Coronavirus information for applicants and offer-holders

We understand that prospective students and offer-holders may have concerns about the ongoing coronavirus outbreak. The University is following the advice from Universities UK, Public Health England and the Foreign and Commonwealth Office.

Read our latest coronavirus information

MEng Civil Engineering with Industrial Experience / Course details

Year of entry: 2021

Course unit details:
Computing & Numerical Methods (Civil)

Unit code MACE20471
Credit rating 10
Unit level Level 2
Teaching period(s) Semester 1
Offered by Civil Engineering Division L5
Available as a free choice unit? No


This unit is the first in the series of Modelling and Simulation modules and thus forms the foundation of computational concepts for students. The module serves as the tool to teach programming and use of computational software both from a structural and fluids perspective. Efficient programming skills and understand the fundamentals of computations is the key for the students to become comfortable with advanced engineering software such as ANSYS, Solid works, Fluent, Star-CCM+ etc.

This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates


• To give students the skills to tackle engineering problems using numerical methods and appropriate scientific software
• To teach structured programming techniques and numerical methods
• To demonstrate the application of some popular computer software packages and programs.


  1. How to solve systems of equations using matrices
  2. How to develop algorithms based on solution techniques
  3. How to use, program and implement algorithms using interpreted language How to solve nonlinear equations numerically
  4. How to implement this in a high level language

Solving systems of equations using matrices - Dr Milan Mihajlovic

Part 1:

  1. Basic concepts of system of equations
  2. Reduction operations
  3. Direct and iterative techniques
  4. Algorithm development

Part 2:

  1. Revision of MATLAB interface, syntax, mathematical operations (includes lab: Familiarity and basics of MATLAB)
  2. Revision of Conditional processing (IF statements), repetition (FOR loops), arrays (includes lab: Basic Programming in MATLAB, pre- and post-processing; lab: Matrix transformations in MATLAB)
  3. Programming and algorithm implementation in MATLAB (includes lab: Advanced programming in MATLAB using direct and iterative techniques for solution of systems of equations)

Solving nonlinear equations numerically - Dr S. Lind

Part 1:

  1. Concepts of solution by iteration
  2. Solution of nonlinear equations for f(x)=0
  3. Numerical differentiation
  4. Introduction to finite differences

Part 2:

  1. Source code and execution, syntax, mathematical operations (lab: Python Basics)
  2. Conditional processing (IF statements), repetition (DO loops), libraries (lab: Repetition and Choice)

Arrays, functions and modules (lab: Arrays and Functions)

Assessment methods

Method Weight
Other 25%
Written exam 50%
Report 25%

Other - Assessed tutorial work

Feedback methods

Week 8 for all MATLAB based assignments and coursework, week 13 for all Fortran based assignments and coursework. Immediate verbal feedback on exercises undertaken in computer tutorials.

Study hours

Scheduled activity hours
eAssessment 36
Lectures 16
Tutorials 20
Independent study hours
Independent study 28

Teaching staff

Staff member Role
Steven Lind Unit coordinator

Return to course details