# Unit information: Computational Modelling 2 in 2016/17

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Computational Modelling 2 CENG25200 10 I/5 Teaching Block 2 (weeks 13 - 24) Dr. O'Donnell Not open None None Department of Civil Engineering Faculty of Engineering

## Description

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 details

22 hours lectures, 20 hours computer labs

## Assessment Details

Single assessment portfolio submitted at the end of the course (100% summative), comprising 20% Programming Principles and 80% Computational Analysis Report