This course has been designed to reflect the wide applications of Computational Fluid Dynamics. You will learn to understand, write and apply CFD methods across a wide broad range of fields, from aerospace, turbomachinery, multi-phase flow and heat transfer, to microflows, environmental flows and fluid-structure interaction problems. Tailor your course by choosing from a range of specialist modules covering application-specific methods and techniques.

At a glance

  • Start dateOctober
  • DurationFull-time MSc - one year, Part-time MSc - up to three years, Full-time PgCert - one year, Part-time PgCert - two years, Full-time PgDip - one year, Part-time PgDip - two years
  • DeliveryTaught modules 50%, Individual research project 50%
  • QualificationMSc, PgDip, PgCert
  • Study typeFull-time / Part-time

Who is it for?

Designed to meet the education needs of graduates and professional engineers who are looking to kick-start an industrial or research career in the rapidly growing field of Computational Fluid Dynamics. This course bridges the gap between the introductory level of undergraduate courses and the applied expertise acquired by engineers using CFD in industry. You will gain the knowledge and appreciation of CFD methods necessary for a strong foundation to a career in this exciting engineering discipline.

Why this course?

The MSc in Computational Fluid Dynamics 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.

Informed by Industry

Our strategic links with industry ensures that all of the materials taught on the course are relevant, timely and meet the needs of organisations competing within the computational analysis sector. This industry led education makes Cranfield graduates some of the most desirable for companies to recruit.

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 Gaylard, Jaguar Land Rover (JLR)
  • Trevor Birch, Defence, Science and Technology Laboratory (DSTL)
  • Chris Fielding, BAE Systems
  • Evgeniy Shapiro, Ricardo
  • Stephen Rolson, EADS
  • Clyde Warsop, BAE Systems
  • Peter Hall, MBDA
  • Chris Newbold, Qinetiq

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. Previously 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.


Accreditation

The MSc in Computational Fluid Dynamics is accredited by the Royal Aeronautical Society (RAes) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. The MSc in Computational Fluid Dynamics is alsio subject to ratification by the Institution of Mechanical Engineers (IMechE) following an accreditation assessment in June 2015.  Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to comply with full CEng registration requirements.

Course details

The taught modules are delivered from October to April via a combination of structured lectures, and computer based labs. 

The core part of the course consists of 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. 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.

Assessment

Taught modules 50%, Individual research project 50%

University Disclaimer

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the core modules and some optional modules affiliated with this programme which ran in the academic year 2016–2017. There is no guarantee that these modules will run for 2017 entry. All modules are subject to change depending on your year of entry.

Core modules

Introduction to Fluid Mechanics and Heat Transfer

Module Leader
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

Module Leader
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

Module Leader
  • Dr Laszlo Konozsy
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

Module Leader
  • Tsoutsanis, Dr Panagiotis P.
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

Module Leader
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

Module Leader
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

Module Leader
  • Antoniadis, Dr Antonios A.F.
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

Module Leader
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

Module Leader
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

Module Leader
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

Module Leader
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

Module Leader
  • Tsoutsanis, Dr Panagiotis P.
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

Module Leader
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

Module Leader
  • Antoniadis, Dr Antonios A.F.
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

Module Leader
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

Module Leader
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

Module Leader
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

Module Leader
  • Rana, Dr Zeeshan Z.A.
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.

Fees and funding

European Union students applying for university places in the 2017 to 2018 academic year and the 2018 to 2019 academic year will still have access to student funding support. Please see the UK Government’s announcement (21 April 2017).

Cranfield University welcomes applications from students from all over the world for our postgraduate programmes. The Home/EU student fees listed continue to apply to EU students.

MSc Full-time £9,000
MSc Part-time £9,000 *
PgDip Full-time £7,200
PgDip Part-time £7,200 *
PgCert Full-time £4,000
PgCert Part-time £4,000 *
  • * Students will be offered the option of paying the full fee up front, or in a maximum of two payments per year; first instalment on receipt of invoice and the second instalment six months later.  

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2017 and 31 July 2018.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A deposit may be payable, depending on your course.
  • Additional fees for extensions to the agreed registration period may be charged and can be found below.
  • 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 Isle of Man) pay Overseas fees.

For further information regarding tuition fees, please refer to our fee notes.

MSc Full-time £18,500
MSc Part-time £18,500 *
PgDip Full-time £15,000
PgDip Part-time £15,000 *
PgCert Full-time £7,500
PgCert Part-time £7,500 *
  • * Students will be offered the option of paying the full fee up front, or in a maximum of two payments per year; first instalment on receipt of invoice and the second instalment six months later.  

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2017 and 31 July 2018.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A deposit may be payable, depending on your course.
  • Additional fees for extensions to the agreed registration period may be charged and can be found below.
  • 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 Isle of Man) pay Overseas fees.

For further information regarding tuition fees, please refer to our fee notes.

Funding Opportunities

To help students find and secure appropriate funding, we have created a funding finder where you can search for suitable sources of funding by filtering the results to suit your needs. Visit the funding finder.

Conacyt (Consejo Nacional de Ciencia y Tecnologia)
Cranfield offers competitive scholarships for Mexican students in conjunction with Conacyt (Consejo Nacional de Ciencia y Tecnologia) in science, technology and engineering.

Postgraduate Loan from Student Finance England
A Postgraduate Loan is now available for UK and EU applicants to help you pay for your Master’s course. You can apply for a loan at GOV.UK

Santander MSc Scholarship
The Santander Scholarship at Cranfield University is worth £5,000 towards tuition fees for full-time master's courses. Check the scholarship page to find out if you are from an eligible Santander Universities programme country.

Chevening Scholarships
Chevening Scholarships are awarded to outstanding emerging leaders to pursue a one-year master’s at Cranfield university. The scholarship includes tuition fees, travel and monthly stipend for Master’s study.

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.

Commonwealth Scholarships for Developing Countries
Students from developing countries who would not otherwise be able to study in the UK can apply for a Commonwealth Scholarship which includes tuition fees, travel and monthly stipend for Master’s study.

Future Finance Student Loans
Future Finance offer student loans of up to £40,000 that can cover living costs and tuition fees for all student at Cranfield University.

Erasmus+ Student Loans
This new loan scheme for EU students is offered by Future Finance and European Investment Fund and provides smart, flexible loans of up to £9,300.

Entry requirements

A first or second class UK Honours degree or equivalent in mathematics, physics, computing or an engineering discipline.

Applicants who do not fulfil the standard entry requirements can apply for the Pre-Masters programme, successful completion of which will qualify them for entry to this course for a second year of study.

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. Our minimum requirements are as follows:

IELTS Academic – 6.5 overall
TOEFL – 92
Pearson PTE Academic – 65
Cambridge English Scale – 180
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 must ensure they can meet the English language requirements set out by UK Visas and Immigration (UKVI) and we recommend booking a IELTS for UKVI test.

Applicants who do not already meet the English language entry requirement for their chosen Cranfield course can apply to attend one of our Presessional English for Academic Purposes (EAP) courses. We offer Winter/Spring and Summer programmes each year to offer holders.


Your career

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
  • Cummins Turbo Technology
  • BHR
  • ESTEC
  • Hindustan Aeronautics Ltd
  • NUMECA
  • ONERA
  • Rio Tinto
  • Rolls-Royce plc
  • Siemens.

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.

Applying

Online application form. UK students are normally expected to attend an interview and financial support is best discussed at this time. Overseas and EU students may be interviewed by telephone.

Apply Now