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Computational Fluid Dynamics – (M.Sc.)

Cranfield University

School of Engineering
Annual Tuition Fee: ≈ € 6,670 - ≈ € 17,950 (non-EEA)
Location: Cranfield / United Kingdom / View location on map ▾ Hide location on map ▴
Duration: 12 months Start Date: October
Educational Form:
  • Taught
Education Variants:
  • Parttime
  • Fulltime
Languages: English 
-0.426842,52.005267

Location of Cranfield University

Computational Fluid Dynamics (CFD) is the science of determining a numerical solution to the governing equations of fluid flow whilst advancing the solution through space and time to obtain a numerical description of the complete flow field of interest.

There has been considerable growth in the development and application of CFD to all aspects of fluid dynamics leading to CFD becoming a standard modelling tool widely utilised within industry. As a consequence there is a considerable demand for specialists in the subject, to apply and develop CFD methods throughout engineering companies and research organisations.

The Master of Science in Computational Fluid Dynamics course provides a solid background for graduates to be able to apply, in an educated manner, CFD as a design tool for engineering applications, providing excellent career opportunities across a broad range of industries. For graduates interested in an academic career the course provides an excellent basis from which to further specialise in the development and application of both numerical algorithms and physical models.

This course has been designed to reflect the wide application of CFD. It covers a broad range of areas from aerospace, turbomachinery, multi-phase flow and heat transfer, to microflows, environmental flows and fluid-structure interaction problems. The course is organised in a modular fashion and is specifically designed to accommodate both full-time and part-time study


Contents

There has been considerable growth in the development and application of CFD to all aspects of fluid dynamics leading to CFD becoming a standard modelling tool widely utilised within industry. As a consequence there is a considerable demand for specialists in the subject, to apply and develop CFD methods throughout engineering companies and research organisations.

Department of Fluid Mechanics and Computational Science led by Professor Dimitris Drikakis, FRaES, FIoN, author of the “High Resolution Methods for Incompressible and Low Speed Flows” CFD textbook (Springer, 2004), has a broad range of expertise including, among other fields, Numerical methods development for computational science; Computational fluid dynamics; Computational & experimental aerodynamics; Transition, turbulence, instabilities and turbulent mixing modelling; Multi-species and multi-phase flows modelling; Computational heat transfer analysis; Shock-material interaction modelling; Environmental flows modelling; Computational fluid dynamics for automotive flows; Nanotechnology and nanoscience, eg fluid-material interfaces, micro/nanofluidics, particles transport.The Department has links with a number of several research establishments and industries such as: DSTL, AWE, UKAEA, MBDA, Rolls-Royce, Aston Martin, Formula 1 companies, Selex, Servomex, Malvern Instruments, Blue Bear Systems Research, Eaton Aerospace Ltd, Eurocopter (Germany), DLR (Germany), QinetiQ, BAE Systems, British Hydromechanics Research (BHR), Los Alamos National Lab (USA), National Physical Laboratory, Daresbury Laboratory, Turbomeca (France), Gamesa (Spain), Lambda GmbH (Austria), Lionix (The Netherlands), St Andrews Centre for Plastic Surgery and Burns (Essex), Guy’s and St Thomas’s NHS Trust (London), among others. The CFD research group comprises 41 researchers at the moment dealing with all aspects of fluid flow modelling, which creates an exciting environment to pursue CFD studies in.

The Master of Science in Computational Fluid Dynamics course provides a solid background for graduates to be able to apply, in an educated manner, CFD as a design tool for engineering applications, providing excellent career opportunities across a broad range of industries. For graduates interested in an academic career the course provides an excellent basis from which to further specialise in the development and application of both numerical algorithms and physical models.

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Requirements

A 1st or 2nd class UK honours degree (or equivalent) in mathematics, physics, computing or an engineering discipline.

Additional Requirements

Minimal degree required: Bachelor's degree
Minimal amount of work experience Not specified

Language Proficiency

Cambridge English: Advanced (CAE): Grade C (Score: 60)

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