Engineering Computations 2


Introduces the principles of engineering computations and probability/statistics. Its purpose is to develop the student's ability to write MATLAB code to solve numerical and statistical problems of engineering interest.


UoN Singapore

  • Trimester 1 - 2015 (Singapore)

Callaghan Campus

  • Semester 2 - 2015

Learning Outcomes

1. To understand and implement basic numerical algorithms for computing solutions of single nonlinear equations and systems of linear equations. To understand and implement the basics of the linear algebra.

2. To understand and implement algorithms for interpolation, curve fitting, numerical differentiation, and numerical integration.

3. To understand and implement numerical methods for solving parabolic and hyperbolic partial differential equations.

4. Demonstrate an understanding of the key concepts of probability and Bayesian inference.

5. Formulate and solve problems dealing with probability and statistics with engineering applications.

6. Demonstrate practical skill in Monte Carlo simulation


The content of the course includes:

  1. The numerical solution of a single nonlinear equation, systems of linear equations, ordinary differential equations, and partial differential equations.
  2. The numerical implementation of interpolation and curve fitting.
  3. An introduction to probability and distribution theory targeted mainly to mechanical engineering applications.
  4. Monte Carlo simulation: theory and practice.
  5. Introduction to Bayesian statistical inference with applications to common engineering probability models

Assumed Knowledge

GENG1003 and MATH2310

Assessment Items

Written Assignment: Assignment 1

Written Assignment: Assignment 2

Quiz: Quiz 1

Quiz: Quiz 2

Formal Examination: Formal Examination

Contact Hours

Computer Lab

Face to Face On Campus 2 hour(s) per Week for Full Term


Face to Face On Campus 3 hour(s) per Week for Full Term

Students enrolled in the part-time evening programme at UoN Singapore will receive equivalent instruction delivered in a block mode of 7 teaching weeks


Face to Face On Campus 3 hour(s) per Week for Full Term