A scalar on a semi-infinite domain with source and sink

In summary, you might try reducing the number of unknowns by solving the equation in the target region.
  • #1
Hoplite
51
0
Hi everyone,

I've been looking at a problem that seems simple at first, but appears to be deceptively difficult (unless I'm missing something).

1. Homework Statement

I've been looking at a problem that involves the diffusion of a scalar quantity, ##q(x)##, on the semi-infinite domain, ##\leq x < \infty##. If ##q(x)## represents a scalar quantity, such as heat, then it can diffuse throughout the domain ##\leq x < \infty##, but won't diffuse out of the boundary at ##x=0##. We don't however know what the value of ##q## is at ##x=0##.

On top of this, there is a source at ##x=a## (delta function), and a sink term that is proportional to the magnitude of ##q(x)##.

Homework Equations


The overall equation is therefore $$\frac{\partial^2 q}{\partial x^2} - q = -\delta (x-a),$$ $$0\leq x <\infty .$$

The Attempt at a Solution


It seems to me that the tricky part here is accounting for the boundary conditions. We know that since the source is at ##x=a## and there is a sink term, ##q(x) \rightarrow 0## as ##x\rightarrow \infty##. But how to account for the boundary condition at ##x=0##? If ##q(x)## were a vector quantity, I would imagine that the method of images could be used. Is there a useful equivalent for scalars?

If we look at the equation, the solution should be of the form, $$q(x)= Ae^{x}+Be^{-x}.$$ By substitution, we can then turn this into $$q(x)= Ce^{x-a}+De^{-(x-a)}.$$ In the ##x>a## region, therefore, ##C=0## (or else ##q## would diverge at infinity). But we can't do anything so simple in the ##0\leq x \leq a## region. So this leaves
$$ q(x) = \begin{cases}Ce^{x-a}+De^{-(x-a)}, & 0\leq x\leq a \\ Ee^{-(x-a)}, & x>a
\end{cases}$$
If I could reduce the number of unknowns from 3 to 1, it could solve it by integrating the governing equation over ##x \in [a^-,a^+]##.

Does anyone have any suggestion for how to proceed?
 
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  • #2
First of all, that is not the heat equation. The heat equation involves a time derivative.

Second, there is no sink in your problem. Heat will dissipate to infinity.
Hoplite said:
I would imagine that the method of images could be used. Is there a useful equivalent for scalars?
The method of images.

Have you done heat conduction on an infinite domain?
 
  • #3
Hi Orodruin, thanks for your response. Yes, it's not the heat equation. I just mentioned heat as an example of a possible scalar quantity. I can see no reason why the time derivative couldn't be removed from the heat equation if the system is assumed to be steady state though.

As for sink terms though, surely the second term on the left-hand-side functions as a sink term?

Heat conduction on an infinite domain would be simple, I'd imagine. You could use the symmetry of the system to reduce the number of unknowns to 1, and then solve by integrating around ##x=a##.

I'm thinking of extending the domain to ##-\infty <x<\infty## and adding an image source term at ##x=-a##. I've only seen the method of images used for vector quantities though, so I want to be sure this is legitimate.
 
  • #4
Hoplite said:
As for sink terms though, surely the second term on the left-hand-side functions as a sink term?

Yes, it is a sink proportional to the value of ##q## itself. Perhaps I did not read your OP well enough at first. However, note that this would generally come with an additional dimensionful constant (of dimension length^-2) in front - otherwise the dimensions

Hoplite said:
I'm thinking of extending the domain to ##-\infty <x<\infty## and adding an image source term at ##x=-a##. I've only seen the method of images used for vector quantities though, so I want to be sure this is legitimate.

Yes, this is perfectly legitimate. You can check that the resulting solution satisfies both your required boundary condition as well as the differential equation in the target region. The method of images is usually presented for scalar fields first. Often as the potential of a vector field for which you want to use it. Here, you can apply either the method of images or do what you started doing, there really is not much difference in difficulty, both involve finding the matching conditions at ##a## and relating to the boundaries.

Hoplite said:
If we look at the equation, the solution should be of the form, $$q(x)= Ae^{x}+Be^{-x}.$$ By substitution, we can then turn this into $$q(x)= Ce^{x-a}+De^{-(x-a)}.$$ In the ##x>a## region, therefore, ##C=0## (or else ##q## would diverge at infinity). But we can't do anything so simple in the ##0\leq x \leq a## region. So this leaves
$$ q(x) = \begin{cases}Ce^{x-a}+De^{-(x-a)}, & 0\leq x\leq a \\ Ee^{-(x-a)}, & x>a
\end{cases}$$
If I could reduce the number of unknowns from 3 to 1, it could solve it by integrating the governing equation over ##x \in [a^-,a^+]##.

Does anyone have any suggestion for how to proceed?

I never liked the "integrating over ##x \in [a^-,a^+]##" argument, which is usually accompanied by a continuity argument at ##a##. This pops right out of the differential equation if you just let ##q(x) = \theta(a-x)q_-(x) + \theta(x-a) q_+(x)##, where ##\theta(x)## is the Heaviside function. Insert this into the differential equation and identify the terms. This will automatically give you the matching conditions at ##x = a##. Note that you also have a boundary condition at ##x = 0## that you have not used yet.
 
  • #5
If you integrate across x = a, you get $$\left(\frac{dq}{dx}\right)_{a^+}-\left(\frac{dq}{dx}\right)_{a^-}=-1$$If q is something like temperature, than, at x =0, dq/dx=0. This would guarantee that no heat enters or leaves the region at x = 0.
 
  • #6
Chestermiller said:
If you integrate across x = a, you get $$\left(\frac{dq}{dx}\right)_{a^+}-\left(\frac{dq}{dx}\right)_{a^-}=-1$$

As I said, I always disliked this argument. The more straight forward way of arguing is what I mentioned in #4 differentiating the Heaviside distributions. The matching conditions - including the continuity condition - follow directly from insertion into the differential equation.
 
  • #7
Orodruin said:
As I said, I always disliked this argument. The more straight forward way of arguing is what I mentioned in #4 differentiating the Heaviside distributions. The matching conditions - including the continuity condition - follow directly from insertion into the differential equation.
Oh. Sorry. I was taught how to do heat transfer problems with a concentrated heat source this way.
 
  • #8
Chestermiller said:
Oh. Sorry. I was taught how to do heat transfer problems with a concentrated heat source this way.
It is not only applicable for heat source problems - but also to other differential equations with delta distributions in the inhomogeneities. Other popular examples include the Schrödinger equation with a delta potential and the wave equation with a point source. I was also taught this way, but I think using the Heaviside distributions is cleaner in some sense. It might just be my preference. The two things to remember are ##\theta'(x) = \delta(x)## and that ##f(x)\delta(x) = f(0)\delta(x)##.
 
  • #9
I see what you mean about the integration method for equations with delta functions, Orodruin. It works in this instance because there's a double derivative in the equation. However, if we were to try to use it to solve, for example $$f'(t) = \delta (t-s),$$ it wouldn't work. So it's not a very general technique.
 
  • #10
Hoplite said:
I see what you mean about the integration method for equations with delta functions, Orodruin. It works in this instance because there's a double derivative in the equation. However, if we were to try to use it to solve, for example $$f'(t) = \delta (t-s),$$ it wouldn't work. So it's not a very general technique.
Why doesn't it work in this case?
 
  • #11
Chestermiller said:
Why doesn't it work in this case?
Because if we integrate both sides over ##a-\epsilon <t< a+\epsilon## (then taking ##\epsilon \rightarrow 0##), the left-hand-side will appear to be zero (because ##f(t)## is incorrectly assumed to continuous with no singularities), while the right-hand-side equals 1.

I say appears to be zero because when I was taught this technique, we were essentially told to remove all first derivatives, which you can only do if you assume ##f(t)## is continuous (which it isn't in this case). I'm not sure if there's a way to use that technique without assuming ##f(t)## to be continuous.
 
  • #12
It works perfectly well in the case ##f'(t) = \delta(t-s)##. Let ##f(t) = \theta(t-s)f_+(t) + \theta(s-t)f_-(t)##. This implies
$$
f'(t) = \delta(t-s) [f_+(s) - f_-(s)] +\theta(t-s)f_+'(t) + \theta(s-t) f_-'(t) = \delta(t-s)
$$
Thus, in order to satisfy the differential equation, you need:
  1. ##f_+(s) - f_-(s) = 1##
  2. ##f_\pm(t)## are constants in their relevant domains.
This leads to ##f(t) = c + \theta(t-s)##.
 

FAQ: A scalar on a semi-infinite domain with source and sink

What is a scalar on a semi-infinite domain with source and sink?

A scalar on a semi-infinite domain with source and sink refers to a mathematical model used in physics and engineering to describe the behavior of a scalar quantity (such as temperature or pressure) on a domain that extends infinitely in one direction, with a source (such as a heat source) and a sink (such as a heat sink) present. It is commonly used to study heat transfer or fluid flow problems.

How is a scalar on a semi-infinite domain with source and sink represented mathematically?

The scalar on a semi-infinite domain with source and sink is typically represented using a partial differential equation, such as the heat or diffusion equation. This equation includes terms for the scalar quantity, its spatial derivatives, and the source and sink terms. Boundary conditions are also specified to determine the behavior of the scalar at the edges of the domain.

What is the significance of studying a scalar on a semi-infinite domain with source and sink?

Studying a scalar on a semi-infinite domain with source and sink can provide insights into the behavior of scalar quantities in real-world systems, such as heat transfer in buildings or air flow around an object. This mathematical model allows for the prediction and analysis of how changes in the source and sink terms or boundary conditions affect the scalar quantity's distribution in the domain.

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This mathematical model has a wide range of applications in fields such as physics, engineering, and environmental science. It can be used to study heat transfer in buildings, diffusion of pollutants in the atmosphere, thermal management in electronic devices, and many other phenomena involving the transport of scalar quantities.

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There are various numerical methods that can be used to solve the partial differential equation representing a scalar on a semi-infinite domain with source and sink. These include finite difference methods, finite element methods, and spectral methods. Each method has its own advantages and limitations, and the choice of method depends on the specific problem being studied.

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