Numerical Method - Unit Wise Questions
1. How can Horner's rule be used to evaluate the f(x) and f(x) of a polynomial at given point? Explain. Write an algorithm and program to calculate a real root of a polynomial using Horner's rule.
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1. What is error? Discuss various types of errors. Estimate a real root of the following nonlinear equation using bisection method or Newton's method correct up to two decimal places sin x - x2 - x + 3 = 0 (3 + 5)
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1. Define the fixed-point iteration method. Given the function f(x) = x2 − 2x − 3 = 0, rearrange the function in such a way that the iteration method converses to its roots. (2+3+3)
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1. Discuss methods of Half Interval and Newton’s for solving the nonlinear equation f(x) = 0. Illustrate the methods by figure and compare them stating their advantages and disadvantages. (8)
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1. Define the types of errors in numerical calculations. Derive the formula for secant method and illustrate the method by figure. (4+4)
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1. Derive the formula to solve nonlinear equation using secant method. Using your formula estimate a real root of following nonlinear equation using secant method correct up to two decimal places x2+ ln x = 3. (3+5)
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1. What is bracketing and non-bracketing method? Explain with the help of example. Estimate a real root of following nonlinear equation using bisection method correct up to two significant figures(3 + 5)
x2sinx + e-x = 3
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1. How is the bisection method convergent to a root of an equation? Apply the bisection method to find a root of the equation (3 + 5)
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1. What are the sources of errors? Discuss various types of errors. Find the roots of the equation x2 + 5.6x − 10= 0 by trial and error method up to 4 significant digits. (1+3+4)
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1. Explain the idea of the secant method to estimate the root of any equation. Using the secant method, estimate the root of the equation x2 - 4x - 10 = 0 with the initial estimates of x1 = 4 and x2 = 2. Do these points bracket a root?(3 + 4 + 1)
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1. How can you use bisection method for the solution of nonlinear equations? Discuss with suitable example.(8)
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2. Describe Newton’s method and its convergence. Find the root of equation f(x) = ex− 4x2 = 0 using Newton method up to 5 decimal places. (4+4)
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1. What is non-linear equation? Derive the required expression to calculate the root of non-linear equation using secant method. Using this expression find a root of following equation.
X2 + cos(x) - e -x - 2 = 0
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1. Derive the formula for Newton Raphson Method. Solve the equation x2 + 4x - 9 = 0 using Newton Raphson method. Assume error precision is 0.01. Discuss drawbacks of the Newton Raphson method.
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4. Write a program to solve a non linear equation using bisection method.
#include<stdio.h>
#include<conio.h>
#include<math.h>
#include<stdlib.h>
float f ( float x)
{
float y;
y= pow(x, 2)+x -2;
return y;
}
void main()
{
float x1, x2, x0, error=0.0001;
int i=0;
printf("\\nEnter two initial guess:");
scanf("%f%f", &x1, &x2);
if (f(x1 )*f(x2 )>0)
{
printf("\\nWrong Input!!");
exit(0);
}
else
{
do
{
x0=(x1+x2)/2;
if(f(x0 )*f(x1 )>0)
x1=x0;
else
x2=x0;
i++;
}while(fabs (f(x0))>error);
}
printf("\\nRoot=%f", x0);
printf("\\nNumber of
iteration=%d",i);
getch();
}
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4. How the half-interval method can estimate a root of non-linear equation? Find a real root of following equation using half-interval method correct up to two decimal places.
x2 - e-x - x = 1
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5. Find the roots of the following equations using Newton’s method.
log x – cos x = 0
Given,
Let the initial guess be 0.5.
Now, let us calculate the root using tabular form.
Here, the 4th and 5th
iteration has same value of x2 up to 2 decimal place, so that root
of given equation is 1.42.
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5. Calculate a real root of the given equation using fixed point iteration correct up to 3 significant figures.
2x3 - 2x = 5
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7. Write an algorithm and program to compute all roots of polynomial using secant method.
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4. Define the terms true error and relative error? Use Horner' method to evaluate polynomial 2x3 - 3x2 + 5x - 2 at x = 3 and write down its algorithm.
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7. Write an algorithm to solve non-linear equation using secant method. On the basis of your algorithm write a C-program that reads two initial guess from keyboard and displays the following information if the solution is obtained:(5 + 7)
a) Calculated root of the equation
b) Required number of iterations
c) Functional value at calculated root
If solution is not obtained within 200 iterations your program should be terminated by displaying the following message:
NO SOLUTION WITHIN 200 ITERATIONS
TRY AGAIN WITH NEW INITIAL VALUES
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7. Write an algorithm and C-program code to solve non-linear equation using Newton’s method. Your program should read an initial guess from keyboard and display the followings if the solution is obtained: (5+7)
- Estimated root of the equation
- Functional value at calculated root
- Required number of iterations
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7. Write an algorithm and a C-program for the fixed point iteration method to find the roots of non-linear equation. (4+8)
OR
Write an algorithm and a C-program for the Lagrange’s interpolation to approximate the functional value at any given x from given n data. (4+8)
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7. Write an algorithm and C program for the secant method to find the roots of non-linear equation.(4 + 8)
OR
Write an algorithm and a C program for the Sinpson's 1/3 rule to integrate a given function.(4 + 8)
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4. Calculate a real negative root of following equation using Newton's method for polynomial.
x4 + 2x3 + 3x2 + 4x = 5
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2. Write an algorithm and a program to compute the interpolation value at a specific point,
given a set of data points, using Lagrange interpolation method.
Algorithm For Lagrange’s
interpolation
1.
Read
the number of data ‘n’.
2.
Read
the value at which value is needed (say y).
3.
Read
available data points x and f(x).
4.
for
i=0 to n
for
j=0 to n
if(i!=j)
L[i]=L[i]*(y-x[j])/(x[i]-x[j])
end
if
end
for
end
for
5.
for
i=0 to n
sum=sum+L[i]*f[i]
end
for
6.
Print
interpolation value ‘sum’ at y.
Stop
Program
#include<stdio.h>
#include<conio.h>
int
main()
{
float x[10], f[10], y, sum=0.0, l;
int n, i, j;
printf("\\nInput number of data:");
scanf("%d", &n);
printf("\\nInput data points x(i) &
f(i):\\n"); for(i=0;i<n;i++)
{
printf("x[%d]=",i);
scanf("%f", &x[i]);
printf("f[%d]=",i);
scanf("%f", &f[i]);
}
printf("\\nFunctional
value:");
scanf("%f",
&y);
for(i=0;i<n;i++)
{
l=1;
for(j=0;j<n;j++)
{
if(j!=i)
{
l=l*(y-x[j])/(x[i]-x[j]);
}
}
sum=sum+l*f[i];
}
printf("\\nValue
at %f=%f", y, sum);
getch();
return
0;
}
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2. What do you mean by interpolation problem? Define divided difference table and construct the table from the following data set. (2+2+4)
OR
Find the least squares line that fits the following data.
What do you mean by linear least square approximation?
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2. Define the linear least squares approximations. Give the data set (xi, yi) as (20.5, 765), (32.7, 826), (51.0, 873), (73.2, 942), (95.7, 1032) find the linear least square to fit given data. (2+6)
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2. Estimate f(3) from the following data using Cubic Spline interpolation.
OR
Find the best fitting quadratic polynomial from following data using least square approximation.
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2. Define interpolation. Find the Lagrange interpolation polynomial to fit the following data. Estimate the value (1 + 6 + 1)
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2. Derive the equation for Lagrange’s interpolating polynomial and find the value of f(x) at x = 1 for the following: (4+4)
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2. Define interpolation. Find the functional value at x=3.6 from the following data using forward difference table:
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2. Given the data
Calculate f(1.35) using Newton's interpolating of order 1 through 3. Choose base points to attain good accuracy. Comment on the accuracy of results on the order of polynomial.(5 + 3)
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2. Define interpolation. Find the Lagrange interpolation polynomial to fit the following data:
Use the polynomial to estimate the value of e15. (2 + 6)
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2. How polynomial interpolation differs with Cubic Spline interpolation? Explain. Find the best fit curve of quadratic polynomial using least square approximation from following data.
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2. How interpolation differs from regression? Write down algorithm and program for Lagrange interpolation.
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3. What do you mean by interpolation and approximation? Use Lagrange interpolation to estimate the value of f(0.6) from the following table of values. (2+6)
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4. Using Newton’s divided difference interpolating polynomial estimate the value of f(x) at x = 2.25 for the function defined as
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6. Estimate the value of ln(3.5) using Newton’s backward difference formula, given the following data
The difference table is
Here,
Now according to Newton’s backward difference formula;
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6. What is Newton's interpolation? Obtain the divided difference table from the following data set and estimate the f(x) at x=2 and x=5.
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7. Write an algorithm and C-program to approximate the functional value at any given x from given n no. of data using Lagrange’s interpolation. (5+7)
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7. Fit a straight line to the following set of data.
We have,
Therefore the linear equation is
y = a + bx
i.e. y = 1.6 + 1.2x
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5. Construct Newton's forward difference table for the given data points and approximate the value of f(x) at x = 15.
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5. What is least squares approximation of fitting a function? How does it differ with polynomial interpolation? Explain with suitable example.
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7. What is linear regression? Fit the linear function to the following data.
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8. What are the problems with polynomial interpolation for large number of data set? How such problems are addressed? Explain with example.
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6. Fit the curve y = ae bx through the following data points.
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6. Find the lowest degree polynomial, which passes through the following points:
Using this polynomial estimate f(x) at x = 0
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7. Fit function of type y = a + bx for the following points using least square method.
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3. Derive Composite Simpson’s 1/3 Rule for numerical integration. How does it improve
the accuracy of integration?
Here, the integration interval is divided into n number of segments of equal width, where n is even number. Then the step size is
We have from simpson’s 1/3 rule,
Therefore,
This equation is called composite Simpson’s 1/3 rule.
It improves the accuracy of integration formulae by locating integration
points in special locations.
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3. How do you find the derivative if the function values are given in a tabulated form? The distance traveled by a vehicle at the intervals of 2 minutes are given as follows. Evaluate the velocity and acceleration of the
Vehicle at time T = 5, 10, 13.
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3. (a) For the function estimate f'(2.1) and f''(2.7) [take h = 0.05] (3)
(b) Evaluate using trapezoidal rule taking h = 0.1 and h = 0.2. Also improve your result using Romberg integration.(4)
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3. Derive the composite formula for the trapezoidal rule with its geometrical figure. Evaluate dx using this rule with n=5, upto 6 decimal places.(4 + 4)
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3. Write Newton-cotes integration formulas in basic form for x = 1, 2, 3 and give their composite rules. Evaluate using the Gaussian integration three point formula. (4+4)
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3. Evaluate using trapezoidal rule with n=10. Also evaluate the same integral using Grossion 3 point formula and compare the result. (4+4)
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3. a) For the function estimate f’(6.3) and f”(6.3) [take h = 0.01] (4)
b) Evaluate using Gaussian integration 3 point formula. (4)
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3. Derive Simpson’s 1/3 rule to evaluate numerical integration. Using this formula evaluate (4 + 4)
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3. Derive Simpson’s 1/3 rule to evaluate numerical integration. Using this formula evaluate (4 + 4)
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3. Derive trapezoidal rule to evaluate numerical integration. Use this formula to evaluate the integral
(2 + 6)
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8. Estimate the first derivative of f(x)=ln x at x=1 using the second order central difference
formula.
Given,
f(x)=ln x
let h=0.1
We have central divided difference formula for second order is
= -1.009
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9. Evaluate the following integration using Romberg integration.
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8. Calculate the integral value of the function given below from x = 1.8 to x = 3.4 using Simpson's 1/3 rule.
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8. Write down algorithm and program for the differentiating continuous function using three point formula.
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9. Evaluate the following integration using Romberg integration.
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9. How Simpson's 1/3 rule differs from trapezoidal rule? Derive the formula for Simpson's 1/3 rule.
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1. Compare Gauss Elimination method and Gauss Jordan method of solving simultaneous equation. Use Gauss Elimination to solve the following system of equation and also write its algorithm.
2x+3y+4z=5
3x+4y+5z=6
4x+5y+6z=7
Comparison between Gauss Elimination method and Gauss Jordan method
- In Gauss- elimination method, the augmented
matrix is reduced to Echelon form using row operations and then back
substitution is applied to get values of unknowns, occurring in a system of
linear equations.
- In Gauss-Jordan method, the augmented matrix is
reduced to reduced Echelon form using elementary row operations to obtain
values of unknowns of a system of linear equations.
- For small system it more convenient to use Gauss Jordan method.
- Gauss Jordan requires more computational work than Gauss Elimination.
Given system of equation,
2x+3y+4z=5
3x+4y+5z=6
4x+5y+6z=7
The augmented matrix of given system is;
Applying,
Applying,
Now,
using backward substitution;
3z
= 0
i.e. z = 0
Finding the value of y using the value of z
Again, finding the value of x using the value of y and z
Hence the value of x, y, z are -2, 3, 0 respectively.
Algorithm
for Gauss elimination method
1.
Start
2. Read the order of matrix ‘n’ and take the
coefficients of linear equation.
3.
Do for k=1 to n-1
Do for i=k+1 to n
Do for j=k+1 to n+1
a[i][j]=a[i][j]-a[i][k]/a[k][k]*a[k][j]
end for j
end for i
end for k
4.
Compute x[n]=a[n][n+1]/a[n][n]
5.
Do for k=n-1 to 1
Sum=0
Do for j=k+1 to n
Sum=Sum+a[k][j]*x[j]
end for j
x[k]=(a[k][n+1]-Sum)/a[k][k]
end for k
6.
Display the result x[k]
7. Stop
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2. What is matrix factorization? How can it be used to solve system of linear equations? Factorize the given matrix A and solve the system of equations Ax=b for given b using L and U matrices.
and
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2. What is matrix factorization? Factorize the given matrix A into LU using Dolittle algorithm and also solve Ax = b for given b using L and U matrices.
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4. Decompose the given matrix [A] into LU form. Then using decomposed matrices L and U solve the system of linear equation Ax = b for given [b].(4 + 4)
OR
How can you calculate the inverse of a matrix? Explain. Solve the system of linear equations Ax = b for given [A] and [b] using Gauss elimination method. (use partial pivoting) (3 + 5)
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4. Solve the following algebraic system of linear equations by Gauss-Jordan algorithm. (8)
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4. What do you mean by ill-conditioned systems? Solve the following system using Dolittle LU decomposition method.(2 + 6)
3x1 + 2x2 + x3 = 24
2x1 + 3x2 + 2x3 = 14
x1 + 2x2 + 3x3 = 14
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4. What do you mean by ill-conditioned systems? Solve the following system using Dolittle LU decomposition method.
3x1 + 2x2 + x3 = 10
2x2 + 3x2 + 2x3 = 14
x1 + 2x2 + 3x3 = 14
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4. Discuss Gauss-Jordan method for solving a system of linear equations. Solve the system
2x1 + 4x2 - 6x3 = -8
x1 + 3x2 +x3 = 10
2x1 - 4x2 - 2x3 = -12
Using Gauss-Jordan method.
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4. What is pivoting? Why is it necessary? Explain. Solve the following set of equations using Gauss elimination or Gauss Seidel method.(3 + 5)
x1 + 10x2 +x3 = 24
10x1 + x2 + x3 = 15
x1 + x2 + 10x3 = 33
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3. Why partial pivoting is used with Naive Gauss Elimination method? Solve the following system of equations using Gauss Elimination method with partial pivoting? How Gauss Jordan method differs from Gauss elimination method?
2x + 2y - z = 6
4x + 2y + 3z = 4
x + y + z = 0
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5. Write an algorithm and program to solve system of linear equations using Gauss- Jordan method. (4+8)
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5. Write an algorithm and program to solve system of linear equations using Gauss-Seidel iterative method. (4+8)
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4. Solve the following set of equation using Gauss elimination or Gauss Jordan method. (8)
3x1 + 5x2 - 3x3 + x4 = 16
2x1 + x2 + x3 + 4x4 = 9
3x1 – 4x2 – x4 = 1
2x1 + x2 – 3x3 + 9x4 = 5
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5. Write algorithm for Gauss- Seidel method for solving the system of linear equations. Also solve the following system of linear equations using that method. (4+4)
10x1 + x2 + x3 = 12
x1 + 10x2 - x3 = 10
x1 - 2x2 + 10x = 9
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7. Discuss the Doolittle LU decomposition method for matrix factorization.
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9. Compare and contrast between Jacobi iterative method and Gauss Seidal method.
Both the Jacobi and Gauss-Seidel methods are iterative
methods for solving the linear system Ax = b.
In the Jacobi method the updated vector x is used for
the computations only after all the variables (i.e. all components of the
vector x) have been updated. On the other hand in the Gauss-Seidel method, the
updated variables are used in the computations as soon as they are updated.
Thus in the Jacobi method, during the computations for a particular iteration, the “known” values are all from the previous iteration. However in the Gauss-Seidel method, the “known” values are a mix of variable values from the previous iteration (whose values have not yet been evaluated in the current iteration), as well as variable values that have already been updated in the current iteration.
Even though the Gauss-Seidel’s method uses the improved values as soon as they are computed, this does not ensure that the Gauss-Seidel’s method would converge faster than Jacobi iterations.
Consider a system of linear equation;
Then, these equation can be written as;
From Gauss Jacobi approximation; we have, (with initial approximation x1 = a, x2 = b & x3 = c)
And, from Gauss Seidel approximation;
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10. Solve the following set of linear equations using Gauss Jordan method.
x2 + 2x3 + 3x4 = 9
7x1 + 6x2 + 5x3 + 4x4 = 33
8x1 + 9x2 + x4 = 27
2x1 + 5x2 + 4x3 + 3x4 = 23
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10. Solve the following set of equations using Gauss Seidel method.
x + 2y + 3z = 4
6x - 4y + 5z = 10
5x + 2y + 2z = 25
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3. What is higher order differential equation? How can you solve the higher order differential equation? Explain. Solve the following differential equation for , taking h=0.25.
with y(1) = 1 and y'(1) = 2
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3. What is initial value problem and boundary value problem? Write an algorithm and program to solve the boundary value problem using shooting method.
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5. Obtain y(1.5) to the following differential equation using Runge-Kutta 4th order method. (8)
taking h = 0.25
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5. Solve the following boundary value problem using shooting method.(8)
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5. (a) How can you solve higher order differential equation? Explain. (3)
(b) Solve the following differential equation within 1 ≤ x ≤ 2 using Runge-Kutta 4th order method. (5)
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5. How can you solve higher order differential equation? Explain. Solve the following differential within 0 ≤ x ≤ 1 using Heun’s method.(3 + 5)
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5. Compare Euler’s method with Heun’s method for solving differential equation. Obtain y(1.5) from given differential equation using Runge-Kutta 4th order method.(4 + 4)
OR
Solve the following boundary value problem using shooting method.(8)
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5. How can you use Taylor series method to find the solution of ordinary differential equation? Use the Taylor method to solve the equation (5 + 3) y' = x2 + y2 for x = 0.25 and x = 0.5 given y(0) = 1
OR
Define boundary value problem. Use shooting method to solve the equation in the interval(1, 2).
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6. Explain the Picard’s proves of successive approximation. Obtain a solution upto the fifth approximation of the equation such that y = 1 when x = 0 using Picard’s process of successive approximations . (2+6)
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7. Define ordinary differential equation of the first order. What do you mean by initial value problem? Find by Taylor’s series method, the values of y at x = 0.1 and x = 0.2 to find places of decimal form
(2 + 6)
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7. Write an algorithm and program for computer to obtain the solution of differential equation using Runge-Kutta Method. {5+7)
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10. Explain about boundary value problem with example? Differentiate it with initial value
problem
Boundary Value Problem
Consider the following linear second order differential equation,
Suppose we are interested in solving this differential equation between the values x = a & z = b. Hence a & b are two values such that a<b. Let us divide the interval [a, b] into n equal subintervals of length h each.
Let x0, x1,.....,xn be the pivotal points and a & b are called the boundary points. Solving the differential equation means finding the values of y0, y1, ....., yn. Suppose y0 and yn are given. That is the solution values at the boundary points are given. Then the differential equation is called a Boundary Value Problem. So, the following is the general form of a boundary value problem.
Difference between Initial value and Boundary value problem
An initial value problem has all of the conditions specified at the same value of the independent variable in the equation (and that value is at the lower boundary of the domain, thus the term “initial” value). On the other hand, a boundary value problem has conditions specified at the extremes of the independent variable. For example, if the independent variable is time over the domain [0,1], an initial value problem would specify a value of y(t) and y‘(t) at time t = 0, while a boundary value problem would specify values for y(t) at both t = 0 and t = 1.
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11. Solve the following differential equation for , taking h = 0.25 using Heun's method.
y'(x) + x2y = 3x, with y(1) = 1
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11. Use the Heun's method to estimate y(0.4) when
y’(x)=x2
+y2 with y(0)=0.
Assume h=0.2
Here,
1st iteration:
2nd
iteration:
Here,
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10. Appropriate the solution of y' = 2x + y , y(0) = 1 using Eulers method with step size 0.1. Approximate the value of y(0.4).
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11. From the following differential equation estimate y(1) using RK 4th order method.
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12. How boundary value problems differs from initial value problems? Discuss shooting method for solving boundary value problem.
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6. Write the finite difference formula for solving Poisson's equation. Hence solve the Poisson equationover the domain 0 ≤ x ≤ 1.5 and 0 ≤ y ≤ 3 with f = 0 on the boundary and h = 0.5 (1 + 7)
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6. (a) Derive a difference equation to solve Laplace equation.(3)
(b) The steady-state two-dimensional heat-flow in a metal plate is defined by . Given the boundary conditions as shown in figure below. find the temperatures at interior points A, B, C, and D.(5)
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6. Derive a difference equation to represent a Poison’s equation. Solve the Poison’s equation ∇2 f = 2x2y2 over the domain 0 ≤ x ≤ 3, 0 ≤ y ≤ 3 with f = 0 on the boundary and h = 1.(3 + 5)
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6. What do you understand by the partial differential equation? Illustrate it with practical example and derive difference equation. (8)
OR
Find the solution of following differential equations using Taylor series method.
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6. Define partial differential equation. Discuss Laplace's equation along with its derivation.(2 + 6)
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6. a) How can you obtain numerical solution of a partial differential equation? Explain.(3)
b) The steady-state two-dimensional heat-flow in a metal plate is defined by Given the boundary conditions as shown in figure below, find the temperature at interior points T1, T2, T3 and T4. (5)
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6. Solve the equation over the square domain 0 ≤ x ≤ 1.5 and 0 ≤ y ≤ 1.5 with f=0 on the boundary [Take h = 0.5]. (8)
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6. Write the finite difference formula for solving Poisson’s equation. Hence solve the Poisson’s equation∇2f = 2x2y2 over the domain 0 ≤ x ≤ 3 and 0 ≤ y ≤ 3 with f = 0 on the boundary and h = 1. (1 + 7)
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6. What do you understand by the partial differential equation? Illustrate it with practical example and derive difference equation. (8)
OR
Find the solution of following differential equations using Taylor series method.
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7. Define a difference equation to represent a Laplace’s equation. Solve the following Laplace equation
For the rectangular plate given as:(3 + 5)
OR
Derive a difference equation to represent a Poison’s equation. Solve the Poison’s equation ∇2 f = 2x2y2 Over the domain 0 ≤ x ≤ 3, 0 ≤ y ≤ 3 with f = 0 on the boundary and h = 1. (3+5)
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7. How can you solve Laplace’s equation? Explain. The steady-state two dimensional heat flow in a metal plate is defined by
OR
A steel plate of size 30 x 30cm is given. Two adjacent sides are placed at 100°C and other side held at 0°C . Find the temperature at interior points, assuming the grid size of 10 x 10cm. (3+5)
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12. Consider a metallic plate of size 90 cm by 90 cm. The two adjacent sides of the plate are maintained at temperature of 1000C and remaining two adjacent sides are held at 2000C. Calculate the steady state temperature at interior points assuming a grid size of 30 cm by 30 cm.
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12. Solve the Poisson’s equation ∇
2
f=2x2
y
2
over the square domain 0 <= x <= 3 and
0 <= y <= 3 with f=0 on the boundary and h=1.
Given Poisson’s eqn. is
h = 1
Let’s divide the domain into grids of 3 x 3 with f = 0 at the boundary as below
Now, from the difference equation for the Poisson’s equation,
Solving
these equations,
Using eq.(ii) in (iii)
Using eq.(ii) in (iv)
& we have eq. (i)
Solving equation (a), (b) & (i) we get,
Using these values in eq. (ii)
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11. A plate of dimension 18cm x 18cm is subjected to temperatures as follows: left side at 1000c, right side at 2000C. Upper part at 500 C, and lower at 1500C. If square grid length of 6cm x 6cm is assumed, what will be the temperature at the interior nodes?
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12. Solve the Poison's equation over the square domain 0 ≤ x ≤ 1.5, 0 ≤ y ≤ 1.5 with f = 0 on the boundary and h = 0.5.
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