Teaching

A summary of courses I teach.

Master program

• Numerical Analysis, WI4014TU, Q1-Q2
  📂 View Course Lecture Slides (PDF)

  1. 📄 Lecture 1: Course structure and mathematical preliminaries
  2. 📄 Lecture 2: Classificatyion and theoretical analysis of PDE’s
  3. 📄 Lecture 3: Finite Difference Method in 1D, order of approximation, properties of 1D FD Laplacian
  4. 📄 Lecture 4: Further details of the Finite-Difference Method in 1D
  5. 📄 Lecture 5: Finite Difference Method in 2D Properties of the 2D FD Laplacian matrix
  6. 📄 Lecture 6: Finite Volume Method in 1D
  7. 📄 Lecture 7: Finite Volume Method in 2D
  8. 📄 Lecture 8: Finite Element Method: Mathematical preliminaries
  9. 📄 Lecture 9: Finite Element Method: Ritz method
  10. 📄 Lecture 10: Finite Element Method: Galerkin method, matrix assembly, FEniCSx
  11. 📄 Lecture 11: Numerical time integration, solution of the diffusion equation
  12. 📄 Lecture 12: Numerical solution of the wave equation
  13. 📄 Lecture 13: Nonlinear Problems, Picard’s method, Newton-Raphson algorithm
  14. 📄 Lecture 14: Linear solvers: direct solvers and classical iterative methods
  15. 📄 Lecture 15: Linear solvers: Krylov subspace, Arnoldi and GMRES algorithms

Bachelor program

• Numerical Analysis for Partial Differential Equations, TW3730TU, Q1.
  📂 View Course Lecture Slides (PDF)

  1. 📄 Lecture 1: Course structure and mathematical preliminaries
  2. 📄 Lecture 2: Classificatyion and theoretical analysis of PDE’s
  3. 📄 Lecture 3: Finite Difference Method in 1D
  4. 📄 Lecture 4: Further details of the Finite-Difference Method in 1D
  5. 📄 Lecture 5: Finite Difference Method in 2D
  6. 📄 Lecture 6: Finite Volume Method in 1D
  7. 📄 Lecture 7: Finite Volume Method in 2D
  8. 📄 Lecture 8: Numerical time integration, solution of the diffusion equation
  9. 📄 Lecture 9: Numerical solution of the wave equation
  10. 📄 Lecture 10: Nonlinear Problems, Picard’s method, Newton-Raphson algorithm
  11. 📄 Lecture 11: Linear solvers: direct solvers and classical iterative methods
  12. 📄 Lecture 12: Linear solvers: Krylov subspace, Arnoldi and GMRES algorithms
• Final Minor Project - Part A, TW3715TU, Q1.
• Final Minor Project - Part B, TW3725TU, Q2.
• Numerieke Wiskunde, WBMT2049T2 and WI2032TH, Q4.
  📂 View Course Lecture Slides (PDF)

  1. 📄 Lecture 1: Numerical computations in finite precision
  2. 📄 Lecture 2: Mathematical preliminaries
  3. 📄 Lecture 3: Interpolation
  4. 📄 Lecture 4: Numerical differentiation
  5. 📄 Lecture 5: Nonlinear equations
  6. 📄 Lecture 6: Systems of nonlinear equations
  7. 📄 Lecture 7: Numerical integration
  8. 📄 Lecture 8: Initial-value problem for ODE, stability of numerical time-integration
  9. 📄 Lecture 9: Local and global truncation errors, consistency and convergence
  10. 📄 Lecture 10: Systems of ODE’s
  11. 📄 Lecture 11: Boundary-value problems for ODE, Finite-Difference Method
  12. 📄 Lecture 12: Review and exam questions - Part A
  13. 📄 Lecture 13: Review and exam questions - Part B