Numerical Solutions of Partial Differential Equations
Master Course, University of Electronic Science and Technology of China, Building, 2020
Numerical PDEs
Course Information
- Numerical Solutions of Partial Differential Equations (1107016008)
- This is an English taught course for students ready for both master and doctor degree.
- The application used to demonstarte the live codes, interactive computing during lecture is call Jupyter Notebook. The notebooks for this course are available to be viewed on link.
- Teaching QQ group (slides, lecture notes, recording): 700601089
Purpose of the Course:
This course presents the fundamentals of modern numerical techniques for a wide range of equations. The emphasis is on building an understanding of the essential ideas that underlie the development, analysis, and practical use of finite difference methods. The goals are:
- To understand the fundamental mathematics theory and algorithms of finite difference methods;
- To be able to implement finite difference methods for simple 1d and 2d problems as well as to evaluate and to interpret the numerical results;
- To be able to solve some engineering problems by using known algorithms.
Textbook:
- Randall J. LeVeque. Finite Difference Methods for Ordinary and Partial Differential Equations, SIAM, 2007.
Reference:
- K. W. Morton and D. F. Mayers. Numerical Solution of Partial Differential Equations, Cambridge University Press 2005.
- Alfio Quarteroni and Alberto Valli. Numerical Approximation of Partial Differential Equations, Springer 1994.
- Susanne C. Brenner, L. Ridgway Scott. The Mathematical Theory of Finite Element Methods, 3rd edition, Springer.
Assessment Method:
Grade for this course is determined by the performance in computer projects and final exams, which are designed based on the course objectives.
Exercise
- Requirement and samples. Exercise Sample (PDF) Latex Sample (PDF) tex
- Exercise 1. PDF tex
- Exercise 2. PDF tex
- Sample Problems PDF
Teaching Contents:
- Chapter 0. Introduction Slide
- Scientific Computing with Python Notebook
- Chapter 1. Finite Difference Approximations [Notebook]
- Chapter 2. Steady States and Boundary Value Problems
- The centered finite difference method for 1d linear BVP. Code Notebook
- The eigenvalues of the matrix from the FDM for 1d linear BVP. Note
- Singularly Perturbed Equations Notebook
- Chapter 3. Elliptic Equations
- Laplace’s Equations Notebook
- Chapter 4. Iterative Methods for Sparse Linear Systems
- Chapter 5. The Initial Value Problem for Ordinary Differential Equations
- Chapter 6. Zero-Stability and Convergence for Initial Value Problems
- Chapter 7. Absolute Stability for Ordinary Differential Equations
- Chapter 8. Stiff Ordinary Differential Equations
- Chapter 9. Diffusion Equations and Parabolic Problems
- Chapter 10. Advection Equations and Hyperbolic Systems
- Advection Equation Notebook
- Chapter 11. Mixed Equations Slide
- Discontinuous Galerkin Methods
