Unit-5
Boundary Value problems
This method is used to solve bounded value problem.
The general two-point linear boundary value problem
With boundary condition
To solve this problem by using finite difference, we divide the interval [a, b] into n sub interval so that .
The approximated function f(x) at the points
………
We use the following central difference formula:
We substitute these value in the given equation and apply the boundary condition to calculate the value of the unknown.
Example1: Solve the boundary value problem defined by
by finite difference method. Compare the solution at y (0.5) by taking h=0.5 and h=0.25.
Given equation
With boundary condition
By finite difference method
…. (iii)
Putting(iii) in (i) we get
…. (iv)
For h=0.5, here for which corresponds to
For i=1 in equation (iv) we get
For h=0.25, here
Which corresponds to
For i=1 in equation (iv) we get
For i=2 in equation (iv) we get
For i=3 in equation (iv) we get
From equation (v), (vi) and (vii) we get
On solving above triangular equation we get
Hence for h=0.5 we get y (0.5) =0.44444
And for h=0.25 we get y (0.5) =0.443674
Example2: Solve the bounded value problem
With boundary condition
Given equation
With
By finite difference method
…. (3)
Putting (3) in equation (1) we have
By finite difference method
…… (4)
Let h=1, we have
Corresponds to
For i=1 in equation (4) we get
For i=2 in equation (4) we get
For i=3 in equation (4) we get
From equation (5), (6) and (7) we get
On solving we get
Example3: Solve the boundary value problem
With y (0) =0 and y (2) =3.62686
Given equation …. (1)
With boundary condition y (0) =0 and y (2) =3.62686…. (2)
By finite difference method
…. (3)
Substituting (3) in equation (1) we get
…. (3)
Let h=0.5 then for
Which corresponds to
For i=1 in equation (3) we get
For i=2 in equation (3) we get
For i=3 in equation (3) we get
From equation (4), (5) and (6) we get
On solving we get
Solving Eigen value problems (Power method)-
To find the approximate values of all the Eigen values and Eigen vectors, iteration method or power method is used.
Power method is used when only the largest and/or the smallest eigen values of a matrix are desired.
Procedure for Power method-
Step-1: First we choose an arbitrary real vector , basically is chosen as-
Step-2: Compute , , , , ………… Put
Step-3: compute , ,
Step-4: The largest Eigen value is
The error in can be find as-
The Eigen vector corresponding to is
How do we determine the smallest Eigen value?
If is the Eigen value of A, then the reciprocal is the Eigen value of , then the reciprocal of the largest Eigen value of will be the smallest Eigen value of A.
Example: Find the largest Eigen value and the corresponding Eigen vector of the matrix
Also find the error in the value of the largest Eigen value.
Sol.
Let us choose the initial vector
Then
Now put , then-
Hence the largest Eigen value is-
And the corresponding Eigen vector is-
The error can be calculated as-
Key takeaways-
4. If is the Eigen value of A, then the reciprocal is the Eigen value of , then the reciprocal of the largest Eigen value of will be the smallest Eigen value of A.
The general linear PDE of the second order in two independent variables is of the form-
Then there are three conditions-
Example: Classify the equation-
Sol.
Here A =
Now
That means,
The equation is hyperbolic.
Example: Classify the equation
Sol.
Here
Hence the equation is parabolic.
Finite Difference Approximation
We construct a rectangular region R in the xy- plane and divide into network of sides and . The intersection points of the dividing lines are called the mesh point, nodal point or grid points.
Then the finite difference approximation for the partial derivative in x-direction is
And
For the above approximation is
…. (1)
… (2)
… (3)
And
… (4)
Similarly, we have the approximations for the derivatives with respect to y
…. (5)
…. (6)
… (7)
And
…. (8)
Replacing the derivatives in any partial differential equation by their corresponding difference approximation (1) to (8), we obtain the finite difference similar to the given equations.
Simple Laplace’s Method:
The Laplace’s equation
Consider the Laplace’s equation in a region R with boundary C. Let R be a square region so that it can be divided into network of small squares of side h. Let the values of on the boundary C be given by and let the interior mesh points be as in figure
The approximate function values at the interior point of the mesh can be calculated by the diagonal five-point formula of in this order
(bigger +)
(X form)
(X form)
(X form)
(X form)
Similarly, the remaining quantities are calculated by using standard five-point diagonal formulas.
(+ form)
(+ form)
(+ form)
(+ form)
In this way all are computed.
Example1: Solve the Laplace’s equation in the domain
The initial values using five diagonal formula we have
Here ,
The remaining quantities are calculated by using standard five-point diagonal formulas.
Hence and .
Example2: Solve the Laplace’s equation for
The initial values using five diagonal formula we have
Here ,
The remaining quantities are calculated by using standard five-point diagonal formulas.
Hence and .
PDEs – Elliptical explicit method:
The Laplace’s equation
And the Poisson’s equation
are the example of elliptic partial differential equation.
The Poisson’s equation
This can be solved by interior mesh points of a square network when the boundary values are known. The standard five-point formula for Poisson’s equation is
After using the above formula, we get the linear equations in the pivotal values
Then these are solved by Gauss Seidal Iteration formula
.
Example1: Solve the elliptical equation for
The initial values using five diagonal formula we have
Here ,
The remaining quantities are calculated by using standard five-point diagonal formulas.
The Above is symmetric about PQ, so that .
We will have iteration process using the Gauss Seidal Formula
First iteration: Putting we get
Second Iteration: Putting , we get
Third Iteration: Putting , we get
Fourth Iteration: Putting , we get
Fifth iteration: Putting n=4 we get
.
Example2: solve the Poisson equation
Let the point be defined by At the point A, . The standard five-point formula at point A is
Or
Or ….(i)
Again, the standard five-point formula at the point B is
Or
Or ...(ii)
Similarly, the standard five-point formula at the point C
Or
Or …. (iii)
Similarly, the standard five-point formula at the point D
Or
Or …. (iv)
From (ii) and (iii) we get =. Hence the iteration formula we have
.
First iteration: Putting . Hence, we obtain
Second iteration: Putting n=1, we get
Third iteration: Putting n=2, we get
Fourth iteration: Putting n=3, we get
Fifth iteration: Putting n=4, we get
Sixth iteration: Putting n=5, we get
Since last two iteration are approximately equal, hence
.
PDEs- parabolic explicit method:
The example of parabolic is one dimensional heat conduction equation
... (1)
Where is the diffusivity of the substance.
Consider a rectangular mesh in plane.
The spacing in x-direction is h and in t direction is k. Let the mesh point or simply we get
And
Substituting these in equation (1) we get
Or … (2)
Where is the mesh ratio parameter.
This formula gives the value of u at position mesh points I nterms of known values of and at the instant . It gives the relation between two-time level therefore known as two level formula.
Also named as Schmidt explicit formula and is true for .
At the above formula reduces to
... (3)
Is known as Bendre-Schmidt recurrence relation which gives the value of u at internal mesh points with the help of boundary conditions.
Example1: Solve the equation with the conditions . Assume. Tabulate u for choosing appropriate value of k?
Here and let ,
Since
The Bendre-Schmidt recurrence formula we have
…. (i)
Also given .
for all values of j, i.e., the entries in the first and the last columns are zero.
Since
(Using
For .
Putting
Putting successively we get
These will give the entries in the second row.
Putting in equation (i), we will get the entries of the third row.
Similarly, successively in (i), the entries of the fourth rows are
obtained.
Hence the values of are as given in the below the table:
0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
0 | 0 | 0.09 | 0.16 | 0.21 | 0.24 | 0.25 | 0.24 | 0.21 | 0.16 | 0.09 | 0 |
1 | 0 | 0.08 | 0.15 | 0.20 | 0.23 | 0.24 | 0.23 | 0.20 | 0.15 | 0.08 | 0 |
2 | 0 | 0.075 | 0.14 | 0.19 | 0.22 | 0.23 | 0.22 | 0.19 | 0.14 | 0.075 | 0 |
3 | 0 | 0.07 | 0.133 | 0.18 | 0.21 | 0.22 | 0.21 | 0.18 | 0.133 | 0.07 | 0 |
Example2: Solve the heat equation
Subject to the conditions and
.
Take and k according to Bendre-Schmidt equation.
Here and let ,
Since
The Bendre-Schmidt recurrence formula we have
…. (i)
Also given .
for all values of j, i.e., the entries in the first and the last columns are zero.
Since
.
.
For
Putting
Putting successively we get
These will give the entries in the second row.
Putting in equation (i), we will get the entries of the third row.
Similarly, successively in (i), the entries of the fourth rows are
obtained.
Hence the values of are as given in the below the table:
0 | 1 | 2 | 3 | 4 | |
0 | 0 | 0.5 | 1 | 0.5 | 0 |
1 | 0 | 0.5 | 0.5 | 0.5 | 0 |
2 | 0 | 0.25 | 0.5 | 0.25 | 0 |
3 | 0 | 0.25 | 0.25 | 0.25 | 0 |
Example3: Use the Bendre-Schmidt formula to solve the heat conduction problem
With the condition and .
Let we see when .
The initial condition is .
Also .
The iteration formula is
=
First iteration: Putting n=0, we get
Second iteration: Putting n=1, we get
Third Iteration: putting n=3, we get
Fourth Iteration: putting n=3, we get
Fifth Iteration: putting n=4, we get
Hence the approximate solution is
Key takeaways-
5. The Poisson’s equation
References