Basic partial differential problem

In summary, to solve a problem like this, you would integrate the partial derivatives with respect to x: \frac{\partial^{2}u}{\partial x^{2}}=0 then you would solve for u(x,y,z) by integrating again with respect to y and z held constant.
  • #1
miniradman
196
0

Homework Statement


Find the solution of each of the following partial differential equation

[itex]\frac{\partial^{2}u}{\partial x^{2}} = 0[/itex]


Homework Equations


assume the product form?
[itex] u(x,y) = f(x)g(y)[/itex] ? (not 100% sure)


The Attempt at a Solution


Hello, I'm only new to PDEs and I was wondering what kind of algorithm is used to solve a function such as this (with no boundary conditions).

I have the solution which states that
therefore:
[itex]\frac{\partial u}{\partial x} = f(y)[/itex]

therefore:
[itex]u(x,y) = xf(y)+g(y)[/itex]

but I cannot see the intuition behind this, does anyone know?
 
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  • #2
miniradman said:

Homework Statement


Find the solution of each of the following partial differential equation

[itex]\frac{\partial^{2}u}{\partial x^{2}} = 0[/itex]


Homework Equations


assume the product form?
[itex] u(x,y) = f(x)g(y)[/itex] ? (not 100% sure)


The Attempt at a Solution


Hello, I'm only new to PDEs and I was wondering what kind of algorithm is used to solve a function such as this (with no boundary conditions).

I have the solution which states that
therefore:
[itex]\frac{\partial u}{\partial x} = f(y)[/itex]

therefore:
[itex]u(x,y) = xf(y)+g(y)[/itex]

but I cannot see the intuition behind this, does anyone know?

Where do constants of integration come from? From the fact that the derivative of a constant is zero.

So here, except that "derivative of a constant is zero" is replaced by "partial derivative with respect to [itex]x[/itex] of a function which doesn't vary with [itex]x[/itex] is zero".
 
  • #3
You understand, I presume, that if the problem were an ordinary differential equation, [itex]\frac{d^2}{dx^2}= 0[/itex], you would solve it by integrating twice: since the second derivative is 0, the first derivative must be a constant: [itex]\frac{du}{dx}= C[/itex]. And now, integrating again, [itex]u(x)= Cx+ D[/itex] where D is the constant of integration.

It's the same basic idea with partial derivatives except that the constant of integration may be a function of the other variables.

[itex]\frac{\partial^{2}u}{\partial x^{2}} = 0[/itex] can be read as
[tex]\frac{\partial }{\partial x}\left(\frac{\partial u}{\partial x}\right)= 0[/tex]

That is, that [itex]\partial u/\partial x[/itex] does not depend upon x. It does NOT, itself, say what variables the partial derivative does depend on. If we are given that the only variable are x and y, then [itex]\partial u/\partial x[/itex] must be a function of y only- and it could be any function of y: [itex]\partial u/\partial u= f(y)[/itex].

The point is that taking the partial derivative with respect to one variable, we treat the other variables as constants. So going the other way, taking the anti-derivative with respect to that variable, the ''constant of integration" may actually depend upon those other variables. If g(y) is a function of y only, [itex]\frac{\partial g}{\partial x}= 0[/itex].

Once we have
[tex]\frac{\partial u}{\partial x}= f(y)[/tex]
integrating again (with respect to x, holding y constant) gives [tex]u(x, y)= f(y)x+ g(y)[/tex] where again, the "constant of integration" can be an arbitrary function of y.

If the independent variables were x, y, and z, the general solution to [itex]\frac{\partial^2 u}{\partial x^2}= 0[/itex] would be u(x, y, z)= f(y,z)x+ g(y, z) where, now, f and g can be any functions of y and z. You should be able to see by differentiating that these do satisfy the equation.

If you had [itex]\frac{\partial^2 u}{\partial x\partial y}= 0[/itex], again assuming that the only variables are x and y, integrating first, with respect to y would give [itex]\partial u/\partial y= f(y)[/itex] where f(y), the "constant of integration" can be any function of y. Integrating again, this time with respect to y, would give u= F(y)+ G(x) where F(y) is an anti-derivative of f(y) (since f(y) was arbitrary so is F(y)) and G(x) is the "constant of integration", an arbitrary function of x.
 
  • #4
Ahhhh, I see now. If I was doing this with in two dimensions, the integral of 0 is just constant c, however because I'm doing this in 3d (w.r.t 2 variables) my constant is now replaced with an arbitrary function. Who has it's function in terms the other variable. Right?
 

Related to Basic partial differential problem

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

A PDE is a mathematical equation that involves partial derivatives of an unknown function of multiple independent variables. It 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 partial derivatives of a function with respect to multiple independent variables, while an ordinary differential equation only involves derivatives with respect to a single independent variable. PDEs are typically used to model systems with more complex geometries and behaviors.

3. What is a boundary condition in a partial differential equation?

A boundary condition is a statement that specifies the behavior of the solution to a partial differential equation at the boundaries of the domain in which it is defined. These conditions are necessary to uniquely determine a solution to the PDE.

4. What are some common techniques for solving basic partial differential equations?

Some common techniques for solving basic PDEs include separation of variables, Fourier analysis, and numerical methods such as finite differences or finite element methods. The specific technique used depends on the type of PDE and the problem being solved.

5. How are partial differential equations used in real-world applications?

PDEs are used to model a wide range of physical phenomena, such as heat transfer, fluid flow, and quantum mechanics. They are also used in financial modeling, image and signal processing, and many other fields. Solving PDEs allows us to better understand and predict the behavior of these systems in real-world scenarios.

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