Solving PDEs: Separation of Vars., Method of Characteristics

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SUMMARY

This discussion focuses on solving linear Partial Differential Equations (PDEs) using the separation of variables and the method of characteristics. Participants highlight that while analytical solutions exist, they are often impractical for complex boundary conditions found in real-life applications. Numerical methods are emphasized as the predominant approach for solving PDEs, with a note that this field encompasses a wide range of techniques beyond basic finite difference methods.

PREREQUISITES
  • Understanding of linear Partial Differential Equations (PDEs)
  • Familiarity with separation of variables and method of characteristics
  • Basic knowledge of numerical methods for PDEs
  • Awareness of Laplace and Fourier transforms
NEXT STEPS
  • Research advanced numerical methods for PDEs, such as finite element analysis
  • Explore the application of Laplace transforms in solving PDEs
  • Learn about the method of characteristics in greater detail
  • Investigate real-world applications of PDEs in engineering and physics
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Students and professionals in mathematics, engineering, and physics who are interested in solving linear PDEs, as well as those looking to deepen their understanding of numerical methods for practical applications.

Abraham
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I've taken a first semester course on PDEs. Basically all we learned was separation of variables and method of characteristics. I understand that there are transforms out there, such as laplace and fourier. However, it looks like there aren't many analytical ways of solving PDEs. Mind you, I'm only talking about linear PDEs. I know nothing of nonlinear ones.

Can anyone tell me what other methods there are to solve PDEs?

Anyone with more experience, can you tell me what other types of PDEs are out there? I know the heat, laplace, and wave eq.

Thx
 
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In "real life" applications, PDEs are almost always solved numerically not analytically.

Even when there are general analytic solutions, it is usually impossible to fit the boundary conditions to "real" regions in space which are not simple rectangles, circles, etc. For example, imagine trying to solve something as "simple" as the wave equation analytically inside a region of 3D space shaped like a real automobile (including the seats, passengers, etc), to decide the most effective places to put sound insulation, loudspeakers for audio equipment, etc.

Numerical solution of PDEs is almost as big a subject area as studying the PDEs themselves. There is a lot more to it than the simple finite difference methods that you find in basic "computational methods" courses.
 

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