Engineering

ECMM121 - Engineering Systems Analysis (2010)

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MODULE TITLEEngineering Systems Analysis CREDIT VALUE30
MODULE CODEECMM121 MODULE CONVENERDr Khurram Wadee (Coordinator), Dr Jacqueline Christmas
DURATION: TERM 1 2 3
DURATION: WEEKS
Number of Students Taking Module (anticipated)
DESCRIPTION - summary of the module content
AIMS - intentions of the module
This module aims to provide a treatment of numerical methods, simulation and optimisation techniques for the modern practising engineer. It also highlights the use of such techniques in the solution of management related problems.
INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)
SYLLABUS PLAN - summary of the structure and academic content of the module
Introduction to numerical methods: Approximation of functions, Taylor series, First-order approximation, Errors, Error propagation. Roots of equations: Interval bisection, the Newton-Raphson technique, the secant method, stopping criteria. Solution of linear simultaneous equations: Gaussian elimination for two, three, n equations, conditioning, determinants, Gauss-Seidel method, conditioning, convergence. Curve fitting and interpolation: Linear regression, goodness of fit, normalized residuals, change of variable, logarithmic plots, polynomial or curvilinear interpolating polynomials, linear interpolation, quadratic interpolation, Lagrange interpolating polynomial, numerical differentiation, first derivatives from Taylor series, second derivatives from Taylor series. Numerical integration: Rectangular rule, trapezium rule, Simpson's rule, multiple application of Simpson's rule. Solution of ordinary differential equations (ODEs): Initial value problems, Euler-Cauchy method, Runge-Kutta methods, second-order Runge-Kutta, fourth-order Runge-Kutta. Simulation methods (deterministic and probabilistic). Multi-objective optimisation techniques. Modern heuristics including genetic algorithms, fuzzy sets and neural networks.
LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities Guided Independent Study Placement / Study Abroad
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
SUMMATIVE ASSESSMENT (% of credit)
Coursework 30 Written Exams 70 Practical Exams
DETAILS OF SUMMATIVE ASSESSMENT
DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
RE-ASSESSMENT NOTES
RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

Reading list for this module:

Type Author Title Edition Publisher Year ISBN Search
Set Acton, F.S. Numerical Methods that Work Mathematical Association of America 1997 0883854503 [Library]
Set Michaelewicz, Z Genetic Algorithms + Data Structures = Evolution Programmes 3rd Springer-Verlag 1996 000-354-055-387-8 [Library]
Set Press, W. H., Flannery, B. P., Teukolsky, S. A. & Vetterling, W. T Numerical recipes in C (or Fortran). The art of scientific programming 2nd New York: Cambridge University Press. 1992 [Library]
CREDIT VALUE 30 ECTS VALUE 15
PRE-REQUISITE MODULES None
CO-REQUISITE MODULES None
NQF LEVEL (FHEQ) M AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Thursday 15 December 2011 LAST REVISION DATE Thursday 15 December 2011
KEY WORDS SEARCH None Defined