Difference between revisions of "Math 511: Numerical Methods for PDEs"

From MathWiki
Jump to: navigation, search
(Minimal learning outcomes)
(Minimal learning outcomes)
Line 25: Line 25:
 
Derive finite difference schemes using Taylor series;
 
Derive finite difference schemes using Taylor series;
  
 
+
Determine the consistency of a difference scheme;
Determine the consistency of a difference scheme;
+
  
 
  Explain the proper function spaces and discrete norms for
 
  Explain the proper function spaces and discrete norms for
Line 32: Line 31:
  
 
  Establish the stability of a difference scheme using
 
  Establish the stability of a difference scheme using
\begin{itemize}
+
(1) Heuristic approach  
Heuristic approach Energy method von Neumann
+
(2) Energy method  
method Matrix method;
+
(3) von Neumann method  
\end{itemize}
+
(4) Matrix method;
  
Recall the CFL condition its relation with stability;
 
  
 +
Recall the CFL condition its relation with stability;
  
  Explain the convergence of the finite difference
+
Explain the convergence of the finite difference
 
approximations and its relation with consistency and stability via
 
approximations and its relation with consistency and stability via
 
Lax theorem;
 
Lax theorem;
  
Determine the order of accuracy of a finite difference
+
Determine the order of accuracy of a finite difference
 
scheme;
 
scheme;
  
Implement finite difference schemes on computers and perform
+
Implement finite difference schemes on computers and perform
 
numerical studies of the stability and convergence properties of
 
numerical studies of the stability and convergence properties of
 
the schemes;
 
the schemes;
  
Explain the  role and the control of numerical diffusion and
+
Explain the  role and the control of numerical diffusion and
 
dispersion in computation ; to determine how numerical phase speed
 
dispersion in computation ; to determine how numerical phase speed
 
and group velocity may deviate from the theoretical phase speed
 
and group velocity may deviate from the theoretical phase speed
Line 57: Line 56:
 
issues;
 
issues;
  
Recall numerical methods that efficiently handle a
+
Recall numerical methods that efficiently handle a
 
multidimensional problem
 
multidimensional problem
  
Recall alternating direction methods that reduce higher
+
Recall alternating direction methods that reduce higher
 
dimensional problems into a sequence of one dimensional problems.
 
dimensional problems into a sequence of one dimensional problems.
  
Recall the maximum principles for numerical schemes for
+
Recall the maximum principles for numerical schemes for
 
Laplace equations;
 
Laplace equations;
  
Recall iterative techniques for solving the linear systems
+
Recall iterative techniques for solving the linear systems
 
resulting from finite element discretization;
 
resulting from finite element discretization;
  

Revision as of 12:35, 19 October 2010

Catalog Information

Title

Numerical Methods for Partial Differential Equations.

Credit Hours

3

Prerequisite

Math 303 or 347; 410; or equivalents.

Description

Finite difference and finite volume methods for partial differential equations. Stability, consistency, and convergence theory.

Desired Learning Outcomes

Prerequisites

Minimal learning outcomes

Derive finite difference schemes using Taylor series;

Determine the consistency of a difference scheme;

Explain the proper function spaces and discrete norms for

grid functions for use in analysis of stability;

Establish the stability of a difference scheme using

(1) Heuristic approach (2) Energy method (3) von Neumann method (4) Matrix method;


Recall the CFL condition its relation with stability;

Explain the convergence of the finite difference approximations and its relation with consistency and stability via Lax theorem;

Determine the order of accuracy of a finite difference scheme;

Implement finite difference schemes on computers and perform numerical studies of the stability and convergence properties of the schemes;

Explain the role and the control of numerical diffusion and dispersion in computation ; to determine how numerical phase speed and group velocity may deviate from the theoretical phase speed and group velocity and the numerical techniques to handle such issues;

Recall numerical methods that efficiently handle a multidimensional problem

Recall alternating direction methods that reduce higher dimensional problems into a sequence of one dimensional problems.

Recall the maximum principles for numerical schemes for Laplace equations;

Recall iterative techniques for solving the linear systems resulting from finite element discretization;

Textbooks

Possible textbooks for this course include (but are not limited to):

Additional topics

Courses for which this course is prerequisite