Differential equation selection and linear transformations

Click For Summary
SUMMARY

This discussion focuses on the selection of differential equations for modeling non-linear processes in applied mathematics. It emphasizes the importance of understanding the physical processes behind data, such as wave height versus boat hull size, to determine the appropriate differential equation. The conversation highlights the distinction between data analysis and modeling, noting that even linear equations can yield nonlinear solutions. Methods for transforming nonlinear equations into linear forms, including Cartan's equivalence method and symmetry mappings, are also mentioned as viable approaches.

PREREQUISITES
  • Understanding of differential equations, particularly linear and nonlinear types.
  • Familiarity with data analysis techniques, including graphing and function fitting.
  • Knowledge of physical processes relevant to the data being modeled, such as wave dynamics.
  • Basic concepts of mathematical transformations and equivalence methods.
NEXT STEPS
  • Research Cartan's equivalence method for transforming nonlinear equations.
  • Study symmetry mappings and their applications in differential equations.
  • Explore the derivation of the wave equation and its linear properties.
  • Learn about the Navier-Stokes equations and their implications in fluid dynamics.
USEFUL FOR

Applied mathematicians, engineers, and scientists involved in modeling complex systems, particularly those dealing with nonlinear processes and differential equations.

JaredPM
Messages
20
Reaction score
0
This may be vague, so I apologize.

I am interested in applied mathematics, so my question is about the process a scientist or engineer uses to determine what differential equation to use for a non-linear process. I am not familiar enough with describing non-linear processes to be able to give you an example, but from what I hear, nonlinear processes are everywhere around us. I have also read that a linear process's inputs are proportional to their outputs, and that they follow the superposition rule.

So, If I were to collect some experimental values on something like testing the height of a wave produced by different sized boats, I could develop a graph of height vs boat hull size. How would I determine if the data collected were linear or nonlinear? If nonlinear, regardless of the differential equation used, how would I transform this into a linear set of equations. So, my question is what constraints have to be met to make a nonlinear process linear? And what effect, does the number of variables play in this analysis?
 
Physics news on Phys.org
First, you should make a distinction between data analysis and modeling. If you have a set of data points like wave height vs boat hull size, you can plot it and try to find a function, linear or otherwise, that fits your data. This already gives you some idea about the complexity of the problem, but doesn't really give you a lot of physical insight.

When you know more about the physical process governing the data, you can construct the differential equation. Some physical processes are linear (take a look at the wiki page for derivation of the wave equation), and some are nonlinear (like navier stokes), but even solutions of simple linear equations do not look linear. dy/dt=y for instance has y=A*exp(x) as a solution. The solution is nonlinear, but the equation is.

When you end up with a nonlinear equation, you might be able to transform it to a linear equation and there are several ways of doing it. Most of these methods are connected somehow, but Cartan's equivalence method is one of them, as well as symmetry mappings. I'm not sure if this is what you're after..

Anyway, I don't really know what you're really after because as you said yourself, your question is rather broad/vague. If you are more specific, we can be too.
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 12 ·
Replies
12
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 10 ·
Replies
10
Views
5K
  • · Replies 1 ·
Replies
1
Views
2K