Last modified: 24 Jun 2020 14:31
The course aims to provide understanding of main principles and techniques underpinning computational fluid dynamics (CFD) combining numerical methods with practical experience using appropriate software. The course develops a foundation for understanding, developing and analysing successful simulations of fluid flows applicable to a broad range of applications.
|Session||First Sub Session||Credit Points||15 credits (7.5 ECTS credits)|
The course will provide insight into physical phenomena in environmental and industrial fluid flows via numerical simulations. Whist this motivates the use of computational technologies, even advanced CFD software may lead to incorrect predictions of fluid flow behaviour if used without sufficient understanding of the underlying algorithms and methods. This course introduces students to computational methods for solving distinct type of partial differential equations (PDE) that arise in fluid dynamic studies.
This course will involve fundamentals of numerical analysis of PDE, introduction to computational linear algebra, discretisation techniques and numerical schemes to solve time-dependent PDE problems, error control and stability analysis, mesh-generation methods and turbulence models. Hands-on sessions with industry standard software are used to develop CFD skills.
Information on contact teaching time is available from the course guide.
lab report (10%)
lab report (10%)
lab report (30%)
online open book exam (50%)
There are no assessments for this course.
|Knowledge Level||Thinking Skill||Outcome|
|Procedural||Understand||Fundamental computational fluid dynamics and applications?• Finite difference and finite volume discretisation of PDE's and how numerical techniques are applied to flow equations?|
|Reflection||Create||• Select appropriate set of numerical methods and discretisation schemes for a particular fluid flow application?• Recognise terminologies used by CFD practitioners|
|Procedural||Understand||CFD workflow procedures including mesh generation, numerical discretisation schemes and solver methods, assignment ofappropriate initial and boundary conditions, preandpostprocessingdata.|
|Reflection||Evaluate||Assess the applicability of a particular model/method and its limitations|