Undergraduate Course: Numerical Methods and Computing 2 (CIVE08017)
Course Outline
| School | School of Engineering |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course includes an introduction to the concepts of scientific computing and a series of lectures and computing lab sessions on important numerical methods often used for the solution of mathematical problems encountered in Civil Engineering. |
| Course description |
Lectures: Titles & Contents
Lectures are used to present the foundations of key numerical methods and their use in solving engineering problems. Emphasis is given on the application of the numerical methods and their implementation as computer algorithms.
L1: Introduction to numerical methods and computing
Introduction to numerical methods - relevance and usefulness. Overview of the course - aims and scope. Assessment and resources information. Preliminaries - general terms and concepts (convergence/divergence, stability, errors, iteration) - and examples.
L2-4: Solution of algebraic equations: non-linear equations
Introduction to non-linear equations. Civil engineering applications; advantages and pitfalls of numerical solution techniques. Alternative strategies: Bisection, False Position, Newton-Raphson and Secant. Analyse problems using different strategies, importance of understanding the function.
L5-7: Numerical integration:
Reasons for integration arising in civil engineering problems; nature of integration, differences between numerical and algebraic integration, format of integration schemes, notation. Trapezium, Simpson's, Simpson's 3/8 and Boole's rules. For each: use, method, validity, effort, errors, and examples. Style of Gauss rules, advantages over Newton-Cotes rules, use of one- and two-point Gauss rules. Three-point and higher rules. Use, errors, examples. Higher order rules.
L8-10: Numerical solution of ODE's
Introduction to solution of Ordinary Differential Equations, derivation and application of the Euler Method. Application of Euler, Euler-Cauchy and Runge-Kutta Methods.
L11: Revision
Applications and worked examples, to further demonstrate use of methods for solving Civil Engineering problems with guidance on checking correct implementation and common errors to avoid.
Lab Supported Self-Study Computing Module (weeks 2-6)
Supported by weekly computing laboratory sessions, the student is introduced, using a specially developed self-study module, to the concepts of scientific programming and the use of a computing tool appropriate for engineering computation. The self-study module consists of five main units, each that broadly cover:
1. Basic Concepts (week 2)
2. Plotting (week 3)
3. Scripts and Functions (week 4)
4. Decision Making (week 5)
5. Loops (week 6)
Each individual unit contains many exercises with example solutions and some that have step-by-step instructions presented as video screen-casts.
Computing Applications Sessions (weeks 7-11)
In the remaining Computing Laboratory sessions a number of exercises are undertaken. These will cover three key numerical methods and their applications as listed below. In each case some basic examples scripts may be provided but must be adapted to implement different methods.
1: Non-linear Equations (week 7)
Students are asked to develop computer programs for the solution of non-linear equations using Newton-Raphson, Bisection and False Position methods. These are then applied to the solution of various mathematical problems, with investigation of issues such as convergence and tolerances.
2. Numerical integration (week 8)
Students develop simple computer programs for the solution of Numerical integration problems, spanning rules of different order.
3: ODEs (week 9)
Students are asked to develop simple computer programs for the solution of ODE's, spanning methods of different order.
4. Labs revision (week 10)
5. Assessment ***compulsory attendance*** (week 11)
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2018/19, Available to all students (SV1)
|
Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 20,
Formative Assessment Hours 1,
Summative Assessment Hours 8,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
59 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
50 %,
Practical Exam
50 %
|
| Additional Information (Assessment) |
Competence in Computing Class Test: 50%
Coursework 50% |
| Feedback |
Mid Semester "Start, Stop, Continue"
Oral Feedback during Computing Laboratory Sessions
Written Feedback on submitted coursework
End of course "post-mortem" |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- demonstrate skills in using computer programming tools for engineering calculations;
- demonstrate ability to construct simple computer algorithms using a programming tool;
- apply simple numerical methods to solve mathematical problems with relevance to civil engineering;
- appreciate the limitations and the applicability of the numerical methods;
- apply computer-based numerical methods for the solution of engineering problems.
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Learning Resources
1. An Interactive Introduction to MATLAB
https://matlab.eng.ed.ac.uk/ |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
10 Lectures, plus revision
10 Computing Laboratory Sessions, including assessment |
| Keywords | numerical method,scientific computing,non-linear equations,numerical integration,ODE's |
Contacts
| Course organiser | Dr Stephen Welch
Tel: (0131 6)50 5734
Email: S.Welch@ed.ac.uk |
Course secretary | Mr Craig Hovell
Tel: (0131 6)51 7080
Email: c.hovell@ed.ac.uk |
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