Unit name | Modern Approaches in Fluids |
---|---|
Unit code | MENGM0034 |
Credit points | 10 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. Lawrie |
Open unit status | Not open |
Pre-requisites |
Thermofluids 1, Thermofluids 2, Engineering Maths 1, Engineerng Maths 2, Fluids 3 (or equivalents) |
Co-requisites |
None |
School/department | Department of Mechanical Engineering |
Faculty | Faculty of Engineering |
Fluid Mechanics is a fascinating subject that draws physics and maths together and is applied in an enormous range of disciplines, from geophysics to medicine to astrophysics. In this course we will focus on those aspects of high Reynolds number fluid mechanics that are relevant to the practicing engineer and aim to equip the student with the understanding necessary to critically assess the various computational, experimental and analytical approaches to predicting and measuring flow behaviour.
The intended learning outcomes are grouped into three areas, A: numerical techniques to model high Reynolds number fluids, B: experimental diagnosis, C: analysis techniques. On successful engagement with the unit the participants should be able to:
- Identify the primary reasons for and estimate the magnitude of error accrual and instability in numerical simulation, experiment and theoretical prediction when applied to a canonical turbulent flow (EA2, EA6m). - Describe the key features and implement simple versions of the algorithms that underlie the image data-processing in industry-standard measurement techniques of particle image velocimetry and laser-induced fluorescence and that underlie the upwind finite-volume explicit approach to numerical simulation (EA3m,SM1m). - Develop a version of the industry-standard k-epsilon model for turbulence for use in a one-dimensional numerical model and compare results with analytical predictions, experimental evidence and three-dimensional numerical simulations (EA3m,SM2m). - Appreciate the scaling properties of a massively-parallel numerical simulation and apply techniques to mitigate communication latency in parallel code. Plan and execute a sequence of week-long simulations to evaluate grid convergence of such methods in highly turbulent flows (EA4m, SM3m).18 lectures
4 Tutorials
12 Demonstrations
Super-computer BlueCrystal is accessed through local terminals by ssh
100% written project on an exemplar problem of a turbulent jet in free space, using data obtained in the experimental and computer laboratories associated with the course and applying statistical image-processing techniques taught in lectures.
Davidson, P., 2015. Turbulence: an introduction for scientists and engineers. Oxford University Press, USA.
Pope, S.B., 2000. Turbulent flows. Cambridge University Press, UK.
Kuethe, A.M., Chow, C.Y. and Fung, Y.C., 1997. Foundations of Aerodynamics, Bases of Aerodynamics Design. 5th Edition. Wiley, USA.
Toro, E.F., 1999. Riemann Solvers and Numerical Methods for Fluid Dynamics: A Practical Introduction 3rd Edition. Springer.