Partial Differential Equation Mathematical Modelling

In summary, the conversation discusses a modelling case on organism propagation and the demonstration of isoprobability contours. It also touches upon the comparison of spreading velocities with purely diffusive processes. The problem is reduced to the heat equation by substituting u(x,t) = e^{\alpha t}v(x,t).
  • #1
Hector Triana
7
2
Salutations,
I have been trying to approach a modelling case about organism propagation which reproducing with velocity $$\alpha$$ spreading randomly according these equations:
$$\frac{du(x,t)}{dt}=k\frac{d^2u}{dx^2} +\alpha u(x,t)\\\ \\ u(x,0)=\delta(x)\\\ \lim\limits_{x \to \pm\infty} u(x,t)=0$$

This studying case requires to demonstrate that isoprobability contours, it means, in the points (x,t) which P(x,t)=P=constant is verified that
$$\frac{x}{t}=\pm [4\alpha k-2k\frac{\log(t)}{t}-\frac{4k}{t}\log(\sqrt{4\pi k} P)]^\frac{1}{2}$$

Another aspect to demonstrate is that $t \to \infty$, the spreading velocity of these contours, it means, the velocity which these organisms are spreading is aproximated to
$$\frac{x}{t}\pm(4\alpha k)^\frac{1}{2}$$

Finally, how to compare this spreading velocity with purely diffusive process $(\alpha=0)$, it means , x is aproximated to $$\sqrt{kt}$$

This is just for academical curiosity and I would like to understand better this kind of cases with Partial Differential Equations. So, I require any guidance or starting steps or explanations to find the solutions because it's an interesting problem.

Thanks very much for your attention.
 
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  • #2
Substituting [itex]u(x,t) = e^{\alpha t}v(x,t)[/itex] reduces the problem to the heat equation, as [tex]
\frac{\partial u}{\partial t} = e^{\alpha t}\frac{\partial v}{\partial t} + \alpha u[/tex] and [tex]
\frac{\partial^2 u}{\partial x^2} = e^{\alpha t} \frac{\partial^2 v}{\partial x^2}[/tex]
 
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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 is used to describe the relationship between a function and its partial derivatives with respect to those variables.

2. How is partial differential equation mathematical modelling used in science?

PDE mathematical modelling is used in science to describe and analyze complex systems and phenomena, such as fluid flow, heat transfer, and quantum mechanics. It allows scientists to mathematically represent and understand these systems, making predictions and solving problems that would otherwise be difficult or impossible.

3. What are some common applications of partial differential equation mathematical modelling?

PDE mathematical modelling has a wide range of applications, including in physics, engineering, finance, and biology. Some specific examples include predicting weather patterns, designing efficient heat exchangers, and understanding the spread of diseases.

4. What are the differences between ordinary differential equations and partial differential equations?

The main difference between ordinary differential equations (ODEs) and PDEs is the number of independent variables. ODEs involve only one independent variable, while PDEs involve multiple independent variables. Additionally, ODEs describe the behavior of a function at a single point, while PDEs describe the behavior of a function across a range of points.

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

There are several techniques for solving PDEs, including separation of variables, Fourier series, and numerical methods such as finite difference and finite element methods. The specific technique used depends on the type of PDE and the boundary conditions of the problem.

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