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Unit information: Computational Modelling 2 in 2018/19

Please note: It is possible that the information shown for future academic years may change due to developments in the relevant academic field. Optional unit availability varies depending on both staffing and student choice.

Unit name Computational Modelling 2
Unit code CENG25200
Credit points 10
Level of study I/5
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Matt O'Donnell
Open unit status Not open
Pre-requisites

None

Co-requisites

None

School/department Department of Civil Engineering
Faculty 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 programming principles test and computational analysis reports.

Reading and References

Essential Matlab for Engineers and Scientists [Paperback] by Brian Hahn, Dan Valentine

Attaway S, MATLAB: A Practical Introduction, Butterworth-Heinemann 9780124058767

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