ME 140A: Numerical Analysis in Engineering

 

·       Professor

·       Syllabus

·       Teaching Assistant

·       Textbook

·       Grading Policy

·       Homework

·       Matlab Primer

·       Midterm Review

 

Professor

Name: Frederic G. Gibou
Office: Engineering II Bldg. room 2334
Phone: 893-7152
e-mail: fgibou@engineering.ucsb.edu

Office Hours: TR 1:45-3:15 pm or by appointment.

Lectures: TR 12:30 - 1:45 pm. Room: LSB 1001

Syllabus

A copy of the syllabus can be found here.

 

  • Thursday September 28: Goals for the class – Presentation of the topics that will be covered.
  • Tuesday October 3: Introduction to linear systems of equations – Dense .vs. Sparse matrices and its implications.
  • Thursday October 5: Direct Methods – LU decomposition (Chapter 4.1-4.2).
  • Tuesday October 10: Direct Methods – Gaussian decomposition and Pivoting (Chapter 4.3).
  • Thursday October 12: Direct Methods – Gaussian decomposition and Pivoting (Chapter 4.4).
  • Thursday October 12: Direct Methods – Pivoting and Analysis of Errors (Chapter 4.4).
  • Thursday October 17: Direct Methods – Pivoting and Analysis of Errors (Chapter 4.4).
  • Thursday October 19: Direct Methods – Pivoting and Analysis of Errors (Chapter 4.4).
  • Thursday October 24: Iterative Methods – Iterative Refinement - Gauss-Seidel and Jacobi (Chapter 4.5-4.6).
  • Thursday October 26: Iterative Methods – Iterative Refinement (Chapter 4.5-4.6).
  • Tuesday October 31: Iterative Methods – Iterative Refinement (Chapter 4.5-4.6).
  • Thursday November 2: ODE – Introduction and Euler Method (Chapter 8.1).
  • Tuesday November 7: Review.
  • Thursday November 9: Midterm. The midterm will cover everything we have covered in lecture. Here is a review.
  • Tuesday November 14: ODE –Methods based on Taylor expansions – Order of accuracy.
  • Thursday November 16: ODE – Runge-Kutta Methods.
  • Tuesday November 21: ODE – Multistep Methods – Adams-Bashforth.
  • Thursday November 23: Thanks Giving.
  • Tuesday November 28: ODE – Multistep Methods – Adams-Moulton and Predictor-Correctors.
  • Thursday November 30: Introduction to PDE – The heat equation.
  • Tuesday December 5: Introduction to PDE – The heat equation.
  • Thursday December 7: Review.

 

  • Tuesday December 12: Final exam – 12:3pm.

 

Teaching Assistants

There are four TAs for this class:

 

 

You are encouraged to visit the TAs during their office hours to get help on the homework.

Textbook

The textbook for the course is David Kincaid and Ward Cheney, Numerical Analysis, Brooks/Cole., Second Edition, 1996.

Additional references, lecture notes and slides will be handed out in class or posted on the web.

Grading Policy

Your grade will be based on homework (25%), one midterm (25%) and a final (50%). The midterm will be on Thursday November 9. A review will be given on Tuesday November 7.

Homework

Working together on homework in groups of two or three students is strongly encouraged.

Homework due Thursday October 12: hw1. . Solution_1a, Solution_1b.

Homework due Thursday October 19: hw2. Solution. Code_Gauss_Pivoting.

Homework due Thursday October 26: hw3. Solution.

Homework due Thursday November 2: hw4. Solution Solution_Jacobi Solution_Jacobi_2 Solution_GS Solution_GS2

No Homework due Thursday November 9 - Midterm.  Here is a review.

Homework due Tuesday November 21: hw5. Solution_hw5_Taylor, Solution_hw5_Taylor_Accuracy, Solution_hw5_RK4, Solution_hw5_RK4_Accuracy

Homework due Thursday November 30: hw6. Solution.

Homework due Thursday December 7: hw7. This homework is optional and is recommended for anyone who plans to take 140B.

Midterm Review

Here is a review. No calculator, books, notes will be allowed. The midterm will cover everything we have covered in lecture.

Matlab Primer

Here is a link to Matlab Primer.