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Computational Fluid Dynamics (CFD) MSc/PgDip/PgCert

Full-time/Part-time

MSc in Computational Fluid Dynamics

The MSC in Computational Fluid Dynamics (CFD) is an inherently interdisciplinary branch of science which has an extremely broad spectrum of applications. Fluid dynamics uses numerical methods and algorithms to solve and analyse problems that involve fluid flows. Sectors such as aviation, space, automotive, medicine and environment are just some industries which have fluid flows in common. 

There has been considerable growth in the development and application of CFD in all aspects of fluid dynamics. CFD has become a standard modelling tool widely utilised within industry. In a recent survey by Technavio (a leading technology research and advisory company), the global market for CFD is projected to grow at 16.5% per year due to increasing computational power and integration of computational fluid dynamics into the design process.

This course has been designed to reflect the wide applications of CFD. It covers a broad range of fields from aerospace, turbo machinery, multiphase environmental flows and fluid-structure interaction problems.

This industry is worth billions of pounds, and as a consequence there is a considerable demand for specialists in the subject which is not covered in sufficient detail at undergraduate level. This course is suitable for graduates and professional engineers who are looking to kick-start an industrial or research career in the rapidly growing field of computational fluid dynamics.



  • Course overview

    The MSc in Computational Fluid Dynamics is made up of eleven compulsory taught modules, and five optional application modules (from a choice of seven), plus an individual research project.

    In addition to management, communication, analytical and research skills, each student will attain at least the following outcomes from this degree course:

    • Demonstrate a critical awareness of the governing equations of fluid mechanics, and their mathematical properties, in various formulations for compressible and incompressible inviscid and viscous flows.
    • Demonstrate a critical awareness of different state-of-the-art CFD methods as used in engineering practice and research and development for both incompressible and compressible flows.
    • Demonstrate a systematic application of the principles and understanding of limitations of techniques for the simulation of turbulent and transitional flows and thus be able to apply these in a critical manner to practical applications.
    • Demonstrate their acquired skills in applying commercial CFD software packages to practical engineering applications.
    • Demonstrate a critical awareness of the underlying principles of numerical analysis, concepts of stability, approximation and convergence and the numerical solution of systems of algebraic equations.

    Students on the part-time programme will complete all of the compulsory modules based on a flexible schedule that will be agreed with the course director.

  • Individual project

    The taught element of the course finishes in May, at which point you will have an excellent understanding of CFD methods and applications. From May to September you will work full-time on your individual research project. The research project gives you the opportunity to produce a detailed piece of work either in close collaboration with industry, or on a particular topic which you are passionate about.

    Recent Individual Research Projects include:

    • A Study of A-pillar Vortices on the Jaguar XF Using Transitional Turbulence Models
    • Aerodynamic Analysis and Optimisation of the Aegis UAV
    • Performance Analysis of Hypervapotron Inlet Region
    • Phase Separation of Oil-water Flow in a Pipe Bend
    • CFD Simulation of a Novel CO Sensor
    • Shock Wave Interaction with Biological Membranes for Drug Therapy
    • High Resolution Implicit Large Eddy Simulation of Ariane 5 Aerodynamics.
  • Modules

    The taught programme for the Computational Fluid Dynamics masters is generally delivered from October to April. The taught modules are delivered via a combination of structured lectures, and computer based labs. The core part of the course consists of eleven modules which are considered to represent the necessary foundation subject material. The course is designed to reflect the broad range of CFD applications by providing a range of optional modules to address specific application areas.

    Core

    • Introduction to Fluid Mechanics and Heat Transfer
      Aim

      To introduce the foundations of fluid mechanics, various formulations of governing equations and their mathematical properties in order to establish a firm basis for other modules.

      Syllabus
      • Introduction to thermodynamics of gases and liquids
      • Introduction to heat transfer
      • Compressible flows
      • Incompressible flows
      • Dimensional analysis and similarity parameters
      • Mathematics of governing equations, classification of PDEs
      • Model equations for fluid dynamics
      • Introduction to unstable and turbulent flows.
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:

      • Demonstrate a critical awareness of the governing equations of fluid mechanics and heat
        transfer in various formulations for compressible and incompressible viscous and inviscid flows
      • Estimate the impact of different physical phenomena based on dimensional analysis
      • Understand mathematical properties of governing equations and be able to critically evaluate correct boundary/initial value problems for various flows
      • Demonstrate the systematic application of the model equations and problems used in CFD
      • Demonstrate a critical awareness of the concepts of stability and turbulence.
    • Numerical Methods for PDEs
      Aim

      To introduce the basics of numerical analysis and numerical methods for partial differential and algebraic equations.

      Syllabus
      • Introduction to numerical analysis
      • Discretisation approaches: finite difference, finite volume, finite element and spectral methods
      • Numerical methods for algebraic equations/systems of equations
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:
       

      • Demonstrate a critical awareness of the principles of numerical analysis and concepts of stability, approximation and convergence
      • Demonstrate the systematic application of the principles of finite difference/volume/element and functional decomposition methods and be able to critically evaluate these in model problems
      • Demonstrate the systematic application of the numerical solution of algebraic equations and systems of equations.
    • Numerical Modelling for Steady and Unsteady Incompressible Flows
      Aim

      To understand the state-of-the-art CFD methods used for computing incompressible flows in science and engineering.

      Syllabus
      • Overview of various formulations of the governing equations and numerical methods for incompressible flows (linear & high-resolution methods)
      • Solution approaches: pressure Poisson, projection (approximate and exact), artificial compressibility
      • Centred schemes
      • TVD and Riemann solvers for incompressible methods
      • Second and high-order methods (time and spatial discretisation).
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:
       

      • Demonstrate a critical awareness of alternative spatial and time discretisation methods for solving fluid mechanics problems governed by the incompressible Navier-Stokes/Euler equations
      • Demonstrate the systematic application of the mathematical and numerical classification and properties of different state-of-the-art CFD incompressible methods
        as used in engineering practice as well as in research and development
      • Demonstrate a critical awareness of uncertainties and limitations associated with each method.
    • Numerical Modelling for Steady and Unsteady Compressible Flows
      Aim

      To introduce basic concepts in the discretisation and numerical solution of the hyperbolic systems of partial differential equations describing the flow of compressible fluids.

      Syllabus
      • Mathematical properties of hyperbolic systems
      • Conservation Laws
      • Non-linearities and shock formation
      • The concept of weak solutions
      • Artificial viscosity
      • Introduction to the Riemann problem
      • Lax-Wendroff scheme
      • McCormack's scheme
      • Method of Lines and Jameson's scheme
      • Introduction to Godunov's method
      • Flux vector splitting methods
      • Approximate Riemann solvers
      • High-order and TVD methods.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:
       

      • Demonstrate a critical awareness of the mathematical properties of hyperbolic partial differential equations
      • Recognise the importance of non-linearities in the formation of shock waves
      • Demonstrate a critical awareness of the application and limitations of finite difference methods for hyperbolic systems of partial differential equations
      • Demonstrate a critical awareness of the characteristics of high-resolution shock capturing schemes
      • Demonstrate the systematic application of approximate Riemann solvers within simple one-dimensional problems.
    • Classical Turbulence Modelling
      Aim

      To introduce students to closure methods for the Navier-Stokes equations as applied to turbulent and transitional flows, and the classical physical modelling approximations required to achieve this.

      Syllabus
      • Introduction to Reynolds Averaged Navier Stokes Modelling
      • Mixing Length Approaches
      • Turbulent Transport
      • Two Equation Models
      • Non-Linear Models
      • Non-equilibrium Models
      • Reynolds Stress Transport Schemes
      • Low-Re Modelling
      • Transition Modelling Extensions
      • Best Practice Guidelines
      • Limits of Current Approximations
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:

      • Demonstrate a critical awareness of the basic principles of turbulence modelling approximations required to close RANS equations
      • Discriminate between different levels of closure and their limitations
      • Appreciate how modelling methods may be extended to transition prediction
      • Critically select between the different types of model available in current codes
    • Advanced Turbulence Modelling and Simulation: LES and DNS
      Aim

      To understand the principles of Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS).

      Syllabus
      • Overview of the basic equations used in LES, including filtered and unfiltered formulations
      • Classical LES and subgrid scale models
      • Implicit LES (numerical and physical principles)
      • Numerical and physical principles of DNS
      • Applications and challenges for LES and DNS.
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:

      • Demonstrate a critical awareness of the numerical and physical principles of LES and DNS in the simulation of transitional and turbulent flow simulations
      • Demonstrate the systematic application of the key computational methods used in LES& DNS, and subgrid scale models used in LES
      • Critically evaluate the challenges in the implementation of LES and DNS in science and engineering.
    • High Performance Computing for CFD
      Aim

      To introduce students to the most advanced current computing capabilities and what these offer over desktop environments.

      Syllabus
      • Desktop versus supercomputing
      • Parallel computing issues
      • Parallellisation approaches for distributed and shared memory systems. MPI and OpenMP
      • Current CFD Process Bottlenecks
      • Whole Product Applications.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Demonstrate a critical awareness of the range of high performance computing(hardware) platforms available for computational fluid dynamics simulations
      • Demonstrate the systematic application of the essential software extensions required for parallel computing
      • Recognise what application of high performance computing can achieve.
    • Managing Uncertainty in Simulations: Validation and Verification
      Aim

      To introduce the concepts of error and uncertainty and how they relate to the credible numerical solution of the partial differential equations encountered in computational fluid mechanics.

      Syllabus
      • The right answer: consistency, stability and convergence revisited
      • Taxonomies of error and uncertainty
      • Principles of code verification
      • Introduction to the method of manufactured solutions
      • Principles of solution verification
      • Role of systematic iterative and space-time grid convergence studies
      • Richardson extrapolation
      • Principles of validation
      • Statistical approaches to epistemic uncertainty
      • Construction of validation hierarchies.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Discriminate between error and uncertainty in computational simulations
      • Recognise the potential sources of error and uncertainty in computational simulations
      • Critically evaluate the tools that are available for the quantification of error and uncertainty in computational simulations
      • Be able to plan and perform credible computational simulations.
    • Grid Generation / CAD
      Aim

      To introduce the concepts of grid generation, including structured and unstructured approaches. To provide hands-on experience using commercial CAD and grid generation packages.

      Syllabus
      • Geometry Modelling and Surface Grids
      • Algebraic Mesh Generation
      • Structured Meshes from Partial Differential Equations
      • Automatic generation of Unstructured Meshes
      • Multiblock Mesh Generation
      • Unstructured grids by Delaunay Triangulation
      • Mesh Adaptation on Unstructured Grids
      • Unstructured Grids for Viscous Flows.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:
       

      • Demonstrate a systematic understanding of the requirements of grid generation for CFD applications
      • Critically evaluate alternative methods for efficiently generating computational grids
      • Demonstrate the systematic application of grid generation through structured single and multiblock grids with controlled grid quality by employing commercial grid generation packages
      • Demonstrate a systematic application of the generation of unstructured grids with controlled grid quality within commercial meshing packages.
    • Data Analysis, Data Fusion and Post Processing
      Aim

      To provide an introduction into the use of visualisation, data mining, and interactive human-computer interfaces for the analysis and interpretation of CFD simulations. Visualisation can be a critical component in helping an engineer gain insight into the typically complex optimisation problems that arise in design. Through the combination of visualisation and user interaction in computer tools, the engineer's insight can help guide the computer in the process of identifying better, more effective designs. Visualisation can also be combined with automated data mining techniques to improve optimisation procedures. To provide hands-on experience using both commercial and community developed visualisation packages.

      Syllabus
      • Data interchange formats
      • Interpretation of data
      • Graphical representation of data
      • Parallel data visualisation
      • Data mining, reduced order modelling, model identification and surrogate models
      • Data fusion
      • Virtual reality visualisation.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Demonstrate a systematic understanding of the alternative techniques for the visualisation and interpretation of CFD results
      • Apply commercial and community developed visualisation software packages to real CFD data
      • Critically evaluate the use of limited simulation data when making engineering decisions.
    • The Role of Experimental Data in CFD
      Aim

      To provide an introduction into practical techniques for experimental data collection and its subsequent post-processing. To contrast the resultant data representation with that obtained through CFD simulation.

      Syllabus
      • Introduction to the measurement of turbulent flows
      • Velocity and pressure measurement by aerodynamic probes
      • Velocity measurement by hot-wires/hot-film
      • Velocity measurement by optical techniques
      • Temperature measurement
      • Simple optical visualisation, Shadowgraph, Schlieren
      • Laser-based temperature and species measurements
      • Laser Induced Fluorescence
      • Skin friction, convective and radiative heat transfer
      • Error analysis.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Demonstrate a critical awareness of the alternative experimental methods available for the investigation of turbulent fluid flow
      • Demonstrate the ability to analyse and interpret quantitative and qualitative observations
      • Demonstrate a critical awareness of the relationship between the observations and the underlying theory
      • Critically interpret experimental data and contrast with that obtained from CFD simulations.

    Optional

    • CFD for Aerospace Applications
      Aim

      To understand the key features of CFD methods used for simulating external flows in aeronautical and aerospace applications.

      Syllabus
      • Overview of external flow problems in aeronautical and aerospace applications
      • CFD methods for subsonic, supersonic and hypersonic regimes
      • CFD methods for design
      • Application examples.
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:

      • Demonstrate a critical awareness of the range of external flow problems in aeronautical and aerospace applications in which CFD methods can be used
      • Demonstrate the systematic application of the key characteristics of CFD methods used in these sectors
      • Critically evaluate the limitations of these methods
      • Demonstrate a critical awareness of the current efforts made by industry and academia for improving the state-of-the-art methods in the above applications.
    • CFD for Micro and Nano Flows
      Aim

      To introduce micro- and nano- scale phenomena and CFD methods used for micro and nanoscale applications.

      Syllabus
      • Introduction to micro- and nano- scale phenomena
      • Areas of CFD application in micro- and nanoscience
      • Borderline continuum/molecular models and their domains of applicability
      • Multiscale modelling.
      Intended Learning Outcomes

      On successful completion of this module, students will be able to:

      • Demonstrate a critical awareness of the physical phenomena specific to flows at micro- and nano-scale
      • Critically evaluate applicability of continuum CFD to a particular problem
      • Demonstrate a critical awareness of the techniques that can be used at the borderline between continuum and molecular levels.
      • Demonstrate the systematic application of the concepts and current state-of-the-art methods involved in solving multiscale problems.
    • CFD for Rotating Wings
      Aim

      To introduce the numerical approaches required to meet the challenges of flows associated with rotating wings, including rotorcraft, propellers, wind turbines and
      turbomachinery.

      Syllabus
      • Introduction to rotary wing aerodynamics
      • Formulation of the governing equations in a rotating inertial frame of reference
      • Numerical approaches to vortex capturing
      • Blade dynamics as an example of fluid-structure interaction
      • Formulation of the governing equations for moving/deforming grids
      • Numerical modelling of dynamic stall.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Demonstrate a critical awareness of the modelling challenges faced in the numerical analysis of rotating wings
      • Demonstrate the systematic application of the Navier-Stokes equations in an appropriate rotating/moving frame of reference
      • Critically evaluate the different modelling approaches that can be taken for vortex dominated flows.
    • CFD for Automotive Flows
      Aim

      To show students how CFD may best be applied to a range of automotive flows.

      Syllabus
      • Application Areas for CFD in automotive engineering
      • Choice of CFD technique appropriate to the problem
      • CFD as a Complement to Experiment
      • High Performance Computing & Design Optimisation
      • Analysing Results.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Critically evaluate appropriate CFD methods for application to different automotive flow regimes
      • Demonstrate a critical awareness of how CFD can complement wind tunnel evaluation of vehicle models
      • Assess the value and limitations of applying CFD to vehicle designs.
    • CFD for Mutiphase Flows and Combustion
      Aim

      To introduce physics of multiphase flows and combustion as well as numerical methods for the simulation of multiphase and reacting flows. To provide examples of applications.

      Syllabus
      • Physical insight into multiphase and reacting flows
      • Governing equations and models for multiphase flows & combustion
      • Numerical methods for multiphase and reacting flows.
      • Particle tracking methods
      • Examples of applications.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Demonstrate a critical awareness of the basic principles of multiphase flows and combustion modelling
      • Critically assess achievements and limitations of current modelling and simulation approaches for multiphase flows and combustion
      • Demonstrate a systematic application of the models within commercial or in-house CFD packages.
    • CFD for Environmental Flows
      Aim

      To introduce the application of CFD to environmental flows in urban, inland and coastal environments.

      Syllabus
      • Atmospheric boundary layer
      • Pollution dispersion in the atmosphere
      • Rivers, estuaries and tidal flows
      • Sediment transport
      • Building and urban aerodynamics
      • Free-surface and shallow-water flows.
      Intended Learning Outcomes

      On successful completion of this course the student will be able to:

      • Critically assess the physical phenomena of environmental flows
      • Demonstrate a critical awareness of the choices to made when selecting the appropriate CFD model for different flow regimes
      • Demonstrate a systematic application of the models within commercial CFD packages.
    • CFD for Fluid-Structure Interaction
      Aim

      To introduce Fluid Structure Interaction (FSI) models and associated computational challenges. To provide examples of FSI problems arising in engineering applications.

      Syllabus
      • Introduction to FSI
      • Physical models (Classical models, Distinction between linear and nonlinear models), Time-linearised models, Nonlinear dynamical models, Reduced-order models
      • Computational challenges of FSI modelling
      • Examples of applications.
      Intended Learning Outcomes

      On successful completion of the module the student will be able to:

      • Demonstrate a critical awareness of the range of FSI problems in engineering applications where CFD methods can be applied
      • Demonstrate the knowledge of mathematical and numerical classification and properties of various numerical models used in FSI computations
      • Critically assess achievements and limitations of current modelling and simulation approaches by reference to practical examples.
  • Assessment

    The taught modules (50%) are assessed by an examination and/or assignment. The Individual Research Project (50%) is assessed by a thesis and oral presentation.

  • Start date, duration and location

    Start date: October

    Duration: 1 year full-time, 3 years part-time.

    Teaching location: Cranfield

  • Overview

    The MSc in Computational Fluid Dynamics at Cranfield provides a solid background so that you will be able to apply CFD methods as a tool for design, analysis and engineering applications. With a strong emphasis on understanding and application of the underlying methods, enthusiastic students will be able to write their own CFD codes during the course.

    Sharing some modules with the MSc in Aerospace Dynamics gives you the opportunity to interact with students from other disciplines. In recent years, our students have been had the opportunity for work-based placements at the Aircraft Research Association (ARA), European Space Agency (ESA) and DAF Trucks.

    Cranfield University is very well located for visiting part-time students from all over the world, and offers a range of library and support facilities to support your studies. This enables students from all over the world to complete this qualification whilst balancing work/life commitments. This Msc programme benefits from a wide range of cultural backgrounds which significantly enhances the learning experience for both staff and students.

  • Accreditation and partnerships

    This course is accredited by:

    • Royal Aeronautical Society (RAeS)
    • Institution of Mechanical Engineers (IMechE)
    • Engineering Council.
  • Informed by industry

    The Industrial Advisory Panel is comprised of senior industry professionals provides input into the curriculum in order to improve the employment prospects of our graduates. Panel members include:

    • Adrian Gaylord, Jaguar Land Rover (JLR)
    • Trevor Birch, Defence, Science and Technology Laboratory (DSTL)
    • Chris Fielding, BAE Systems
    • Anastassios Kokkalis, Voith
    • Stephen Rolson, EADS
    • Clyde Warsop, BAE Systems.
  • Your teaching team

    You will be taught by experienced academic staff from Cranfield University including:

    Our staff are active researchers as well as tutors, with clients that include AWE, NASA Jet Propulsion Laboratory, European Space Research and Technology Centre (ESTEC), Jaguar Land Rover, BAE Systems, MBDA, MoD and SEA. Our teaching team work closely with business and have academic and industrial experience. Knowledge gained working with our clients is continually fed back into the teaching programme, to ensure that you benefit from the very latest knowledge and techniques affecting industry.

    The course also includes visiting lecturers from industry who will relate the theory to current best practice. In recent years, our students have received lectures from industry speakers including:

    • Clyde Warsop, Executive Scientist , BAE Systems
    • Marco Hahn, Senior Project Scientist, ARA
    • Keith McKay, Consultant, ex-BAE Systems
    • Johnathan Green, Senior Project Manager, BMT Fluid Mechanics Ltd
    • Geoff Le Good, Managing Director, GL Aerodynamics
    • Adrian Gaylard, Technical Specialist - Aerodynamics, Jaguar Land Rover
    • Andy Wade, Technical Services CFD Team Leader, ANSYS
    • Richard Mitchell, Technical Services Structural Mechanics Team Leader, ANSYS
    • Matthew Sorrell, CFD Team Leader, Red Bull Technology.
  • Facilities and resources

    Students on the Computational Fluid Dynamics masters course benefit from a wealth of Cranfield’s excellent computational facilities, which provides students the opportunity to run large scale computational thesis projects. In addition to the excellent facilities, the staff at Cranfield conduct world leading research into CFD methods and analysis of fluid flows in applications, as diverse as nano-scale detectors through to hypersonic re-entry.

    Cranfield University offer a comprehensive library and information service, and are committed to meeting the needs of students, creating a comfortable environment with areas for individual and group work as well as silent study.

    Experience and familiarity with using the more specialist industry resources will be recognised and valued by future employers. Developing skills to make the most of our rich information environment at Cranfield is not only important to you whilst you are studying, it is also vital for your future employability and career progression.

  • Entry Requirements

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

    English language

    If you are an international student you will need to provide evidence that you have achieved a satisfactory test result in an English qualification. The minimum standard expected from a number of accepted courses are as follows:

    IELTS - 6.5

    TOEFL - 92 

    TOEIC - 800 (Important: this test is not currently accepted by the UK Home Office for Tier 4 (General) visa applications)

    Pearson PTE Academic - 65

    Cambridge English: Advanced - C

    Cambridge English: Proficiency - C

    In addition to these minimum scores you are also expected to achieve a balanced score across all elements of the test. We reserve the right to reject any test score if any one element of the test score is too low.

    We can only accept tests taken within two years of your registration date (with the exception of Cambridge English tests which have no expiry date).

    Students requiring a Tier 4 (General) visa will also need to meet the UKBA Tier 4 General Visa English language requirements. The UK Home Office are not currently accepting TOEFL or TOEIC tests for Tier 4 (General) visa applications. Other restrictions from the UK Home Office may apply from time to time and we will advise applicants of these restrictions where appropriate.

    ATAS Certificate

    Students requiring a Tier 4 General Student visa to study in the UK may need to apply for an ATAS certificate to study this course.

  • Fees

    Home/EU student

    MSc Full-time - £9,000

    *

    For taught courses where the registration is 2 years or longer, students will be offered the option of paying the full fee up front, or to pay in four equal instalments at six month intervals (i.e. the full fee to be paid over the first two years of their registration). For courses lasting less than two years, students will be offered the option of paying the full fee up front, or to pay in four equal instalments at three month intervals.

    MSc Part-time - £9,000 *

    PgDip Full-time - £7,200

    PgDip Part-time - £7,200 *

    PgCert Full-time - £3,600

    PgCert Part-time - £3,600 *

    Overseas student

    MSc Full-time - £17,500

    MSc Part-time - £17,500 *

    PgDip Full-time - £14,000

    PgDip Part-time - £14,000 *

    PgCert Full-time - £7,000

    PgCert Part-time - £7,000 *

    Fee notes:

    • The fees outlined here apply to all students whose initial date of registration falls on or between 1 August 2015 and 31 July 2016 and the University reserves the right to amend fees without notice.
    • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
    • Additional fees for extensions to registration may be charged.
    • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and the Isle of Man) pay Overseas fees.
  • Funding

    Bursaries towards tuition fees are available subject to qualifications. Please contact the Course Director for more information.

    Aerospace MSc Bursary Scheme - Course List

    Aerospace MSc Bursary Scheme - List of eligible courses available to study at Cranfield University.

    More
    Cranfield Postgraduate Loan Scheme (CPLS)

    The Cranfield Postgraduate Loan Scheme (CPLS) is a funding programme providing affordable tuition fee and maintenance loans for full-time UK/EU students studying technology-based MSc courses.

    More
  • Application process

    Online application form. Applicants may be invited to attend for interview. Applicants based outside of the UK may be interviewed either by telephone or video conference.

  • Career opportunities

    Strategic industrial links ensure that the course meets the needs of the organisations competing within the computational sector therefore making our graduates some of the most desirable in the world for companies to recruit.

    An increasing demand for CFD specialists with in depth technical knowledge and practical skills within a wide range of sectors has seen our graduates employed by leading companies including:

    • Alstom
    • BAE Systems
    • Rolls-Royce
    • European Space Agency
    • Bentley Motors.

    Roughly one third of our graduates go on to register for PhD degrees, many on the basis of their MSc individual research project. Thesis topics are often supplied by individual companies on in-company problems with a view to employment after graduation – an approach that is being actively encouraged by a growing number of industries.