Non Linear PDE in 2 dimensions

In summary, the conversation is about solving a PDE with a boundary condition and the method of characteristics is suggested as a possible solution. The use of the chain rule and initial conditions are explained and it is noted that the boundary condition should not be a characteristic curve to avoid issues with intersections.
  • #1
L0r3n20
36
2
Hi all. I'm trying to solve this PDE but I really can't figure how. The equation is
[tex]
f(x,y) + \partial_x f(x,y) - 4 \partial_x f(x,y) \partial_y f(x,y) = 0
[/tex]
As a first approximation I think it would be possible to consider [tex] \partial_y f [/tex] a function of only y and [tex] \partial_x f [/tex] a function of only x but even in this case I couldn't find a general solution.
Any idea?
 
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  • #2
L0r3n20 said:
Hi all. I'm trying to solve this PDE but I really can't figure how. The equation is
[tex]
f(x,y) + \partial_x f(x,y) - 4 \partial_x f(x,y) \partial_y f(x,y) = 0
[/tex]
As a first approximation I think it would be possible to consider [tex] \partial_y f [/tex] a function of only y and [tex] \partial_x f [/tex] a function of only x but even in this case I couldn't find a general solution.
Any idea?

Your equation needs to be supplemented by a boundary condition: say [itex]f(x,g(x)) = h(x)[/itex] for suitable [itex]g(x)[/itex].

The method of characteristics looks like a good bet.

By the chain rule,
[tex]
\frac{\mathrm{d}f}{\mathrm{d}t} = \frac{\partial f}{\partial x}\frac{\mathrm{d}x}{\mathrm{d}t} + \frac{\partial f}{\partial y}\frac{\mathrm{d}y}{\mathrm{d}t}
[/tex]
which by comparison with your equation gives the following system:
[tex]
\frac{\mathrm{d}x}{\mathrm{d}t} = 1 \\
\frac{\mathrm{d}y}{\mathrm{d}t} = -4\frac{\partial f}{\partial x} \\
\frac{\mathrm{d}f}{\mathrm{d}t} = - f
[/tex]
subject to the initial conditions [itex]f(0) = f_0 = h(x_0)[/itex], [itex]x(0) = x_0[/itex], [itex]y(0) = y_0 = g(x_0)[/itex] so that [itex]f(x_0,g(x_0)) = h(x_0)[/itex].

Solving the first equation gives [itex]x = t + x_0[/itex], and the third gives [itex]f = f_0e^{-t} = f_0e^{x_0-x}[/itex]. Substituting these into the second gives
[tex]
\frac{\mathrm{d}y}{\mathrm{d}t} = 4f \\
[/tex]
so that [itex]y = y_0 + 4f_0(1 - e^{-t})[/itex].

Therefore given a characteristic starting at [itex](x_0,g(x_0))[/itex], the value of the function at [itex](x,y) = (x_0, g(x_0) + 4h(x_0)(1 - e^{-t}))[/itex] is [itex]h(x_0)e^{-t}[/itex].

It is of vital importance that the curve [itex](x,g(x))[/itex] on which the boundary condition is given is not a characteristic (ie a curve [itex](x(t),y(t)[/itex]) for some [itex](x_0,y_0)[/itex]). There may also be a problem if characteristics intersect.
 

1. What is the difference between a linear and non-linear partial differential equation (PDE) in 2 dimensions?

A linear PDE is an equation where the dependent variable and its derivatives appear only in a linear form, meaning there are no products or powers of the dependent variable. In contrast, a non-linear PDE contains products or powers of the dependent variable and its derivatives.

2. How do you solve a non-linear PDE in 2 dimensions?

Solving non-linear PDEs often involves using numerical methods, such as finite difference or finite element methods, to approximate the solution. In some cases, analytical solutions can be found using techniques like separation of variables or change of variables.

3. What are some real-world applications of non-linear PDEs in 2 dimensions?

Non-linear PDEs are used to model a wide range of physical phenomena, including fluid flow, heat transfer, and electromagnetic fields. They are also commonly used in mathematical finance to model option pricing and risk management.

4. Can non-linear PDEs be solved analytically in 2 dimensions?

It depends on the specific form of the PDE and the boundary conditions. In general, non-linear PDEs do not have closed-form solutions, but there are some special cases where analytical solutions can be found.

5. Are there any software packages or tools available for solving non-linear PDEs in 2 dimensions?

Yes, there are many software packages and tools available for solving non-linear PDEs, including MATLAB, Mathematica, and COMSOL Multiphysics. These programs use numerical methods to approximate the solutions of non-linear PDEs and allow for visualization and analysis of the results.

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