Plotting Solutions Using Finite Difference Method with M = N = 20

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SUMMARY

The discussion focuses on implementing the finite difference method (FDM) to solve the equation \(\nabla^2 u = 1\) on a grid defined by M = N = 20. The boundary conditions are specified as \(u(x,0) = x(1-x)\), \(u(x,1) = x(1-x)\), and \(u(0,y) = 0\), \(u(1,y) = 0\). Participants share insights on discretizing the domain and constructing the mesh for accurate plotting of the solution. The conversation emphasizes the importance of grid resolution and numerical stability in achieving reliable results.

PREREQUISITES
  • Finite Difference Method (FDM) fundamentals
  • Understanding of boundary value problems
  • Basic knowledge of numerical analysis
  • Proficiency in a programming language for plotting (e.g., Python with Matplotlib)
NEXT STEPS
  • Explore the implementation of the finite difference method in Python
  • Learn about boundary value problem techniques and their applications
  • Study numerical stability and convergence in finite difference schemes
  • Investigate visualization techniques for numerical solutions using Matplotlib
USEFUL FOR

Mathematicians, engineers, and computer scientists interested in numerical methods, particularly those focused on solving partial differential equations using the finite difference method.

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How do I use the finite difference method with M = N = 20 to obtain a plot of the solution of

[tex]\nabla[/tex]2u = 1, 0 < x < 1, 0 < y < 1,
u(x,0) = x(1-x), u(x,1) = x(1-x), 0 [tex]\leq[/tex] y [tex]\leq[/tex] 1,
u(0,y) = 0, u(1,y) = 0, 0 [tex]\leq[/tex] y [tex]\leq[/tex] 1.
 
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Okay, what have you done on this? In particular, what would [itex]\nabla^2 u= 1[/math] look like in terms of this mesh?[/itex]
 

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