Computer Aided Engineering (CAE) covers the use of computers in all activities from the design to the manufacture of a product. It is at the forefront of information technology and of crucial importance to economies around the world. It is a vital part of many global industries including those of automotive, aerospace, oil, defence, finance and health. 

This specialist option of the MSc Computational and Software Techniques in Engineering has been developed to reflect the wide application of CAE and to deliver qualified engineers of the highest standard into industries operating in the fields of computational and software engineering.


  • Start dateSeptember
  • Duration1 year full-time, 2-3 years part-time.
  • DeliveryTaught modules 45%, Group project 5%, Individual research project 50%<br>
  • QualificationMSc
  • Study typeFull-time / Part-time
  • CampusCranfield campus

Who is it for?

Suitable for candidates from a broad range of engineering and applied mathematical backgrounds, including aeronautic, automotive, mechanical and electrical engineering, in addition to those with a mathematical and computational sciences training, who wish to both develop and complement their existing skill-set in these important areas.

The specialist taught modules are designed to provide you with the knowledge, programming techniques and practical skills necessary to develop and use core CAE solution software over a wide range of industrial settings.

Why this course?

We are a leader in applied mathematics and computing applications. The CAE option benefits from the knowledge and experience gained by the staff through their strong industrial links, particularly our well-established research collaborations with the petrochemical, automotive, aeronautical and financial sectors.

This course produces well qualified graduates, ready to take on professional roles without additional training on the job. In recent years, key employers have requested a student visit to showcase their graduate roles.

This course is also available on a part-time basis, enabling you to combine studying alongside full-time employment. We are very well located for visiting part-time students from across the UK and Europe.

Informed by Industry

This course is directed by an industrial advisory panel who meet twice a year to ensure that it provides generic hands-on skills and up-to-date knowledge adaptable to the wide variety of applications that this field addresses.

A number of members also attend the annual student thesis presentations which take place at the end of July, a month or so before the end of the course. This provides a good opportunity to meet key employers.

Industry Advisory Panel members include:

  • Dr Adam Vile, Excelian
  • Mr Darren Baldwin, Excelian
  • Mr Matthew Breach, Ultra Electronics Sonar Systems
  • Mr Nigel Sedgewick, Selex
  • Dr Sanjiv Sharma, Airbus UK
  • Dr Steve King, Rolls Royce
  • Dr Julian Turnbull, Black and Veatch
  • Mr Jon Loach, FACTSET
  • Prof David Emerson  (Scientific Computing, STFC Daresbury )
  • Dr Stuart Barnes (Software Engineer, Cambridge).

Course details

The course consists of twelve core modules, including a group design project, plus an individual research project. A combination of mathematical, computational and hands-on use of industry standard CAE systems form the basis of the specialist modules, covering the theory and application of CAE based software for the modelling, analysis and simulation, in diverse fields such as automotive, aeronautical, flow related industries, data fitting and visualisation.

Group project

The process of software production is rarely an activity undertaken by an individual developer. In today’s software industry, many different specialists are required to contribute to the creation of software. To ensure a high level of quality in the final product, different roles and responsibilities must be brought together into a single team and therefore clear lines of communication between team members are crucial if the project is to be a success.

The group design project is intended to give you invaluable experience of delivering a project within an industry structured team. The project allows you to develop a range of skills including learning how to establish team member roles and responsibilities, project management, delivering technical presentations and gaining experience of working in teams that include members with a variety of expertise and often with members who are based remotely.

Part-time students are encouraged to participate in a group project as it provides a wealth of learning opportunities. However, an option of an individual dissertation is available if agreed with the Course Director.

Previous Group Projects have included:

  • Component Stress Analysis
  • Steel Tube Joints Flow Study.

Individual project

The individual research project allows you to delve deeper into an area of specific interest. It is very common for industrial partners to put forward real world problems or areas of development as potential research project topics. For part-time students it is common that their research project is undertaken in collaboration with their place of work.

Previous Individual Research Projects have included:

  • Analysis of Aircraft Control Surface
  • Comparative Analysis of Parallel Performance and Scalability of Incompressible CFD Solvers
  • Automated Workflow for a Car Roof-box Optimisation
  • Design Optimisation of Helical Gear Pair in Helicopter Transmission Systems
  • Design and Analysis of an Adjustable Rear View Car Spoiler
  • Surfboard Modelling Using CFD
  • Displacement Mapping Using Splines.
  • Aircraft Fuel System Failure Detection.


Taught modules 45%, Group project 5%, Individual research project 50%


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 compulsory modules and (where applicable) some elective modules affiliated with this programme which ran in the academic year 2018–2019. There is no guarantee that these modules will run for 2019 entry. All modules are subject to change depending on your year of entry.

Compulsory modules
All the modules in the following list need to be taken as part of this course

C Programming (pre-requisite)


    The module aims to cover all the main elements making up the C programming language and to provide many illustrative examples of their use in practice. Use is made of ‘hands-on’ workshops which enable the student to gain confidence with the language and form a preparation for the practical assignment which forms a major part of the course. An Ansi-standard C compiler and development environment is employed.

    • Variables, operators and expressions
    • Statements and flow control
    • Functions
    • Pointers and arrays
    • Strings
    • Structures and other derived types
    • Dynamic memory
    • Allocation
    • Input and output.
Intended learning outcomes

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

  • Demonstrate a good understanding of the main elements making up a procedural language
  • Use functions, pointers and structures in the C language
  • Write a C program of moderate complexity given a formal specification
  • Understand the concept of dynamic memory allocation and be able to use it in practical applications
  • Apply knowledge and skills to the implementation of advanced data structures in the C language.

Computational Methods

Module Leader
  • Dr Irene Moulitsas

    The module aims to provide an understanding of a variety of computational methods for integration, solution of differential equations and solution of linear systems of equations.


    The module explores numerical integration methods; the numerical solution of differential equations using finite difference approximations including formulation, accuracy and stability; matrices and types of linear systems, direct elimination methods, conditioning and stability of solutions, iterative methods for the solution of linear systems.

Intended learning outcomes On successful completion of this module a student should be able to:
1. Implement and use numerical integration methods.
2. Use appropriate techniques to formulate numerical solutions to differential equations.
3. Evaluate properties of numerical methods for the solution of differential equations.
4. Choose and implement appropriate methods for solving differential equations.
5. Evaluate properties of systems of linear equations.
6. Choose and implement appropriate methods for solving systems of linear equations.
7. Evaluate the behaviour of the numerical methods and the numerical solutions.

C++ Programming

Module Leader
  • Dr Irene Moulitsas

    Object oriented programming (OOP) is the standard programming methodology used in nearly all fields of major software construction today, including engineering and science and C++ is one of the most heavily employed languages. This module aims to answer the question ‘what is OOP’ and to provide the student with the understanding and skills necessary to write well designed and robust OO programs in C++. Students will learn how to write C++ code that solves problems in the field of computational engineering, particularly focusing on techniques for constructing and solving linear systems and differential equations. Hands-on programming sessions and assignment series of exercises form an essential part of the course.
    An introduction to the Python language is also provided.

    • The OOP methodology and method, Classes, abstraction and encapsulation;
    • Destructors and memory management, Function and operator overloading, Inheritance and aggregation, Polymorphism and virtual functions, Stream input and output;
    • Templates, Exception handling, The C++ Standard Library and STL.
Intended learning outcomes

On successful completion of this module a student should be able to:

1. Apply the principles of the object oriented programming methodology - abstraction, encapsulation, inheritance and aggregation - when writing C++ programs.
2. Create robust C++ programs of simple to moderate complexity given a suitable specification.
3. Use the Standard Template Library and other third party class libraries to assist in the development of C++ programs.
4. Solve a range of numerical problems in computational engineering using C++.
5. Use development environments and associated software engineering tools to assist in the construction of robust C++ programs.
6. Evaluate existing C++ programs and assess their adherence to good OOP principles and practice.

Computer Graphics

Module Leader
  • Dr Karl Jenkins

    Computer graphics is a key element in the effective presentation and manipulation of data in engineering software. The aim of this module is to provide an in depth overview of the mathematical and software principles behind 2D and 3D visualisation, the viewing pipeline, and practical implementation in the widely used OpenGL graphics library. Representative GUI based 2D and 3D OpenGL applications using the Windows environment are used. Reference is also made to the programming model employed in OpenGL-ES, the version of OpenGL created for embedded devices and the basis for Android and iPhone apps. Hands-on exercises and an assignment supplement the learning process.

    • Mathematical principles behind 2D and 3D visualisation, Matrix transformations, The viewing pipeline, Modelling, viewing and projection, OpenGL graphics library, GLSL and shader programming.
    • Development of CG applications using OpenGL, GLSL and Qt, UI
    • WebGL, OpenGL-ES.

Intended learning outcomes On successful completion of this module a student should be able to:
1. Apply the principles of the viewing pipeline to compute device coordinates from a suitable ‘world coordinate system’ model.
2. Use the mathematical basis behind 2D/3D modelling and viewing to solve visualisation problems in OpenGL.
3. Understand, write and use basic shader programs using GLSL
4. Create simple interactive computer graphics based applications using OpenGL, GLSL (the shading language) and Qt.
5. Evaluate the major differences between the different version of OpenGL.

Management for Technology

    The importance of technology leadership in driving the technical aspects of an organisations products, innovation, programmes, operations and strategy is paramount, especially in today’s turbulent commercial environment with its unprecedented pace of technological development. Demand for ever more complex products and services has become the norm.  The challenge for today’s manager is to deal with uncertainty, to allow technological innovation and change to flourish but also to remain within planned parameters of performance.  Many organisations engaged with technological innovation struggle to find engineers with the right skills.  Specifically, engineers have extensive subject/discipline knowledge but do not understand management processes in organisational context.  In addition, STEM graduates often lack interpersonal skills.
    • Engineers and Technologists in organisations: The role of organisations and the challenges facing engineers and technologies.
    • People management: Understanding you. Understanding other people. Working in teams. Dealing with conflicts.
    • The Business Environment: Understanding the business environment; identifying key trends and their implications for the organisation.
    • Strategy and Marketing: Developing effective strategies; Focusing on the customer; building competitive advantage; The role of strategic assets.
    • Finance: Profit and loss accounts. Balance sheets. Cash flow forecasting.Project appraisal.
    • New product development: Commercialising technology. Market drivers. Time to market. Focusing technology. Concerns.
    • Business game: Working in teams (companies), students will set up and run a technology company and make decisions on investment, R&D funding, operations, marketing and sales strategy.
    • Negotiation: Preparation for Negotiations. Negotiation process. Win-Win solutions.
    • Presentation skills: Understanding your audience. Focusing your message. Successful presentations. Getting your message across.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Recognise the importance of teamwork in the performance and success of organisations with particular reference to commercialising technological innovation.
  • Operate as an effective team member, recognising the contribution of individuals within the team, and capable of developing team working skills in themselves and others to improve the overall performance of a team.
  • Compare and evaluate the impact of the key functional areas (strategy, marketing and finance) on the commercial performance of an organisation, relevant to the manufacture of a product or provision of a technical service.
  • Design and deliver an effective presentation that justifies and supports any decisions or recommendations made
  • Argue and defend their judgements through constructive communication and negotiating skills.

Geometric Modelling and Design

Module Leader
  • Dr Karl Jenkins
    The aim of this module is to provide the student with the knowledge and practice of the mathematical techniques and the principal algorithms used for the construction and implementation of parametric curve, surface and solid geometry. The material covered here forms the basis of free-form modelling as used in all major CAD/CAM systems and, more generally, in the fields of visualisation and computer graphics. Hands-on programming exercises and a modelling assignment form part of the course.
    Wireframe, surface and solid geometry, Polynomial and spline interpolation, B-spline curve and surface interpolation and approximation, Some advanced modelling techniques, Solid model representation schemes, Boundary representation models.
Intended learning outcomes On successful completion of this module a student should be able to:
1. Solve a range of basic numerical problems in B-spline curve and surface data fitting and modelling.
2. Apply B-spline curve and surface theory and algorithms to the construction of data fitting programs in a CAD modelling setting.
3. Use the mathematical and computational techniques deployed in the creation of 3D geometric modelling software to extend existing implementations.
4. Evaluate a CAD system in terms of the range of free-form modelling operations offered.
5. Use the principles behind solid model representation schemes to judge the capabilities of a solid modeller.

CAE Applications and PLM

Module Leader
  • Dr Karl Jenkins
    The aim of the CAE Solid Modelling module is to introduce students to key concepts, techniques and applications of a 3D Solid Modelling system. Use is made of structured computer based workshops which employ an industry standard system (CATIA) for 3D Solid Modelling. Introductory lectures are reinforced by the ‘hands-on’ approach through a series of part, assembly and surface modelling exercises covering the major workbenches available in the CAD system.
    • Introduction to CATIA CAE Solid Modelling Software,
    • Some benefits of using solid modelling and the CAE approach,
    • Different construction methods for 3D geometrical models,
    • Parametric and variational design,
    • Production of drafting setup details from 3D geometrical parts,
    • Modifying parts and features,
    • Part, Assembly and Surface Modelling workbenches
Intended learning outcomes On successful completion of this module a student should be able to:
1. Create solid geometrical parts using a variety of fundamental CAD construction techniques including parametric and variational design/.
2. Apply skills necessary to carry out a variety of Solid Modelling tasks.
3. Use drafting tools to generate 2D drawings from 3D geometrical parts.
4. Evaluate a CAE Solid Modelling tool in terms of the range of solid and surface construction techniques offered.
5. Build CAD models of reasonable complexity from a given specification using a combination of part, assembly and surface modelling techniques

Advanced Engineering Analysis

Module Leader
  • Dr Karl Jenkins
    The numerical solutions of partial differential equations are used for simulating physical systems and phenomena and for the investigation of a wide range engineering applications. These numerical solutions may used in engineering design optimisation to explore the implications of design changes. The aim of this course is to provide the student with the mathematical background to the discretisation of partial differential equations using finite element and finite difference approaches, and an insight into methods for their solution along with the vital numerical techniques for the analysis of the solution and numerical errors.

    • Introduction to Simulation, Finite Element Methods, Finite Difference Methods,
    • Numerical Solution to Partial Differential Equations: Parabolic, Elliptic, Hyperbolic
    • Stability Analysis and Truncation Errors, Case Studies
Intended learning outcomes On successful completion of this module a student should be able to:
1. Understand the mathematical principles of the discretisation methods.
2. Identify problems which are suitable for finite element or finite difference solution.
3. Demonstrate a working knowledge of numerical solution methods.
4. Demonstrate an understanding of stability analysis and numerical errors.

Computational Engineering (Fluids)

Module Leader
  • Dr Karl Jenkins
    To introduce the techniques and tools for modelling, simulating and analysing realistic computational engineering problems for industrial applications with practical hands on experience of commercial software packages used in industry.

    • Introduction to Computational Engineering
    • Fundamental equations
    • The Computational Engineering Process
    • Fluid Simulation for Computer Graphics
    • Modelling techniques
    • Practical sessions
Intended learning outcomes On successful completion of this module a student should be able to:
1. An understanding of the Computational Engineering Process.
2. Understand the governing equations for fluid systems and how to solve them computationally.
3. Be able to write code to solve problems and undertake practical problems using commercial software
4. Appreciate the wide range of applications using computational engineering for fluids.

CAE Advanced Applications


    This course covers more advanced aspects of CAE, the aim being to introduce students to key concepts and techniques in the use of CAE application software tools. Use is made of structured computer based workshops which employ industry standard systems for CAD through to Engineering Analysis.

    • Introduction to I-DEAS CAE Finite Element Analysis (FEA) Simulation software
    • CAE FEA Pre- and Post- Processing
    • Free mesh and Mapped mesh techniques
    • Quality checks on nodes and elements
    • Finite element and geometry based boundary conditions
    • Utilising solids based modelling geometry for downstream CAE FEA
    • CAE linear statics analysis using the I-DEAS CAE FEA Simulation software
    • Case Studies.
Intended learning outcomes

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

  • Demonstrate an understanding of how modern CAE Analysis tools are used
  • Use free mesh and mapped mesh generation techniques
  • Generate finite element analysis models by using either geometry from the I-DEAS solid modeller or an external CAD system.
  • Use the I-DEAS Simulation Analysis module to run linear static analysis modules.

Advanced Graphics

Module Leader
  • Dr Karl Jenkins

    High performance computer graphics are used in many areas of software application development, and are fundamental to games, entertainment, CAD and scientific visualisation. The aim of this module is to introduce students to the advanced techniques used in the generation of computer graphics. Building on the basic methods of the Introductory course, students will learn how to generate more realistic effects, such as the use of lighting and surface details to create realistic representations of computer generated graphical objects and display them to the screen.

    Surfaces and Tessellation, Geometric and Raster Algorithms, Light, Illumination and Shading, Texture Mapping, Bump Mapping, Displacement Mapping, Environment Mapping, Introduction to Virtual Reality.
Intended learning outcomes On successful completion of this module a student should be able to:
1. Understand the concepts, underlying principles and operation of a range of advanced computer graphics algorithms and techniques;
2. Optimize the graphics pipeline by implementing surface algorithms, such as surface tessellation and rendering, leading to real-time performance;
3. Understand the models of interaction between light and materials, as well as being able to demonstrate a practical capability of implementing such methods;
4. Implement algorithms using the OpenGL graphics library and GLSL and apply these techniques to solving a specific problem in computer graphics.

Applications of Computational Engineering Design Optimisation - Group Project

Module Leader
  • Dr Karl Jenkins
    This module aims to provide the student with the mathematical, programming and computational skills used in solving a practical engineering design optimisation problem so that they can undertake a group project.
    • Specification of optimisation problem - design parameters, objective function, constraints 
    • Geometry construction – curve/surface fitting, product data exchange, CAD modelling
    • Algorithm implementation - monte carlo (or other) archiving strategy, quality measure extraction
Intended learning outcomes On successful completion of this module a student should be able to:
1. Create an optimisation model to solve a specified design problem.
2. Evaluate the features of an optimisation model and assess the qualities of the solution obtained.
3. Apply the principles of B-spline curve and surface creation and CAD modelling techniques to the generation of surface/solid geometry starting from a point data set and/or suitable mathematical formulae.
4. Use a number of programming and CAD based tools, including data exchange, to assist the design optimisation process.
5. Communicate clearly in terms of written reports, project meetings and presentations to specialist and non-specialist audiences.
6. Practice good teamwork coordination, negotiation and interfacing skills.

Teaching team

Cranfield University is a leader in applied mathematics and computing applications, and you will be taught by experienced Cranfield staff including: Our staff are practitioners as well as tutors, with clients that include: Airbus Conoco Phillips Siemens TATA Motors. Our teaching team work closely with business and have academic and industrial experience.Knowledge gained working with our clients and partners 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 and academia who will relate the theory to current best practice. In recent years, students on the CAE option have received lectures from external speakers including: Dr Steve King, Rolls-Royce Dr Terry Hewit, University of Manchester.

Your career

The Computer Aided Engineering option is designed to equip you with the skills required to pursue a successful career working both in the UK and overseas. This course attracts enquiries from companies in rapidly expanding engineering IT industry sector across the EU and beyond who wish to recruit high quality graduates.

There is considerable demand for students with expertise in engineering software development and for those who have strong technical programming skills in industry standard languages and tools.

Typically our graduates are employed by software houses and consultancies, or by CAD/CAM and other engineering companies in software development roles and industrial research.  

A selection of companies that have recruited our graduates include:

  • Design Manager, Hindustan Aeronautics Ltd
  • Financial Software Developer, Bloomberg
  • Research Engineer, Moodstocks SAS
  • PLM Consultant, PCO Innovation
  • Software Developer, CAE Engineering
  • Computer Science Engineer, Sopra Group
  • IT Archietecture Consultant, Solucom
  • Asset Management Engineering, EON UK
  • Mathematical Software Engineer, Arithmetica Ltd
  • Analyst, Morgan Stanley.

How to apply

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.