BEng Civil Engineering

There is a compulsory field course for Civil Engineering students which incurs a subsidised fee* (approx. £100) that contributes to travel, accommodation and subsistence. You are expected to bring your own wet weather clothing and footwear.

The exact cost and dates of the trip are confirmed at the start of your second year.

* In accordance with current University policy, this fee is restricted to be not more than 1% of the annual tuition fee of the course

The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.

For further information about scholarships and bursaries you can explore our undergraduate fees pages , visit scholarships and bursaries , and check the Department's funding pages .

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.

• 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)

Other - Assessed tutorial work

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.