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for a past academic year. Please see the current academic year for up to date information.
| Unit name |
Computational Modelling 2 |
| Unit code |
CENG25200 |
| Credit points |
10 |
| Level of study |
I/5
|
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24)
|
| Unit director |
Dr. O'Donnell |
| Open unit status |
Not open |
| Pre-requisites |
None
|
| Co-requisites |
None
|
| School/department |
School of Electrical, Electronic and Mechanical Engineering |
| Faculty |
Faculty of Engineering |
Description including Unit Aims
Aims: This unit aims to enable students to develop an awareness of the scope and limitations of computational modelling in a representative range of civil engineering problems. Students will also gain an understanding of the implications of various assumptions that can be made when creating a computer model of a real problem.
- Introduction to Matlab Programming
- Introduction to the principles of programming.
- Variables, condition structures, loops, subroutine and functions
- Introduction to Finite Difference Analysis (FDA)
- Numerical differentiation
- Solution of differential equations using FDA.
- Introduction to Finite Element Analysis (FEA)
- Development of FEA program within MATLAB, from first principles
- Definition of geometry, fixity, material properties, loading and boundary constraints, necessary partitioning, solution of system of equations, computation of deflections, actions and member stress resultants.
- Validation of Engineering Programs
- Commercial FE codes
- Methods of modelling of real civil engineering systems with approximate FE/FD models and accuracy of results
- Second order effects, P-Δ , introduction to non-linear analysis
Intended Learning Outcomes
At the end of this course, successful students will:
- have an appreciation of the importance of numerical modelling in engineering practice;
- be able to write programs which can generate model data for use in other packages;
- be able to identify and apply strategies for validating and correcting engineering computer models;
- understand the theoretical basis for both finite element and finite difference methods;
- understand how different assumptions made in the production of a numerical model will affect the output from an analysis and understand the limitations of some of the analysis and design packages that are used by engineers.
- Demonstrated an understanding of programme structures and coding best practice
Teaching Information
22 hours lectures, 20 hours computer labs
Assessment Information
Single assessment portfolio submitted at the end of the course (100% summative), comprising 20% Programming Principles and 80% Computational Analysis Report
Reading and References
Essential Matlab for Engineers and Scientists [Paperback] by Brian Hahn, Dan Valentine
Attaway S, MATLAB: A Practical Introduction, Butterworth-Heinemann 9780124058767
