Solving Partial Differential Equation

In summary, the conversation involved discussing how to solve a partial differential equation ##u_{xy}=2yu_x## for ##u(x,y)##. The solution involved using a substitution and solving for the x and y dependencies separately. By setting ##u_x = f## and solving for f(y), the equation could be reduced to an ordinary differential equation. Then, by plugging this back into ##u_x = f##, the x dependence could be found.
  • #1
Peter Alexander
26
3
1. The problem statement, all variables, and given/known data
Task requires you to solve a partial differential equation $$u_{xy}=2yu_x$$ for ##u(x,y)##. A hint is given that a partial differential equation can be solved in terms of ordinary differential equations.
According to the solution sheet, the result should be ##u(x,y)=e^{y^2}f(x) + g(y)## where ##f,\:g## seem to be two arbitrary functions.

Homework Equations


I don't think there are any relevant equations to explicitly mention.

The Attempt at a Solution


I believe that a solution to the task hides somewhere in the example I've solved before. Given a partial differential equation $$u_{xx}=0$$ which has to be solved for ##u(x,y)##, I've simply assumed that $$u(x,y) \rightarrow u(x)$$which evidently produced a second order linear homogeneous ODE. Then, I would simply use ##u(x)=e^{ax}## and its second order derivative to find a general solution ##u(x,y) = c_1(y)+xc_2(y)##.

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If I would want to produce the same ODE in my example, then I guess I should be looking at the partial derivatives and what they have in common. I can see that both sides of the equation include a partial derivative with respect to ##x##, so can I make a substitution ##u_x = v## or something like that?

But a problem with this approach is t

I am stuck solving this task. I would like to ask for some help, but I do not expect anyone to solve my homework instead of me. Instead, all I'm asking for is some guidance or tips I can use to solve the task myself.

PS: I hope you're having a wonderful Monday!
 
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  • #2
Try calling the function ##u_x = f##. Then the equation reduces to the ODE ##f_y = 2 y f##. Solve this for f(y), then plug this back into ##u_x = f## to get the x dependence.
 
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Likes Peter Alexander and Chestermiller
  • #3
Thank you so much! I actually managed to find a solution this way, thanks!
 

FAQ: Solving Partial Differential Equation

1. What is a partial differential equation (PDE)?

A PDE is a mathematical equation that involves multiple independent variables and their partial derivatives. It describes the relationship between a function and its partial derivatives, and is commonly used to model physical phenomena in fields such as physics, engineering, and economics.

2. What is the difference between a partial differential equation and an ordinary differential equation?

A partial differential equation involves multiple independent variables, whereas an ordinary differential equation only involves one independent variable. This means that the solution to a PDE is a function of multiple variables, while the solution to an ODE is a function of a single variable.

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

There are several methods that can be used to solve PDEs, including separation of variables, integral transforms, numerical methods, and the method of characteristics. The choice of method depends on the specific PDE and its boundary conditions.

4. What are boundary conditions in the context of solving PDEs?

Boundary conditions are constraints that are applied to a PDE at the boundaries of the domain in which it is being solved. They specify the behavior of the solution at the boundaries and are necessary to obtain a unique solution to the PDE.

5. What are some real-world applications of solving partial differential equations?

PDEs have a wide range of applications in various fields, such as fluid dynamics, heat transfer, electromagnetism, and quantum mechanics. They are used to model and understand complex phenomena in these fields, and their solutions can help to make predictions and inform decision-making processes.

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