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Unit information: Modern Approaches in Fluids in 2018/19

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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

Description

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.

Intended learning outcomes

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).

Teaching details

18 lectures

4 Tutorials

12 Demonstrations

Super-computer BlueCrystal is accessed through local terminals by ssh

Assessment Details

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.

Reading and References

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.

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