Partial Differential Equation

In summary, a user is urgently seeking assistance in solving a specific equation using either matlab or TDMA and Gauss-Seidel line relaxation. The equation involves a non-linearity represented by the variable A. The user's email is provided for further communication.
  • #1
tetirichie
3
0
Hi

Urgent Thanks in advance.

Could somebody who knows how to solve the above mentioned equation please assist.The equation needs to be solved using any language but I am now very comfortable with matlab.

I am trying to solve the following eqaution using TDMA and Gauss-Seidel line relaxation:

[tex]A\frac{\partial^2 \phi}{\partial x^2} + \frac{\partial^2 \phi}{\partial y^2} = 0[/tex]

[tex]A = 1 - M^2_\infty - (\gamma + 1)\frac{M^2_\infty}{u_\infty}\frac{\partial \phi}{\partial x}[/tex]

[tex]u_\infty = 1 ; M^2_\infty = 0.975 ; \gamma = 1.4[/tex]

My email is teti@myself.com

With Regards,

Richard
 
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  • #2
Are there any problems with an iteration loop on A to handle the non-linearity embedded in it?
 
  • #3


Hi Richard,

Thank you for reaching out for assistance with solving your partial differential equation. I am not able to solve it for you, but I can provide some guidance and resources that may be helpful.

A partial differential equation (PDE) is an equation that involves multiple independent variables and their partial derivatives. In your case, the equation has two independent variables, x and y, and their second order partial derivatives. PDEs are commonly used in physics, engineering, and other fields to model complex systems and phenomena.

To solve a PDE, there are various numerical methods that can be used, such as finite difference, finite element, and spectral methods. TDMA (Tri-Diagonal Matrix Algorithm) and Gauss-Seidel line relaxation are two specific methods that can be used to solve PDEs numerically. These methods involve breaking down the problem into a system of linear equations and iteratively solving them to approximate the solution to the PDE.

Since you mentioned that you are comfortable with MATLAB, you may find it helpful to use the built-in functions and tools in MATLAB for solving PDEs. MATLAB has a PDE Toolbox that allows you to specify the PDE, boundary conditions, and numerical method, and it will solve the equation for you. There are also many online resources and tutorials available for using MATLAB for PDEs.

I hope this information helps you in solving your equation. If you have any further questions or need clarification, please feel free to reach out. Best of luck with your project!

Regards,
 

1. What is a partial differential equation?

A partial differential equation (PDE) is a mathematical equation that involves multiple independent variables and their partial derivatives. It describes the relationship between the variables and how they change in relation to each other.

2. What are some applications of partial differential equations?

PDEs have numerous applications in various fields such as physics, engineering, economics, and biology. They are used to model and study complex systems and phenomena, including fluid dynamics, heat transfer, population dynamics, and financial markets.

3. How do partial differential equations differ from ordinary differential equations?

Ordinary differential equations involve only one independent variable, while PDEs involve multiple independent variables. Additionally, PDEs often involve partial derivatives, while ordinary differential equations only involve ordinary derivatives.

4. What are the different types of partial differential equations?

There are several types of PDEs, including elliptic, parabolic, and hyperbolic equations. Each type has different properties and behaviors, and they are used to model different physical phenomena.

5. What methods are used to solve partial differential equations?

There are several methods for solving PDEs, including separation of variables, method of characteristics, finite difference methods, and numerical methods. The choice of method depends on the specific PDE and its properties.

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