,(8),5,0,0,1,(4400)/(8)=550 rarr],[Z=0,,Z_(j),0,0,0,0,0,],[,,C_(j)-Z_(j),1500 uarr,1200,0,0,0,]:}\begin{array}{|c|c|c|c|c|c|c|c|c|} \hline \text { Iteration-1 } & & C_j & 1500 & 1200 & 0 & 0 & 0 & \\ \hline \boldsymbol{B} & C_{\boldsymbol{B}} & \boldsymbol{X}_{\boldsymbol{B}} & \boldsymbol{x}_1 & \boldsymbol{x}_2 & \boldsymbol{S}_{\mathbf{1}} & \boldsymbol{S}_{\mathbf{2}} & \boldsymbol{S}_{\mathbf{3}} & \begin{array}{c} \frac{\boldsymbol{X}_{\boldsymbol{B}}}{\boldsymbol{x}_{\mathbf{1}}} \\ \hline S_1 \end{array} \\ \hline S_2 & 0 & 2500 & 3 & 5 & 0 & 1 & 0 & \frac{2500}{3}=833.3333 \\ \hline S_3 & 0 & 4400 & (8) & 5 & 0 & 0 & 1 & \frac{4400}{8}=550 \rightarrow \\ \hline \boldsymbol{Z}=\mathbf{0} & & \boldsymbol{Z}_{\boldsymbol{j}} & \mathbf{0} & \mathbf{0} & \mathbf{0} & \mathbf{0} & \mathbf{0} & \\ \hline & & C_j-Z_j & 1500 \uparrow & 1200 & 0 & 0 & 0 & \\ \hline \end{array} Iteration-1 Cj15001200000BCBXBx1x2S1S2S3XBx1S1S2025003501025003=833.3333S304400(8)500144008=550Z=0Zj00000CjZj15001200000
Positive maximum C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj is 1500 and its column index is 1 . So, the entering variable is x 1 x 1 x_(1)x_1x1.
Minimum ratio is 550 and its row index is 3 . So, the leaving basis variable is S 3 S 3 S_(3)S_3S3.
:.\therefore The pivot element is 8 .
Entering = x 1 = x 1 =x_(1)=x_1=x1, Departing = S 3 = S 3 =S_(3)=S_3=S3, Key Element = 8 = 8 =8=8=8
R 3 ( R 3 ( R_(3)(R_3(R3( new ) = R 3 ( ) = R 3 ( )=R_(3)()=R_3()=R3( old ) ÷ 8 ) ÷ 8 )-:8) \div 8)÷8
R 1 ( R 1 ( R_(1)(R_1(R1( new ) = R 1 ( ) = R 1 ( )=R_(1)()=R_1()=R1( old ) 6 R 3 ( ) 6 R 3 ( )-6R_(3)()-6 R_3()6R3( new ) ) )))
R 2 ( R 2 ( R_(2)(R_2(R2( new ) = R 2 ( ) = R 2 ( )=R_(2)()=R_2()=R2( old ) 3 R 3 ( ) 3 R 3 ( )-3R_(3)()-3 R_3()3R3( new ) ) )))
Iteration-2 C j C j C_(j)C_jCj 1500 1200 0 0 0
B B BBB C B C B C_(B)C_BCB X B X B X_(B)X_BXB x 1 x 1 x_(1)x_1x1 x 2 x 2 x_(2)x_2x2 s 1 s 1 s_(1)s_1s1 s 2 s 2 s_(2)s_2s2 S 3 S 3 S_(3)S_3S3 MinRatio X B x 2  MinRatio  X B x 2 {:[” MinRatio “],[(X_(B))/(x_(2))]:}\begin{array}{c}\text { MinRatio } \\ \frac{X_B}{x_2}\end{array} MinRatio XBx2
s 1 s 1 s_(1)s_1s1 0 300 0 (1.25) 1 0 -0.75 300 1.25 = 240 300 1.25 = 240 (300)/(1.25)=240 rarr\frac{300}{1.25}=240 \rightarrow3001.25=240
S 2 S 2 S_(2)S_2S2 0 850 0 3.125 0 1 -0.375 850 3.125 = 272 850 3.125 = 272 (850)/(3.125)=272\frac{850}{3.125}=2728503.125=272
x 1 x 1 x_(1)x_1x1 1500 550 1 0.625 0 0 0.125 550 0.625 = 880 550 0.625 = 880 (550)/(0.625)=880\frac{550}{0.625}=8805500.625=880
Z = 8 2 5 0 0 0 Z = 8 2 5 0 0 0 Z=825000Z=\mathbf{8 2 5 0 0 0}Z=825000 Z j Z j Z_(j)Z_jZj 1500 937.5 0 0 187.5
C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj 0 262.5 262.5 262.5 uarr262.5 \uparrow262.5 0 0 -187.5
Iteration-2 C_(j) 1500 1200 0 0 0 B C_(B) X_(B) x_(1) x_(2) s_(1) s_(2) S_(3) ” MinRatio (X_(B))/(x_(2))” s_(1) 0 300 0 (1.25) 1 0 -0.75 (300)/(1.25)=240 rarr S_(2) 0 850 0 3.125 0 1 -0.375 (850)/(3.125)=272 x_(1) 1500 550 1 0.625 0 0 0.125 (550)/(0.625)=880 Z=825000 Z_(j) 1500 937.5 0 0 187.5 C_(j)-Z_(j) 0 262.5 uarr 0 0 -187.5 | Iteration-2 | | $C_j$ | 1500 | 1200 | 0 | 0 | 0 | | | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | | $B$ | $C_B$ | $X_B$ | $x_1$ | $x_2$ | $s_1$ | $s_2$ | $S_3$ | $\begin{array}{c}\text { MinRatio } \\ \frac{X_B}{x_2}\end{array}$ | | $s_1$ | 0 | 300 | 0 | (1.25) | 1 | 0 | -0.75 | $\frac{300}{1.25}=240 \rightarrow$ | | $S_2$ | 0 | 850 | 0 | 3.125 | 0 | 1 | -0.375 | $\frac{850}{3.125}=272$ | | $x_1$ | 1500 | 550 | 1 | 0.625 | 0 | 0 | 0.125 | $\frac{550}{0.625}=880$ | | $Z=\mathbf{8 2 5 0 0 0}$ | | $Z_j$ | 1500 | 937.5 | 0 | 0 | 187.5 | | | | | $C_j-Z_j$ | 0 | $262.5 \uparrow$ | 0 | 0 | -187.5 | |
Positive maximum C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj is 262.5 and its column index is 2 . So, the entering variable is x 2 x 2 x_(2)x_2x2.
Minimum ratio is 240 and its row index is 1 . So, the leaving basis variable is S 1 S 1 S_(1)S_1S1.
:.\therefore The pivot element is 1.25 .
Entering = x 2 = x 2 =x_(2)=x_2=x2, Departing = S 1 = S 1 =S_(1)=S_1=S1, Key Element = 1.25 = 1.25 =1.25=1.25=1.25
R 1 ( new ) = R 1 ( old ) ÷ 1.25 R 2 ( new ) = R 2 ( old ) 3.125 R 1 ( new ) R 3 ( new ) = R 3 ( old ) 0.625 R 1 ( new ) R 1 (  new  ) = R 1 (  old  ) ÷ 1.25 R 2 (  new  ) = R 2 (  old  ) 3.125 R 1 (  new  ) R 3 (  new  ) = R 3 (  old  ) 0.625 R 1 (  new  ) {:[R_(1)(” new “)=R_(1)(” old “)-:1.25],[R_(2)(” new “)=R_(2)(” old “)-3.125R_(1)(” new “)],[R_(3)(” new “)=R_(3)(” old “)-0.625R_(1)(” new “)]:}\begin{aligned} & R_1(\text { new })=R_1(\text { old }) \div 1.25 \\ & R_2(\text { new })=R_2(\text { old })-3.125 R_1(\text { new }) \\ & R_3(\text { new })=R_3(\text { old })-0.625 R_1(\text { new }) \end{aligned}R1( new )=R1( old )÷1.25R2( new )=R2( old )3.125R1( new )R3( new )=R3( old )0.625R1( new )
Iteration-3 C j C j C_(j)C_jCj 1500 1200 0 0 0
B B B\boldsymbol{B}B C B C B C_(B)\boldsymbol{C}_{\boldsymbol{B}}CB X B X B X_(B)\boldsymbol{X}_{\boldsymbol{B}}XB x 1 x 1 x_(1)\boldsymbol{x}_{\mathbf{1}}x1 x 2 x 2 x_(2)\boldsymbol{x}_{\mathbf{2}}x2 S 1 S 1 S_(1)\boldsymbol{S}_{\mathbf{1}}S1 S 2 S 2 S_(2)\boldsymbol{S}_{\mathbf{2}}S2 S 3 S 3 S_(3)\boldsymbol{S}_{\mathbf{3}}S3 MinRatio
x 2 x 2 x_(2)x_2x2 1200 240 0 1 0.8 0 -0.6
S 2 S 2 S_(2)S_2S2 0 100 0 0 -2.5 1 1.5
x 1 x 1 x_(1)x_1x1 1500 400 1 0 -0.5 0 0.5
Z = 8 8 8 0 0 0 Z = 8 8 8 0 0 0 Z=888000\boldsymbol{Z}=\mathbf{8 8 8 0 0 0}Z=888000 Z j Z j Z_(j)\boldsymbol{Z}_{\boldsymbol{j}}Zj 1 5 0 0 1 5 0 0 1500\mathbf{1 5 0 0}1500 1 2 0 0 1 2 0 0 1200\mathbf{1 2 0 0}1200 2 1 0 2 1 0 210\mathbf{2 1 0}210 0 0 0\mathbf{0}0 3 0 3 0 30\mathbf{3 0}30
C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj 0 0 -210 0 -30
Iteration-3 C_(j) 1500 1200 0 0 0 B C_(B) X_(B) x_(1) x_(2) S_(1) S_(2) S_(3) MinRatio x_(2) 1200 240 0 1 0.8 0 -0.6 S_(2) 0 100 0 0 -2.5 1 1.5 x_(1) 1500 400 1 0 -0.5 0 0.5 Z=888000 Z_(j) 1500 1200 210 0 30 C_(j)-Z_(j) 0 0 -210 0 -30 | Iteration-3 | | $C_j$ | 1500 | 1200 | 0 | 0 | 0 | | | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | | $\boldsymbol{B}$ | $\boldsymbol{C}_{\boldsymbol{B}}$ | $\boldsymbol{X}_{\boldsymbol{B}}$ | $\boldsymbol{x}_{\mathbf{1}}$ | $\boldsymbol{x}_{\mathbf{2}}$ | $\boldsymbol{S}_{\mathbf{1}}$ | $\boldsymbol{S}_{\mathbf{2}}$ | $\boldsymbol{S}_{\mathbf{3}}$ | MinRatio | | $x_2$ | 1200 | 240 | 0 | 1 | 0.8 | 0 | -0.6 | | | $S_2$ | 0 | 100 | 0 | 0 | -2.5 | 1 | 1.5 | | | $x_1$ | 1500 | 400 | 1 | 0 | -0.5 | 0 | 0.5 | | | $\boldsymbol{Z}=\mathbf{8 8 8 0 0 0}$ | | $\boldsymbol{Z}_{\boldsymbol{j}}$ | $\mathbf{1 5 0 0}$ | $\mathbf{1 2 0 0}$ | $\mathbf{2 1 0}$ | $\mathbf{0}$ | $\mathbf{3 0}$ | | | | | $C_j-Z_j$ | 0 | 0 | -210 | 0 | -30 | |
Since all C j Z j 0 C j Z j 0 C_(j)-Z_(j) <= 0C_j-Z_j \leq 0CjZj0
Hence, optimal solution is arrived with value of variables as :
x 1 = 400 , x 2 = 240 x 1 = 400 , x 2 = 240 x_(1)=400,x_(2)=240x_1=400, x_2=240x1=400,x2=240
Max Z = 888000 Max Z = 888000 Max Z=888000\operatorname{Max} Z=888000MaxZ=888000

Conclusion

Through iterative calculations and optimizations, the LP problem reached an optimal solution where:
  • x 1 = 400 x 1 = 400 x_(1)=400x_1=400x1=400 tons (mixture in the ratio 3 : 3 : 4 3 : 3 : 4 3:3:43: 3: 43:3:4 )
  • x 2 = 240 x 2 = 240 x_(2)=240x_2=240x2=240 tons (mixture in the ratio 2 : 4 : 2 2 : 4 : 2 2:4:22: 4: 22:4:2 )
    Maximum Profit:
    The maximum profit that the firm can achieve with this optimal solution is: Max Z = 888 , 000 Max Z = 888 , 000 Max Z=888,000\operatorname{Max} Z=888,000MaxZ=888,000 (in Rs.)
2.(a) दर्शाइए कि ( R , + ) ( R , + ) (R,+)(\mathbb{R},+)(R,+) मोड्यूलो Z Z Z\mathbb{Z}Z का विभाग समूह, सम्मिश्र तल में एकांक वृत्त पर सम्मिश्र संख्याओं के गुणनात्मक समूह से तुल्यकारी होता है । यहाँ पर R R R R RRR RRR, वास्तबिक संख्याओं का समुच्चय है तथा Z Z Z\mathbb{Z}Z पूर्णांकों का समुच्चय है ।
Show that the quotient group of ( R , + ) ( R , + ) (R,+)(\mathbb{R},+)(R,+) modulo Z Z Z\mathbb{Z}Z is isomorphic to the multiplicative group of complex numbers on the unit circle in the complex plane. Here R R RRR is the set of real numbers and Z Z Z\mathbb{Z}Z is the set of integers.
Answer:
To show that the quotient group of ( R , + ) ( R , + ) (R,+)(\mathbb{R},+)(R,+) modulo Z Z Z\mathbb{Z}Z is isomorphic to the multiplicative group of complex numbers on the unit circle, we will define an isomorphism between these two groups and then prove that this mapping is indeed an isomorphism.

Quotient Group Definition

The quotient group of ( R , + ) ( R , + ) (R,+)(\mathbb{R},+)(R,+) modulo Z Z Z\mathbb{Z}Z is denoted as R / Z R / Z R//Z\mathbb{R}/\mathbb{Z}R/Z and consists of all cosets of the form r + Z r + Z r+Zr + \mathbb{Z}r+Z where r R r R r inRr \in \mathbb{R}rR. Here, r + Z r + Z r+Zr + \mathbb{Z}r+Z represents the set of all real numbers differing by an integer from r r rrr.

Multiplicative Group of Complex Numbers on the Unit Circle

The multiplicative group of complex numbers on the unit circle is the set of all complex numbers of the form e 2 π i θ e 2 π i θ e^(2pi i theta)e^{2\pi i \theta}e2πiθ where θ R θ R theta inR\theta \in \mathbb{R}θR and i i iii is the imaginary unit. This group is usually denoted as U ( 1 ) U ( 1 ) U(1)U(1)U(1) or S 1 S 1 S^(1)S^1S1.

Define an Isomorphism

Let’s define a function f : R / Z U ( 1 ) f : R / Z U ( 1 ) f:R//Zrarr U(1)f: \mathbb{R}/\mathbb{Z} \to U(1)f:R/ZU(1) as follows:
f ( r + Z ) = e 2 π i r f ( r + Z ) = e 2 π i r f(r+Z)=e^(2pi ir)f(r + \mathbb{Z}) = e^{2\pi i r}f(r+Z)=e2πir

Prove Isomorphism

To prove that f f fff is an isomorphism, we need to show that f f fff is a bijective homomorphism.

1. Homomorphism

A function f f fff is a homomorphism if for all a , b R / Z a , b R / Z a,b inR//Za, b \in \mathbb{R}/\mathbb{Z}a,bR/Z:
f ( a + b ) = f ( a ) f ( b ) f ( a + b ) = f ( a ) f ( b ) f(a+b)=f(a)*f(b)f(a + b) = f(a) \cdot f(b)f(a+b)=f(a)f(b)
Let’s verify this property for our function f f fff:
f ( ( r 1 + Z ) + ( r 2 + Z ) ) = f ( r 1 + r 2 + Z ) = e 2 π i ( r 1 + r 2 ) = e 2 π i r 1 e 2 π i r 2 = f ( r 1 + Z ) f ( r 2 + Z ) f ( ( r 1 + Z ) + ( r 2 + Z ) ) = f ( r 1 + r 2 + Z ) = e 2 π i ( r 1 + r 2 ) = e 2 π i r 1 e 2 π i r 2 = f ( r 1 + Z ) f ( r 2 + Z ) f((r_(1)+Z)+(r_(2)+Z))=f(r_(1)+r_(2)+Z)=e^(2pi i(r_(1)+r_(2)))=e^(2pi ir_(1))*e^(2pi ir_(2))=f(r_(1)+Z)*f(r_(2)+Z)f((r_1 + \mathbb{Z}) + (r_2 + \mathbb{Z})) = f(r_1 + r_2 + \mathbb{Z}) = e^{2\pi i (r_1 + r_2)} = e^{2\pi i r_1} \cdot e^{2\pi i r_2} = f(r_1 + \mathbb{Z}) \cdot f(r_2 + \mathbb{Z})f((r1+Z)+(r2+Z))=f(r1+r2+Z)=e2πi(r1+r2)=e2πir1e2πir2=f(r1+Z)f(r2+Z)

2. Injective (One-to-One)

A function f f fff is injective if different elements in the domain map to different elements in the codomain.
If f ( r 1 + Z ) = f ( r 2 + Z ) f ( r 1 + Z ) = f ( r 2 + Z ) f(r_(1)+Z)=f(r_(2)+Z)f(r_1 + \mathbb{Z}) = f(r_2 + \mathbb{Z})f(r1+Z)=f(r2+Z), then:
e 2 π i r 1 = e 2 π i r 2 r 1 r 2 Z r 1 + Z = r 2 + Z e 2 π i r 1 = e 2 π i r 2 r 1 r 2 Z r 1 + Z = r 2 + Z e^(2pi ir_(1))=e^(2pi ir_(2))Longrightarrowr_(1)-r_(2)inZLongrightarrowr_(1)+Z=r_(2)+Ze^{2\pi i r_1} = e^{2\pi i r_2} \implies r_1 – r_2 \in \mathbb{Z} \implies r_1 + \mathbb{Z} = r_2 + \mathbb{Z}e2πir1=e2πir2r1r2Zr1+Z=r2+Z

3. Surjective (Onto)

A function f f fff is surjective if every element in the codomain has a preimage in the domain.
For any e 2 π i θ U ( 1 ) e 2 π i θ U ( 1 ) e^(2pi i theta)in U(1)e^{2\pi i \theta} \in U(1)e2πiθU(1), θ + Z R / Z θ + Z R / Z theta+ZinR//Z\theta + \mathbb{Z} \in \mathbb{R}/\mathbb{Z}θ+ZR/Z is a preimage, since:
f ( θ + Z ) = e 2 π i θ f ( θ + Z ) = e 2 π i θ f(theta+Z)=e^(2pi i theta)f(\theta + \mathbb{Z}) = e^{2\pi i \theta}f(θ+Z)=e2πiθ

Conclusion

Since f f fff is a bijective homomorphism, it is an isomorphism. Thus, the quotient group R / Z R / Z R//Z\mathbb{R}/\mathbb{Z}R/Z is isomorphic to the multiplicative group of complex numbers on the unit circle, U ( 1 ) U ( 1 ) U(1)U(1)U(1) or S 1 S 1 S^(1)S^1S1.
2.(b) निम्नलिखित रैख्रिक प्रोग्रामन समस्या को Big M M M\mathrm{M}M विधि से हल कीजिए तथा दर्शाइए कि समस्या के परिमित इष्टतम हल हैं। साथ ही उद्देश्य फलन का मान भी ज्ञात कीजिए :
न्यूनतमीकरण कीजिए z = 3 x 1 + 5 x 2 z = 3 x 1 + 5 x 2 z=3x_(1)+5x_(2)z=3 x_1+5 x_2z=3x1+5x2
बशाते कि x 1 + 2 x 2 8 x 1 + 2 x 2 8 x_(1)+2x_(2) >= 8x_1+2 x_2 \geqslant 8x1+2x28
3 x 1 + 2 x 2 12 5 x 1 + 6 x 2 60 , x 1 , x 2 0 . 3 x 1 + 2 x 2 12 5 x 1 + 6 x 2 60 , x 1 , x 2 0 . {:[3x_(1)+2x_(2) >= 12],[5x_(1)+6x_(2) <= 60″,”],[x_(1)”,”x_(2) >= 0.]:}\begin{aligned} &3 x_1+2 x_2 \geqslant 12 \\ &5 x_1+6 x_2 \leqslant 60, \\ &x_1, x_2 \geqslant 0 . \end{aligned}3x1+2x2125x1+6x260,x1,x20.
Solve the following linear programming problem by Big M-method and show that the problem has finite optimal solutions. Also find the value of the objective function :
Minimize z = 3 x 1 + 5 x 2 z = 3 x 1 + 5 x 2 z=3x_(1)+5x_(2)z=3 x_1+5 x_2z=3x1+5x2
subject to x 1 + 2 x 2 8 x 1 + 2 x 2 8 x_(1)+2x_(2) >= 8x_1+2 x_2 \geqslant 8x1+2x28
3 x 1 + 2 x 2 12 5 x 1 + 6 x 2 60 , x 1 , x 2 0 . 3 x 1 + 2 x 2 12 5 x 1 + 6 x 2 60 , x 1 , x 2 0 . {:[3x_(1)+2x_(2) >= 12],[5x_(1)+6x_(2) <= 60″,”],[x_(1)”,”x_(2) >= 0.]:}\begin{aligned} &3 x_1+2 x_2 \geqslant 12 \\ &5 x_1+6 x_2 \leqslant 60, \\ &x_1, x_2 \geqslant 0 . \end{aligned}3x1+2x2125x1+6x260,x1,x20.
Answer:
The problem is converted to canonical form by adding slack, surplus and artificial variables as appropiate
  1. As the constraint-1 is of type ‘ >=\geq ‘ we should subtract surplus variable S 1 S 1 S_(1)S_1S1 and add artificial variable A 1 A 1 A_(1)A_1A1
  2. As the constraint-2 is of type ‘ >=\geq ‘ we should subtract surplus variable S 2 S 2 S_(2)S_2S2 and add artificial variable A 2 A 2 A_(2)A_2A2
  3. As the constraint-3 is of type ‘ <=\leq ‘ we should add slack variable S 3 S 3 S_(3)S_3S3
    After introducing slack,surplus, artificial variables
Min Z = 3 x 1 + 5 x 2 + 0 S 1 + 0 S 2 + 0 S 3 + M A 1 + M A 2 subject to x 1 + 2 x 2 S 1 + A 1 = 8 3 x 1 + 2 x 2 S 2 + A 2 = 12 5 x 1 + 6 x 2 + S 3 = 60 and x 1 , x 2 , S 1 , S 2 , S 3 , A 1 , A 2 0  Min  Z = 3 x 1 + 5 x 2 + 0 S 1 + 0 S 2 + 0 S 3 + M A 1 + M A 2  subject to  x 1 + 2 x 2 S 1 + A 1 = 8 3 x 1 + 2 x 2 S 2 + A 2 = 12 5 x 1 + 6 x 2 + S 3 = 60  and  x 1 , x 2 , S 1 , S 2 , S 3 , A 1 , A 2 0 {:[” Min “Z=3x_(1)+5x_(2)+0S_(1)+0S_(2)+0S_(3)+MA_(1)+MA_(2)],[” subject to “],[x_(1)+2x_(2)-S_(1)+A_(1)=8],[3x_(1)+2x_(2)-S_(2)quad+A_(2)=12],[5x_(1)+6x_(2)+S_(3)quad=60],[” and “x_(1)”,”x_(2)”,”S_(1)”,”S_(2)”,”S_(3)”,”A_(1)”,”A_(2) >= 0],[]:}\begin{aligned} & \text { Min } Z=3 x_1+5 x_2+0 S_1+0 S_2+0 S_3+M A_1+M A_2 \\ & \text { subject to } \\ & x_1+2 x_2-S_1+A_1=8 \\ & 3 x_1+2 x_2-S_2 \quad+A_2=12 \\ & 5 x_1+6 x_2+S_3 \quad=60 \\ & \text { and } x_1, x_2, S_1, S_2, S_3, A_1, A_2 \geq 0 \\ & \end{aligned} Min Z=3x1+5x2+0S1+0S2+0S3+MA1+MA2 subject to x1+2x2S1+A1=83x1+2x2S2+A2=125x1+6x2+S3=60 and x1,x2,S1,S2,S3,A1,A20
Negative minimum C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj is 4 M + 3 4 M + 3 -4M+3-4 M+34M+3 and its column index is 1 . So, the entering variable is x 1 x 1 x_(1)x_1x1.
Minimum ratio is 4 and its row index is 2 . So, the leaving basis variable is A 2 A 2 A_(2)A_2A2.
:.\therefore The pivot element is 3 .
Entering = x 1 = x 1 =x_(1)=x_1=x1, Departing = A 2 = A 2 =A_(2)=A_2=A2, Key Element = 3 = 3 =3=3=3
R 2 ( R 2 ( R_(2)(R_2(R2( new ) = R 2 ( ) = R 2 ( )=R_(2)()=R_2()=R2( old ) ÷ 3 ) ÷ 3 )-:3) \div 3)÷3
R 1 ( R 1 ( R_(1)(R_1(R1( new ) = R 1 ) = R 1 )=R_(1))=R_1)=R1 (old) R 2 R 2 -R_(2)-R_2R2 (new)
R 3 ( R 3 ( R_(3)(R_3(R3( new ) = R 3 ( ) = R 3 ( )=R_(3)()=R_3()=R3( old ) 5 R 2 ( ) 5 R 2 ( )-5R_(2)()-5 R_2()5R2( new ) ) )))
Iteration-2 C j C j C_(j)C_jCj 3 5 0 0 0 M M MMM
B B B\boldsymbol{B}B C B C B C_(B)C_BCB X B X B X_(B)X_BXB x 1 x 1 x_(1)x_1x1 x 2 x 2 x_(2)x_2x2 s 1 s 1 s_(1)s_1s1 S 2 S 2 S_(2)S_2S2 S 3 S 3 S_(3)S_3S3 A 1 A 1 A_(1)A_1A1 MinRatio X B x 2  MinRatio  X B x 2 {:[” MinRatio “],[(X_(B))/(x_(2))]:}\begin{array}{c}\text { MinRatio } \\ \frac{X_B}{x_2}\end{array} MinRatio XBx2
A 1 A 1 A_(1)A_1A1 M M MMM 4 0 (1.3333) -1 0.3333 0 1 4 1.3333 = 3 4 1.3333 = 3 (4)/(1.3333)=3rarr\frac{4}{1.3333}=3 \rightarrow41.3333=3
x 1 x 1 x_(1)x_1x1 3 4 1 0.6667 0 -0.3333 0 0 4 0.6667 = 6 4 0.6667 = 6 (4)/(0.6667)=6\frac{4}{0.6667}=640.6667=6
S 3 S 3 S_(3)S_3S3 0 40 0 2.6667 0 1.6667 1 0 40 2.6667 = 15 40 2.6667 = 15 (40)/(2.6667)=15\frac{40}{2.6667}=15402.6667=15
Z = 4 M + 12 Z = 4 M + 12 Z=4M+12Z=4 M+12Z=4M+12 Z j Z j Z_(j)Z_jZj 3 1.3333 M + 2 1.3333 M + 2 1.3333 M+21.3333 M+21.3333M+2 M M -M-MM 0.3333 M 1 0.3333 M 1 0.3333 M-10.3333 M-10.3333M1 0 0 0\mathbf{0}0 M M MMM
C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj 0 1.3333 M + 3 1.3333 M + 3 -1.3333 M+3uarr-1.3333 M+3 \uparrow1.3333M+3 M M MMM 0.3333 M + 1 0.3333 M + 1 -0.3333 M+1-0.3333 M+10.3333M+1 0 0
Iteration-2 C_(j) 3 5 0 0 0 M B C_(B) X_(B) x_(1) x_(2) s_(1) S_(2) S_(3) A_(1) ” MinRatio (X_(B))/(x_(2))” A_(1) M 4 0 (1.3333) -1 0.3333 0 1 (4)/(1.3333)=3rarr x_(1) 3 4 1 0.6667 0 -0.3333 0 0 (4)/(0.6667)=6 S_(3) 0 40 0 2.6667 0 1.6667 1 0 (40)/(2.6667)=15 Z=4M+12 Z_(j) 3 1.3333 M+2 -M 0.3333 M-1 0 M C_(j)-Z_(j) 0 -1.3333 M+3uarr M -0.3333 M+1 0 0 | Iteration-2 | | $C_j$ | 3 | 5 | 0 | 0 | 0 | $M$ | | | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | | $\boldsymbol{B}$ | $C_B$ | $X_B$ | $x_1$ | $x_2$ | $s_1$ | $S_2$ | $S_3$ | $A_1$ | $\begin{array}{c}\text { MinRatio } \\ \frac{X_B}{x_2}\end{array}$ | | $A_1$ | $M$ | 4 | 0 | (1.3333) | -1 | 0.3333 | 0 | 1 | $\frac{4}{1.3333}=3 \rightarrow$ | | $x_1$ | 3 | 4 | 1 | 0.6667 | 0 | -0.3333 | 0 | 0 | $\frac{4}{0.6667}=6$ | | $S_3$ | 0 | 40 | 0 | 2.6667 | 0 | 1.6667 | 1 | 0 | $\frac{40}{2.6667}=15$ | | $Z=4 M+12$ | | $Z_j$ | 3 | $1.3333 M+2$ | $-M$ | $0.3333 M-1$ | $\mathbf{0}$ | $M$ | | | | | $C_j-Z_j$ | 0 | $-1.3333 M+3 \uparrow$ | $M$ | $-0.3333 M+1$ | 0 | 0 | |
Negative minimum C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj is 1.3333 M + 3 1.3333 M + 3 -1.3333 M+3-1.3333 M+31.3333M+3 and its column index is 2 . So, the entering variable is x 2 x 2 x_(2)x_2x2.
Minimum ratio is 3 and its row index is 1 . So, the leaving basis variable is A 1 A 1 A_(1)A_1A1.
:.\therefore The pivot element is 1.3333 .
Entering = x 2 = x 2 =x_(2)=x_2=x2, Departing = A 1 = A 1 =A_(1)=A_1=A1, Key Element = 1.3333 = 1.3333 =1.3333=1.3333=1.3333
R 1 ( new ) = R 1 ( old ) ÷ 1.3333 R 2 ( new ) = R 2 ( old ) 0.6667 R 1 ( new ) R 3 ( new ) = R 3 ( old ) 2.6667 R 1 ( new ) R 1 (  new  ) = R 1 (  old  ) ÷ 1.3333 R 2 (  new  ) = R 2 (  old  ) 0.6667 R 1 (  new  ) R 3 (  new  ) = R 3 (  old  ) 2.6667 R 1 (  new  ) {:[R_(1)(” new “)=R_(1)(” old “)-:1.3333],[R_(2)(” new “)=R_(2)(” old “)-0.6667R_(1)(” new “)],[R_(3)(” new “)=R_(3)(” old “)-2.6667R_(1)(” new “)]:}\begin{aligned} & R_1(\text { new })=R_1(\text { old }) \div 1.3333 \\ & R_2(\text { new })=R_2(\text { old })-0.6667 R_1(\text { new }) \\ & R_3(\text { new })=R_3(\text { old })-2.6667 R_1(\text { new }) \end{aligned}R1( new )=R1( old )÷1.3333R2( new )=R2( old )0.6667R1( new )R3( new )=R3( old )2.6667R1( new )
Iteration-3 C j C j C_(j)C_jCj 3 5 0 0 0
B B B\boldsymbol{B}B C B C B C_(B)\boldsymbol{C}_{\boldsymbol{B}}CB X B X B X_(B)\boldsymbol{X}_{\boldsymbol{B}}XB x 1 x 1 x_(1)\boldsymbol{x}_{\mathbf{1}}x1 x 2 x 2 x_(2)\boldsymbol{x}_{\mathbf{2}}x2 S 1 S 1 S_(1)\boldsymbol{S}_{\mathbf{1}}S1 S 2 S 2 S_(2)\boldsymbol{S}_{\mathbf{2}}S2 S 3 S 3 S_(3)\boldsymbol{S}_{\mathbf{3}}S3 MinRatio
x 2 x 2 x_(2)x_2x2 5 3 0 1 -0.75 0.25 0
x 1 x 1 x_(1)x_1x1 3 2 1 0 0.5 -0.5 0
S 3 S 3 S_(3)S_3S3 0 32 0 0 2 1 1
Z = 2 1 Z = 2 1 Z=21\boldsymbol{Z}=\mathbf{2 1}Z=21 Z j Z j Z_(j)\boldsymbol{Z}_{\boldsymbol{j}}Zj 3 3 3\mathbf{3}3 5 5 5\mathbf{5}5 2 . 2 5 2 . 2 5 -2.25\mathbf{- 2 . 2 5}2.25 0 . 2 5 0 . 2 5 -0.25\mathbf{- 0 . 2 5}0.25 0 0 0\mathbf{0}0
C j Z j C j Z j C_(j)-Z_(j)C_j-Z_jCjZj 0 0 2.25 0.25 0
Iteration-3 C_(j) 3 5 0 0 0 B C_(B) X_(B) x_(1) x_(2) S_(1) S_(2) S_(3) MinRatio x_(2) 5 3 0 1 -0.75 0.25 0 x_(1) 3 2 1 0 0.5 -0.5 0 S_(3) 0 32 0 0 2 1 1 Z=21 Z_(j) 3 5 -2.25 -0.25 0 C_(j)-Z_(j) 0 0 2.25 0.25 0 | Iteration-3 | | $C_j$ | 3 | 5 | 0 | 0 | 0 | | | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | | $\boldsymbol{B}$ | $\boldsymbol{C}_{\boldsymbol{B}}$ | $\boldsymbol{X}_{\boldsymbol{B}}$ | $\boldsymbol{x}_{\mathbf{1}}$ | $\boldsymbol{x}_{\mathbf{2}}$ | $\boldsymbol{S}_{\mathbf{1}}$ | $\boldsymbol{S}_{\mathbf{2}}$ | $\boldsymbol{S}_{\mathbf{3}}$ | MinRatio | | $x_2$ | 5 | 3 | 0 | 1 | -0.75 | 0.25 | 0 | | | $x_1$ | 3 | 2 | 1 | 0 | 0.5 | -0.5 | 0 | | | $S_3$ | 0 | 32 | 0 | 0 | 2 | 1 | 1 | | | $\boldsymbol{Z}=\mathbf{2 1}$ | | $\boldsymbol{Z}_{\boldsymbol{j}}$ | $\mathbf{3}$ | $\mathbf{5}$ | $\mathbf{- 2 . 2 5}$ | $\mathbf{- 0 . 2 5}$ | $\mathbf{0}$ | | | | | $C_j-Z_j$ | 0 | 0 | 2.25 | 0.25 | 0 | |
Since all C j Z j 0 C j Z j 0 C_(j)-Z_(j) >= 0C_j-Z_j \geq 0CjZj0
Hence, optimal solution is arrived with value of variables as :
x 1 = 2 , x 2 = 3 x 1 = 2 , x 2 = 3 x_(1)=2,x_(2)=3x_1=2, x_2=3x1=2,x2=3
Min Z = 21 Min Z = 21 Min Z=21\operatorname{Min} Z=21MinZ=21
2.(c) दर्शाइए कि यदि R R R\mathbb{R}R के विदृत अन्तराल ( a , b ) ( a , b ) (a,b)(a, b)(a,b) पर परिभाषित फलन f f fff अवमुख हो, तो बह संतत है । उदाहरण के द्वारा दर्शाइए कि यदि विवृत अन्तराल होने की शर्त न हो, बब अवमुख फलन का संतत होना आवश्यक नहीं है ।
Show that if a function f f fff defined on an open interval ( a , b ) ( a , b ) (a,b)(a, b)(a,b) of R R R\mathbb{R}R is convex, then f f fff is continuous. Show, by example, if the condition of open interval is dropped, then the convex function need not be continuous.
Answer:

Proof that a Convex Function on an Open Interval is Continuous

A function f : ( a , b ) R f : ( a , b ) R f:(a,b)rarrRf: (a, b) \to \mathbb{R}f:(a,b)R is convex if, for any x , y ( a , b ) x , y ( a , b ) x,y in(a,b)x, y \in (a, b)x,y(a,b) and any λ ( 0 , 1 ) λ ( 0 , 1 ) lambda in(0,1)\lambda \in (0, 1)λ(0,1), the following inequality holds:
f ( λ x + ( 1 λ ) y ) λ f ( x ) + ( 1 λ ) f ( y ) f ( λ x + ( 1 λ ) y ) λ f ( x ) + ( 1 λ ) f ( y ) f(lambda x+(1-lambda)y) <= lambda f(x)+(1-lambda)f(y)f(\lambda x + (1 – \lambda)y) \leq \lambda f(x) + (1 – \lambda)f(y)f(λx+(1λ)y)λf(x)+(1λ)f(y)
To show that f f fff is continuous on ( a , b ) ( a , b ) (a,b)(a, b)(a,b), we need to show that for every point c ( a , b ) c ( a , b ) c in(a,b)c \in (a, b)c(a,b), for every ϵ > 0 ϵ > 0 epsilon > 0\epsilon > 0ϵ>0, there exists a δ > 0 δ > 0 delta > 0\delta > 0δ>0 such that if | x c | < δ | x c | < δ |x-c| < delta|x – c| < \delta|xc|<δ, then | f ( x ) f ( c ) | < ϵ | f ( x ) f ( c ) | < ϵ |f(x)-f(c)| < epsilon|f(x) – f(c)| < \epsilon|f(x)f(c)|<ϵ.

Proof:

Let c ( a , b ) c ( a , b ) c in(a,b)c \in (a, b)c(a,b) and let x ( a , b ) x ( a , b ) x in(a,b)x \in (a, b)x(a,b) be such that x < c x < c x < cx < cx<c. Since f f fff is convex, for any t ( 0 , 1 ) t ( 0 , 1 ) t in(0,1)t \in (0, 1)t(0,1), we have:
f ( ( 1 t ) c + t x ) ( 1 t ) f ( c ) + t f ( x ) f ( ( 1 t ) c + t x ) ( 1 t ) f ( c ) + t f ( x ) f((1-t)c+tx) <= (1-t)f(c)+tf(x)f((1 – t)c + tx) \leq (1 – t)f(c) + tf(x)f((1t)c+tx)(1t)f(c)+tf(x)
Let’s rearrange terms and isolate f ( x ) f ( x ) f(x)f(x)f(x):
f ( x ) f ( ( 1 t ) c + t x ) ( 1 t ) f ( c ) t f ( x ) f ( ( 1 t ) c + t x ) ( 1 t ) f ( c ) t f(x) >= (f((1-t)c+tx)-(1-t)f(c))/(t)f(x) \geq \frac{f((1 – t)c + tx) – (1 – t)f(c)}{t}f(x)f((1t)c+tx)(1t)f(c)t
Now, let’s take the limit as t 0 + t 0 + t rarr0^(+)t \to 0^+t0+:
f ( x ) lim t 0 + f ( ( 1 t ) c + t x ) ( 1 t ) f ( c ) t = f ( c ) + lim t 0 + f ( ( 1 t ) c + t x ) f ( c ) t f ( x ) lim t 0 + f ( ( 1 t ) c + t x ) ( 1 t ) f ( c ) t = f ( c ) + lim t 0 + f ( ( 1 t ) c + t x ) f ( c ) t f(x) >= lim_(t rarr0^(+))(f((1-t)c+tx)-(1-t)f(c))/(t)=f(c)+lim_(t rarr0^(+))(f((1-t)c+tx)-f(c))/(t)f(x) \geq \lim_{{t \to 0^+}} \frac{f((1 – t)c + tx) – (1 – t)f(c)}{t} = f(c) + \lim_{{t \to 0^+}} \frac{f((1 – t)c + tx) – f(c)}{t}f(x)limt0+f((1t)c+tx)(1t)f(c)t=f(c)+limt0+f((1t)c+tx)f(c)t
The limit on the right side exists because f f fff is convex, and it represents the right-hand derivative of f f fff at c c ccc. Thus, f f fff has a right-hand limit at every point in ( a , b ) ( a , b ) (a,b)(a, b)(a,b).
Similarly, by considering points x > c x > c x > cx > cx>c, we can show that f f fff has a left-hand limit at every point in ( a , b ) ( a , b ) (a,b)(a, b)(a,b).
Since f f fff has both left-hand and right-hand limits at every point in ( a , b ) ( a , b ) (a,b)(a, b)(a,b), and these limits are equal, f f fff is continuous on ( a , b ) ( a , b ) (a,b)(a, b)(a,b).

Counterexample when the Open Interval Condition is Dropped

Consider the function f : [ 0 , 1 ] R f : [ 0 , 1 ] R f:[0,1]rarrRf: [0, 1] \to \mathbb{R}f:[0,1]R defined as follows:
f ( x ) = { 0 if x = 0 1 if 0 < x 1 f ( x ) = 0 if  x = 0 1 if  0 < x 1 f(x)={[0,”if “x=0],[1,”if “0 < x <= 1]:}f(x) = \begin{cases} 0 & \text{if } x = 0 \\ 1 & \text{if } 0 < x \leq 1 \end{cases}f(x)={0if x=01if 0<x1
This function is convex because for any x , y [ 0 , 1 ] x , y [ 0 , 1 ] x,y in[0,1]x, y \in [0, 1]x,y[0,1] and any λ ( 0 , 1 ) λ ( 0 , 1 ) lambda in(0,1)\lambda \in (0, 1)λ(0,1), the inequality
f ( λ x + ( 1 λ ) y ) λ f ( x ) + ( 1 λ ) f ( y ) f ( λ x + ( 1 λ ) y ) λ f ( x ) + ( 1 λ ) f ( y ) f(lambda x+(1-lambda)y) <= lambda f(x)+(1-lambda)f(y)f(\lambda x + (1 – \lambda)y) \leq \lambda f(x) + (1 – \lambda)f(y)f(λx+(1λ)y)λf(x)+(1λ)f(y)
holds. However, this function is not continuous at x = 0 x = 0 x=0x = 0x=0, as the left-hand limit does not exist, and the right-hand limit at x = 0 x = 0 x=0x = 0x=0 is 1 1 111, which is not equal to f ( 0 ) = 0 f ( 0 ) = 0 f(0)=0f(0) = 0f(0)=0.
  1. (a) क्षेत्र ( Z 13 , + 13 , x 13 ) Z 13 , + 13 , x 13 (Z_(13),+_(13),x_(13))\left(\mathscr{Z}_{13},+_{13}, x_{13}\right)(Z13,+13,x13), जहाँ पर + 13 + 13 +_(13)+_{13}+13 तथा x 13 x 13 x_(13)x_{13}x13 क्रमशः योग मोडयूलो 13 व गुणन मोडयूलो 13 निरूपित करते है, के गुणनात्मक समूह के सभी उचित उपसमूहों को ज्ञात कीजिए।
Find all the proper subgroups of the multiplicative group of the field ( Z 13 , + 13 , × 13 ) Z 13 , + 13 , × 13 (Z_(13),+_(13),xx_(13))\left(\mathcal{Z}_{13},+_{13}, \times_{13}\right)(Z13,+13,×13), where + 13 + 13 +_(13)+{ }_{13}+13 and x 13 x 13 x_(13)x_{13}x13 represent addition modulo 13 and multiplication modulo 13 respectively.
Answer:
To find all the proper subgroups of the multiplicative group of the field ( Z 13 , + 13 , × 13 ) Z 13 , + 13 , × 13 (Z_(13),+_(13),xx_(13))\left(\mathbb{Z}_{13},+_{13}, \times_{13}\right)(Z13,+13,×13), we need to consider the elements and their orders in this group.
The multiplicative group of a finite field is formed by the nonzero elements of that field under multiplication. In this case, we are working with Z 13 Z 13 Z_(13)\mathbb{Z}_{13}Z13, so the nonzero elements are { 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 } { 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 } {1,2,3,4,5,6,7,8,9,10,11,12}\{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12\}{1,2,3,4,5,6,7,8,9,10,11,12}.

Finding the Generator

The generator of the multiplicative group Z 13 Z 13 Z_(13)^(**)\mathbb{Z}_{13}^*Z13 is 2 2 222. This means that every element in the multiplicative group Z 13 Z 13 Z_(13)^(**)\mathbb{Z}_{13}^*Z13 can be represented as a power of 2 2 222 modulo 13 13 131313, confirming that Z 13 Z 13 Z_(13)^(**)\mathbb{Z}_{13}^*Z13 is indeed a cyclic group.
The cyclic group generated by 2 2 222 is as follows:
{ 2 , 4 , 8 , 3 , 6 , 12 , 11 , 9 , 5 , 10 , 7 , 1 } { 2 , 4 , 8 , 3 , 6 , 12 , 11 , 9 , 5 , 10 , 7 , 1 } {2,4,8,3,6,12,11,9,5,10,7,1}\{2, 4, 8, 3, 6, 12, 11, 9, 5, 10, 7, 1\}{2,4,8,3,6,12,11,9,5,10,7,1}

Finding the Proper Subgroups

Now, let’s find all the proper subgroups of this cyclic group. A proper subgroup is a subgroup that is not equal to the entire group. The proper subgroups of the cyclic group generated by 2 2 222 are as follows:
  1. Subgroup generated by 2 2 222: { 1 , 2 , 4 , 8 , 3 , 6 , 12 , 11 , 9 , 5 , 10 , 7 } { 1 , 2 , 4 , 8 , 3 , 6 , 12 , 11 , 9 , 5 , 10 , 7 } {1,2,4,8,3,6,12,11,9,5,10,7}\{1, 2, 4, 8, 3, 6, 12, 11, 9, 5, 10, 7\}{1,2,4,8,3,6,12,11,9,5,10,7} (This is the entire group, so it is not a proper subgroup)
  2. Subgroup generated by powers of 2 2 222 with step 2 2 222: { 1 , 4 , 3 , 12 , 9 , 10 } { 1 , 4 , 3 , 12 , 9 , 10 } {1,4,3,12,9,10}\{1, 4, 3, 12, 9, 10\}{1,4,3,12,9,10} (Order 6 6 666)
  3. Subgroup generated by powers of 2 2 222 with step 3 3 333: { 1 , 8 , 12 , 5 } { 1 , 8 , 12 , 5 } {1,8,12,5}\{1, 8, 12, 5\}{1,8,12,5} (Order 4 4 444)
  4. Subgroup generated by powers of 2 2 222 with step 4 4 444: { 1 , 3 , 9 } { 1 , 3 , 9 } {1,3,9}\{1, 3, 9\}{1,3,9} (Order 3 3 333)
  5. Subgroup generated by powers of 2 2 222 with step 6 6 666: { 1 , 12 } { 1 , 12 } {1,12}\{1, 12\}{1,12} (Order 2 2 222)
  6. Subgroup generated by powers of 2 2 222 with step 12 12 121212: { 1 } { 1 } {1}\{1\}{1} (Trivial subgroup)

Conclusion

The proper subgroups of the multiplicative group of the field ( Z 13 , + 13 , × 13 ) Z 13 , + 13 , × 13 (Z_(13),+_(13),xx_(13))\left(\mathbb{Z}_{13},+_{13}, \times_{13}\right)(Z13,+13,×13) are:
  1. { 1 , 4 , 3 , 12 , 9 , 10 } { 1 , 4 , 3 , 12 , 9 , 10 } {1,4,3,12,9,10}\{1, 4, 3, 12, 9, 10\}{1,4,3,12,9,10} (Order 6 6 666)
  2. { 1 , 8 , 12 , 5 } { 1 , 8 , 12 , 5 } {1,8,12,5}\{1, 8, 12, 5\}{1,8,12,5} (Order 4 4 444)
  3. { 1 , 3 , 9 } { 1 , 3 , 9 } {1,3,9}\{1, 3, 9\}{1,3,9} (Order 3 3 333)
  4. { 1 , 12 } { 1 , 12 } {1,12}\{1, 12\}{1,12} (Order 2 2 222)
  5. { 1 } { 1 } {1}\{1\}{1} (Trivial subgroup)
Each of these subgroups is closed under multiplication modulo 13 13 131313 and contains the identity element 1 1 111.
3.(b) अवशेष प्रमेय के अनुप्रयोग के द्वारा दर्शाइए कि 0 d x ( x 2 + a 2 ) 2 = π 4 a 3 , a > 0 0 d x x 2 + a 2 2 = π 4 a 3 , a > 0 int_(0)^(oo)(dx)/((x^(2)+a^(2))^(2))=(pi)/(4a^(3)),a > 0\int_0^{\infty} \frac{d x}{\left(x^2+a^2\right)^2}=\frac{\pi}{4 a^3}, a>00dx(x2+a2)2=π4a3,a>0.
Show by applying the residue theorem that 0 d x ( x 2 + a 2 ) 2 = π 4 a 3 , a > 0 0 d x x 2 + a 2 2 = π 4 a 3 , a > 0 int_(0)^(oo)(dx)/((x^(2)+a^(2))^(2))=(pi)/(4a^(3)),a > 0\int_0^{\infty} \frac{d x}{\left(x^2+a^2\right)^2}=\frac{\pi}{4 a^3}, a>00dx(x2+a2)2=π4a3,a>0.
Answer:
Introduction:
In this problem, we are asked to prove the integral identity 0 d x ( x 2 + a 2 ) 2 = π 4 a 3 0 d x ( x 2 + a 2 ) 2 = π 4 a 3 int_(0)^(oo)(dx)/((x^(2)+a^(2))^(2))=(pi)/(4a^(3))\int_0^{\infty} \frac{dx}{(x^2 + a^2)^2} = \frac{\pi}{4a^3}0dx(x2+a2)2=π4a3 where a > 0 a > 0 a > 0a > 0a>0. We will use the residue theorem to evaluate this integral.
Step 1: Setting up the Contour Integral:
We consider the contour integral
c d z ( z 2 + a 2 ) 2 = c f ( z ) d z c d z ( z 2 + a 2 ) 2 = c f ( z ) d z int _(c)(dz)/((z^(2)+a^(2))^(2))=int _(c)f(z)dz\int_c \frac{dz}{(z^2 + a^2)^2} = \int_c f(z) dzcdz(z2+a2)2=cf(z)dz
where f ( z ) = 1 ( z 2 + a 2 ) 2 f ( z ) = 1 ( z 2 + a 2 ) 2 f(z)=(1)/((z^(2)+a^(2))^(2))f(z) = \frac{1}{(z^2 + a^2)^2}f(z)=1(z2+a2)2, and c c ccc is a contour consisting of a large semicircle T T TTT of radius R R RRR together with a part of the real axis from x = R x = R x=-Rx = -Rx=R to R R RRR.
Step 2: Applying the Residue Theorem:
By Cauchy’s residue theorem, we have:
c f ( z ) d z = 2 π i Res c f ( z ) d z = 2 π i Res int _(c)f(z)dz=2pi i sum”Res”\int_c f(z) dz = 2\pi i \sum \text{Res}cf(z)dz=2πiRes
where the sum is taken over the residues of f ( z ) f ( z ) f(z)f(z)f(z) inside the contour c c ccc.
We first consider the behavior of f ( z ) f ( z ) f(z)f(z)f(z) as z z zzz approaches infinity:
lim z z f ( z ) = lim z z ( z 2 + a 2 ) 2 = lim z z z 4 ( a 2 z 2 + 1 ) 2 = 0 lim z z f ( z ) = lim z z ( z 2 + a 2 ) 2 = lim z z z 4 a 2 z 2 + 1 2 = 0 lim_(z rarr oo)zf(z)=lim_(z rarr oo)(z)/((z^(2)+a^(2))^(2))=lim_(z rarr oo)(z)/(z^(4)((a^(2))/(z^(2))+1)^(2))=0\lim_{z \to \infty} zf(z) = \lim_{z \to \infty} \frac{z}{(z^2 + a^2)^2} = \lim_{z \to \infty} \frac{z}{z^4 \left(\frac{a^2}{z^2} + 1\right)^2} = 0limzzf(z)=limzz(z2+a2)2=limzzz4(a2z2+1)2=0
Therefore, as R R R rarr ooR \to \inftyR, the integral over the semicircle T T TTT, lim R T f ( z ) d z lim R T f ( z ) d z lim_(R rarr oo)int _(T)f(z)dz\lim_{R \to \infty} \int_T f(z) dzlimRTf(z)dz, approaches zero.
Hence, we have:
lim R T f ( z ) d z = 0 lim R T f ( z ) d z = 0 lim_(R rarr oo)int _(T)f(z)dz=0\lim_{R \to \infty} \int_T f(z) dz = 0limRTf(z)dz=0
Now, taking R R R rarr ooR \to \inftyR in the original contour integral equation, we get:
d x ( a 2 + x 2 ) 2 + 0 = 2 π i Res d x a 2 + x 2 2 + 0 = 2 π i Res int_(-oo)^(oo)(dx)/((a^(2)+x^(2))^(2))+0=2pi i sum Res\int_{-\infty}^{\infty} \frac{d x}{\left(a^2+x^2\right)^2}+0=2 \pi i \sum \operatorname{Res}dx(a2+x2)2+0=2πiRes
Step 3: Finding the Residue:
The poles of f ( z ) = 1 ( z 2 + a 2 ) 2 f ( z ) = 1 ( z 2 + a 2 ) 2 f(z)=(1)/((z^(2)+a^(2))^(2))f(z) = \frac{1}{(z^2 + a^2)^2}f(z)=1(z2+a2)2 are given by ( z 2 + a 2 ) 2 = 0 ( z 2 + a 2 ) 2 = 0 (z^(2)+a^(2))^(2)=0(z^2 + a^2)^2 = 0(z2+a2)2=0, which implies z = ± a i z = ± a i z=+-aiz = \pm aiz=±ai (twice). However, only the pole at z = a i z = a i z=aiz = aiz=ai (of order 2) lies inside the contour c c ccc.
To find the residue at a i a i aiaiai, we calculate:
ϕ ( z ) = ( z a i ) 2 f ( z ) = ( z a i ) 2 1 ( z 2 + a 2 ) 2 = 1 ( z + a i ) 2 ϕ ( z ) = ( z a i ) 2 f ( z ) = ( z a i ) 2 1 ( z 2 + a 2 ) 2 = 1 ( z + a i ) 2 {:[phi(z)=(z-ai)^(2)f(z)],[=(z-ai)^(2)(1)/((z^(2)+a^(2))^(2))],[=(1)/((z+ai)^(2))]:}\begin{aligned} \phi(z) &= (z – ai)^2 f(z) \\ &= (z – ai)^2 \frac{1}{(z^2 + a^2)^2} \\ &= \frac{1}{(z + ai)^2} \end{aligned}ϕ(z)=(zai)2f(z)=(zai)21(z2+a2)2=1(z+ai)2
Taking the derivative of ϕ ( z ) ϕ ( z ) phi(z)\phi(z)ϕ(z), we get:
ϕ ( z ) = 2 ( z + a i ) 3 ϕ ( z ) = 2 ( z + a i ) 3 phi^(‘)(z)=-(2)/((z+ai)^(3))\phi'(z) = -\frac{2}{(z + ai)^3}ϕ(z)=2(z+ai)3
Therefore, the residue at a i a i aiaiai is given by:
Residue at a i = ϕ ( a i ) = 2 ( a i + a i ) 3 = 1 4 a 3 i Residue at  a i = ϕ ( a i ) = 2 ( a i + a i ) 3 = 1 4 a 3 i “Residue at “ai=phi^(‘)(ai)=-(2)/((ai+ai)^(3))=(1)/(4a^(3)i)\text{Residue at } ai = \phi'(ai) = -\frac{2}{(ai + ai)^3} = \frac{1}{4a^3i}Residue at ai=ϕ(ai)=2(ai+ai)3=14a3i
Conclusion:
Putting all the pieces together, we have:
d x ( a 2 + x 2 ) 2 + 0 = 2 π i × 1 4 a 3 i d x ( a 2 + x 2 ) 2 + 0 = 2 π i × 1 4 a 3 i int_(-oo)^(oo)(dx)/((a^(2)+x^(2))^(2))+0=2pi i xx(1)/(4a^(3)i)\int_{-\infty}^{\infty} \frac{dx}{(a^2 + x^2)^2} + 0 = 2\pi i \times \frac{1}{4a^3i}dx(a2+x2)2+0=2πi×14a3i
Simplifying, we find:
d x ( a 2 + x 2 ) 2 = π 2 a 3 d x ( a 2 + x 2 ) 2 = π 2 a 3 int_(-oo)^(oo)(dx)/((a^(2)+x^(2))^(2))=(pi)/(2a^(3))\int_{-\infty}^{\infty} \frac{dx}{(a^2 + x^2)^2} = \frac{\pi}{2a^3}dx(a2+x2)2=π2a3
As d x ( a 2 + x 2 ) 2 d x ( a 2 + x 2 ) 2 (dx)/((a^(2)+x^(2))^(2))\frac{dx}{(a^2 + x^2)^2}dx(a2+x2)2 is an even function.
So,
2 × 0 d x ( x 2 + a 2 ) 2 = π 2 a 3 , a > 0 2 × 0 d x ( x 2 + a 2 ) 2 = π 2 a 3 , a > 0 2xxint_(0)^(oo)(dx)/((x^(2)+a^(2))^(2))=(pi)/(2a^(3)),quad a > 02\times \int_0^{\infty} \frac{dx}{(x^2 + a^2)^2} = \frac{\pi}{2a^3}, \quad a > 02×0dx(x2+a2)2=π2a3,a>0
0 d x ( x 2 + a 2 ) 2 = π 4 a 3 , a > 0 0 d x ( x 2 + a 2 ) 2 = π 4 a 3 , a > 0 int_(0)^(oo)(dx)/((x^(2)+a^(2))^(2))=(pi)/(4a^(3)),quad a > 0\int_0^{\infty} \frac{dx}{(x^2 + a^2)^2} = \frac{\pi}{4a^3}, \quad a > 00dx(x2+a2)2=π4a3,a>0
  1. (c) अधोलिखित समीकरणों के रेखिकतः स्वतंत्र समुच्चय में कितने आधारी हल हैं ? उन सभी को ज्ञात कीजिए ।
2 x 1 x 2 + 3 x 3 + x 4 = 6 4 x 1 2 x 2 x 3 + 2 x 4 = 10 . 2 x 1 x 2 + 3 x 3 + x 4 = 6 4 x 1 2 x 2 x 3 + 2 x 4 = 10 . {:[2x_(1)-x_(2)+3x_(3)+x_(4)=6],[4x_(1)-2x_(2)-x_(3)+2x_(4)=10.]:}\begin{aligned} &2 x_1-x_2+3 x_3+x_4=6 \\ &4 x_1-2 x_2-x_3+2 x_4=10 . \end{aligned}2x1x2+3x3+x4=64x12x2x3+2x4=10.
How many basic solutions are there in the following linearly independent set of equations? Find all of them.
2 x 1 x 2 + 3 x 3 + x 4 = 6 4 x 1 2 x 2 x 3 + 2 x 4 = 10 . 2 x 1 x 2 + 3 x 3 + x 4 = 6 4 x 1 2 x 2 x 3 + 2 x 4 = 10 . {:[2x_(1)-x_(2)+3x_(3)+x_(4)=6],[4x_(1)-2x_(2)-x_(3)+2x_(4)=10.]:}\begin{aligned} &2 x_1-x_2+3 x_3+x_4=6 \\ &4 x_1-2 x_2-x_3+2 x_4=10 . \end{aligned}2x1x2+3x3+x4=64x12x2x3+2x4=10.
Answer:

Given System of Equations:

2 x 1 x 2 + 3 x 3 + x 4 = 6 4 x 1 2 x 2 x 3 + 2 x 4 = 10 . 2 x 1 x 2 + 3 x 3 + x 4 = 6 4 x 1 2 x 2 x 3 + 2 x 4 = 10 . {:[2x_(1)-x_(2)+3x_(3)+x_(4)=6],[4x_(1)-2x_(2)-x_(3)+2x_(4)=10.]:}\begin{aligned} &2 x_1-x_2+3 x_3+x_4=6 \\ &4 x_1-2 x_2-x_3+2 x_4=10 . \end{aligned}2x1x2+3x3+x4=64x12x2x3+2x4=10.

Method:

To find the basic solutions, we will express the non-pivot variables in terms of the pivot variables and then set each pivot variable to 1 (and the others to 0) one at a time to find the basic solutions.
Let’s write the augmented matrix for the given system of equations and then perform row operations to get it to reduced row echelon form (RREF):

Augmented Matrix:

[ 2 1 3 1 6 4 2 1 2 10 ] 2 1 3 1 6 4 2 1 2 10 [[2,-1,3,1,6],[4,-2,-1,2,10]]\left[\begin{array}{cccc|c} 2 & -1 & 3 & 1 & 6 \\ 4 & -2 & -1 & 2 & 10 \end{array}\right][21316421210]

Row Operations to get RREF:

  1. Swap R 1 R 1 R_(1)R_1R1 and R 2 R 2 R_(2)R_2R2:
[ 4 2 1 2 10 2 1 3 1 6 ] 4 2 1 2 10 2 1 3 1 6 [[4,-2,-1,2,10],[2,-1,3,1,6]]\left[\begin{array}{cccc|c} 4 & -2 & -1 & 2 & 10 \\ 2 & -1 & 3 & 1 & 6 \end{array}\right][42121021316]
  1. R 2 R 2 1 2 R 1 R 2 R 2 1 2 R 1 R_(2)larrR_(2)-(1)/(2)R_(1)R_2 \leftarrow R_2 – \frac{1}{2} R_1R2R212R1:
[ 4 2 1 2 10 0 0 7 2 0 1 ] 4 2 1 2 10 0 0 7 2 0 1 [[4,-2,-1,2,10],[0,0,(7)/(2),0,1]]\left[\begin{array}{cccc|c} 4 & -2 & -1 & 2 & 10 \\ 0 & 0 & \frac{7}{2} & 0 & 1 \end{array}\right][421210007201]
  1. R 1 R 1 + 1 7 R 2 R 1 R 1 + 1 7 R 2 R_(1)larrR_(1)+(1)/(7)R_(2)R_1 \leftarrow R_1 + \frac{1}{7} R_2R1R1+17R2:
[ 4 2 0 2 17 7 0 0 1 0 2 7 ] 4 2 0 2 17 7 0 0 1 0 2 7 [[4,-2,0,2,(17)/(7)],[0,0,1,0,(2)/(7)]]\left[\begin{array}{cccc|c} 4 & -2 & 0 & 2 & \frac{17}{7} \\ 0 & 0 & 1 & 0 & \frac{2}{7} \end{array}\right][4202177001027]

Expressing Variables:

From the RREF, we have:
  • Pivot variables: x 3 x 3 x_(3)x_3x3
  • Non-pivot variables: x 1 x 1 x_(1)x_1x1, x 2 x 2 x_(2)x_2x2, and x 4 x 4 x_(4)x_4x4
Expressing the non-pivot variables in terms of the pivot variable:
  1. From the second row: x 3 = 2 7 x 3 = 2 7 x_(3)=(2)/(7)x_3 = \frac{2}{7}x3=27
  2. From the first row: x 1 = 1 4 ( 17 7 2 x 4 + 2 x 2 ) = 17 28 + 1 2 x 2 1 2 x 4 x 1 = 1 4 17 7 2 x 4 + 2 x 2 = 17 28 + 1 2 x 2 1 2 x 4 x_(1)=(1)/(4)((17)/(7)-2x_(4)+2x_(2))=(17)/(28)+(1)/(2)x_(2)-(1)/(2)x_(4)x_1 = \frac{1}{4} \left(\frac{17}{7} – 2x_4 + 2x_2 \right) = \frac{17}{28} + \frac{1}{2}x_2 – \frac{1}{2}x_4x1=14(1772x4+2x2)=1728+12x212x4

Finding Basic Solutions:

  1. Set x 2 = 1 x 2 = 1 x_(2)=1x_2 = 1x2=1, x 4 = 0 x 4 = 0 x_(4)=0x_4 = 0x4=0:
    • x 1 = 17 28 + 1 2 = 20 7 x 1 = 17 28 + 1 2 = 20 7 x_(1)=(17)/(28)+(1)/(2)=(20)/(7)x_1 = \frac{17}{28} + \frac{1}{2} = \frac{20}{7}x1=1728+12=207
    • x 3 = 2 7 x 3 = 2 7 x_(3)=(2)/(7)x_3 = \frac{2}{7}x3=27
    • Basic Solution: ( 20 7 , 1 , 2 7 , 0 ) 20 7 , 1 , 2 7 , 0 ((20)/(7),1,(2)/(7),0)\left(\frac{20}{7}, 1, \frac{2}{7}, 0\right)(207,1,27,0)
  2. Set x 2 = 0 x 2 = 0 x_(2)=0x_2 = 0x2=0, x 4 = 1 x 4 = 1 x_(4)=1x_4 = 1x4=1:
    • x 1 = 17 28 1 2 = 19 7 x 1 = 17 28 1 2 = 19 7 x_(1)=(17)/(28)-(1)/(2)=(19)/(7)x_1 = \frac{17}{28} – \frac{1}{2} = \frac{19}{7}x1=172812=197
    • x 3 = 2 7 x 3 = 2 7 x_(3)=(2)/(7)x_3 = \frac{2}{7}x3=27
    • Basic Solution: ( 19 7 , 0 , 2 7 , 1 ) 19 7 , 0 , 2 7 , 1 ((19)/(7),0,(2)/(7),1)\left(\frac{19}{7}, 0, \frac{2}{7}, 1\right)(197,0,27,1)

Conclusion:

The basic solutions for the given system of linearly independent equations are:
  1. ( 20 7 , 1 , 2 7 , 0 ) 20 7 , 1 , 2 7 , 0 ((20)/(7),1,(2)/(7),0)\left(\frac{20}{7}, 1, \frac{2}{7}, 0\right)(207,1,27,0)
  2. ( 19 7 , 0 , 2 7 , 1 ) 19 7 , 0 , 2 7 , 1 ((19)/(7),0,(2)/(7),1)\left(\frac{19}{7}, 0, \frac{2}{7}, 1\right)(197,0,27,1)
4.(a) मान लीजिए कि R R R\mathbb{R}R सभी वास्तविक संख्याओं का समुच्चय है तथा f : R R f : R R f:RrarrRf: \mathbb{R} \rightarrow \mathbb{R}f:RR ऐसा फलन है कि समी x , y R x , y R x,y inRx, y \in \mathbb{R}x,yR के लिए निम्नलिखित समीकरण लागू होते हैं :
(i) f ( x + y ) = f ( x ) + f ( y ) f ( x + y ) = f ( x ) + f ( y ) f(x+y)=f(x)+f(y)f(x+y)=f(x)+f(y)f(x+y)=f(x)+f(y)
(ii) f ( x y ) = f ( x ) f ( y ) f ( x y ) = f ( x ) f ( y ) f(xy)=f(x)f(y)f(x y)=f(x) f(y)f(xy)=f(x)f(y)
दर्शाइए कि सभी x R x R AA x inR\forall x \in \mathbb{R}xR के लिए या तो f ( x ) = 0 f ( x ) = 0 f(x)=0f(x)=0f(x)=0 या f ( x ) = x f ( x ) = x f(x)=xf(x)=xf(x)=x है।
Suppose R R R\mathbb{R}R be the set of all real numbers and f : R R f : R R f:RrarrRf: \mathbb{R} \rightarrow \mathbb{R}f:RR is a function such that the following equations hold for all x , y R x , y R x,y inRx, y \in \mathbb{R}x,yR :
(i) f ( x + y ) = f ( x ) + f ( y ) f ( x + y ) = f ( x ) + f ( y ) f(x+y)=f(x)+f(y)f(x+y)=f(x)+f(y)f(x+y)=f(x)+f(y)
(ii) f ( x y ) = f ( x ) f ( y ) f ( x y ) = f ( x ) f ( y ) f(xy)=f(x)f(y)f(x y)=f(x) f(y)f(xy)=f(x)f(y)
Show that x R x R AA x inR\forall x \in \mathbb{R}xR either f ( x ) = 0 f ( x ) = 0 f(x)=0f(x)=0f(x)=0, or, f ( x ) = x f ( x ) = x f(x)=xf(x)=xf(x)=x.
Answer:
To solve this problem, we will use the given properties of the function f : R R f : R R f:RrarrRf: \mathbb{R} \rightarrow \mathbb{R}f:RR and try to deduce the possible forms of the function.

Given Properties:

  1. f ( x + y ) = f ( x ) + f ( y ) f ( x + y ) = f ( x ) + f ( y ) f(x+y)=f(x)+f(y)f(x + y) = f(x) + f(y)f(x+y)=f(x)+f(y) (Additive property)
  2. f ( x y ) = f ( x ) f ( y ) f ( x y ) = f ( x ) f ( y ) f(x*y)=f(x)*f(y)f(x \cdot y) = f(x) \cdot f(y)f(xy)=f(x)f(y) (Multiplicative property)

Step 1: Evaluate f ( 0 ) f ( 0 ) f(0)f(0)f(0)

Let’s start by finding the value of f ( 0 ) f ( 0 ) f(0)f(0)f(0). We can use the additive property for this:
f ( 0 ) = f ( 0 + 0 ) = f ( 0 ) + f ( 0 ) f ( 0 ) = f ( 0 + 0 ) = f ( 0 ) + f ( 0 ) f(0)=f(0+0)=f(0)+f(0)f(0) = f(0 + 0) = f(0) + f(0)f(0)=f(0+0)=f(0)+f(0)
f ( 0 ) = 0 f ( 0 ) = 0 f(0)=0f(0) = 0f(0)=0

Step 2: Evaluate f ( 1 ) f ( 1 ) f(1)f(1)f(1)

Let’s find the value of f ( 1 ) f ( 1 ) f(1)f(1)f(1) using the multiplicative property:
f ( 1 ) = f ( 1 1 ) = f ( 1 ) f ( 1 ) f ( 1 ) = f ( 1 1 ) = f ( 1 ) f ( 1 ) f(1)=f(1*1)=f(1)*f(1)f(1) = f(1 \cdot 1) = f(1) \cdot f(1)f(1)=f(11)=f(1)f(1)
Let’s assume f ( 1 ) = a f ( 1 ) = a f(1)=af(1) = af(1)=a, then:
a = a a a = a a a=a*aa = a \cdot aa=aa
a 2 = a a 2 = a a^(2)=aa^2 = aa2=a
a ( a 1 ) = 0 a ( a 1 ) = 0 a(a-1)=0a(a – 1) = 0a(a1)=0
So, f ( 1 ) = a = 0 f ( 1 ) = a = 0 f(1)=a=0f(1) = a = 0f(1)=a=0 or f ( 1 ) = a = 1 f ( 1 ) = a = 1 f(1)=a=1f(1) = a = 1f(1)=a=1

Step 3: Evaluate f ( x ) f ( x ) f(x)f(x)f(x) for any x x xxx

Let’s use the additive property to find the value of f ( x ) f ( x ) f(x)f(x)f(x) for any x x xxx:
f ( x ) = f ( 1 x ) = f ( 1 ) f ( x ) f ( x ) = f ( 1 x ) = f ( 1 ) f ( x ) f(x)=f(1*x)=f(1)*f(x)f(x) = f(1 \cdot x) = f(1) \cdot f(x)f(x)=f(1x)=f(1)f(x)
If f ( 1 ) = 0 f ( 1 ) = 0 f(1)=0f(1) = 0f(1)=0, then f ( x ) = 0 f ( x ) = 0 f ( x ) = 0 f ( x ) = 0 f(x)=0*f(x)=0f(x) = 0 \cdot f(x) = 0f(x)=0f(x)=0 for all x x xxx.
If f ( 1 ) = 1 f ( 1 ) = 1 f(1)=1f(1) = 1f(1)=1, then f ( x ) = 1 f ( x ) = f ( x ) f ( x ) = 1 f ( x ) = f ( x ) f(x)=1*f(x)=f(x)f(x) = 1 \cdot f(x) = f(x)f(x)=1f(x)=f(x) for all x x xxx.

Step 4: Conclusion

Based on the above steps, we can conclude that for all x R x R x inRx \in \mathbb{R}xR, either f ( x ) = 0 f ( x ) = 0 f(x)=0f(x) = 0f(x)=0 or f ( x ) = x f ( x ) = x f(x)=xf(x) = xf(x)=x.

Detailed Conclusion:

  1. If f ( 1 ) = 0 f ( 1 ) = 0 f(1)=0f(1) = 0f(1)=0, then the function f : R R f : R R f:RrarrRf: \mathbb{R} \rightarrow \mathbb{R}f:RR is the zero function, i.e., f ( x ) = 0 f ( x ) = 0 f(x)=0f(x) = 0f(x)=0 for all x R x R x inRx \in \mathbb{R}xR.
  2. If f ( 1 ) = 1 f ( 1 ) = 1 f(1)=1f(1) = 1f(1)=1, then the function f : R R f : R R f:RrarrRf: \mathbb{R} \rightarrow \mathbb{R}f:RR is the identity function, i.e., f ( x ) = x f ( x ) = x f(x)=xf(x) = xf(x)=x for all x R x R x inRx \in \mathbb{R}xR.
Thus, the function f f fff is either the zero function or the identity function, satisfying the given conditions.
4.(b) फलन 1 ( 1 + z 2 ) ( z + 2 ) 1 1 + z 2 ( z + 2 ) (1)/((1+z^(2))(z+2))\frac{1}{\left(1+z^2\right)(z+2)}1(1+z2)(z+2) को निरूपित करने वाली लाँरेन्ज श्रेणी ज्ञात कीजिए जब
(i) | z | < 1 | z | < 1 |z| < 1|z|<1|z|<1
(ii) 1 < | z | < 2 1 < | z | < 2 1 < |z| < 21<|z|<21<|z|<2
(iii) | z | > 2 | z | > 2 |z| > 2|z|>2|z|>2
Find the Laurent’s series which represent the function 1 ( 1 + z 2 ) ( z + 2 ) 1 1 + z 2 ( z + 2 ) (1)/((1+z^(2))(z+2))\frac{1}{\left(1+z^2\right)(z+2)}1(1+z2)(z+2) when
(i) | z | < 1 | z | < 1 |z| < 1|z|<1|z|<1
(ii) 1 < | z | < 2 1 < | z | < 2 1 < |z| < 21<|z|<21<|z|<2
(iii) | z | > 2 | z | > 2 |z| > 2|z|>2|z|>2
Answer:
Let
f ( z ) = 1 ( 1 + z 2 ) ( z + 2 ) f ( z ) = 1 1 + z 2 ( z + 2 ) f(z)=(1)/((1+z^(2))(z+2))f(z)=\frac{1}{\left(1+z^2\right)(z+2)}f(z)=1(1+z2)(z+2)
Resolving into partial fractions ;
f ( z ) = A z + B 1 + z 2 + C z + 2 1 = ( A z + B ) ( z + 2 ) + C ( 1 + z 2 ) 1 = z 2 ( A + C ) + z ( B + 2 A ) + ( 2 B + C ) f ( z ) = A z + B 1 + z 2 + C z + 2 1 = ( A z + B ) ( z + 2 ) + C 1 + z 2 1 = z 2 ( A + C ) + z ( B + 2 A ) + ( 2 B + C ) {:[f(z)=(Az+B)/(1+z^(2))+(C)/(z+2)],[1=(Az+B)(z+2)+C(1+z^(2))],[1=z^(2)(A+C)+z(B+2A)+(2B+C)]:}\begin{aligned} f(z) & =\frac{\mathrm{A} z+\mathrm{B}}{1+z^2}+\frac{\mathrm{C}}{z+2} \\ 1 & =(\mathrm{A} z+\mathrm{B})(z+2)+\mathrm{C}\left(1+z^2\right) \\ 1 & =z^2(\mathrm{~A}+\mathrm{C})+z(\mathrm{~B}+2 \mathrm{~A})+(2 \mathrm{~B}+\mathrm{C}) \end{aligned}f(z)=Az+B1+z2+Cz+21=(Az+B)(z+2)+C(1+z2)1=z2( A+C)+z( B+2 A)+(2 B+C)
or
Comparing coefficients of z 2 z 2 z^(2)z^2z2 and z z zzz and constant on both the sides, we get
1 = 2 B + C 0 = A + C 0 = B + 2 A } B = 2 C B = 2 5 , C = 1 5 , A = 1 5 f ( z ) = 1 ( 1 + z 2 ) ( z + 2 ) 1 = 2 B + C 0 = A + C 0 = B + 2 A B = 2 C B = 2 5 , C = 1 5 , A = 1 5 f ( z ) = 1 1 + z 2 ( z + 2 ) {:[{:[1=2B+C],[0=A+C],[0=B+2A]}=>B=2C],[:.],[B=(2)/(5)”,”C=(1)/(5)”,”A=-(1)/(5)],[f(z)=(1)/((1+z^(2))(z+2))],[]:}\begin{aligned} & \left.\begin{array}{l} 1=2 B+C \\ 0=A+C \\ 0=B+2 A \end{array}\right\} \Rightarrow B=2 C \\ & \therefore \\ & \mathrm{B}=\frac{2}{5}, \mathrm{C}=\frac{1}{5}, \mathrm{~A}=-\frac{1}{5} \\ & f(z)=\frac{1}{\left(1+z^2\right)(z+2)} \\ & \end{aligned}1=2B+C0=A+C0=B+2A}B=2CB=25,C=15, A=15f(z)=1(1+z2)(z+2)
= 1 5 ( z 2 ) 1 + z 2 + 1 5 ( z + 2 ) . = 1 5 ( z 2 ) 1 + z 2 + 1 5 ( z + 2 ) . =-(1)/(5)((z-2))/(1+z^(2))+(1)/(5(z+2)).=-\frac{1}{5} \frac{(z-2)}{1+z^2}+\frac{1}{5(z+2)} .=15(z2)1+z2+15(z+2).
(i) | z | < 1 | z | < 1 |z| < 1|z|<1|z|<1,
f ( z ) = 1 5 1 2 ( 1 + 1 2 z ) 1 + 2 z 5 ( 1 + z 2 ) 1 f ( z ) = 1 5 1 2 1 + 1 2 z 1 + 2 z 5 1 + z 2 1 f(z)=(1)/(5)*(1)/(2)*(1+(1)/(2)*z)^(-1)+(2-z)/(5)(1+z^(2))^(-1)f(z)=\frac{1}{5} \cdot \frac{1}{2} \cdot\left(1+\frac{1}{2} \cdot z\right)^{-1}+\frac{2-z}{5}\left(1+z^2\right)^{-1}f(z)=1512(1+12z)1+2z5(1+z2)1
Binomial expansion of ( 1 + z ) 1 ( 1 + z ) 1 (1+z)^(-1)(1+z)^{-1}(1+z)1 is valid only when | z | < 1 | z | < 1 |z| < 1|z|<1|z|<1.
f ( z ) = 1 10 0 ( 1 ) n ( z 2 ) n + 2 z 5 0 ( 1 ) n z 2 n . f ( z ) = 1 10 0 ( 1 ) n z 2 n + 2 z 5 0 ( 1 ) n z 2 n . :.quad f(z)=(1)/(10)sum_(0)^(oo)(-1)^(n)((z)/(2))^(n)+(2-z)/(5)sum_(0)^(oo)(-1)^(n)*z^(2n).\therefore \quad f(z)=\frac{1}{10} \sum_0^{\infty}(-1)^n\left(\frac{z}{2}\right)^n+\frac{2-z}{5} \sum_0^{\infty}(-1)^n \cdot z^{2 n} .f(z)=1100(1)n(z2)n+2z50(1)nz2n.
This is a series in positive powers of z z zzz, so it is an expansion of f ( z ) f ( z ) f(z)f(z)f(z) in a Taylor’s series within the circle | z | = 1 | z | = 1 |z|=1|z|=1|z|=1.
(ii) 1 < | z | < 2 1 < | z | < 2 1 < |z| < 21<|z|<21<|z|<2
f ( z ) = 1 10 ( 1 + 1 2 z ) 1 + 2 z 5 1 z 2 ( 1 + 1 z 2 ) 1 = 1 10 0 ( 1 ) n ( z 2 ) n + 2 z 5 z 2 0 ( 1 ) n ( 1 z 2 ) n . f ( z ) = 1 10 1 + 1 2 z 1 + 2 z 5 1 z 2 1 + 1 z 2 1 = 1 10 0 ( 1 ) n z 2 n + 2 z 5 z 2 0 ( 1 ) n 1 z 2 n . {:[f(z)=(1)/(10)(1+(1)/(2)z)^(-1)+(2-z)/(5)*(1)/(z^(2))(1+(1)/(z^(2)))^(-1)],[=(1)/(10)sum_(0)^(oo)(-1)^(n)((z)/(2))^(n)+(2-z)/(5z^(2))sum_(0)^(oo)(-1)^(n)*((1)/(z^(2)))^(n).]:}\begin{aligned} f(z) & =\frac{1}{10}\left(1+\frac{1}{2} z\right)^{-1}+\frac{2-z}{5} \cdot \frac{1}{z^2}\left(1+\frac{1}{z^2}\right)^{-1} \\ & =\frac{1}{10} \sum_0^{\infty}(-1)^n\left(\frac{z}{2}\right)^n+\frac{2-z}{5 z^2} \sum_0^{\infty}(-1)^n \cdot\left(\frac{1}{z^2}\right)^n . \end{aligned}f(z)=110(1+12z)1+2z51z2(1+1z2)1=1100(1)n(z2)n+2z5z20(1)n(1z2)n.
This is a series in positive and negative powers of z z zzz, so it is an expansion of f ( z ) f ( z ) f(z)f(z)f(z) in a Laurent’s series within the region 1 < | z | < 2 1 < | z | < 2 1 < |z| < 21<|z|<21<|z|<2.
(iii) | z | > 2 | z | > 2 |z| > 2|z|>2|z|>2
f ( z ) = 1 5 1 z + 2 1 5 z 2 1 + z 2 = 1 5 z ( 1 + 2 z ) 1 1 5 ( z 2 ) 1 z 2 ( 1 + 1 z 2 ) 1 = 1 5 z ( 0 ( 1 ) n ( 2 z ) n ) 1 5 ( 1 z 2 z 2 ) 0 ( 1 ) n ( 1 z 2 ) n f ( z ) = 1 5 1 z + 2 1 5 z 2 1 + z 2 = 1 5 z 1 + 2 z 1 1 5 ( z 2 ) 1 z 2 1 + 1 z 2 1 = 1 5 z 0 ( 1 ) n 2 z n 1 5 1 z 2 z 2 0 ( 1 ) n 1 z 2 n {:[f(z)=(1)/(5)*(1)/(z+2)-(1)/(5)*(z-2)/(1+z^(2))],[=(1)/(5z)(1+(2)/(z))^(-1)-(1)/(5)(z-2)*(1)/(z^(2))(1+(1)/(z^(2)))^(-1)],[=(1)/(5z)(sum_(0)^(oo)(-1)^(n)((2)/(z))^(n))-(1)/(5)((1)/(z)-(2)/(z^(2)))sum_(0)^(oo)(-1)^(n)((1)/(z^(2)))^(n)]:}\begin{aligned} f(z) & =\frac{1}{5} \cdot \frac{1}{z+2}-\frac{1}{5} \cdot \frac{z-2}{1+z^2} \\ & =\frac{1}{5 z}\left(1+\frac{2}{z}\right)^{-1}-\frac{1}{5}(z-2) \cdot \frac{1}{z^2}\left(1+\frac{1}{z^2}\right)^{-1} \\ & =\frac{1}{5 z}\left(\sum_0^{\infty}(-1)^n\left(\frac{2}{z}\right)^n\right)-\frac{1}{5}\left(\frac{1}{z}-\frac{2}{z^2}\right) \sum_0^{\infty}(-1)^n\left(\frac{1}{z^2}\right)^n \end{aligned}f(z)=151z+215z21+z2=15z(1+2z)115(z2)1z2(1+1z2)1=15z(0(1)n(2z)n)15(1z2z2)0(1)n(1z2)n
This is Laurent’s series within the ring shaped region (or annulus) 2 < z < R 2 < z < R 2 < z < R2<z<\mathrm{R}2<z<R where R R R\mathrm{R}R is large.
4.(c) एक फैक्ट्री में पाँच प्रचालक O 1 , O 2 , O 3 , O 4 , O 5 O 1 , O 2 , O 3 , O 4 , O 5 O_(1),O_(2),O_(3),O_(4),O_(5)\mathrm{O}_1, \mathrm{O}_2, \mathrm{O}_3, \mathrm{O}_4, \mathrm{O}_5O1,O2,O3,O4,O5 तथा पाँच मशीनें M 1 , M 2 , M 3 , M 4 , M 5 M 1 , M 2 , M 3 , M 4 , M 5 M_(1),M_(2),M_(3),M_(4),M_(5)\mathrm{M}_1, \mathrm{M}_2, \mathrm{M}_3, \mathrm{M}_4, \mathrm{M}_5M1,M2,M3,M4,M5 हैं । परिचालन लागत, जब कि O i O i O_(i)\mathrm{O}_{\mathrm{i}}Oi प्रचालक M j ( i , j = 1 , 2 , , 5 ) M j ( i , j = 1 , 2 , , 5 ) M_(j)(i,j=1,2,dots,5)\mathrm{M}_{\mathrm{j}}(\mathrm{i}, \mathrm{j}=1,2, \ldots, 5)Mj(i,j=1,2,,5) मशीन को परिचालन करता है, दी गई हैं। लेकिन एक प्रतिबन्ध है कि O 3 O 3 O_(3)\mathrm{O}_3O3 को तीसरी मशीन M 3 M 3 M_(3)\mathrm{M}_3M3 का परिचालन करने तथा O 2 O 2 O_(2)\mathrm{O}_2O2 को पाँचर्वीं मरीन M 5 M 5 M_(5)\mathrm{M}_5M5 का परिचालन करने की इजाज़त नह्ही दी जा सकती है। लागत आव्यूह नीचे दी है । इएतम नियतन तथा इए्टम नियतन की लागत ज्ञात कीजिए।
M 1 M 2 M 3 M 4 M 5 O 1 24 29 18 32 19 O 2 17 26 34 22 21 O 3 27 16 28 17 25 O 4 22 18 28 30 24 O 5 28 16 31 24 27 M 1 M 2 M 3 M 4 M 5 O 1 24 29 18 32 19 O 2 17 26 34 22 21 O 3 27 16 28 17 25 O 4 22 18 28 30 24 O 5 28 16 31 24 27 [,M_(1),M_(2),M_(3),M_(4),M_(5)],[O_(1),24,29,18,32,19],[O_(2),17,26,34,22,21],[O_(3),27,16,28,17,25],[O_(4),22,18,28,30,24],[O_(5),28,16,31,24,27]\begin{array}{rrrrrr} \hline & M_1 & M_2 & M_3 & M_4 & M_5 \\ \hline O_1 & 24 & 29 & 18 & 32 & 19 \\ \hline O_2 & 17 & 26 & 34 & 22 & 21 \\ \hline O_3 & 27 & 16 & 28 & 17 & 25 \\ \hline O_4 & 22 & 18 & 28 & 30 & 24 \\ \hline O_5 & 28 & 16 & 31 & 24 & 27 \\ \hline \end{array}M1M2M3M4M5O12429183219O21726342221O32716281725O42218283024O52816312427
In a factory there are five operators O 1 , O 2 , O 3 , O 4 , O 5 O 1 , O 2 , O 3 , O 4 , O 5 O_(1),O_(2),O_(3),O_(4),O_(5)\mathrm{O}_1, \mathrm{O}_2, \mathrm{O}_3, \mathrm{O}_4, \mathrm{O}_5O1,O2,O3,O4,O5 and five machines M 1 , M 2 , M 3 , M 4 , M 5 M 1 , M 2 , M 3 , M 4 , M 5 M_(1),M_(2),M_(3),M_(4),M_(5)\mathrm{M}_1, \mathrm{M}_2, \mathrm{M}_3, \mathrm{M}_4, \mathrm{M}_5M1,M2,M3,M4,M5. The operating costs are given when the O 1 O 1 O_(1)\mathrm{O}_1O1 operator operates the M j M j M_(j)\mathrm{M}_jMj machine ( i , j = 1 , 2 , , 5 ) ( i , j = 1 , 2 , , 5 ) (i,j=1,2,dots,5)(\mathrm{i}, \mathrm{j}=1,2, \ldots, 5)(i,j=1,2,,5). But there is a restriction that O 3 O 3 O_(3)\mathrm{O}_3O3 cannot be allowed to operate the third machine M 3 M 3 M_(3)\mathrm{M}_3M3 and O 2 O 2 O_(2)\mathrm{O}_2O2 cannot be allowed to operate the fifth machine M 5 + M 5 + M_(5+)\mathrm{M}_{5+}M5+ The cost matrix is given above. Find the optimal assignment and the optimal assignment cost also.
M 1 M 2 M 3 M 4 M 5 O 1 24 29 18 32 19 O 2 17 26 34 22 21 O 3 27 16 28 17 25 O 4 22 18 28 30 24 O 5 28 16 31 24 27 M 1 M 2 M 3 M 4 M 5 O 1 24 29 18 32 19 O 2 17 26 34 22 21 O 3 27 16 28 17 25 O 4 22 18 28 30 24 O 5 28 16 31 24 27 [,M_(1),M_(2),M_(3),M_(4),M_(5)],[O_(1),24,29,18,32,19],[O_(2),17,26,34,22,21],[O_(3),27,16,28,17,25],[O_(4),22,18,28,30,24],[O_(5),28,16,31,24,27]\begin{array}{rrrrrr} \hline & M_1 & M_2 & M_3 & M_4 & M_5 \\ \hline O_1 & 24 & 29 & 18 & 32 & 19 \\ \hline O_2 & 17 & 26 & 34 & 22 & 21 \\ \hline O_3 & 27 & 16 & 28 & 17 & 25 \\ \hline O_4 & 22 & 18 & 28 & 30 & 24 \\ \hline O_5 & 28 & 16 & 31 & 24 & 27 \\ \hline \end{array}M1M2M3M4M5O12429183219O21726342221O32716281725O42218283024O52816312427
Answer:

Introduction

In the realm of operational research, assignment problems are pivotal, especially in manufacturing settings where optimal assignments of jobs to resources are crucial for efficiency and cost-effectiveness. This problem involves a factory with five operators, O 1 , O 2 , O 3 , O 4 , O 5 O 1 , O 2 , O 3 , O 4 , O 5 O_(1),O_(2),O_(3),O_(4),O_(5)O_1, O_2, O_3, O_4, O_5O1,O2,O3,O4,O5, and five machines, M 1 , M 2 , M 3 , M 4 , M 5 M 1 , M 2 , M 3 , M 4 , M 5 M_(1),M_(2),M_(3),M_(4),M_(5)M_1, M_2, M_3, M_4, M_5M1,M2,M3,M4,M5, each with associated operating costs. The objective is to find the optimal assignment of operators to machines such that the total operating cost is minimized, considering certain restrictions. Specifically, operator O 3 O 3 O_(3)O_3O3 is not allowed to operate machine M 3 M 3 M_(3)M_3M3, and operator O 2 O 2 O_(2)O_2O2 is not allowed to operate machine M 5 M 5 M_(5)M_5M5.
This is the original cost matrix:
24 29 18 32 19 17 26 34 22 21 27 16 28 17 25 22 18 28 30 24 28 16 31 24 27 24 29 18 32 19 17 26 34 22 21 27 16 28 17 25 22 18 28 30 24 28 16 31 24 27 {:[24,29,18,32,19],[17,26,34,22,21],[27,16,28,17,25],[22,18,28,30,24],[28,16,31,24,27]:}\begin{array}{lllll}24 & 29 & 18 & 32 & 19 \\ 17 & 26 & 34 & 22 & 21 \\ 27 & 16 & 28 & 17 & 25 \\ 22 & 18 & 28 & 30 & 24 \\ 28 & 16 & 31 & 24 & 27\end{array}24291832191726342221271628172522182830242816312427
Subtract row minima
We subtract the row minimum from each row:
6 11 0 14 1 ( 18 ) 0 9 17 5 4 ( 17 ) 11 0 12 1 9 ( 16 ) 4 0 10 12 6 ( 18 ) 12 0 15 8 11 ( 16 ) 6 11 0 14 1 ( 18 ) 0 9 17 5 4 ( 17 ) 11 0 12 1 9 ( 16 ) 4 0 10 12 6 ( 18 ) 12 0 15 8 11 ( 16 ) {:[6,11,0,14,1,(-18)],[0,9,17,5,4,(-17)],[11,0,12,1,9,(-16)],[4,0,10,12,6,(-18)],[12,0,15,8,11,(-16)]:}\begin{array}{rrrrrr}6 & 11 & 0 & 14 & 1 & (-18) \\ 0 & 9 & 17 & 5 & 4 & (-17) \\ 11 & 0 & 12 & 1 & 9 & (-16) \\ 4 & 0 & 10 & 12 & 6 & (-18) \\ 12 & 0 & 15 & 8 & 11 & (-16)\end{array}6110141(18)091754(17)1101219(16)4010126(18)12015811(16)
Subtract column minima
We subtract the column minimum from each column:
6 11 0 13 0 0 9 17 4 3 11 0 12 0 8 4 0 10 11 5 12 0 15 7 10 ( 1 ) ( 1 ) 6 11 0 13 0 0 9 17 4 3 11 0 12 0 8 4 0 10 11 5 12 0 15 7 10 ( 1 ) ( 1 ) {:[6,11,0,13,0],[0,9,17,4,3],[11,0,12,0,8],[4,0,10,11,5],[12,0,15,7,10],[,,,(-1),(-1)]:}\begin{array}{rrrrr} 6 & 11 & 0 & 13 & 0 \\ 0 & 9 & 17 & 4 & 3 \\ 11 & 0 & 12 & 0 & 8 \\ 4 & 0 & 10 & 11 & 5 \\ 12 & 0 & 15 & 7 & 10 \\ & & & (-1) & (-1) \end{array}61101300917431101208401011512015710(1)(1)
Cover all zeros with a minimum number of lines
There are 4 lines required to cover all zeros:
6 6 6\mathbf{6}6 1 1 1 1 11\mathbf{1 1}11 0 0 0\mathbf{0}0 1 3 1 3 13\mathbf{1 3}13 0 0 0\mathbf{0}0 x x x\mathbf{x}x
0 0 0\mathbf{0}0 9 9 9\mathbf{9}9 1 7 1 7 17\mathbf{1 7}17 4 4 4\mathbf{4}4 3 3 3\mathbf{3}3 x x x\mathbf{x}x
1 1 1 1 11\mathbf{1 1}11 0 0 0\mathbf{0}0 1 2 1 2 12\mathbf{1 2}12 0 0 0\mathbf{0}0 8 8 8\mathbf{8}8 x x x\mathbf{x}x
4 4 4\mathbf{4}4 0 0 0\mathbf{0}0 10 11 5
12 0 0 0\mathbf{0}0 15 7 10
x x x\mathbf{x}x
6 11 0 13 0 x 0 9 17 4 3 x 11 0 12 0 8 x 4 0 10 11 5 12 0 15 7 10 x | $\mathbf{6}$ | $\mathbf{1 1}$ | $\mathbf{0}$ | $\mathbf{1 3}$ | $\mathbf{0}$ | $\mathbf{x}$ | | —: | —: | —: | —: | —: | —: | | $\mathbf{0}$ | $\mathbf{9}$ | $\mathbf{1 7}$ | $\mathbf{4}$ | $\mathbf{3}$ | $\mathbf{x}$ | | $\mathbf{1 1}$ | $\mathbf{0}$ | $\mathbf{1 2}$ | $\mathbf{0}$ | $\mathbf{8}$ | $\mathbf{x}$ | | $\mathbf{4}$ | $\mathbf{0}$ | 10 | 11 | 5 | | | 12 | $\mathbf{0}$ | 15 | 7 | 10 | | | | $\mathbf{x}$ | | | | |
Create additional zeros
The number of lines is smaller than 5 5 5\mathbf{5}5. The smallest uncovered number is 4 . We subtract this number from all uncovered elements and add it to all elements that are covered twice:
6 15 0 13 0 0 13 17 4 3 11 4 12 0 8 0 0 6 7 1 8 0 11 3 6 6 15 0 13 0 0 13 17 4 3 11 4 12 0 8 0 0 6 7 1 8 0 11 3 6 {:[6,15,0,13,0],[0,13,17,4,3],[11,4,12,0,8],[0,0,6,7,1],[8,0,11,3,6]:}\begin{array}{rrrrr}6 & 15 & 0 & 13 & 0 \\ 0 & 13 & 17 & 4 & 3 \\ 11 & 4 & 12 & 0 & 8 \\ 0 & 0 & 6 & 7 & 1 \\ 8 & 0 & 11 & 3 & 6\end{array}61501300131743114120800671801136
Cover all zeros with a minimum number of lines
There are 4 lines required to cover all zeros:
6 1 5 0 1 3 0 x 0 1 3 17 4 3 1 1 4 1 2 0 8 x 0 0 6 7 1 8 0 11 3 6 x x 6 1 5 0 1 3 0 x 0 1 3 17 4 3 1 1 4 1 2 0 8 x 0 0 6 7 1 8 0 11 3 6 x x {:[6,15,0,13,0,x],[0,13,17,4,3,],[11,4,12,0,8,x],[0,0,6,7,1,],[8,0,11,3,6,],[x,x,,,,]:}\begin{array}{rrrrrr}\mathbf{6} & \mathbf{1 5} & \mathbf{0} & \mathbf{1 3} & \mathbf{0} & \mathbf{x} \\ \mathbf{0} & \mathbf{1 3} & 17 & 4 & 3 & \\ \mathbf{1 1} & \mathbf{4} & \mathbf{1 2} & \mathbf{0} & \mathbf{8} & \mathbf{x} \\ \mathbf{0} & \mathbf{0} & 6 & 7 & 1 & \\ \mathbf{8} & \mathbf{0} & 11 & 3 & 6 & \\ \mathbf{x} & \mathbf{x} & & & & \end{array}6150130x01317431141208x00671801136xx
Create additional zeros
The number of lines is smaller than 5 5 5\mathbf{5}5. The smallest uncovered number is 1 . We subtract this number from all uncovered elements and add it to all elements that are covered twice:
7 16 0 13 0 0 13 16 3 2 12 5 12 0 8 0 0 5 6 0 8 0 10 2 5 7 16 0 13 0 0 13 16 3 2 12 5 12 0 8 0 0 5 6 0 8 0 10 2 5 {:[7,16,0,13,0],[0,13,16,3,2],[12,5,12,0,8],[0,0,5,6,0],[8,0,10,2,5]:}\begin{array}{rrrrr}7 & 16 & 0 & 13 & 0 \\ 0 & 13 & 16 & 3 & 2 \\ 12 & 5 & 12 & 0 & 8 \\ 0 & 0 & 5 & 6 & 0 \\ 8 & 0 & 10 & 2 & 5\end{array}71601300131632125120800560801025
Cover all zeros with a minimum number of lines
There are 5 lines required to cover all zeros:
7 16 0 13 0 x 0 13 16 3 2 x 12 5 12 0 8 x 0 0 5 6 0 x 8 0 10 2 5 x 7 16 0 13 0 x 0 13 16 3 2 x 12 5 12 0 8 x 0 0 5 6 0 x 8 0 10 2 5 x {:[7,16,0,13,0,x],[0,13,16,3,2,x],[12,5,12,0,8,x],[0,0,5,6,0,x],[8,0,10,2,5,x]:}\begin{array}{rrrrrr}7 & 16 & 0 & 13 & 0 & x \\ 0 & 13 & 16 & 3 & 2 & x \\ 12 & 5 & 12 & 0 & 8 & x \\ 0 & 0 & 5 & 6 & 0 & x \\ 8 & 0 & 10 & 2 & 5 & x\end{array}7160130x0131632x1251208x00560x801025x
The optimal assignment
Because there are 5 lines required, the zeros cover an optimal assignment:
7 16 0 13 0 0 13 16 3 2 12 5 12 0 8 0 0 5 6 0 8 0 10 2 5 7 16 0 13 0 0 13 16 3 2 12 5 12 0 8 0 0 5 6 0 8 0 10 2 5 [[7,16,0,13,0],[0,13,16,3,2],[12,5,12,0,8],[0,0,5,6,0],[8,0,10,2,5]]\begin{array}{|rrrrr|}7 & 16 & \mathbf{0} & 13 & 0 \\ \mathbf{0} & 13 & 16 & 3 & 2 \\ 12 & 5 & 12 & \mathbf{0} & 8 \\ 0 & 0 & 5 & 6 & \mathbf{0} \\ 8 & \mathbf{0} & 10 & 2 & 5\end{array}71601300131632125120800560801025
This corresponds to the following optimal assignment in the original cost matrix:
24 29 1 8 1 8 18\mathbf{1 8}18 32 19
1 7 1 7 17\mathbf{1 7}17 26 34 22 21
27 16 28 1 7 1 7 17\mathbf{1 7}17 25
22 18 28 30 2 4 2 4 24\mathbf{2 4}24
28 1 6 1 6 16\mathbf{1 6}16 31 24 27
24 29 18 32 19 17 26 34 22 21 27 16 28 17 25 22 18 28 30 24 28 16 31 24 27| 24 | 29 | $\mathbf{1 8}$ | 32 | 19 | | :— | :— | :— | :— | :— | | $\mathbf{1 7}$ | 26 | 34 | 22 | 21 | | 27 | 16 | 28 | $\mathbf{1 7}$ | 25 | | 22 | 18 | 28 | 30 | $\mathbf{2 4}$ | | 28 | $\mathbf{1 6}$ | 31 | 24 | 27 |
The optimal value equals 92 .

Conclusion

Through meticulous application of the Hungarian Algorithm, we have successfully determined the optimal assignment of operators to machines, adhering to the given restrictions and minimizing the total operating cost. The optimal assignments are as follows: O 1 O 1 O_(1)O_1O1 to M 3 M 3 M_(3)M_3M3, O 2 O 2 O_(2)O_2O2 to M 1 M 1 M_(1)M_1M1, O 3 O 3 O_(3)O_3O3 to M 4 M 4 M_(4)M_4M4, O 4 O 4 O_(4)O_4O4 to M 5 M 5 M_(5)M_5M5, and O 5 O 5 O_(5)O_5O5 to M 2 M 2 M_(2)M_2M2, resulting in a minimized total operating cost of 92. This optimal assignment ensures that the factory operates at the highest possible efficiency, given the constraints, and incurs the least amount of operating cost, thereby maximizing the overall productivity and cost-effectiveness of the manufacturing process.
खण्ड ‘B’ SECTION ‘B’
5.(a) दीर्घवृत्तज : x 2 + 4 y 2 + 4 z 2 = 4 x 2 + 4 y 2 + 4 z 2 = 4 x^(2)+4y^(2)+4z^(2)=4x^2+4 y^2+4 z^2=4x2+4y2+4z2=4 के उन समी स्पर्श-तलों के संकाय का आंशिक अवकल समीकरण ज्ञात कीजिए, जो x y x y xyx yxy समतल के लम्बवत नहीं हैं।
Find the partial differential equation of the family of all tangent planes to the ellipsoid: x 2 + 4 y 2 + 4 z 2 = 4 x 2 + 4 y 2 + 4 z 2 = 4 x^(2)+4y^(2)+4z^(2)=4x^2+4 y^2+4 z^2=4x2+4y2+4z2=4, which are not perpendicular to the x y x y xyx yxy plane.
Answer:

Given Ellipsoid

The given ellipsoid is represented by the equation:
x 2 + 4 y 2 + 4 z 2 = 4 (1) x 2 + 4 y 2 + 4 z 2 = 4 (1) x^(2)+4y^(2)+4z^(2)=4quad(1)x^2 + 4y^2 + 4z^2 = 4 \quad \text{(1)}x2+4y2+4z2=4(1)

Tangent Plane to the Ellipsoid

The equation of the tangent plane to the ellipsoid at a point P ( x 1 , y 1 , z 1 ) P ( x 1 , y 1 , z 1 ) P(x_(1),y_(1),z_(1))P(x_1, y_1, z_1)P(x1,y1,z1) is given by:
x x 1 + 4 y y 1 + 4 z z 1 = 4 (2) x x 1 + 4 y y 1 + 4 z z 1 = 4 (2) xx_(1)+4yy_(1)+4zz_(1)=4quad(2)x x_1 + 4y y_1 + 4z z_1 = 4 \quad \text{(2)}xx1+4yy1+4zz1=4(2)

General Equation of a Plane

Let the general equation of a plane be represented as:
l x + m y + n z = P (3) l x + m y + n z = P (3) lx+my+nz=P quad(3)lx + my + nz = P \quad \text{(3)}lx+my+nz=P(3)

Coefficient Relations

Comparing the coefficients in equations (2) and (3), we have:
x 1 l = 4 y 1 m = 4 z 1 n = 4 P (4) x 1 l = 4 y 1 m = 4 z 1 n = 4 P (4) (x_(1))/(l)=(4y_(1))/(m)=(4z_(1))/(n)=(4)/(P)quad(4)\frac{x_1}{l} = \frac{4y_1}{m} = \frac{4z_1}{n} = \frac{4}{P} \quad \text{(4)}x1l=4y1m=4z1n=4P(4)
From equation (4), we can express x 1 x 1 x_(1)x_1x1, y 1 y 1 y_(1)y_1y1, and z 1 z 1 z_(1)z_1z1 as:
x 1 = 4 l P y 1 = m P z 1 = n P (5) x 1 = 4 l P y 1 = m P z 1 = n P (5) x_(1)=(4l)/(P)quady_(1)=(m)/(P)quadz_(1)=(n)/(P)quad(5)x_1 = \frac{4l}{P} \quad y_1 = \frac{m}{P} \quad z_1 = \frac{n}{P} \quad \text{(5)}x1=4lPy1=mPz1=nP(5)

Substituting Back into the Ellipsoid Equation

Substituting equation (5) back into equation (1) gives:
16 l 2 P 2 + 4 m 2 P 2 + 4 n 2 P 2 = 4 (6) 16 l 2 P 2 + 4 m 2 P 2 + 4 n 2 P 2 = 4 (6) (16l^(2))/(P^(2))+(4m^(2))/(P^(2))+(4n^(2))/(P^(2))=4quad(6)\frac{16l^2}{P^2} + \frac{4m^2}{P^2} + \frac{4n^2}{P^2} = 4 \quad \text{(6)}16l2P2+4m2P2+4n2P2=4(6)
4 l 2 + m 2 + n 2 = P 2 (7) 4 l 2 + m 2 + n 2 = P 2 (7) =>4l^(2)+m^(2)+n^(2)=P^(2)quad(7)\Rightarrow 4l^2 + m^2 + n^2 = P^2 \quad \text{(7)}4l2+m2+n2=P2(7)

Equation of the Tangent Plane

Substituting the values from equation (4) into equation (3) gives the equation of the tangent plane as:
l x + m y + n z = ± 4 l 2 + m 2 + n 2 (8) l x + m y + n z = ± 4 l 2 + m 2 + n 2 (8) lx+my+nz=+-sqrt(4l^(2)+m^(2)+n^(2))quad(8)lx + my + nz = \pm \sqrt{4l^2 + m^2 + n^2} \quad \text{(8)}lx+my+nz=±4l2+m2+n2(8)

Condition for the Plane not being Perpendicular to the x y x y xyxyxy-plane

Since the plane is not perpendicular to the x y x y xyxyxy-plane, we can write equation (8) as:
l n x + m n y + z = ± 4 ( l n ) 2 + ( m n ) 2 + 1 l n x + m n y + z = ± 4 l n 2 + m n 2 + 1 (l)/(n)x+(m)/(n)y+z=+-sqrt(4((l)/(n))^(2)+((m)/(n))^(2)+1)\frac{l}{n} x+\frac{m}{n} y+z= \pm \sqrt{4\left(\frac{l}{n}\right)^2+\left(\frac{m}{n}\right)^2+1}lnx+mny+z=±4(ln)2+(mn)2+1
α x + β y + z = ± 4 α 2 + β 2 + 1 (9) α x + β y + z = ± 4 α 2 + β 2 + 1 (9) alpha x+beta y+z=+-sqrt(4alpha^(2)+beta^(2)+1)quad(9)\alpha x + \beta y + z = \pm \sqrt{4\alpha^2 + \beta^2 + 1} \quad \text{(9)}αx+βy+z=±4α2+β2+1(9)

Partial Differential Equation

Differentiating equation (9) partially with respect to x x xxx and y y yyy, we get:
α + z x = 0 z x = α α = p (10) α + z x = 0 z x = α α = p (10) alpha+(del z)/(del x)=0quad=>quad(del z)/(del x)=-alphaquad=>quad alpha=-p quad(10)\alpha + \frac{\partial z}{\partial x} = 0 \quad \Rightarrow \quad \frac{\partial z}{\partial x} = -\alpha \quad \Rightarrow \quad \alpha = -p \quad \text{(10)}α+zx=0zx=αα=p(10)
β + z y = 0 z y = β β = q (11) β + z y = 0 z y = β β = q (11) beta+(del z)/(del y)=0quad=>quad(del z)/(del y)=-betaquad=>quad beta=-q quad(11)\beta + \frac{\partial z}{\partial y} = 0 \quad \Rightarrow \quad \frac{\partial z}{\partial y} = -\beta \quad \Rightarrow \quad \beta = -q \quad \text{(11)}β+zy=0zy=ββ=q(11)
Substituting equations (10) and (11) back into equation (9) gives:
p x + ( q ) y + z = ± 4 p 2 + q 2 + 1 (12) p x + ( q ) y + z = ± 4 p 2 + q 2 + 1 (12) -px+(-q)y+z=+-sqrt(4p^(2)+q^(2)+1)quad(12)-px + (-q)y + z = \pm \sqrt{4p^2 + q^2 + 1} \quad \text{(12)}px+(q)y+z=±4p2+q2+1(12)
( p x + q y z ) 2 = 4 p 2 + q 2 + 1 (13) ( p x + q y z ) 2 = 4 p 2 + q 2 + 1 (13) =>(px+qy-z)^(2)=4p^(2)+q^(2)+1quad(13)\Rightarrow (px + qy – z)^2 = 4p^2 + q^2 + 1 \quad \text{(13)}(px+qyz)2=4p2+q2+1(13)

Conclusion

Equation (13) is the required partial differential equation representing the family of all tangent planes to the given ellipsoid, which are not perpendicular to the x y x y xyxyxy-plane.
5.(b) न्यूटन के अग्रांतर फार्मूले से निम्नतम-घातीय बहुपद u x u x u_(x)u_xux ज्ञात कीजिए जब कि u 1 = 1 , u 2 = 9 u 1 = 1 , u 2 = 9 u_(1)=1,u_(2)=9u_1=1, u_2=9u1=1,u2=9, u 3 = 25 , u 4 = 55 u 3 = 25 , u 4 = 55 u_(3)=25,u_(4)=55u_3=25, u_4=55u3=25,u4=55 तथा u 5 = 105 u 5 = 105 u_(5)=105u_5=105u5=105 दिया गया है ।
Using Newton’s forward difference formula find the lowest degree polynomial u x u x u_(x)u_xux when it is given that u 1 = 1 , u 2 = 9 , u 3 = 25 , u 4 = 55 u 1 = 1 , u 2 = 9 , u 3 = 25 , u 4 = 55 u_(1)=1,u_(2)=9,u_(3)=25,u_(4)=55u_1=1, u_2=9, u_3=25, u_4=55u1=1,u2=9,u3=25,u4=55 and u 5 = 105 u 5 = 105 u_(5)=105u_5=105u5=105.
Answer:
The value of table for x x xxx and y y yyy
x x x\mathbf{x}x 1 2 3 4 5
y y y\mathbf{y}y 1 9 25 55 105
x 1 2 3 4 5 y 1 9 25 55 105| $\mathbf{x}$ | 1 | 2 | 3 | 4 | 5 | | :—: | :—: | :—: | :—: | :—: | :—: | | $\mathbf{y}$ | 1 | 9 | 25 | 55 | 105 |
Newton’s forward difference interpolation method to find solution
Newton’s forward difference table is
x x x\mathbf{x}x y y y\mathbf{y}y Δ y Δ y Delta y\boldsymbol{\Delta y}Δy Δ 2 y Δ 2 y Delta^(2)y\Delta^{\mathbf{2}} \boldsymbol{y}Δ2y Δ 3 y Δ 3 y Delta^(3)y\Delta^{\mathbf{3}} yΔ3y Δ 4 Δ 4 Delta^(4)\boldsymbol{\Delta}^{\mathbf{4}} \boldsymbol{~}Δ4 
1 1 1\mathbf{1}1 1 1 1\mathbf{1}1
8 8 8\mathbf{8}8
2 2 2\mathbf{2}2 9 8 8 8\mathbf{8}8
16 6 6 6\mathbf{6}6
3 3 3\mathbf{3}3 2 5 2 5 25\mathbf{2 5}25 14 0 0 0\mathbf{0}0
30 6
4 4 4\mathbf{4}4 5 5 5 5 55\mathbf{5 5}55 20
50
5 5 5\mathbf{5}5 105
x y Delta y Delta^(2)y Delta^(3)y Delta^(4) 1 1 8 2 9 8 16 6 3 25 14 0 30 6 4 55 20 50 5 105 | $\mathbf{x}$ | $\mathbf{y}$ | $\boldsymbol{\Delta y}$ | $\Delta^{\mathbf{2}} \boldsymbol{y}$ | $\Delta^{\mathbf{3}} y$ | $\boldsymbol{\Delta}^{\mathbf{4}} \boldsymbol{~}$ | | :—: | :—: | :—: | :—: | :—: | :—: | | $\mathbf{1}$ | $\mathbf{1}$ | | | | | | | | $\mathbf{8}$ | | | | | $\mathbf{2}$ | 9 | | $\mathbf{8}$ | | | | | | 16 | | $\mathbf{6}$ | | | $\mathbf{3}$ | $\mathbf{2 5}$ | | 14 | | $\mathbf{0}$ | | | | 30 | | 6 | | | $\mathbf{4}$ | $\mathbf{5 5}$ | | 20 | | | | | | 50 | | | | | $\mathbf{5}$ | 105 | | | | |
Newton’s forward difference interpolation formula is
y ( x ) = y 0 + p Δ y 0 + p ( p 1 ) 2 ! Δ 2 y 0 + p ( p 1 ) ( p 2 ) 3 ! Δ 3 y 0 + p ( p 1 ) ( p 2 ) ( p 3 ) 4 ! Δ 4 y 0 p = x x 0 h = x 1 1 = x 1 y ( x ) = y 0 + p Δ y 0 + p ( p 1 ) 2 ! Δ 2 y 0 + p ( p 1 ) ( p 2 ) 3 ! Δ 3 y 0 + p ( p 1 ) ( p 2 ) ( p 3 ) 4 ! Δ 4 y 0 p = x x 0 h = x 1 1 = x 1 {:[y(x)=y_(0)+p Deltay_(0)+(p(p-1))/(2!)*Delta^(2)y_(0)+(p(p-1)(p-2))/(3!)*Delta^(3)y_(0)+(p(p-1)(p-2)(p-3))/(4!)*Delta^(4)y_(0)],[p=(x-x_(0))/(h)=(x-1)/(1)=x-1]:}\begin{aligned} & y(x)=y_0+p \Delta y_0+\frac{p(p-1)}{2 !} \cdot \Delta^2 y_0+\frac{p(p-1)(p-2)}{3 !} \cdot \Delta^3 y_0+\frac{p(p-1)(p-2)(p-3)}{4 !} \cdot \Delta^4 y_0 \\ & p=\frac{x-x_0}{h}=\frac{x-1}{1}=x-1 \end{aligned}y(x)=y0+pΔy0+p(p1)2!Δ2y0+p(p1)(p2)3!Δ3y0+p(p1)(p2)(p3)4!Δ4y0p=xx0h=x11=x1
Substituting these values, we get
y ( x ) = 1 + ( x 1 ) × 8 + ( x 1 ) ( x 2 ) 2 × 8 + ( x 1 ) ( x 2 ) ( x 3 ) 6 × 6 + ( x 1 ) ( x 2 ) ( x 3 ) ( x 4 ) 24 × 0 y ( x ) = 1 + 8 × ( x 1 ) + 4 × ( x 2 3 x + 2 ) + 1 × ( x 3 6 x 2 + 11 x 6 ) y ( x ) = 1 + ( 8 x 8 ) + ( 4 x 2 12 x + 8 ) + ( x 3 6 x 2 + 11 x 6 ) y ( x ) = x 3 2 x 2 + 7 x 5 y ( x ) = 1 + ( x 1 ) × 8 + ( x 1 ) ( x 2 ) 2 × 8 + ( x 1 ) ( x 2 ) ( x 3 ) 6 × 6 + ( x 1 ) ( x 2 ) ( x 3 ) ( x 4 ) 24 × 0 y ( x ) = 1 + 8 × ( x 1 ) + 4 × x 2 3 x + 2 + 1 × x 3 6 x 2 + 11 x 6 y ( x ) = 1 + ( 8 x 8 ) + 4 x 2 12 x + 8 + x 3 6 x 2 + 11 x 6 y ( x ) = x 3 2 x 2 + 7 x 5 {:[y(x)=1+(x-1)xx8+((x-1)(x-2))/(2)xx8+((x-1)(x-2)(x-3))/(6)xx6+((x-1)(x-2)(x-3)(x-4))/(24)xx0],[y(x)=1+8xx(x-1)+4xx(x^(2)-3x+2)+1xx(x^(3)-6x^(2)+11 x-6)],[y(x)=1+(8x-8)+(4x^(2)-12 x+8)+(x^(3)-6x^(2)+11 x-6)],[y(x)=x^(3)-2x^(2)+7x-5]:}\begin{aligned} & y(x)=1+(x-1) \times 8+\frac{(x-1)(x-2)}{2} \times 8+\frac{(x-1)(x-2)(x-3)}{6} \times 6+\frac{(x-1)(x-2)(x-3)(x-4)}{24} \times 0 \\ & y(x)=1+8 \times(x-1)+4 \times\left(x^2-3 x+2\right)+1 \times\left(x^3-6 x^2+11 x-6\right) \\ & y(x)=1+(8 x-8)+\left(4 x^2-12 x+8\right)+\left(x^3-6 x^2+11 x-6\right) \\ & y(x)=x^3-2 x^2+7 x-5 \end{aligned}y(x)=1+(x1)×8+(x1)(x2)2×8+(x1)(x2)(x3)6×6+(x1)(x2)(x3)(x4)24×0y(x)=1+8×(x1)+4×(x23x+2)+1×(x36x2+11x6)y(x)=1+(8x8)+(4x212x+8)+(x36x2+11x6)y(x)=x32x2+7x5
5.(c) एक असंपीडय तरल प्रवाह के लिए वेग ( u , v , w ) ( u , v , w ) (u,v,w)(u, v, w)(u,v,w) के दो घटक u = x 2 + 2 y 2 + 3 z 2 u = x 2 + 2 y 2 + 3 z 2 u=x^(2)+2y^(2)+3z^(2)u=x^2+2 y^2+3 z^2u=x2+2y2+3z2 v = x 2 y y 2 z + z x v = x 2 y y 2 z + z x v=x^(2)y-y^(2)z+zxv=x^2 y-y^2 z+z xv=x2yy2z+zx दिए गए हैं। वेग के तीसरे घटक w w www का निर्धारण कीजिए ताकि वे सांतत्य समीकरण को सन्तुष्ट करें। त्वरण के z z zzz-घटक को भी ज्ञात कीजिए।
For an incompressible fluid flow, two components of velocity ( u , v , w ) ( u , v , w ) (u,v,w)(u, v, w)(u,v,w) are given by u = x 2 + 2 y 2 + 3 z 2 , v = x 2 y y 2 z + z x u = x 2 + 2 y 2 + 3 z 2 , v = x 2 y y 2 z + z x u=x^(2)+2y^(2)+3z^(2),v=x^(2)y-y^(2)z+zxu=x^2+2 y^2+3 z^2, v=x^2 y-y^2 z+z xu=x2+2y2+3z2,v=x2yy2z+zx. Determine the third component w w www so that they satisfy the equation of continuity. Also, find the z-component of acceleration.
Answer:
Introduction:
In this problem, we are given two components of velocity ( u , v , w ) ( u , v , w ) (u,v,w)(u, v, w)(u,v,w) for an incompressible fluid flow, specifically u = x 2 + 2 y 2 + 3 z 2 u = x 2 + 2 y 2 + 3 z 2 u=x^(2)+2y^(2)+3z^(2)u = x^2 + 2y^2 + 3z^2u=x2+2y2+3z2 and v = x 2 y y 2 z + z x v = x 2 y y 2 z + z x v=x^(2)y-y^(2)z+zxv = x^2y – y^2z + zxv=x2yy2z+zx. The task is to determine the third component w w www such that the velocity components satisfy the equation of continuity. Additionally, we need to find the z z zzz-component of acceleration.
Step 1: Continuity Equation and Solving for w w www:
We start by applying the continuity equation for incompressible flow in Cartesian coordinates:
u x + v y + w z = 0 u x + v y + w z = 0 (del u)/(del x)+(del v)/(del y)+(del w)/(del z)=0\frac{\partial u}{\partial x} + \frac{\partial v}{\partial y} + \frac{\partial w}{\partial z} = 0ux+vy+wz=0
Plugging in the given expressions for u u uuu and v v vvv, we get:
2 x + x 2 2 y z + w z = 0 2 x + x 2 2 y z + w z = 0 2x+x^(2)-2yz+(del w)/(del z)=02x + x^2 – 2yz + \frac{\partial w}{\partial z} = 02x+x22yz+wz=0
Now, isolate w z w z (del w)/(del z)\frac{\partial w}{\partial z}wz by rearranging the equation:
w z = 2 y z 2 x x 2 w z = 2 y z 2 x x 2 (del w)/(del z)=2yz-2x-x^(2)\frac{\partial w}{\partial z} = 2yz – 2x – x^2wz=2yz2xx2
Step 2: Integrating to Find w w www:
To find w w www, we integrate the above equation with respect to z z zzz. This will involve an arbitrary function f ( x , y ) f ( x , y ) f(x,y)f(x, y)f(x,y) since we are integrating with respect to only one variable. The equation becomes:
w = y z 2 2 x z x 2 z + f ( x , y ) w = y z 2 2 x z x 2 z + f ( x , y ) w=yz^(2)-2xz-x^(2)z+f(x,y)w = yz^2 – 2xz – x^2z + f(x, y)w=yz22xzx2z+f(x,y)
So, w w www is given by the above expression, including the arbitrary function f ( x , y ) f ( x , y ) f(x,y)f(x, y)f(x,y).
Step 3: Finding the z z zzz-Component of Acceleration:
The z z zzz-component of acceleration a z a z a_(z)a_zaz is given by:
a z = ( q ) w + ω t a z = ( q ) w + ω t a_(z)=(q*grad)w+(del omega)/(del t)a_z =(q \cdot \nabla) w+\frac{\partial \omega}{\partial t}az=(q)w+ωt
a z = u w x + v w y + w w z a z = u w x + v w y + w w z a_(z)=u(del w)/(del x)+v(del w)/(del y)+w(del w)/(del z)a_z = u \frac{\partial w}{\partial x} + v \frac{\partial w}{\partial y} + w \frac{\partial w}{\partial z}az=uwx+vwy+wwz
Now, we need to substitute the given expressions for u u uuu, v v vvv, and w w www into this expression and calculate a z a z a_(z)a_zaz.
Therefore,
a z = ( x 2 + 2 y 2 + 3 z 2 ) ( f x 2 z 2 x z ) + ( x 2 y y 2 z + x z ) ( f y + z 2 ) + ( y z 2 2 x z x 2 z + f ( x , y ) ) ( 2 y z 2 z x 2 ) a z = x 2 + 2 y 2 + 3 z 2 f x 2 z 2 x z + x 2 y y 2 z + x z f y + z 2 + y z 2 2 x z x 2 z + f ( x , y ) 2 y z 2 z x 2 {:[a_(z)=(x^(2)+2y^(2)+3z^(2))((del f)/(del x)-2z-2xz)],[+(x^(2)y-y^(2)z+xz)((del f)/(del y)+z^(2))],[+(yz^(2)-2xz-x^(2)z+f(x,y))(2yz-2z-x^(2))]:}\begin{aligned} a_z & = \left(x^2 + 2y^2 + 3z^2\right)\left(\frac{\partial f}{\partial x} – 2z – 2xz\right) \\ & + \left(x^2y – y^2z + xz\right)\left(\frac{\partial f}{\partial y} + z^2\right) \\ & + \left(yz^2 – 2xz – x^2z + f(x, y)\right)\left(2yz – 2z – x^2\right) \end{aligned}az=(x2+2y2+3z2)(fx2z2xz)+(x2yy2z+xz)(fy+z2)+(yz22xzx2z+f(x,y))(2yz2zx2)
This expression represents the z z zzz-component of acceleration a z a z a_(z)a_zaz for the given velocity components u u uuu, v v vvv, and w w www.
Conclusion:
The third component w w www that satisfies the equation of continuity is given by w = y z 2 2 x z x 2 z + f ( x , y ) w = y z 2 2 x z x 2 z + f ( x , y ) w=yz^(2)-2xz-x^(2)z+f(x,y)w = yz^2 – 2xz – x^2z + f(x, y)w=yz22xzx2z+f(x,y), where f ( x , y ) f ( x , y ) f(x,y)f(x, y)f(x,y) is an arbitrary function of x x xxx and y y yyy.
The z z zzz-component of acceleration a z a z a_(z)a_zaz is given by the complex expression involving the derivatives of f ( x , y ) f ( x , y ) f(x,y)f(x, y)f(x,y) and the given velocity components.
5.(d) विराम अवस्था से प्रारम्भ हो कर एक रेलगाड़ी की रफतार (किमी/घं में) विभिन्न समयों (मिनट में) पर निम्न सारणी के द्वारा दी गई है :
सिम्पसन के 1 3 1 3 (1)/(3)\frac{1}{3}13 नियम के इस्तेमाल से प्रारंभ से 20 मिनटों में चली गई सन्तिकट दूरी (किमी. में) ज्ञात कीजिए ।
समय (मिनट) Time (Minutes) 2 4 6 8 10 12 14 16 18 20
रफ़तार (किमी /घं) Speed ( ( ((( Km/h ) ) ))) 10 18 25 29 32 20 11 5 2 8.5 8.5 8.58.58.5
समय (मिनट) Time (Minutes) 2 4 6 8 10 12 14 16 18 20 रफ़तार (किमी /घं) Speed ( Km/h ) 10 18 25 29 32 20 11 5 2 8.5| समय (मिनट) Time (Minutes) | 2 | 4 | 6 | 8 | 10 | 12 | 14 | 16 | 18 | 20 | | :— | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | :—: | | रफ़तार (किमी /घं) Speed $($ Km/h $)$ | 10 | 18 | 25 | 29 | 32 | 20 | 11 | 5 | 2 | $8.5$ |
Starting from rest in the beginning, the speed (in Km / h Km / h Km//h\mathrm{Km} / \mathrm{h}Km/h ) of a train at different times (in minutes) is given by the above table:
Using Simpson’s 1 3 1 3 (1)/(3)\frac{1}{3}13 rd rule, find the approximate distance travelled (in Km Km Km\mathrm{Km}Km ) in 20 minutes from the beginning.
Answer:
To find the approximate distance traveled using Simpson’s 1 3 1 3 (1)/(3)\frac{1}{3}13rd rule, we can use the formula:
Distance = h 3 [ y 0 + 4 ( y 1 + y 3 + + y n 1 ) + 2 ( y 2 + y 4 + + y n 2 ) + y n ] Distance = h 3 y 0 + 4 ( y 1 + y 3 + + y n 1 ) + 2 ( y 2 + y 4 + + y n 2 ) + y n “Distance”=(h)/(3)[y_(0)+4(y_(1)+y_(3)+dots+y_(n-1))+2(y_(2)+y_(4)+dots+y_(n-2))+y_(n)]\text{Distance} = \frac{h}{3} \left[ y_0 + 4(y_1 + y_3 + \ldots + y_{n-1}) + 2(y_2 + y_4 + \ldots + y_{n-2}) + y_n \right]Distance=h3[y0+4(y1+y3++yn1)+2(y2+y4++yn2)+yn]
Here, h h hhh is the width of each interval, y 0 , y 1 , , y n y 0 , y 1 , , y n y_(0),y_(1),dots,y_(n)y_0, y_1, \ldots, y_ny0,y1,,yn are the function values at each interval, and n n nnn is the number of intervals.

Given Data

The given data points are in minutes and km/h. We have 10 intervals of 2 minutes each, so h = 2 h = 2 h=2h = 2h=2 minutes = 1 30 = 1 30 =(1)/(30)= \frac{1}{30}=130 hours.
The speed values y 0 , y 1 , , y 10 y 0 , y 1 , , y 10 y_(0),y_(1),dots,y_(10)y_0, y_1, \ldots, y_{10}y0,y1,,y10 in km/h are given as:
  • y 0 = 0 y 0 = 0 y_(0)=0y_0 = 0y0=0 km/h (starting from rest)
  • y 1 = 10 y 1 = 10 y_(1)=10y_1 = 10y1=10 km/h
  • y 2 = 18 y 2 = 18 y_(2)=18y_2 = 18y2=18 km/h
  • y 3 = 25 y 3 = 25 y_(3)=25y_3 = 25y3=25 km/h
  • y 4 = 29 y 4 = 29 y_(4)=29y_4 = 29y4=29 km/h
  • y 5 = 32 y 5 = 32 y_(5)=32y_5 = 32y5=32 km/h
  • y 6 = 20 y 6 = 20 y_(6)=20y_6 = 20y6=20 km/h
  • y 7 = 11 y 7 = 11 y_(7)=11y_7 = 11y7=11 km/h
  • y 8 = 5 y 8 = 5 y_(8)=5y_8 = 5y8=5 km/h
  • y 9 = 2 y 9 = 2 y_(9)=2y_9 = 2y9=2 km/h
  • y 10 = 8.5 y 10 = 8.5 y_(10)=8.5y_{10} = 8.5y10=8.5 km/h

Calculation

Let’s substitute the given values into Simpson’s 1 3 1 3 (1)/(3)\frac{1}{3}13rd rule formula to find the approximate distance traveled in 20 minutes.

Substitution

Here is the substitution part with the given values:
  • Interval width, h = 2 h = 2 h=2h = 2h=2 minutes = 1 30 = 1 30 =(1)/(30)= \frac{1}{30}=130 hours.
  • Speed values, y 0 = 0 y 0 = 0 y_(0)=0y_0 = 0y0=0, y 1 = 10 y 1 = 10 y_(1)=10y_1 = 10y1=10, y 2 = 18 y 2 = 18 y_(2)=18y_2 = 18y2=18, y 3 = 25 y 3 = 25 y_(3)=25y_3 = 25y3=25, y 4 = 29 y 4 = 29 y_(4)=29y_4 = 29y4=29, y 5 = 32 y 5 = 32 y_(5)=32y_5 = 32y5=32, y 6 = 20 y 6 = 20 y_(6)=20y_6 = 20y6=20, y 7 = 11 y 7 = 11 y_(7)=11y_7 = 11y7=11, y 8 = 5 y 8 = 5 y_(8)=5y_8 = 5y8=5, y 9 = 2 y 9 = 2 y_(9)=2y_9 = 2y9=2, and y 10 = 8.5 y 10 = 8.5 y_(10)=8.5y_{10} = 8.5y10=8.5 km/h.
Substituting these into Simpson’s 1 3 1 3 (1)/(3)\frac{1}{3}13rd rule formula:
Distance = 1 30 3 [ 0 + 4 ( 10 + 25 + 32 + 11 + 2 ) + 2 ( 18 + 29 + 20 + 5 ) + 8.5 ] Distance = 1 30 3 0 + 4 ( 10 + 25 + 32 + 11 + 2 ) + 2 ( 18 + 29 + 20 + 5 ) + 8.5 “Distance”=((1)/(30))/(3)[0+4(10+25+32+11+2)+2(18+29+20+5)+8.5]\text{Distance} = \frac{\frac{1}{30}}{3} \left[ 0 + 4(10 + 25 + 32 + 11 + 2) + 2(18 + 29 + 20 + 5) + 8.5 \right]Distance=1303[0+4(10+25+32+11+2)+2(18+29+20+5)+8.5]
Distance = 5.25 Km Distance = 5.25  Km “Distance”=5.25″ Km”\text{Distance} = 5.25 \text{ Km}Distance=5.25 Km
This is the approximate distance traveled by the train in the first 20 minutes from the beginning.
5.(e) समीकरण : x e x 1 = 0 x e x 1 = 0 xe^(x)-1=0x e^x-1=0xex1=0 को द्विभाजन-विधि के द्वारा, दशमलव के 4 अंकों तक, हल करने के लिए, आधारी ऐल्लोरिथ्म लिखिए।
Write down the basic algorithm for solving the equation : x e x 1 = 0 x e x 1 = 0 xe^(x)-1=0x e^x-1=0xex1=0 by bisection method, correct to 4 decimal places.
Answer:
The Bisection Method is a root-finding algorithm that divides the interval into two subintervals and then selects the subinterval where the function changes sign, indicating the presence of a root. Here’s a basic algorithm to solve the equation x e x 1 = 0 x e x 1 = 0 xe^(x)-1=0xe^x – 1 = 0xex1=0 using the Bisection Method:

Algorithm for Bisection Method

Step 1: Define the Function

Define the function f ( x ) = x e x 1 f ( x ) = x e x 1 f(x)=xe^(x)-1f(x) = xe^x – 1f(x)=xex1.

Step 2: Choose Interval [a, b]

Choose an interval [ a , b ] [ a , b ] [a,b][a, b][a,b] such that f ( a ) f ( b ) < 0 f ( a ) f ( b ) < 0 f(a)*f(b) < 0f(a) \cdot f(b) < 0f(a)f(b)<0, indicating that there is a root in the interval.

Step 3: Calculate Midpoint

Calculate the midpoint c c ccc of the interval [ a , b ] [ a , b ] [a,b][a, b][a,b] as:
c = a + b 2 c = a + b 2 c=(a+b)/(2)c = \frac{a + b}{2}c=a+b2

Step 4: Evaluate Function at Midpoint

Evaluate the function at the midpoint:
f ( c ) = c e c 1 f ( c ) = c e c 1 f(c)=ce^(c)-1f(c) = ce^c – 1f(c)=cec1

Step 5: Update Interval

  • If f ( c ) = 0 f ( c ) = 0 f(c)=0f(c) = 0f(c)=0, then c c ccc is the root of the equation.
  • If f ( a ) f ( c ) < 0 f ( a ) f ( c ) < 0 f(a)*f(c) < 0f(a) \cdot f(c) < 0f(a)f(c)<0, then the root lies in the interval [ a , c ] [ a , c ] [a,c][a, c][a,c], so update b = c b = c b=cb = cb=c.
  • If f ( b ) f ( c ) < 0 f ( b ) f ( c ) < 0 f(b)*f(c) < 0f(b) \cdot f(c) < 0f(b)f(c)<0, then the root lies in the interval [ c , b ] [ c , b ] [c,b][c, b][c,b], so update a = c a = c a=ca = ca=c.

Step 6: Check Tolerance

Check if the width of the interval [ a , b ] [ a , b ] [a,b][a, b][a,b] is less than the desired tolerance, 10 4 10 4 10^(-4)10^{-4}104 for 4 decimal places. If the width is less than the tolerance, then stop the algorithm, and the midpoint c c ccc is the approximate root. Otherwise, go back to Step 3.

Step 7: Return the Root

Return the value of c c ccc as the approximate root of the equation, correct to 4 decimal places.
Its Iterations are; when we enter the values.
n a f ( a ) b f ( b ) c = a + b 2 f ( c ) Update 1 0 1 1 1.7183 0.5 0.1756 a = c 2 0.5 0.1756 1 1.7183 0.75 0.5878 b = c 3 0.5 0.1756 0.75 0.5878 0.625 0.1677 b = c 4 0.5 0.1756 0.625 0.1677 0.5625 0.0128 a = c 5 0.5625 0.0128 0.625 0.1677 0.5938 0.0751 b = c 6 0.5625 0.0128 0.5938 0.0751 0.5781 0.0306 b = c 7 0.5625 0.0128 0.5781 0.0306 0.5703 0.0088 b = c 8 0.5625 0.0128 0.5703 0.0088 0.5664 0.002 a = c 9 0.5664 0.002 0.5703 0.0088 0.5684 0.0034 b = c 10 0.5664 0.002 0.5684 0.0034 0.5674 0.0007 b = c 11 0.5664 0.002 0.5674 0.0007 0.5669 0.0007 a = c 12 0.5669 0.0007 0.5674 0.0007 0.5671 0 a = c n a f ( a ) b f ( b ) c = a + b 2 f ( c )  Update  1 0 1 1 1.7183 0.5 0.1756 a = c 2 0.5 0.1756 1 1.7183 0.75 0.5878 b = c 3 0.5 0.1756 0.75 0.5878 0.625 0.1677 b = c 4 0.5 0.1756 0.625 0.1677 0.5625 0.0128 a = c 5 0.5625 0.0128 0.625 0.1677 0.5938 0.0751 b = c 6 0.5625 0.0128 0.5938 0.0751 0.5781 0.0306 b = c 7 0.5625 0.0128 0.5781 0.0306 0.5703 0.0088 b = c 8 0.5625 0.0128 0.5703 0.0088 0.5664 0.002 a = c 9 0.5664 0.002 0.5703 0.0088 0.5684 0.0034 b = c 10 0.5664 0.002 0.5684 0.0034 0.5674 0.0007 b = c 11 0.5664 0.002 0.5674 0.0007 0.5669 0.0007 a = c 12 0.5669 0.0007 0.5674 0.0007 0.5671 0 a = c {:[n,a,f(a),b,f(b),c=(a+b)/(2),f(c),” Update “],[1,0,-1,1,1.7183,0.5,-0.1756,a=c],[2,0.5,-0.1756,1,1.7183,0.75,0.5878,b=c],[3,0.5,-0.1756,0.75,0.5878,0.625,0.1677,b=c],[4,0.5,-0.1756,0.625,0.1677,0.5625,-0.0128,a=c],[5,0.5625,-0.0128,0.625,0.1677,0.5938,0.0751,b=c],[6,0.5625,-0.0128,0.5938,0.0751,0.5781,0.0306,b=c],[7,0.5625,-0.0128,0.5781,0.0306,0.5703,0.0088,b=c],[8,0.5625,-0.0128,0.5703,0.0088,0.5664,-0.002,a=c],[9,0.5664,-0.002,0.5703,0.0088,0.5684,0.0034,b=c],[10,0.5664,-0.002,0.5684,0.0034,0.5674,0.0007,b=c],[11,0.5664,-0.002,0.5674,0.0007,0.5669,-0.0007,a=c],[12,0.5669,-0.0007,0.5674,0.0007,0.5671,0,a=c]:}\begin{array}{|c|c|c|c|c|c|c|c|} \hline \boldsymbol{n} & \boldsymbol{a} & \boldsymbol{f}(\boldsymbol{a}) & \boldsymbol{b} & \boldsymbol{f ( b )} & \boldsymbol{c}=\frac{\boldsymbol{a}+\boldsymbol{b}}{\mathbf{2}} & \boldsymbol{f}(\boldsymbol{c}) & \text { Update } \\ \hline 1 & 0 & -1 & 1 & 1.7183 & 0.5 & -0.1756 & a=c \\ \hline 2 & 0.5 & -0.1756 & 1 & 1.7183 & 0.75 & 0.5878 & b=c \\ \hline 3 & 0.5 & -0.1756 & 0.75 & 0.5878 & 0.625 & 0.1677 & b=c \\ \hline 4 & 0.5 & -0.1756 & 0.625 & 0.1677 & 0.5625 & -0.0128 & a=c \\ \hline 5 & 0.5625 & -0.0128 & 0.625 & 0.1677 & 0.5938 & 0.0751 & b=c \\ \hline 6 & 0.5625 & -0.0128 & 0.5938 & 0.0751 & 0.5781 & 0.0306 & b=c \\ \hline 7 & 0.5625 & -0.0128 & 0.5781 & 0.0306 & 0.5703 & 0.0088 & b=c \\ \hline 8 & 0.5625 & -0.0128 & 0.5703 & 0.0088 & 0.5664 & -0.002 & a=c \\ \hline 9 & 0.5664 & -0.002 & 0.5703 & 0.0088 & 0.5684 & 0.0034 & b=c \\ \hline 10 & 0.5664 & -0.002 & 0.5684 & 0.0034 & 0.5674 & 0.0007 & b=c \\ \hline 11 & 0.5664 & -0.002 & 0.5674 & 0.0007 & 0.5669 & -0.0007 & a=c \\ \hline 12 & 0.5669 & -0.0007 & 0.5674 & 0.0007 & 0.5671 & 0 & a=c \\ \hline \end{array}naf(a)bf(b)c=a+b2f(c) Update 10111.71830.50.1756a=c20.50.175611.71830.750.5878b=c30.50.17560.750.58780.6250.1677b=c40.50.17560.6250.16770.56250.0128a=c50.56250.01280.6250.16770.59380.0751b=c60.56250.01280.59380.07510.57810.0306b=c70.56250.01280.57810.03060.57030.0088b=c80.56250.01280.57030.00880.56640.002a=c90.56640.0020.57030.00880.56840.0034b=c100.56640.0020.56840.00340.56740.0007b=c110.56640.0020.56740.00070.56690.0007a=c120.56690.00070.56740.00070.56710a=c
  1. (a) आंशिक अवकल समीकरण :
( y 3 x 2 x 4 ) p + ( 2 y 4 x 3 y ) q = 9 z ( x 3 y 3 ) , का, y 3 x 2 x 4 p + 2 y 4 x 3 y q = 9 z x 3 y 3 , का,  (y^(3)x-2x^(4))p+(2y^(4)-x^(3)y)q=9z(x^(3)-y^(3))”, का, “\left(y^3 x-2 x^4\right) p+\left(2 y^4-x^3 y\right) q=9 z\left(x^3-y^3\right) \text {, का, }(y3x2x4)p+(2y4x3y)q=9z(x3y3), का, 
जहाँ p = z x , q = z y p = z x , q = z y p=(del z)/(del x),q=(del z)/(del y)p=\frac{\partial z}{\partial x}, q=\frac{\partial z}{\partial y}p=zx,q=zy है, का व्यापक हल ज्ञात कीजिए, तथा इसके, वक्र: x = t , y = t 2 , z = 1 x = t , y = t 2 , z = 1 x=t,y=t^(2),z=1x=t, y=t^2, z=1x=t,y=t2,z=1
में से गुजरने वाले समाकल पृष्ठ को भी ज्ञात कीजिए।
Find the general solution of the partial differential equation:
( y 3 x 2 x 4 ) p + ( 2 y 4 x 3 y ) q = 9 z ( x 3 y 3 ) , y 3 x 2 x 4 p + 2 y 4 x 3 y q = 9 z x 3 y 3 (y^(3)x-2x^(4))p+(2y^(4)-x^(3)y)q=9z(x^(3)-y^(3))”, “\left(y^3 x-2 x^4\right) p+\left(2 y^4-x^3 y\right) q=9 z\left(x^3-y^3\right) \text {, }(y3x2x4)p+(2y4x3y)q=9z(x3y3)
where p = z x , q = z y p = z x , q = z y p=(del z)/(del x),q=(del z)/(del y)p=\frac{\partial z}{\partial x}, q=\frac{\partial z}{\partial y}p=zx,q=zy, and find its integral surface that passes through the curve:
x = t , y = t 2 , z = 1 . x = t , y = t 2 , z = 1 x=t,y=t^(2),z=1″. “x=t, y=t^2, z=1 \text {. }x=t,y=t2,z=1
Answer:
Here Lagrange’s auxilliary equations are
d x y 3 x 2 x 4 = d y 2 y 4 x 3 y = d z 9 z ( x 3 y 3 ) ( 1 ) d x y 3 x 2 x 4 = d y 2 y 4 x 3 y = d z 9 z x 3 y 3 ( 1 ) (dx)/(y^(3)x-2x^(4))=(dy)/(2y^(4)-x^(3)y)=(dz)/(9z(x^(3)-y^(3)))—-(1)\frac{d x}{y^3 x-2 x^4}=\frac{d y}{2 y^4-x^3 y}=\frac{d z}{9 z\left(x^3-y^3\right)} —-(1)dxy3x2x4=dy2y4x3y=dz9z(x3y3)(1)
Choosing 1 x , 1 y , 1 3 z 1 x , 1 y , 1 3 z (1)/(x),(1)/(y),(1)/(3z)\frac{1}{\mathrm{x}}, \frac{1}{\mathrm{y}}, \frac{1}{3 \mathrm{z}}1x,1y,13z as multipliers, we have
Each fraction = 1 x d x + 1 y d y + 1 3 z d z 1 x ( y 3 x 2 x 4 ) + 1 y ( 2 y 4 x 3 y ) + 1 3 z 9 z ( x 3 y 3 ) = 1 x d x + 1 y d y + 1 3 z d z ( y 3 2 x 3 ) + ( 2 y 3 x 3 ) + ( 3 x 3 3 y 3 )  Each fraction  = 1 x d x + 1 y d y + 1 3 z d z 1 x y 3 x 2 x 4 + 1 y 2 y 4 x 3 y + 1 3 z 9 z x 3 y 3 = 1 x d x + 1 y d y + 1 3 z d z y 3 2 x 3 + 2 y 3 x 3 + 3 x 3 3 y 3 {:[” Each fraction “=((1)/(x)dx+(1)/(y)dy+(1)/(3z)dz)/((1)/(x)(y^(3)x-2x^(4))+(1)/(y)(2y^(4)-x^(3)y)+(1)/(3z)9z(x^(3)-y^(3)))],[=((1)/(x)dx+(1)/(y)dy+(1)/(3z)dz)/((y^(3)-2x^(3))+(2y^(3)-x^(3))+(3x^(3)-3y^(3)))]:}\begin{aligned} \text { Each fraction } & =\frac{\frac{1}{x} d x+\frac{1}{y} d y+\frac{1}{3 z} d z}{\frac{1}{x}\left(y^3 x-2 x^4\right)+\frac{1}{y}\left(2 y^4-x^3 y\right)+\frac{1}{3 z} 9 z\left(x^3-y^3\right)} \\ & =\frac{\frac{1}{x} d x+\frac{1}{y} d y+\frac{1}{3 z} d z}{\left(y^3-2 x^3\right)+\left(2 y^3-x^3\right)+\left(3 x^3-3 y^3\right)} \end{aligned} Each fraction =1xdx+1ydy+13zdz1x(y3x2x4)+1y(2y4x3y)+13z9z(x3y3)=1xdx+1ydy+13zdz(y32x3)+(2y3x3)+(3x33y3)
Each fraction = 1 x d x + 1 y d y + 1 3 z d z 0 = 1 x d x + 1 y d y + 1 3 z d z 0 =((1)/(x)dx+(1)/(y)dy+(1)/(3z)dz)/(0)=\frac{\frac{1}{x} d x+\frac{1}{y} d y+\frac{1}{3 z} d z}{0}=1xdx+1ydy+13zdz0
1 x d x + 1 y d y + 1 3 z d z = 0 1 x d x + 1 y d y + 1 3 z d z = 0 :.(1)/(x)dx+(1)/(y)dy+(1)/(3z)dz=0\therefore \frac{1}{x} d x+\frac{1}{y} d y+\frac{1}{3 z} d z=01xdx+1ydy+13zdz=0
Integrating, we get log x + log y + 1 3 log z = log a log x + log y + 1 3 log z = log a log x+log y+(1)/(3)log z=log a\log x+\log y+\frac{1}{3} \log z=\log alogx+logy+13logz=loga
or log ( xyz 1 / 3 ) = log a log xyz 1 / 3 = log a quad log(xyz^(1//3))=log a\quad \log \left(\mathrm{xyz}^{1 / 3}\right)=\log \mathrm{a}log(xyz1/3)=loga or xyz 1 / 3 = a ( 2 ) xyz 1 / 3 = a ( 2 ) xyz^(1//3)=a—-(2)\mathrm{xyz}^{1 / 3}=\mathrm{a}—-(2)xyz1/3=a(2)
Again choosing 2 x y , x 2 , 0 2 x y , x 2 , 0 -2xy,x^(2),0-2 x y, x^2, 02xy,x2,0 as multipliers, we have
each fraction = 2 x y d x + x 2 d y 2 x y ( y 3 x 2 x 4 ) + x 2 ( 2 y 4 x 3 y ) = 2 x y d x + x 2 d y 3 x 5 y ( 3 )  each fraction  = 2 x y d x + x 2 d y 2 x y y 3 x 2 x 4 + x 2 2 y 4 x 3 y = 2 x y d x + x 2 d y 3 x 5 y ( 3 ) {:[” each fraction “=(-2xydx+x^(2)dy)/(-2xy(y^(3)x-2x^(4))+x^(2)(2y^(4)-x^(3)y))],[=(-2xydx+x^(2)dy)/(3x^(5)y)—-(3)]:}\begin{aligned} & \text { each fraction }=\frac{-2 x y d x+x^2 d y}{-2 x y\left(y^3 x-2 x^4\right)+x^2\left(2 y^4-x^3 y\right)} \\ & =\frac{-2 x y d x+x^2 d y}{3 x^5 y}—-(3) \end{aligned} each fraction =2xydx+x2dy2xy(y3x2x4)+x2(2y4x3y)=2xydx+x2dy3x5y(3)
And taking y 2 , 2 x y , 0 y 2 , 2 x y , 0 y^(2),-2xy,0y^2,-2 x y, 0y2,2xy,0 as multipliers, we have
each fraction = y 2 d x 2 x y d y y 2 ( y 3 x 2 x 4 ) 2 x y ( 2 y 4 x 3 y ) = y 2 d x 2 x y d y 3 x y 5 ( 4 )  each fraction  = y 2 d x 2 x y d y y 2 y 3 x 2 x 4 2 x y 2 y 4 x 3 y = y 2 d x 2 x y d y 3 x y 5 ( 4 ) {:[” each fraction “=(y^(2)dx-2xydy)/(y^(2)(y^(3)x-2x^(4))-2xy(2y^(4)-x^(3)y))],[=(y^(2)dx-2xydy)/(-3xy^(5))—-(4)]:}\begin{aligned} \text { each fraction } & =\frac{y^2 d x-2 x y d y}{y^2\left(y^3 x-2 x^4\right)-2 x y\left(2 y^4-x^3 y\right)} \\ & =\frac{y^2 d x-2 x y d y}{-3 x y^5}—-(4) \end{aligned} each fraction =y2dx2xydyy2(y3x2x4)2xy(2y4x3y)=y2dx2xydy3xy5(4)
From (3) and (4), we get
2 x y d x + x 2 d y 3 x 5 y = y 2 d x 2 x y d y 3 x y 5 or 2 x y d x + x 2 d y x 4 = y 2 d x 2 x y d y y 4 or 2 x 3 y d x + 1 x 2 d y = [ 1 y 2 d x 2 y 3 x d y ] or d ( y x 2 ) = d ( x y 2 ) 2 x y d x + x 2 d y 3 x 5 y = y 2 d x 2 x y d y 3 x y 5  or  2 x y d x + x 2 d y x 4 = y 2 d x 2 x y d y y 4  or  2 x 3 y d x + 1 x 2 d y = 1 y 2 d x 2 y 3 x d y  or  d y x 2 = d x y 2 {:[-(2xydx+x^(2)dy)/(3x^(5)y)=(y^(2)dx-2xydy)/(-3xy^(5))],[” or “quad-(2xydx+x^(2)dy)/(x^(4))=(y^(2)dx-2xydy)/(-y^(4))],[” or “quad-(2)/(x^(3))ydx+(1)/(x^(2))dy=-[(1)/(y^(2))dx-(2)/(y^(3))xdy]],[” or “quad d((y)/(x^(2)))=-d((x)/(y^(2)))]:}\begin{aligned} & -\frac{2 x y d x+x^2 d y}{3 x^5 y}=\frac{y^2 d x-2 x y d y}{-3 x y^5} \\ & \text { or } \quad-\frac{2 x y d x+x^2 d y}{x^4}=\frac{y^2 d x-2 x y d y}{-y^4} \\ & \text { or } \quad-\frac{2}{x^3} y d x+\frac{1}{x^2} d y=-\left[\frac{1}{y^2} d x-\frac{2}{y^3} x d y\right] \\ & \text { or } \quad d\left(\frac{y}{x^2}\right)=-d\left(\frac{x}{y^2}\right) \end{aligned}2xydx+x2dy3x5y=y2dx2xydy3xy5 or 2xydx+x2dyx4=y2dx2xydyy4 or 2x3ydx+1x2dy=[1y2dx2y3xdy] or d(yx2)=d(xy2)
Integrating, we get y x 2 = x y 2 + b y x 2 = x y 2 + b (y)/(x^(2))=-(x)/(y^(2))+b\frac{y}{x^2}=-\frac{x}{y^2}+byx2=xy2+b
or x y 2 + y x 2 = b ( 5 ) x y 2 + y x 2 = b ( 5 ) quad(x)/(y^(2))+(y)/(x^(2))=b—-(5)\quad \frac{x}{y^2}+\frac{y}{x^2}=b—-(5)xy2+yx2=b(5))
From (2) and (5), the general integral of given equation is ϕ ( x y z 1 / 3 , x y 2 + y x 2 ) = 0 ϕ x y z 1 / 3 , x y 2 + y x 2 = 0 phi(xyz^(1//3),(x)/(y^(2))+(y)/(x^(2)))=0\phi\left(x y z^{1 / 3}, \frac{x}{y^2}+\frac{y}{x^2}\right)=0ϕ(xyz1/3,xy2+yx2)=0 where ϕ ϕ phi\phiϕ is an arbitrary function.

Given Equations:

  1. The general integral of the given PDE is:
ϕ ( x y z 1 / 3 , x y 2 + y x 2 ) = 0 ϕ x y z 1 / 3 , x y 2 + y x 2 = 0 phi(xyz^(1//3),(x)/(y^(2))+(y)/(x^(2)))=0\phi\left(xyz^{1/3}, \frac{x}{y^2} + \frac{y}{x^2}\right) = 0ϕ(xyz1/3,xy2+yx2)=0
  1. The curve is defined as:
x = t x = t x=tx = tx=t
y = t 2 y = t 2 y=t^(2)y = t^2y=t2
z = 1 z = 1 z=1z = 1z=1
Substitute the given curve equations into the general integral to find the form of the function ϕ ϕ phi\phiϕ:

Step 1: Substitute the Curve Equations

ϕ ( t ( t 2 ) ( 1 ) 1 / 3 , t ( t 2 ) 2 + t 2 t 2 ) = 0 ϕ t ( t 2 ) ( 1 ) 1 / 3 , t ( t 2 ) 2 + t 2 t 2 = 0 phi(t(t^(2))(1)^(1//3),(t)/((t^(2))^(2))+(t^(2))/(t^(2)))=0\phi\left(t(t^2)(1)^{1/3}, \frac{t}{(t^2)^2} + \frac{t^2}{t^2}\right) = 0ϕ(t(t2)(1)1/3,t(t2)2+t2t2)=0
ϕ ( t 3 , 1 t 3 + 1 ) = 0 ϕ t 3 , 1 t 3 + 1 = 0 phi(t^(3),(1)/(t^(3))+1)=0\phi\left(t^3, \frac{1}{t^3} + 1\right) = 0ϕ(t3,1t3+1)=0

Step 2: Solve for ϕ ϕ phi\phiϕ

To find the integral surface that passes through the given curve, we need to determine the form of the function ϕ ϕ phi\phiϕ that satisfies the above equation for all values of t t ttt.
Let’s denote the arguments of ϕ ϕ phi\phiϕ as:
u = t 3 u = t 3 u=t^(3)u = t^3u=t3
v = 1 t 3 + 1 v = 1 t 3 + 1 v=(1)/(t^(3))+1v = \frac{1}{t^3} + 1v=1t3+1
So, the equation becomes:
ϕ ( u , v ) = 0 ϕ ( u , v ) = 0 phi(u,v)=0\phi(u, v) = 0ϕ(u,v)=0
Since we are looking for an integral surface passing through the given curve, we can consider ϕ ϕ phi\phiϕ as a constant for this specific curve, say C C CCC:
ϕ ( u , v ) = C ϕ ( u , v ) = C phi(u,v)=C\phi(u, v) = Cϕ(u,v)=C

Step 3: Formulate the Integral Surface

The integral surface of the given partial differential equation that passes through the curve x = t x = t x=tx = tx=t, y = t 2 y = t 2 y=t^(2)y = t^2y=t2, and z = 1 z = 1 z=1z = 1z=1 is represented by:
ϕ ( x y z 1 / 3 , x y 2 + y x 2 ) = C ϕ x y z 1 / 3 , x y 2 + y x 2 = C phi(xyz^(1//3),(x)/(y^(2))+(y)/(x^(2)))=C\phi\left(xyz^{1/3}, \frac{x}{y^2} + \frac{y}{x^2}\right) = Cϕ(xyz1/3,xy2+yx2)=C
where C C CCC is a constant specific to this curve, and it represents the specific integral surface passing through the given curve in the family of integral surfaces represented by the general integral.

Conclusion:

The integral surface of the given partial differential equation that passes through the specified curve is characterized by the function ϕ ϕ phi\phiϕ with the constant C C CCC specific to this curve. The exact value of C C CCC can be determined if more information or specific conditions related to the curve or the integral surface are provided.
  1. (b) अधोलिखित संख्याओं के समतुल्यों को उनके सम्मुख दर्शाई गई विशिष्ट संख्या पद्धति में, ज्ञात कीजिए।
    (i) ( 111011 101 ) 2 ( 111011 101 ) 2 (111011*101)_(2)(111011 \cdot 101)_2(111011101)2 को दशमलव पद्धति में
    (ii) ( 1000111110000 00101100 ) 2 ( 1000111110000 00101100 ) 2 (1000111110000-00101100)_(2)(1000111110000-00101100)_2(100011111000000101100)2 को षड़दशमलव पद्धति में
    (iii) ( C 4 F 2 ) 16 ( C 4 F 2 ) 16 (C4F2)_(16)(\mathrm{C} 4 \mathrm{~F} 2)_{16}(C4 F2)16 को दशमलव पद्वति में
    (iv) ( 418 ) 10 ( 418 ) 10 (418)_(10)(418)_{10}(418)10 को द्विआधारी पद्धति में
Find the equivalent of numbers given in a specified number system to the system mentioned against them.
(i) ( 111011 101 ) 2 ( 111011 101 ) 2 (111011*101)_(2)(111011 \cdot 101)_2(111011101)2 to decimal system
(ii) ( 1000111110000 00101100 ) 2 ( 1000111110000 00101100 ) 2 (1000111110000*00101100)_(2)(1000111110000 \cdot 00101100)_2(100011111000000101100)2 to hexadecimal system
(iii) ( C 4 F 2 ) 16 ( C 4 F 2 ) 16 (C4F2)_(16)(\mathrm{C} 4 \mathrm{~F} 2)_{16}(C4 F2)16 to decimal system
(iv) ( 418 ) 10 ( 418 ) 10 (418)_(10)(418)_{10}(418)10 to binary system
Answer:
(i) ( 111011 101 ) 2 to decimal system  (i)  ( 111011 101 ) 2  to decimal system  ” (i) “(111011*101)_(2)” to decimal system “\text { (i) }(111011 \cdot 101)_2 \text { to decimal system } (i) (111011101)2 to decimal system 
111011.101
= 1 × 2 5 + 1 × 2 4 + 1 × 2 3 + 0 × 2 2 + 1 × 2 1 + 1 × 2 0 + 1 × 1 2 1 + 0 × 1 2 2 + 1 × 1 2 3 = 1 × 32 + 1 × 16 + 1 × 8 + 0 × 4 + 1 × 2 + 1 × 1 + 1 × 0.5 + 0 × 0.25 + 1 × 0.125 = 32 + 16 + 8 + 0 + 2 + 1 + 0.5 + 0 + 0.125 = 59.625 = 1 × 2 5 + 1 × 2 4 + 1 × 2 3 + 0 × 2 2 + 1 × 2 1 + 1 × 2 0 + 1 × 1 2 1 + 0 × 1 2 2 + 1 × 1 2 3 = 1 × 32 + 1 × 16 + 1 × 8 + 0 × 4 + 1 × 2 + 1 × 1 + 1 × 0.5 + 0 × 0.25 + 1 × 0.125 = 32 + 16 + 8 + 0 + 2 + 1 + 0.5 + 0 + 0.125 = 59.625 {:[=1xx2^(5)+1xx2^(4)+1xx2^(3)+0xx2^(2)+1xx2^(1)+1xx2^(0)+1xx(1)/(2^(1))+0xx(1)/(2^(2))+1xx(1)/(2^(3))],[=1xx32+1xx16+1xx8+0xx4+1xx2+1xx1+1xx0.5+0xx0.25+1xx0.125],[=32+16+8+0+2+1+0.5+0+0.125],[=59.625]:}\begin{aligned} & =1 \times 2^5+1 \times 2^4+1 \times 2^3+0 \times 2^2+1 \times 2^1+1 \times 2^0+1 \times \frac{1}{2^1}+0 \times \frac{1}{2^2}+1 \times \frac{1}{2^3} \\ & =1 \times 32+1 \times 16+1 \times 8+0 \times 4+1 \times 2+1 \times 1+1 \times 0.5+0 \times 0.25+1 \times 0.125 \\ & =32+16+8+0+2+1+0.5+0+0.125 \\ & =59.625 \end{aligned}=1×25+1×24+1×23+0×22+1×21+1×20+1×121+0×122+1×123=1×32+1×16+1×8+0×4+1×2+1×1+1×0.5+0×0.25+1×0.125=32+16+8+0+2+1+0.5+0+0.125=59.625
( 111011.101 ) 2 = ( 59.625 ) 10 ( 111011.101 ) 2 = ( 59.625 _ ) 10 :.(111011.101)_(2)=(59.625 _)_(10)\therefore(111011.101)_2=(\underline{59.625})_{10}(111011.101)2=(59.625)10
(ii) ( 1000111110000.00101100 ) 2 to hexadecimal system  (ii)  ( 1000111110000.00101100 ) 2  to hexadecimal system  ” (ii) “(1000111110000.00101100)_(2)” to hexadecimal system “\text { (ii) }(1000111110000.00101100)_2 \text { to hexadecimal system } (ii) (1000111110000.00101100)2 to hexadecimal system 
0001 1 0001 1 1111 15 0000 0 0010 2 1100 12 ( 1000111110000.00101100 ) 2 = ( 11 F 0.2 C ) 16 0001 1 0001 1 1111 15 0000 0 0010 2 1100 12 ( 1000111110000.00101100 ) 2 = ( 11 F 0.2 C _ ) 16 {:[(0001)/(1)(0001)/(1)(1111)/(15)(0000)/(0)*(0010)/(2)(1100)/(12)],[:.(1000111110000.00101100)_(2)=(11 F 0.2 C_)_(16)]:}\begin{aligned} & \frac{0001}{1} \frac{0001}{1} \frac{1111}{15} \frac{0000}{0} \cdot \frac{0010}{2} \frac{1100}{12} \\ & \therefore(1000111110000.00101100)_2=(\underline{11 F 0.2 C})_{16} \end{aligned}00011000111111150000000102110012(1000111110000.00101100)2=(11F0.2C)16
(iii) ( C 4 F 2 ) 16 to decimal system  (iii)  ( C 4 F 2 ) 16  to decimal system  ” (iii) “(C4F2)_(16)” to decimal system “\text { (iii) }(C 4 F 2)_{16} \text { to decimal system } (iii) (C4F2)16 to decimal system 
C 4 F 2 C 4 F 2 C4F2C 4 F 2C4F2
= C × 16 3 + 4 × 16 2 + F × 16 1 + 2 × 16 0 = 12 × 4096 + 4 × 256 + 15 × 16 + 2 × 1 = 49152 + 1024 + 240 + 2 = 50418 = C × 16 3 + 4 × 16 2 + F × 16 1 + 2 × 16 0 = 12 × 4096 + 4 × 256 + 15 × 16 + 2 × 1 = 49152 + 1024 + 240 + 2 = 50418 {:[=C xx16^(3)+4xx16^(2)+F xx16^(1)+2xx16^(0)],[=12 xx4096+4xx256+15 xx16+2xx1],[=49152+1024+240+2],[=50418]:}\begin{aligned} & =C \times 16^3+4 \times 16^2+F \times 16^1+2 \times 16^0 \\ & =12 \times 4096+4 \times 256+15 \times 16+2 \times 1 \\ & =49152+1024+240+2 \\ & =50418 \end{aligned}=C×163+4×162+F×161+2×160=12×4096+4×256+15×16+2×1=49152+1024+240+2=50418
( C 4 F 2 ) 16 = ( 50418 ) 10 ( C 4 F 2 ) 16 = ( 50418 _ ) 10 :.(C4F2)_(16)=(50418 _)_(10)\therefore(\mathrm{C} 4 \mathrm{~F} 2)_{16}=(\underline{50418})_{10}(C4 F2)16=(50418)10
(iv) ( 418 ) 10 to binary system  (iv)  ( 418 ) 10  to binary system  ” (iv) “(418)_(10)” to binary system “\text { (iv) }(418)_{10} \text { to binary system } (iv) (418)10 to binary system 
418 2 209 0 2 104 1 2 52 0 2 26 0 ↑↑ 2 13 0 ↑↑ 2 6 1 2 3 0 2 1 1 0 1 ( 418 ) 10 = ( 110100010 ) 2 418 2 209 0 2 104 1 2 52 0 2 26 0 ↑↑ 2 13 0 ↑↑ 2 6 1 2 3 0 2 1 1 0 1 ( 418 ) 10 = ( 110100010 ) 2 {:[{:[,418,],[2,209,0uarr],[2,104,1uarr],[2,52,0uarr],[2,26,0uarr uarr],[2,13,0uarr uarr],[2,6,1uarr],[2,3,0uarr],[2,1,1uarr],[,0,1uarr]:}],[:.(418)_(10)=(110100010)_(2)]:}\begin{aligned} &\begin{array}{|c|c|c|} \hline & 418 & \\ \hline 2 & 209 & 0 \uparrow \\ \hline 2 & 104 & 1 \uparrow \\ \hline 2 & 52 & 0 \uparrow \\ \hline 2 & 26 & 0 \uparrow \uparrow \\ \hline 2 & 13 & 0 \uparrow \uparrow \\ \hline 2 & 6 & 1 \uparrow \\ \hline 2 & 3 & 0 \uparrow \\ \hline 2 & 1 & 1 \uparrow \\ \hline & 0 & 1 \uparrow \\ \hline \end{array}\\ &\therefore(418)_{10}=(110100010)_2 \end{aligned}418220902104125202260↑↑2130↑↑26123021101(418)10=(110100010)2
6.(c) मान लीजिए किसी यांत्रिक-निकाय का लेगरान्जियन :
L = 1 2 m ( a x ˙ 2 + 2 b x ˙ y ˙ + c y ˙ 2 ) 1 2 k ( a x 2 + 2 b x y + c y 2 ) , L = 1 2 m a x ˙ 2 + 2 b x ˙ y ˙ + c y ˙ 2 1 2 k a x 2 + 2 b x y + c y 2 , L=(1)/(2)m(ax^(˙)^(2)+2b(x^(˙))(y^(˙))+cy^(˙)^(2))-(1)/(2)k(ax^(2)+2bxy+cy^(2)),L=\frac{1}{2} m\left(a \dot{x}^2+2 b \dot{x} \dot{y}+c \dot{y}^2\right)-\frac{1}{2} k\left(a x^2+2 b x y+c y^2\right),L=12m(ax˙2+2bx˙y˙+cy˙2)12k(ax2+2bxy+cy2),
के द्वारा द्योतित है जहाँ a , b , c , m ( > 0 ) , k ( > 0 ) a , b , c , m ( > 0 ) , k ( > 0 ) a,b,c,m( > 0),k( > 0)a, b, c, m(>0), k(>0)a,b,c,m(>0),k(>0) स्थिरांक हैं तथा b 2 a c b 2 a c b^(2)!=acb^2 \neq a cb2ac लेगरान्जियन समीकरणों को लिखिए तथा निकाय को पहचानिए ।
Suppose the Lagrangian of a mechanical system is given by
L = 1 2 m ( a x ˙ 2 + 2 b x ˙ y ˙ + c y ˙ 2 ) 1 2 k ( a x 2 + 2 b x y + c y 2 ) , L = 1 2 m a x ˙ 2 + 2 b x ˙ y ˙ + c y ˙ 2 1 2 k a x 2 + 2 b x y + c y 2 , L=(1)/(2)m(ax^(˙)^(2)+2b(x^(˙))(y^(˙))+cy^(˙)^(2))-(1)/(2)k(ax^(2)+2bxy+cy^(2)),L=\frac{1}{2} m\left(a \dot{x}^2+2 b \dot{x} \dot{y}+c \dot{y}^2\right)-\frac{1}{2} k\left(a x^2+2 b x y+c y^2\right),L=12m(ax˙2+2bx˙y˙+cy˙2)12k(ax2+2bxy+cy2),
where a , b , c , m ( > 0 ) , k ( > 0 ) a , b , c , m ( > 0 ) , k ( > 0 ) a,b,c,m( > 0),k( > 0)a, b, c, m(>0), k(>0)a,b,c,m(>0),k(>0) are constants and b 2 a c b 2 a c b^(2)!=acb^2 \neq a cb2ac. Write down the Lagrangian equations of motion and identify the system.
Answer:
Introduction:
Given the Lagrangian of a mechanical system, we need to find the Lagrangian equations of motion and identify the system. The Lagrangian is defined as:
L = 1 2 m ( a x ˙ 2 + 2 b x ˙ y ˙ + c y ˙ 2 ) 1 2 k ( a x 2 + 2 b x y + c y 2 ) , L = 1 2 m a x ˙ 2 + 2 b x ˙ y ˙ + c y ˙ 2 1 2 k a x 2 + 2 b x y + c y 2 , L=(1)/(2)m(ax^(˙)^(2)+2b(x^(˙))(y^(˙))+cy^(˙)^(2))-(1)/(2)k(ax^(2)+2bxy+cy^(2)),L=\frac{1}{2} m\left(a \dot{x}^2+2 b \dot{x} \dot{y}+c \dot{y}^2\right)-\frac{1}{2} k\left(a x^2+2 b x y+c y^2\right),L=12m(ax˙2+2bx˙y˙+cy˙2)12k(ax2+2bxy+cy2),
where a , b , c , m ( > 0 ) , k ( > 0 ) a , b , c , m ( > 0 ) , k ( > 0 ) a,b,c,m( > 0),k( > 0)a, b, c, m(>0), k(>0)a,b,c,m(>0),k(>0) are constants, and b 2 a c b 2 a c b^(2)!=acb^2 \neq a cb2ac.
Lagrangian Equations of Motion:
To find the Lagrangian equations of motion, we’ll calculate the partial derivatives of L L LLL with respect to x x xxx, y y yyy, x ˙ x ˙ x^(˙)\dot{x}x˙, and y ˙ y ˙ y^(˙)\dot{y}y˙.
L x = 1 2 k ( 2 a x + 2 b y ) = k ( a x + b y ) (1) L x = 1 2 k ( 2 a x + 2 b y ) = k ( a x + b y ) (1) (del L)/(del x)=-(1)/(2)k(2ax+2by)=-k(ax+by)quad(1)\frac{\partial L}{\partial x} = -\frac{1}{2} k(2 a x+2 b y) = -k(a x+b y) \quad \text{(1)}Lx=12k(2ax+2by)=k(ax+by)(1)
L x ˙ = 1 2 m ( 2 a x ˙ + 2 b y ˙ ) = m ( a x ˙ + b y ˙ ) (2) L x ˙ = 1 2 m ( 2 a x ˙ + 2 b y ˙ ) = m ( a x ˙ + b y ˙ ) (2) (del L)/(del(x^(˙)))=(1)/(2)m(2ax^(˙)+2by^(˙))=m(ax^(˙)+by^(˙))quad(2)\frac{\partial L}{\partial \dot{x}} = \frac{1}{2} m(2 a \dot{x}+2 b \dot{y}) = m(a \dot{x}+b \dot{y}) \quad \text{(2)}Lx˙=12m(2ax˙+2by˙)=m(ax˙+by˙)(2)
L y = 1 2 k ( 2 b x + 2 c y ) = k ( b x + c y ) (3) L y = 1 2 k ( 2 b x + 2 c y ) = k ( b x + c y ) (3) (del L)/(del y)=-(1)/(2)k(2bx+2cy)=-k(bx+cy)quad(3)\frac{\partial L}{\partial y} = -\frac{1}{2} k(2 b x+2 c y) = -k(b x+c y) \quad \text{(3)}Ly=12k(2bx+2cy)=k(bx+cy)(3)
L y ˙ = 1 2 m ( 2 b x ˙ + 2 c y ˙ ) = m ( b x ˙ + c y ˙ ) (4) L y ˙ = 1 2 m ( 2 b x ˙ + 2 c y ˙ ) = m ( b x ˙ + c y ˙ ) (4) (del L)/(del(y^(˙)))=(1)/(2)m(2bx^(˙)+2cy^(˙))=m(bx^(˙)+cy^(˙))quad(4)\frac{\partial L}{\partial \dot{y}} = \frac{1}{2} m(2 b \dot{x}+2 c \dot{y}) = m(b \dot{x}+c \dot{y}) \quad \text{(4)}Ly˙=12m(2bx˙+2cy˙)=m(bx˙+cy˙)(4)
Lagrangian Equations of Motion:
The Lagrangian equations of motion are given by:
d d t ( L x ˙ ) L x = 0 (5) d d t L x ˙ L x = 0 (5) (d)/(dt)((del L)/(del(x^(˙))))-(del L)/(del x)=0quad(5)\frac{d}{d t}\left(\frac{\partial L}{\partial \dot{x}}\right)-\frac{\partial L}{\partial x}=0 \quad \text{(5)}ddt(Lx˙)Lx=0(5)
and
d d t ( L y ˙ ) L y = 0 (6) d d t L y ˙ L y = 0 (6) (d)/(dt)((del L)/(del(y^(˙))))-(del L)/(del y)=0quad(6)\frac{d}{d t}\left(\frac{\partial L}{\partial \dot{y}}\right)-\frac{\partial L}{\partial y}=0 \quad \text{(6)}ddt(Ly˙)Ly=0(6)
Substituting the partial derivatives from equations (1)-(4) into equations (5) and (6), we get:
( a x ¨ + b y ¨ ) + k ( a x + b y ) = 0 (7) ( a x ¨ + b y ¨ ) + k ( a x + b y ) = 0 (7) (ax^(¨)+by^(¨))+k(ax+by)=0quad(7)(a \ddot{x}+b \ddot{y})+k(a x+b y)=0 \quad \text{(7)}(ax¨+by¨)+k(ax+by)=0(7)
m ( b x ˙ + c y ¨ ) + k ( b x + c y ) = 0 (8) m ( b x ˙ + c y ¨ ) + k ( b x + c y ) = 0 (8) m(bx^(˙)+cy^(¨))+k(bx+cy)=0quad(8)m(b \dot{x}+c \ddot{y})+k(b x+c y)=0 \quad \text{(8)}m(bx˙+cy¨)+k(bx+cy)=0(8)
Solving for Equations of Motion:
Subtracting equation (8) multiplied by b b bbb from equation (7) multiplied by a a aaa gives:
m ( a c b 2 ) x ¨ + k ( a c b 2 ) x = 0 m ( a c b 2 ) x ¨ + k ( a c b 2 ) x = 0 m(ac-b^(2))x^(¨)+k(ac-b^(2))x=0m(ac-b^2) \ddot{x}+k(ac-b^2) x=0m(acb2)x¨+k(acb2)x=0
x ¨ = ( k / m ) x (A) x ¨ = ( k / m ) x (A) =>x^(¨)=-(k//m)x quad(A)\Rightarrow \ddot{x}=-(k / m) x \quad \text{(A)}x¨=(k/m)x(A)
Similarly, subtracting equation (7) multiplied by b b bbb from equation (8) multiplied by a a aaa yields:
m ( b 2 a c ) y ¨ + k ( b 2 a c ) y = 0 m ( b 2 a c ) y ¨ + k ( b 2 a c ) y = 0 m(b^(2)-ac)y^(¨)+k(b^(2)-ac)y=0m(b^2-ac) \ddot{y}+k(b^2-ac) y=0m(b2ac)y¨+k(b2ac)y=0
y ¨ = ( k / m ) y (B) y ¨ = ( k / m ) y (B) =>y^(¨)=-(k//m)y quad(B)\Rightarrow \ddot{y}=-(k / m) y \quad \text{(B)}y¨=(k/m)y(B)
Conclusion:
From equations (A) and (B), we have obtained the required equations of motion for the system. The system is identified as a 2-D Harmonic oscillator.
7.(a) आंशिक अवकल समीकरण :
( 2 D 2 5 D D + 2 D 2 ) z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y 2 D 2 5 D D + 2 D 2 z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y (2D^(2)-5DD^(‘)+2D^(‘2))z=5sin(2x+y)+24(y-x)+e^(3x+4y)\left(2 D^2-5 D D^{\prime}+2 D^{\prime 2}\right) z=5 \sin (2 x+y)+24(y-x)+e^{3 x+4 y}(2D25DD+2D2)z=5sin(2x+y)+24(yx)+e3x+4y को हल कीजिए
जहाँ D x , D y D x , D y D-=(del)/(del x)quad,D^(‘)-=(del)/(del y)D \equiv \frac{\partial}{\partial x} \quad, D^{\prime} \equiv \frac{\partial}{\partial y}Dx,Dy.
Solve the partial differential equation:
( 2 D 2 5 D D + 2 D 2 ) z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y 2 D 2 5 D D + 2 D 2 z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y (2D^(2)-5DD^(‘)+2D^(‘2))z=5sin(2x+y)+24(y-x)+e^(3x+4y)\left(2 D^2-5 D D^{\prime}+2 D^{\prime 2}\right) z=5 \sin (2 x+y)+24(y-x)+e^{3 x+4 y}(2D25DD+2D2)z=5sin(2x+y)+24(yx)+e3x+4y
where D = x , D y D = x , D y D=(del)/(del x),D^(‘)-=(del)/(del y)D=\frac{\partial}{\partial x}, D^{\prime} \equiv \frac{\partial}{\partial y}D=x,Dy.
Answer:
Introduction:
In this solution, we will solve a partial differential equation given by:
( 2 D 2 5 D D + 2 D 2 ) z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y 2 D 2 5 D D + 2 D 2 z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y (2D^(2)-5DD^(‘)+2D^(‘2))z=5sin(2x+y)+24(y-x)+e^(3x+4y)\left(2 D^2-5 D D^{\prime}+2 D^{\prime 2}\right) z=5 \sin (2 x+y)+24(y-x)+e^{3 x+4 y}(2D25DD+2D2)z=5sin(2x+y)+24(yx)+e3x+4y
where D = x D = x D=(del)/(del x)D=\frac{\partial}{\partial x}D=x and D y D y D^(‘)-=(del)/(del y)D^{\prime} \equiv \frac{\partial}{\partial y}Dy.
Equation Analysis:
Given P.D.E is
( 2 D 2 5 D D + 5 D 2 ) z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y 2 D 2 5 D D + 5 D 2 z = 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y (2D^(2)-5DD^(‘)+5D^(‘2))z=5sin(2x+y)+24(y-x)+e^(3x+4y)\left(2 D^2-5 D D^{\prime}+5 D^{\prime 2}\right) z=5 \sin (2 x+y)+24(y-x)+e^{3 x+4 y}(2D25DD+5D2)z=5sin(2x+y)+24(yx)+e3x+4y
The auxiliary equation is calculated as follows:
2 m 2 5 m + 2 = 0 (Auxiliary Equation) 2 m 2 5 m + 2 = 0 (Auxiliary Equation) 2m^(2)-5m+2=0quad(Auxiliary Equation)2 m^2-5 m+2=0 \quad \text{(Auxiliary Equation)}2m25m+2=0(Auxiliary Equation)
Solving this equation yields two values for m m mmm: m = 1 2 m = 1 2 m=(1)/(2)m = \frac{1}{2}m=12 and m = 1 m = 1 m=1m = 1m=1.
Solution Process:
We start by finding the general solution using the values of m m mmm obtained from the auxiliary equation:
  1. ϕ 1 ( y + x / 2 ) + ϕ 2 ( y + 2 x ) ϕ 1 ( y + x / 2 ) + ϕ 2 ( y + 2 x ) phi_(1)(y+x//2)+phi_(2)(y+2x)\phi_1(y+x/2) + \phi_2(y+2x)ϕ1(y+x/2)+ϕ2(y+2x) for m = 1 2 m = 1 2 m=(1)/(2)m = \frac{1}{2}m=12.
  2. ϕ 1 ( 2 y + x ) + ϕ 2 ( y + 2 x ) ϕ 1 ( 2 y + x ) + ϕ 2 ( y + 2 x ) phi_(1)(2y+x)+phi_(2)(y+2x)\phi_1(2y+x) + \phi_2(y+2x)ϕ1(2y+x)+ϕ2(y+2x) for m = 1 m = 1 m=1m = 1m=1.
Intermediate Steps:
Now, let’s break down the solution into parts:
Now P . I . = 1 2 D 2 5 D D + 2 D 2 [ 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y ] P . I = 1 2 D 2 5 D D + 2 D 2 [ 5 sin ( 2 x + y ] + 1 2 D 2 5 D D + 2 D 2 24 ( y x ) + 1 2 D 2 5 D D + 2 D 2 e 3 x + 4 y P . I 2 = 1 2 D 2 5 D D + 2 D 2 [ 24 ( y x ) ] = 24 1 2 D 2 5 D D + 2 D 2 ( y x ) = 24 1 2 ( 1 ) 2 5 × 1 × 1 + 2 × ( 1 ) 2 v d u d v = 24 20 v 2 2 d v  Now  P . I . = 1 2 D 2 5 D D + 2 D 2 5 sin ( 2 x + y ) + 24 ( y x ) + e 3 x + 4 y P . I = 1 2 D 2 5 D D + 2 D 2 5 sin ( 2 x + y ] + 1 2 D 2 5 D D + 2 D 2 24 ( y x ) + 1 2 D 2 5 D D + 2 D 2 e 3 x + 4 y P . I 2 = 1 2 D 2 5 D D + 2 D 2 [ 24 ( y x ) ] = 24 1 2 D 2 5 D D + 2 D 2 ( y x ) = 24 1 2 ( 1 ) 2 5 × 1 × 1 + 2 × ( 1 ) 2 v d u d v = 24 20 v 2 2 d v {:[” Now “P.I.=(1)/(2D^(2)-5DD^(‘)+2D^(‘2))[5sin(2x+y)+24(y-x)+e^(3x+4y)]],[P.I=(1)/(2D^(2)-5DD^(‘)+2D^(‘2))[5sin(2x+y]+(1)/(2D^(2)-5DD^(‘)+2D^(‘2))24(y-x):}],[+(1)/(2D^(2)-5DD^(‘)+2D^(‘2))*e^(3x+4y)],[P.I_(2)=(1)/(2D^(2)-5DD^(‘)+2D^(‘2))[24(y-x)]],[=24*(1)/(2D^(2)-5DD^(‘)+2D^(‘2))(y-x)],[=24*(1)/(2(-1)^(2)-5xx1xx-1+2xx(1)^(2))∬vdudv],[=(24)/(20)int(v^(2))/(2)dv],[]:}\begin{aligned} & \text { Now } P . I.=\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}}\left[5 \sin (2 x+y)+24(y-x)+e^{3 x+4 y}\right] \\ & P . I=\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}}\left[5 \sin (2 x+y]+\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}} 24(y-x)\right. \\ &+\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}} \cdot e^{3 x+4 y} \\ & P . I_2=\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}}[24(y-x)] \\ & =24 \cdot \frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}}(y-x) \\ & =24 \cdot \frac{1}{2(-1)^2-5 \times 1 \times-1+2 \times(1)^2} \iint v d u d v \\ & =\frac{24}{20} \int \frac{v^2}{2} d v \\ & \end{aligned} Now P.I.=12D25DD+2D2[5sin(2x+y)+24(yx)+e3x+4y]P.I=12D25DD+2D2[5sin(2x+y]+12D25DD+2D224(yx)+12D25DD+2D2e3x+4yP.I2=12D25DD+2D2[24(yx)]=2412D25DD+2D2(yx)=2412(1)25×1×1+2×(1)2vdudv=2420v22dv
P I 2 = 24 20 ( v 3 6 ) = 1 5 ( y x ) 3 P I 3 = 1 2 D 2 5 D D + 2 D 2 e 2 x + 3 y . = e 2 x + 3 y 1 2 ( 2 ) 2 5 × 2 × 3 + 2 × 9 = e 2 x + 3 y 1 8 30 + 18 = e 2 x + 3 y 4 P I 1 = 1 2 D 2 5 D D + 2 D 2 [ 5 sin ( 2 x + y ) ] = 5 [ 1 2 D 2 5 D D + 2 D 2 sin ( 2 x + y ) ] P I 2 = 24 20 v 3 6 = 1 5 ( y x ) 3 P I 3 = 1 2 D 2 5 D D + 2 D 2 e 2 x + 3 y . = e 2 x + 3 y 1 2 ( 2 ) 2 5 × 2 × 3 + 2 × 9 = e 2 x + 3 y 1 8 30 + 18 = e 2 x + 3 y 4 P I 1 = 1 2 D 2 5 D D + 2 D 2 [ 5 sin ( 2 x + y ) ] = 5 1 2 D 2 5 D D + 2 D 2 sin ( 2 x + y ) {:[P*I_(2)=(24)/(20)*((v^(3))/(6))=(1)/(5)(y-x)^(3)],[P*I_(3)=(1)/(2D^(2)-5DD^(‘)+2D^(‘2))*e^(2x+3y).],[=e^(2x+3y)*(1)/(2(2)^(2)-5xx2xx3+2xx9)],[=e^(2x+3y)*(1)/(8-30+18)=(-e^(2x+3y))/(4)],[P*I_(1)=(1)/(2D^(2)-5DD^(‘)+2D^(‘2))[5sin(2x+y)]],[=5[(1)/(2D^(2)-5DD^(‘)+2D^(2))sin(2x+y)]]:}\begin{aligned} P \cdot I_2 & =\frac{24}{20} \cdot\left(\frac{v^3}{6}\right)=\frac{1}{5}(y-x)^3 \\ P \cdot I_3 & =\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}} \cdot e^{2 x+3 y} . \\ & =e^{2 x+3 y} \cdot \frac{1}{2(2)^2-5 \times 2 \times 3+2 \times 9} \\ & =e^{2 x+3 y} \cdot \frac{1}{8-30+18}=\frac{-e^{2 x+3 y}}{4} \\ P \cdot I_1 & =\frac{1}{2 D^2-5 D D^{\prime}+2 D^{\prime 2}}[5 \sin (2 x+y)] \\ & =5\left[\frac{1}{2 D^2-5 D D^{\prime}+2 D^2} \sin (2 x+y)\right] \end{aligned}PI2=2420(v36)=15(yx)3PI3=12D25DD+2D2e2x+3y.=e2x+3y12(2)25×2×3+2×9=e2x+3y1830+18=e2x+3y4PI1=12D25DD+2D2[5sin(2x+y)]=5[12D25DD+2D2sin(2x+y)]
= 5 1 ( D 2 D ) [ ( 2 D D ) sin ( 2 x + y ) ] = 5 1 ( D 2 D ) [ 1 2 2 1 sin v d v ] where v = 2 x + y = 5. 1 ( D 2 D ) × 1 3 ( cos v ) P I 1 = 5 3 1 D 2 D cos V = 5 3 x 1 ! 1 ! cos ( 2 x + y ) P I = P I 1 + P I 2 + P I 3 P I = 5 3 x cos ( 2 x + y ) + 1 5 ( y x ) 3 e 2 x + 3 y 4 = 5 1 ( D 2 D ) 2 D D sin ( 2 x + y ) = 5 1 D 2 D 1 2 2 1 sin v d v  where  v = 2 x + y =  5.  1 D 2 D × 1 3 ( cos v ) P I 1 = 5 3 1 D 2 D cos V = 5 3 x 1 ! 1 ! cos ( 2 x + y ) P I = P I 1 + P I 2 + P I 3 P I = 5 3 x cos ( 2 x + y ) + 1 5 ( y x ) 3 e 2 x + 3 y 4 {:[{:=5*(1)/((D-2D)[(2D-D^(‘)))sin(2x+y)]],[=5*(1)/((D-2D^(‘)))[(1)/(2*2-1)int sin vdv]” where “v=2x+y],[=” 5. “(1)/((D-2D^(‘)))xx(1)/(3)(-cos v)],[PI_(1)=(-5)/(3)*(1)/(D-2D^(‘))cos V=(-5)/(3)*(x)/(1!*1!)cos(2x+y)],[:.PI=PI_(1)+PI_(2)+PI_(3)],[P*I=-(5)/(3)x cos(2x+y)+(1)/(5)(y-x)^(3)-(e^(2x+3y))/(4)],[]:}\begin{aligned} & \left.=5 \cdot \frac{1}{(D-2 D)\left[\left(2 D-D^{\prime}\right)\right.} \sin (2 x+y)\right] \\ & =5 \cdot \frac{1}{\left(D-2 D^{\prime}\right)}\left[\frac{1}{2 \cdot 2-1} \int \sin v d v\right] \text { where } v=2 x+y \\ & =\text { 5. } \frac{1}{\left(D-2 D^{\prime}\right)} \times \frac{1}{3}(-\cos v) \\ & P I_1=\frac{-5}{3} \cdot \frac{1}{D-2 D^{\prime}} \cos V=\frac{-5}{3} \cdot \frac{x}{1 ! \cdot 1 !} \cos (2 x+y) \\ & \therefore P I=P I_1+P I_2+P I_3 \\ & P \cdot I=-\frac{5}{3} x \cos (2 x+y)+\frac{1}{5}(y-x)^3-\frac{e^{2 x+3 y}}{4} \\ & \end{aligned}=51(D2D)[(2DD)sin(2x+y)]=51(D2D)[1221sinvdv] where v=2x+y= 5. 1(D2D)×13(cosv)PI1=531D2DcosV=53x1!1!cos(2x+y)PI=PI1+PI2+PI3PI=53xcos(2x+y)+15(yx)3e2x+3y4
Conclusion:
Combining the results of the partial integrals, we obtain the final expression for P . I P . I P.IP.IP.I:
P . I = 5 3 x cos ( 2 x + y ) + 1 5 ( y x ) 3 e 2 x + 3 y 4 P . I = 5 3 x cos ( 2 x + y ) + 1 5 ( y x ) 3 e 2 x + 3 y 4 P.I=-(5)/(3)x cos(2x+y)+(1)/(5)(y-x)^(3)-(e^(2x+3y))/(4)P.I = -\frac{5}{3} x \cos (2 x+y) + \frac{1}{5}(y-x)^3 – \frac{e^{2 x+3 y}}{4}P.I=53xcos(2x+y)+15(yx)3e2x+3y4
The general solution for the given partial differential equation is then found by adding this P . I P . I P.IP.IP.I to the complementary function (C.F):
y = C . F + P . I = ϕ 1 ( 2 y + x ) + ϕ 2 ( y + 2 x ) 5 3 x cos ( 2 x + y ) + 1 5 ( y x ) 3 e 2 x + 3 y 4 y = C . F + P . I = ϕ 1 ( 2 y + x ) + ϕ 2 ( y + 2 x ) 5 3 x cos ( 2 x + y ) + 1 5 ( y x ) 3 e 2 x + 3 y 4 y=C.F+P.I=phi_(1)(2y+x)+phi_(2)(y+2x)-(5)/(3)x cos(2x+y)+(1)/(5)(y-x)^(3)-(e^(2x+3y))/(4)y = C.F + P.I = \phi_1(2 y+x) + \phi_2(y+2 x) – \frac{5}{3} x \cos (2 x+y) + \frac{1}{5}(y-x)^3 – \frac{e^{2 x+3 y}}{4}y=C.F+P.I=ϕ1(2y+x)+ϕ2(y+2x)53xcos(2x+y)+15(yx)3e2x+3y4
This completes the solution to the partial differential equation.
7.(b) स्थिराँकों a , b , c a , b , c a,b,ca, b, ca,b,c के मान निकालिए ताकि क्षेत्रकलन-सूत्र
o h f ( x ) d x = h [ a f ( o ) + b f ( h 3 ) + c f ( h ) ] o h f ( x ) d x = h a f ( o ) + b f h 3 + c f ( h ) int_(o)^(h)f(x)dx=h[af(o)+bf((h)/(3))+cf(h)]\int_o^h f(x) d x=h\left[a f(o)+b f\left(\frac{h}{3}\right)+c f(h)\right]ohf(x)dx=h[af(o)+bf(h3)+cf(h)] अधिक से अधिक सम्भव घातीय बहुपदों के लिए सही हो । अताएव रुंडन-न्रुटि का क्रम भी ज्ञात कीजिए ।
Find the values of the constants a , b , c a , b , c a,b,ca, b, ca,b,c such that the quadrature formula o h f ( x ) d x = h [ a f ( o ) + b f ( h 3 ) + c f ( h ) ] o h f ( x ) d x = h a f ( o ) + b f h 3 + c f ( h ) int_(o)^(h)f(x)dx=h[af(o)+bf((h)/(3))+cf(h)]\int_o^h f(x) d x=h\left[a f(o)+b f\left(\frac{h}{3}\right)+c f(h)\right]ohf(x)dx=h[af(o)+bf(h3)+cf(h)] is exact for polynomials of as high degree as possible, and hence find the order of the truncation error.
Answer:
To find the values of the constants a a aaa, b b bbb, and c c ccc in the quadrature formula, we will use the method of undetermined coefficients. We will test the quadrature formula on polynomials of increasing degree until it is no longer exact. The quadrature formula is given as:
0 h f ( x ) d x = h [ a f ( 0 ) + b f ( h 3 ) + c f ( h ) ] 0 h f ( x ) d x = h a f ( 0 ) + b f h 3 + c f ( h ) int_(0)^(h)f(x)dx=h[af(0)+bf((h)/(3))+cf(h)]\int_0^h f(x) \, dx = h \left[ a f(0) + b f\left(\frac{h}{3}\right) + c f(h) \right]0hf(x)dx=h[af(0)+bf(h3)+cf(h)]

Step 1: Test with a Constant Function

Let’s start with a constant function, f ( x ) = 1 f ( x ) = 1 f(x)=1f(x) = 1f(x)=1:
0 h 1 d x = h [ a 1 + b 1 + c 1 ] 0 h 1 d x = h a 1 + b 1 + c 1 int_(0)^(h)1dx=h[a*1+b*1+c*1]\int_0^h 1 \, dx = h \left[ a \cdot 1 + b \cdot 1 + c \cdot 1 \right]0h1dx=h[a1+b1+c1]
h = h ( a + b + c ) h = h ( a + b + c ) h=h(a+b+c)h = h(a + b + c)h=h(a+b+c)
For the formula to be exact for constant functions, we must have:
a + b + c = 1 a + b + c = 1 a+b+c=1a + b + c = 1a+b+c=1 (Equation 1) (Equation 1) (Equation 1)\text{(Equation 1)}(Equation 1)

Step 2: Test with a Linear Function

Next, let’s test with a linear function, f ( x ) = x f ( x ) = x f(x)=xf(x) = xf(x)=x:
0 h x d x = h [ a 0 + b ( h 3 ) + c h ] 0 h x d x = h a 0 + b h 3 + c h int_(0)^(h)xdx=h[a*0+b*((h)/(3))+c*h]\int_0^h x \, dx = h \left[ a \cdot 0 + b \cdot \left(\frac{h}{3}\right) + c \cdot h \right]0hxdx=h[a0+b(h3)+ch]
1 2 h 2 = h [ b h 3 + c h ] 1 2 h 2 = h b h 3 + c h (1)/(2)h^(2)=h[(bh)/(3)+ch]\frac{1}{2} h^2 = h \left[ \frac{b h}{3} + c h \right]12h2=h[bh3+ch]
1 2 h = b h 3 + c h 1 2 h = b h 3 + c h (1)/(2)h=(bh)/(3)+ch\frac{1}{2} h = \frac{b h}{3} + c h12h=bh3+ch
1 2 = b 3 + c 1 2 = b 3 + c (1)/(2)=(b)/(3)+c\frac{1}{2} = \frac{b}{3} + c12=b3+c
For the formula to be exact for linear functions, we must have:
b 3 + c = 1 2 b 3 + c = 1 2 (b)/(3)+c=(1)/(2)\frac{b}{3} + c = \frac{1}{2}b3+c=12 (Equation 2) (Equation 2) (Equation 2)\text{(Equation 2)}(Equation 2)

Step 3: Test with a Quadratic Function

Next, let’s test with a quadratic function, f ( x ) = x 2 f ( x ) = x 2 f(x)=x^(2)f(x) = x^2f(x)=x2:
0 h x 2 d x = h [ a 0 + b ( h 3 ) 2 + c h 2 ] 0 h x 2 d x = h a 0 + b h 3 2 + c h 2 int_(0)^(h)x^(2)dx=h[a*0+b*((h)/(3))^(2)+c*h^(2)]\int_0^h x^2 \, dx = h \left[ a \cdot 0 + b \cdot \left(\frac{h}{3}\right)^2 + c \cdot h^2 \right]0hx2dx=h[a0+b(h3)2+ch2]
1 3 h 3 = h [ b h 2 9 + c h 2 ] 1 3 h 3 = h b h 2 9 + c h 2 (1)/(3)h^(3)=h[(bh^(2))/(9)+ch^(2)]\frac{1}{3} h^3 = h \left[ \frac{b h^2}{9} + c h^2 \right]13h3=h[bh29+ch2]
1 3 h 2 = b h 2 9 + c h 2 1 3 h 2 = b h 2 9 + c h 2 (1)/(3)h^(2)=(bh^(2))/(9)+ch^(2)\frac{1}{3} h^2 = \frac{b h^2}{9} + c h^213h2=bh29+ch2
1 3 = b 9 + c 1 3 = b 9 + c (1)/(3)=(b)/(9)+c\frac{1}{3} = \frac{b}{9} + c13=b9+c
For the formula to be exact for quadratic functions, we must have:
b 9 + c = 1 3 b 9 + c = 1 3 (b)/(9)+c=(1)/(3)\frac{b}{9} + c = \frac{1}{3}b9+c=13 (Equation 3) (Equation 3) (Equation 3)\text{(Equation 3)}(Equation 3)

Step 4: Solve the System of Equations

Now, we have a system of three equations with three unknowns:
  1. a + b + c = 1 a + b + c = 1 a+b+c=1a + b + c = 1a+b+c=1
  2. b 3 + c = 1 2 b 3 + c = 1 2 (b)/(3)+c=(1)/(2)\frac{b}{3} + c = \frac{1}{2}b3+c=12
  3. b 9 + c = 1 3 b 9 + c = 1 3 (b)/(9)+c=(1)/(3)\frac{b}{9} + c = \frac{1}{3}b9+c=13
Let’s solve this system of equations to find the values of a a aaa, b b bbb, and c c ccc.
The solution to the system of equations is:
a = 0 a = 0 a=0a = 0a=0
b = 3 4 b = 3 4 b=(3)/(4)b = \frac{3}{4}b=34
c = 1 4 c = 1 4 c=(1)/(4)c = \frac{1}{4}c=14

Order of the Truncation Error

To find the order of the truncation error, we need to determine the highest degree of polynomial for which the quadrature formula is exact. Since we have found the exact values of a a aaa, b b bbb, and c c ccc by testing the quadrature formula on polynomials up to degree 2 (quadratic), the formula is exact for polynomials of degree 2 or less.
Thus, the order of the truncation error is O ( h 3 ) O ( h 3 ) O(h^(3))O(h^3)O(h3), where h h hhh is the step size, as the error term will be proportional to the third derivative of the function being integrated.
Hence the required formula is
0 h f ( x ) d x = h / 4 [ 3 f ( h / 3 ) + f ( h ) ] 0 h f ( x ) d x = h / 4 [ 3 f ( h / 3 ) + f ( h ) ] int_(0)^(h)f(x)dx=h//4[3f(h//3)+f(h)]\int_0^h f(x) d x=h / 4[3 f(h / 3)+f(h)]0hf(x)dx=h/4[3f(h/3)+f(h)]
The truncation error of the formula is given by
T . E . = c / 3 ! f ( ξ ) , 0 < ξ < h where C = 0 h x 3 d x h [ b h 3 27 + c h 3 ] = h 4 36 T . E . = c / 3 ! f ( ξ ) , 0 < ξ < h  where  C = 0 h x 3 d x h b h 3 27 + c h 3 = h 4 36 {:[T.E.=c//3!f^(”’)(xi)”,”0 < xi < h],[” where “C=int_(0)^(h)x^(3)dx-h[(bh^(3))/(27)+ch^(3)]=-(h^(4))/(36)]:}\begin{aligned} T. E. & =c / 3! f^{\prime \prime \prime}(\xi), 0<\xi<h \\ \text { where } C & =\int_0^h x^3 d x-h\left[\frac{b h^3}{27}+c h^3\right]=-\frac{h^4}{36} \end{aligned}T.E.=c/3!f(ξ),0<ξ<h where C=0hx3dxh[bh327+ch3]=h436
Hence we have.
T E = h 4 216 f ( ξ ) = O ( h 4 ) . T E = h 4 216 f ( ξ ) = O h 4 . TE=(-h^(4))/(216)f^(”’)(xi)=O(h^(4)).T E=\frac{-h^4}{216} f^{\prime \prime \prime}(\xi)=O\left(h^4\right) .TE=h4216f(ξ)=O(h4).
7.(c) किसी यांत्रिक निकाय का हैमिल्टोनियन H = p 1 q 1 a q 1 2 + b q 2 2 p 2 q 2 H = p 1 q 1 a q 1 2 + b q 2 2 p 2 q 2 H=p_(1)q_(1)-aq_(1)^(2)+bq_(2)^(2)-p_(2)q_(2)H=p_1 q_1-a q_1^2+b q_2^2-p_2 q_2H=p1q1aq12+bq22p2q2 के द्वारा द्योतित है, जहाँ a , b a , b a,ba, ba,b स्थिरांक हैं। हैमिल्टोनियन समीकरणों का हल निकालिए तथा दर्शाइए कि p 2 b q 2 q 1 = p 2 b q 2 q 1 = (p_(2)-bq_(2))/(q_(1))=\frac{p_2-b q_2}{q_1}=p2bq2q1= स्थिराँक ।
The Hamiltonian of a mechanical system is given by, H = p 1 q 1 a q 1 2 + b q 2 2 p 2 q 2 H = p 1 q 1 a q 1 2 + b q 2 2 p 2 q 2 H=p_(1)q_(1)-aq_(1)^(2)+bq_(2)^(2)-p_(2)q_(2)H=p_1 q_1-a q_1^2+b q_2^2-p_2 q_2H=p1q1aq12+bq22p2q2, where a, b are the constants. Solve the Hamiltonian equations and show that p 2 b q 2 q 1 = p 2 b q 2 q 1 = (p_(2)-bq_(2))/(q_(1))=\frac{p_2-b q_2}{q_1}=p2bq2q1= constant.
Answer:
The Hamiltonian of a mechanical system is given by, H = p 1 q 1 a q 1 2 + b q 2 2 p 2 q 2 H = p 1 q 1 a q 1 2 + b q 2 2 p 2 q 2 H=p_(1)q_(1)-aq_(1)^(2)+bq_(2)^(2)-p_(2)q_(2)H=p_1 q_1-a q_1^2+b q_2^2-p_2 q_2H=p1q1aq12+bq22p2q2, where a a aaa, b b bbb are constants. We are to solve the Hamiltonian equations and show that p 2 b q 2 q 1 = p 2 b q 2 q 1 = (p_(2)-bq_(2))/(q_(1))=\frac{p_2-b q_2}{q_1}=p2bq2q1= constant.

Solution:

Let us consider the generalized coordinates q 1 , q 2 q 1 , q 2 q_(1),q_(2)q_1, q_2q1,q2 and the generalized components of momentum p 1 , p 2 p 1 , p 2 p_(1),p_(2)p_1, p_2p1,p2. The Hamiltonian equations are given by:
p ˙ i = H q i and q ˙ i = H p i p ˙ i = H q i and q ˙ i = H p i p^(˙)_(i)=-(del H)/(delq_(i))quad”and”quadq^(˙)_(i)=(del H)/(delp_(i))\dot{p}_i=-\frac{\partial H}{\partial q_i} \quad \text{and} \quad \dot{q}_i=\frac{\partial H}{\partial p_i}p˙i=Hqiandq˙i=Hpi
where i = 1 , 2 i = 1 , 2 i=1,2i=1,2i=1,2.
Applying the Hamiltonian equations to the given Hamiltonian, we have:
  1. q ˙ 1 = q 1 d q 1 d t = q 1 q 1 = c 1 e t q ˙ 1 = q 1 d q 1 d t = q 1 q 1 = c 1 e t q^(˙)_(1)=q_(1)=>(dq_(1))/(dt)=q_(1)=>q_(1)=c_(1)e^(t)\dot{q}_1=q_1 \Rightarrow \frac{dq_1}{dt}=q_1 \Rightarrow q_1=c_1 e^tq˙1=q1dq1dt=q1q1=c1et
  2. p ˙ 1 = 2 a q 1 p 1 d p 1 d t + p 1 = 2 a c 1 e t p 1 = a c 1 e t + c 2 e t p ˙ 1 = 2 a q 1 p 1 d p 1 d t + p 1 = 2 a c 1 e t p 1 = a c 1 e t + c 2 e t p^(˙)_(1)=2aq_(1)-p_(1)=>(dp_(1))/(dt)+p_(1)=2ac_(1)e^(t)=>p_(1)=ac_(1)e^(t)+c_(2)e^(-t)\dot{p}_1=2 a q_1-p_1 \Rightarrow \frac{dp_1}{dt}+p_1=2 a c_1 e^t \Rightarrow p_1=a c_1 e^t+c_2 e^{-t}p˙1=2aq1p1dp1dt+p1=2ac1etp1=ac1et+c2et (using integrating factor e t e t e^(t)e^tet)
  3. q ˙ 2 = q 2 q 2 = c 3 e t q ˙ 2 = q 2 q 2 = c 3 e t q^(˙)_(2)=-q_(2)=>q_(2)=c_(3)e^(-t)\dot{q}_2=-q_2 \Rightarrow q_2=c_3 e^{-t}q˙2=q2q2=c3et
  4. p ˙ 2 = p 2 2 b q 2 d p 2 d t p 2 = 2 b c 3 e t p 2 = b c 3 e t + c 4 e t p ˙ 2 = p 2 2 b q 2 d p 2 d t p 2 = 2 b c 3 e t p 2 = b c 3 e t + c 4 e t p^(˙)_(2)=p_(2)-2bq_(2)=>(dp_(2))/(dt)-p_(2)=-2bc_(3)e^(-t)=>p_(2)=bc_(3)e^(-t)+c_(4)e^(t)\dot{p}_2=p_2-2 b q_2 \Rightarrow \frac{dp_2}{dt}-p_2=-2 b c_3 e^{-t} \Rightarrow p_2=b c_3 e^{-t}+c_4 e^tp˙2=p22bq2dp2dtp2=2bc3etp2=bc3et+c4et (using integrating factor e t e t e^(-t)e^{-t}et)
Now, let’s consider the expression p 2 b q 2 q 1 p 2 b q 2 q 1 (p_(2)-bq_(2))/(q_(1))\frac{p_2-b q_2}{q_1}p2bq2q1:
p 2 b q 2 q 1 = b c 3 e t + c 4 e t b c 3 e t c 1 e t = c 4 e t c 1 e t = c 4 c 1 = constant p 2 b q 2 q 1 = b c 3 e t + c 4 e t b c 3 e t c 1 e t = c 4 e t c 1 e t = c 4 c 1 = constant (p_(2)-bq_(2))/(q_(1))=(bc_(3)e^(-t)+c_(4)e^(t)-bc_(3)e^(-t))/(c_(1)e^(t))=(c_(4)e^(t))/(c_(1)e^(t))=(c_(4))/(c_(1))=”constant”\frac{p_2-b q_2}{q_1} = \frac{b c_3 e^{-t}+c_4 e^t-b c_3 e^{-t}}{c_1 e^t} = \frac{c_4 e^t}{c_1 e^t} = \frac{c_4}{c_1} = \text{constant}p2bq2q1=bc3et+c4etbc3etc1et=c4etc1et=c4c1=constant

Conclusion:

The expression p 2 b q 2 q 1 p 2 b q 2 q 1 (p_(2)-bq_(2))/(q_(1))\frac{p_2-b q_2}{q_1}p2bq2q1 is indeed a constant, as shown above, under the solutions of the Hamiltonian equations for the given mechanical system.
8.(a) बूलीय व्यंजक :
( a + b ) ( b ¯ + c ) + b ( a ¯ + c ) ( a + b ) ( b ¯ + c ) + b ( a ¯ + c ) (a+b)*( bar(b)+c)+b*( bar(a)+ vec(c))(a+b) \cdot(\bar{b}+c)+b \cdot(\bar{a}+\vec{c})(a+b)(b¯+c)+b(a¯+c) को बूलीय-बीजगणित के नियमों का उपयोग करने के द्वारा सरल कीजिए। इस की सत्यता-सारणी से इसको मिनटर्म प्रसामान्य रूप में लिखिए।
Simplify the boolean expression: ( a + b ) ( b ¯ + c ) + b ( a ¯ + c ¯ ) ( a + b ) ( b ¯ + c ) + b ( a ¯ + c ¯ ) (a+b)*( bar(b)+c)+b*( bar(a)+ bar(c))(a+b) \cdot(\bar{b}+c)+b \cdot(\bar{a}+\bar{c})(a+b)(b¯+c)+b(a¯+c¯) by using the laws of boolean algebra. From its truth table write it in minterm normal form.
Answer:
To simplify the given Boolean expression, we will use the laws of Boolean algebra. The given expression is:
( a + b ) ( b + c ) + b ( a + c ) ( a + b ) ( b ¯ + c ) + b ( a ¯ + c ¯ ) (a+b)*( bar(b)+c)+b*( bar(a)+ bar(c))(a + b) \cdot (\overline{b} + c) + b \cdot (\overline{a} + \overline{c})(a+b)(b+c)+b(a+c)

Step 1: Simplification

Let’s simplify the expression step by step:

Distributive Law:

= a ( b + c ) + b ( b + c ) + b ( a + c ) = a ( b ¯ + c ) + b ( b ¯ + c ) + b ( a ¯ + c ¯ ) =a*( bar(b)+c)+b*( bar(b)+c)+b*( bar(a)+ bar(c))= a \cdot (\overline{b} + c) + b \cdot (\overline{b} + c) + b \cdot (\overline{a} + \overline{c})=a(b+c)+b(b+c)+b(a+c)

Absorption Law:

= a ( b + c ) + b + b ( a + c ) = a ( b ¯ + c ) + b + b ( a ¯ + c ¯ ) =a*( bar(b)+c)+b+b*( bar(a)+ bar(c))= a \cdot (\overline{b} + c) + b + b \cdot (\overline{a} + \overline{c})=a(b+c)+b+b(a+c)

Absorption Law:

= a ( b + c ) + b = a ( b ¯ + c ) + b =a*( bar(b)+c)+b= a \cdot (\overline{b} + c) + b=a(b+c)+b

Step 2: Truth Table and Minterm Normal Form

Now, let’s create a truth table for the simplified expression and then write the expression in minterm normal form. The minterm normal form is the OR of all the minterms where the output is 1.
a a aaa b b bbb c c ccc b + c b ¯ + c bar(b)+c\overline{b} + cb+c a ( b + c ) a ( b ¯ + c ) a*( bar(b)+c)a \cdot (\overline{b} + c)a(b+c) a ( b + c ) + b a ( b ¯ + c ) + b a*( bar(b)+c)+ba \cdot (\overline{b} + c) + ba(b+c)+b
0 0 0 1 0 0
0 0 1 1 0 0
0 1 0 0 0 1
0 1 1 1 0 1
1 0 0 1 1 1
1 0 1 1 1 1
1 1 0 0 0 1
1 1 1 1 1 1

Minterm Normal Form:

The minterm normal form is the OR of all the minterms where the output is 1. From the truth table, the minterms where the output is 1 are when a , b , c a , b , c a,b,ca, b, ca,b,c are:
  • 001 001 001001001 (Minterm 1)
  • 011 011 011011011 (Minterm 3)
  • 100 100 100100100 (Minterm 4)
  • 101 101 101101101 (Minterm 5)
  • 110 110 110110110 (Minterm 6)
  • 111 111 111111111 (Minterm 7)
So, the minterm normal form of the given Boolean expression is:
Σ m ( 1 , 3 , 4 , 5 , 6 , 7 ) Σ m ( 1 , 3 , 4 , 5 , 6 , 7 ) Sigma m(1,3,4,5,6,7)\Sigma m(1, 3, 4, 5, 6, 7)Σm(1,3,4,5,6,7)
or
From Truth Fable, Minter normal form is
a ¯ b c ¯ + a ¯ b c + a b ¯ c ¯ + a b ¯ c + a b c ¯ + a b c a ¯ b c ¯ + a ¯ b c + a b ¯ c ¯ + a b ¯ c + a b c ¯ + a b c bar(a)b bar(c)+ bar(a)bc+a bar(b) bar(c)+a bar(b)c+ab bar(c)+abc\bar{a} b \bar{c}+\bar{a} b c+a \bar{b} \bar{c}+a \bar{b} c+a b \bar{c}+a b ca¯bc¯+a¯bc+ab¯c¯+ab¯c+abc¯+abc
8.(b) एक द्विविमीय विभव-प्रवाह के लिए वेग विभव ϕ = x 2 y x y 2 + 1 3 ( x 3 y 3 ) ϕ = x 2 y x y 2 + 1 3 x 3 y 3 phi=x^(2)y-xy^(2)+(1)/(3)(x^(3)-y^(3))\phi=x^2 y-x y^2+\frac{1}{3}\left(x^3-y^3\right)ϕ=x2yxy2+13(x3y3) के द्वारा दिया गया है । x x xxx y y yyy दिशाओं के अनुदिश वेग घटकों का निर्धारण कीजिए । धारा-फलन ψ ψ psi\psiψ का भी निर्धारण कीजिए और जाँच कीजिए कि क्या ϕ ϕ phi\phiϕ एक सम्भव प्रवाह को निस्पित करता है अथवा नहीं।
For a two-dimensional potential flow, the velocity potential is given by ϕ = x 2 y x y 2 + 1 3 ( x 3 y 3 ) ϕ = x 2 y x y 2 + 1 3 x 3 y 3 phi=x^(2)y-xy^(2)+(1)/(3)(x^(3)-y^(3))\phi=x^2 y-x y^2+\frac{1}{3}\left(x^3-y^3\right)ϕ=x2yxy2+13(x3y3). Determine the velocity components along the directions x x xxx and y y yyy. Also, determine the stream function ψ ψ psi\psiψ and check whether ϕ ϕ phi\phiϕ represents a possible case of flow or not.
Answer:
Velocity Components:
Let q = u i ^ + v ȷ ^ q = u i ^ + v ȷ ^ vec(q)=u hat(i)+v hat(ȷ)\vec{q}=u \hat{i}+v \hat{\jmath}q=ui^+vȷ^. Then,
u = ϕ x u = ( 2 x y y 2 + x 2 ) u = y 2 x 2 2 x y u = ϕ x u = 2 x y y 2 + x 2 u = y 2 x 2 2 x y {:[u=-(del phi)/(del x)],[ Longrightarrow u=-(2xy-y^(2)+x^(2))],[ Longrightarrow u=y^(2)-x^(2)-2xy]:}\begin{aligned} & u=-\frac{\partial \phi}{\partial x} \\ & \Longrightarrow u=-\left(2 x y-y^2+x^2\right) \\ & \Longrightarrow u=y^2-x^2-2 x y \end{aligned}u=ϕxu=(2xyy2+x2)u=y2x22xy
Also,
v = ϕ y v = ( x 2 2 x y y 2 ) v = y 2 x 2 + 2 x y v = ϕ y v = x 2 2 x y y 2 v = y 2 x 2 + 2 x y {:[v=-(del phi)/(del y)],[=>v=-(x^(2)-2xy-y^(2))],[ Longrightarrow v=y^(2)-x^(2)+2xy]:}\begin{aligned} & v=-\frac{\partial \phi}{\partial y} \\ & \Rightarrow v=-\left(x^2-2 x y-y^2\right) \\ & \Longrightarrow v=y^2-x^2+2 x y \end{aligned}v=ϕyv=(x22xyy2)v=y2x2+2xy
Stream Function ψ ψ psi\psiψ:
We know that ϕ + i ψ ϕ + i ψ phi+i psi\phi+i \psiϕ+iψ is an analytic function and satisfies Cauchy Riemann equations.
So, ψ y = u and ψ x = v ψ x = y 2 x 2 + 2 x y  So,  ψ y = u  and  ψ x = v ψ x = y 2 x 2 + 2 x y {:[” So, “(del psi)/(del y)=u” and “(del psi)/(del x)=v],[=>quad(del psi)/(del x)=y^(2)-x^(2)+2xy]:}\begin{aligned} & \text { So, } \frac{\partial \psi}{\partial y}=u \text { and } \frac{\partial \psi}{\partial x}=v \\ & \Rightarrow \quad \frac{\partial \psi}{\partial x}=y^2-x^2+2 x y \end{aligned} So, ψy=u and ψx=vψx=y2x2+2xy
Integrating with respect to x x xxx:
ψ = x y 2 x 3 3 + x 2 y + f ( y ) ψ = x y 2 x 3 3 + x 2 y + f ( y ) psi=xy^(2)-(x^(3))/(3)+x^(2)y+f(y)\psi=x y^2-\frac{x^3}{3}+x^2 y+f(y)ψ=xy2x33+x2y+f(y)
Now,
ψ y = 2 x y + x 2 + f ( y ) ψ y = u x 2 + 2 x y + f ( y ) = x 2 + 2 x y y 2 f ( y ) = y 2 d f d y = y 2 f = y 3 3 + c ψ y = 2 x y + x 2 + f ( y ) ψ y = u x 2 + 2 x y + f ( y ) = x 2 + 2 x y y 2 f ( y ) = y 2 d f d y = y 2 f = y 3 3 + c {:[(del psi)/(del y)=2xy+x^(2)+f^(‘)(y)],[(del psi)/(del y)=-u],[=>x^(2)+2xy+f^(‘)(y)=x^(2)+2xy-y^(2)],[=>f^(‘)(y)=-y^(2)],[(df)/(dy)=-y^(2)],[=>f=(-y^(3))/(3)+c]:}\begin{aligned} & \frac{\partial \psi}{\partial y}=2 x y+x^2+f^{\prime}(y) \\ & \frac{\partial \psi}{\partial y}=-u \\ & \Rightarrow x^2+2 x y+f^{\prime}(y)=x^2+2 x y-y^2 \\ & \Rightarrow f^{\prime}(y)=-y^2 \\ & \frac{d f}{d y}=-y^2 \\ & \Rightarrow f=\frac{-y^3}{3}+c \end{aligned}ψy=2xy+x2+f(y)ψy=ux2+2xy+f(y)=x2+2xyy2f(y)=y2dfdy=y2f=y33+c
So,
ψ = x y 2 ( x 3 + y 3 ) 3 + x 2 y + c ψ = 0 at origin c = 0 ψ = x y 2 x 3 + y 3 3 + x 2 y + c ψ = 0  at origin  c = 0 {:[psi=xy^(2)-((x^(3)+y^(3)))/(3)+x^(2)y+c],[psi=0″ at origin “Longrightarrow c=0]:}\begin{aligned} & \psi=x y^2-\frac{\left(x^3+y^3\right)}{3}+x^2 y+c \\ & \psi=0 \text { at origin } \Longrightarrow c=0 \end{aligned}ψ=xy2(x3+y3)3+x2y+cψ=0 at origin c=0
So, ψ = x y 2 + x 2 y ( x 3 + y 3 ) 3 ψ = x y 2 + x 2 y x 3 + y 3 3 psi=xy^(2)+x^(2)y-((x^(3)+y^(3)))/(3)\psi=x y^2+x^2 y-\frac{\left(x^3+y^3\right)}{3}ψ=xy2+x2y(x3+y3)3
Checking for Possible Flow:
Since u x + y y = 2 x 2 y + 2 y + 2 x = 0 u x + y y = 2 x 2 y + 2 y + 2 x = 0 (del u)/(del x)+(del y)/(del y)=-2x-2y+2y+2x=0\frac{\partial u}{\partial x}+\frac{\partial y}{\partial y}=-2 x-2 y+2 y+2 x=0ux+yy=2x2y+2y+2x=0,
Longrightarrow\Longrightarrow Equation of continuity is satisfied,
Longrightarrow\Longrightarrow It is a possible flow.
  1. (c) एक पतली वलयिका (एनुलस) क्षेत्र 0 < a r b , 0 θ 2 π 0 < a r b , 0 θ 2 π 0 < a <= r <= b,0 <= theta <= 2pi0<a \leqslant r \leqslant b, 0 \leqslant \theta \leqslant 2 \pi0<arb,0θ2π को घेरती है । इसके तल तापअवरोधी हैं.। आन्तरिक किलारे के साथ-साथ ताप 0 0 0^(@)0^{\circ}0 पर स्थिर रखा जाता है जबकि बाह्य किनारे का ताप T = K cos θ 2 T = K cos θ 2 T=K cos((theta)/(2))T=K \cos \frac{\theta}{2}T=Kcosθ2 पर बनाए रखा जाता है, जहाँ K K KKK एक स्थिरांक है । बलयिका में ताप-वितरण का निर्धारण कीजिए ।
A thin annulus occupies the region 0 < a r b , 0 θ 2 π 0 < a r b , 0 θ 2 π 0 < a <= r <= b,0 <= theta <= 2pi0<a \leqslant r \leqslant b, 0 \leqslant \theta \leqslant 2 \pi0<arb,0θ2π. The faces are insulated. Along the inner edge the temperature is maintained at 0 0 0^(@)0^{\circ}0, while along the outer edge the temperature is held at T = K cos θ 2 T = K cos θ 2 T=K cos((theta)/(2))T=K \cos \frac{\theta}{2}T=Kcosθ2, where K K KKK is a constant. Determine the temperature distribution in the annulus.
Answer:

Formulating the Differential Equation:

The problem is mathematically formulated as solving Laplace’s equation:
2 T = 0 for a r b , 0 θ 2 π 2 T = 0 for a r b , 0 θ 2 π grad^(2)T=0quad”for”quad a <= r <= b,quad0 <= theta <= 2pi\nabla^2 T = 0 \quad \text{for} \quad a \leq r \leq b, \quad 0 \leq \theta \leq 2 \pi2T=0forarb,0θ2π
with the boundary conditions:
T ( a , θ ) = 0 and T ( b , θ ) = K cos θ 2 T ( a , θ ) = 0 and T ( b , θ ) = K cos θ 2 T(a,theta)=0quad”and”quad T(b,theta)=K cos((theta)/(2))T(a, \theta) = 0 \quad \text{and} \quad T(b, \theta) = K \cos \frac{\theta}{2}T(a,θ)=0andT(b,θ)=Kcosθ2

General Solution of Laplace’s Equation:

The required general solution of Laplace’s equation in polar coordinates is given by:
T ( r , θ ) = ( c 1 r n + c 2 r n ) ( A cos n θ + B sin n θ ) T ( r , θ ) = c 1 r n + c 2 r n A cos n θ + B sin n θ T(r,theta)=(c_(1)r^(n)+c_(2)r^(-n))(A cos n theta+B sin n theta)T(r, \theta) = \left(c_1 r^n + c_2 r^{-n}\right) \left(A \cos n \theta + B \sin n \theta\right)T(r,θ)=(c1rn+c2rn)(Acosnθ+Bsinnθ)
The principle of superposition gives
T ( r , θ ) = n = 1 [ r n a 2 n λ n ] ( A n cos n θ + B n sin n θ ) T ( r , θ ) = n = 1 r n a 2 n λ n A n cos n θ + B n sin n θ T(r,theta)=sum_(n=1)^(oo)[r^(n)-(a^(2n))/(lambda ^(n))](A_(n)cos n theta+B_(n)sin n theta)∣T(r, \theta)=\sum_{n=1}^{\infty}\left[r^n-\frac{a^{2 n}}{\lambda^n}\right]\left(A_n \cos n \theta+B_n \sin n \theta\right) \midT(r,θ)=n=1[rna2nλn](Ancosnθ+Bnsinnθ)
Now, using B C B C BCB CBC ii), we obtain
T ( b , θ ) = k cos θ 2 = n = 1 [ b n b n a 2 n ] [ A n cos n θ + B n sin n θ T ( b , θ ) = k cos θ 2 = n = 1 b n b n a 2 n A n cos n θ + B n sin n θ T(b,theta)=k cos((theta)/(2))=sum_(n=1)^(oo)[b^(n)-b^(-n)a^(2n)][A_(n)cos n theta+B_(n)sin n theta:}T(b, \theta)=k \cos \frac{\theta}{2}=\sum_{n=1}^{\infty}\left[b^n-b^{-n} a^{2 n}\right]\left[A_n \cos n \theta+B_n \sin n \theta\right.T(b,θ)=kcosθ2=n=1[bnbna2n][Ancosnθ+Bnsinnθ
Which is a full-range fourier series.
Hence,
A ˙ n ( b n b n a 2 n ) = 1 π 0 2 π k cos θ 2 cos n θ d θ = k 2 π 0 2 π [ cos [ n + 1 2 ] θ + cos ( n 1 2 ) θ ] d θ = k 2 π [ sin ( n + 1 / 2 ) θ ( n + 1 / 2 ) + sin ( n 1 / 2 ) θ ( n 1 / 2 ) ] 0 2 π = 0 ie A n = 0 A ˙ n b n b n a 2 n = 1 π 0 2 π k cos θ 2 cos n θ d θ = k 2 π 0 2 π cos n + 1 2 θ + cos n 1 2 θ d θ = k 2 π sin ( n + 1 / 2 ) θ ( n + 1 / 2 ) + sin ( n 1 / 2 ) θ ( n 1 / 2 ) 0 2 π = 0  ie  A n = 0 {:[A^(˙)_(n)(b^(n)-b^(-n)a^(2n))=(1)/(pi)int_(0)^(2pi)k cos((theta)/(2))cos n theta d theta],[=(k)/(2pi)int_(0)^(2pi)[cos[n+(1)/(2)]theta+cos(n-(1)/(2))theta]d theta],[=(k)/(2pi)[(sin(n+1//2)theta)/((n+1//2))+(sin(n-1//2)theta)/((n-1//2))]_(0)^(2pi)],[=0quad” ie “A_(n)=0]:}\begin{aligned} \dot{A}_n\left(b^n-b^{-n} a^{2 n}\right) & =\frac{1}{\pi} \int_0^{2 \pi} k \cos \frac{\theta}{2} \cos n \theta d \theta \\ & =\frac{k}{2 \pi} \int_0^{2 \pi}\left[\cos \left[n+\frac{1}{2}\right] \theta+\cos \left(n-\frac{1}{2}\right) \theta\right] d \theta \\ & =\frac{k}{2 \pi}\left[\frac{\sin (n+1 / 2) \theta}{(n+1 / 2)}+\frac{\sin (n-1 / 2) \theta}{(n-1 / 2)}\right]_0^{2 \pi} \\ & =0 \quad \text { ie } A_n=0 \end{aligned}A˙n(bnbna2n)=1π02πkcosθ2cosnθdθ=k2π02π[cos[n+12]θ+cos(n12)θ]dθ=k2π[sin(n+1/2)θ(n+1/2)+sin(n1/2)θ(n1/2)]02π=0 ie An=0
Implying A n = 0 A n = 0 A_(n)=0A_n=0An=0. Also
B n ( b n b n a 2 n ) = k n ¯ 0 2 π cos θ / 2 sin n θ d θ = k 2 π 0 2 π [ sin ( n + 1 2 ) θ + sin ( ( n 1 2 ) θ ] ] d θ B n b n b n a 2 n = k n ¯ 0 2 π cos θ / 2 sin n θ d θ = k 2 π 0 2 π sin n + 1 2 θ + sin ( n 1 2 ) θ d θ {:[Bn(b^(n)-b^(-n)a^(2n))=(k)/(( bar(n)))int_(0)^(2pi)cos theta//2sin n theta d theta],[=(k)/(2pi)int_(0)^(2pi)[sin(n+(1)/(2))theta+sin((n-(1)/(2))theta]]d theta]:}\begin{aligned} & B n\left(b^n-b^{-n} a^{2 n}\right)=\frac{k}{\bar{n}} \int_0^{2 \pi} \cos \theta / 2 \sin n \theta d \theta \\ & =\frac{k}{2 \pi} \int_0^{2 \pi}\left[\sin \left(n+\frac{1}{2}\right) \theta+\sin \left((n-\frac{1}{2}) \theta\right]\right] d \theta \end{aligned}Bn(bnbna2n)=kn¯02πcosθ/2sinnθdθ=k2π02π[sin(n+12)θ+sin((n12)θ]]dθ
= k 2 π [ cos ( n + 1 / 2 ) n + 1 / 2 + cos ( n 1 / 2 ) θ 2 n 1 / 2 ] 0 2 π = k 2 π [ 1 n + 1 / 2 1 n + 1 / 2 1 n 1 / 2 1 n 1 / 2 ) = k π [ 1 n + 1 / 2 + 1 n 1 / 2 ] = k π [ 2 n n 2 1 / 4 ] . B n ( b n b n a 2 n ) = 8 k n π ( 4 n 2 1 ) = k 2 π cos ( n + 1 / 2 ) n + 1 / 2 + cos ( n 1 / 2 ) θ 2 n 1 / 2 0 2 π = k 2 π 1 n + 1 / 2 1 n + 1 / 2 1 n 1 / 2 1 n 1 / 2 = k π 1 n + 1 / 2 + 1 n 1 / 2 = k π 2 n n 2 1 / 4 . B n b n b n a 2 n = 8 k n π 4 n 2 1 {:[=(-k)/(2pi)[(cos(n+1//2))/(n+1//2)+(cos(n-1//2)theta^(2))/(n-1//2)]_(0)^(2pi)],[=(-k)/(2pi)[-(1)/(n+1//2)-(1)/(n+1//2)-(1)/(n-1//2)-(1)/(n-1//2))],[=(k)/( pi)[(1)/(n+1//2)+(1)/(n-1//2)]=(k)/( pi)[(2n)/(n^(2)-1//4)].],[:.Bn(b^(n)-b^(-n)a^(2n))=(8kn)/(pi(4n^(2)-1))]:}\begin{aligned} & =\frac{-k}{2 \pi}\left[\frac{\cos (n+1 / 2)}{n+1 / 2}+\frac{\cos (n-1 / 2) \theta^2}{n-1 / 2}\right]_0^{2 \pi} \\ & =\frac{-k}{2 \pi}\left[-\frac{1}{n+1 / 2}-\frac{1}{n+1 / 2}-\frac{1}{n-1 / 2}-\frac{1}{n-1 / 2}\right) \\ & =\frac{k}{\pi}\left[\frac{1}{n+1 / 2}+\frac{1}{n-1 / 2}\right]=\frac{k}{\pi}\left[\frac{2 n}{n^2-1 / 4}\right] . \\ & \therefore B n\left(b^n-b^{-n} a^{2 n}\right)=\frac{8 k n}{\pi\left(4 n^2-1\right)} \end{aligned}=k2π[cos(n+1/2)n+1/2+cos(n1/2)θ2n1/2]02π=k2π[1n+1/21n+1/21n1/21n1/2)=kπ[1n+1/2+1n1/2]=kπ[2nn21/4].Bn(bnbna2n)=8knπ(4n21)
Thus, the temperature distribution in annulus is given by.
T ( r , θ ) = δ k π n = 1 n 4 n 2 1 [ ( s / a ) n ( a / a ) n ( b / a ) n ( a / b ) n ] sin θ T ( r , θ ) = δ k π n = 1 n 4 n 2 1 ( s / a ) n ( a / a ) n ( b / a ) n ( a / b ) n sin θ T(r,theta)=(delta k)/(pi)sum_(n=1)^(oo)(n)/(4n^(2)-1)[((s//a)^(n)-(a//a)^(n))/((b//a)^(n)-(a//b)^(n))]sin thetaT(r, \theta)=\frac{\delta k}{\pi} \sum_{n=1}^{\infty} \frac{n}{4 n^2-1}\left[\frac{(s / a)^n-(a / a)^n}{(b / a)^n-(a / b)^n}\right] \sin \thetaT(r,θ)=δkπn=1n4n21[(s/a)n(a/a)n(b/a)n(a/b)n]sinθ
Which is required result.
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