This course addresses the design, development, procurement, use and management of models and simulations for applications in experimentation, training, testing, analysis and assessment of military forces, systems and equipment.

The application of Modelling and Simulation continues to enhance and transform both systems development and training. It allows representation of increasingly complex equipment, systems and scenarios for the purposes of decision support and helps to reduce wear on live equipment and on test and training areas.

Overview

  • Start dateSeptember
  • DurationMSc - One year full-time, up to five years part-time. PgDip: Up to one year full-time, up to four years part-time. PgCert: Up to one year full-time, up to three years part-time
  • DeliveryAssessment is 50% by coursework, 10% by exam and 40% thesis/dissertation
  • QualificationMSc, PgDip, PgCert
  • Study typeFull-time / Part-time
  • CampusCranfield University at Shrivenham

Who is it for?

The course is suitable for both military and civilian personnel, including those from defence industry and government departments.

Ten places are normally available for the full-time cohort.

Why this course?

On successful completion of the course you will be familiar with the technologies, methodologies, principles and terminology of modelling and simulation as used across defence, including the challenges and issues as well as the benefits. Through use of facilities such as the Simulation and Synthetic Environment Laboratory (SSEL), with its wide range of specialist applications, students will gain a broad understanding of modelling and simulation in areas such as training, acquisition, decision-support, analysis and experimentation.

Informed by Industry

The aim of the Industrial Advisory Panel, which is common to all components of the AMOR Postgraduate Suite (which comprises the DSM and MOR courses) is to offer advice and input to the course director and the teaching team in terms of curriculum content, acquisition skills and other attributes that the practitioner community may be seeking from graduates of the course. Currently the Industrial Advisory Panel for this programme has members on it from both the defence industry and the MOD.

Course details

Standard modules normally comprise a week of teaching (or equivalent for the limited distance learning options available), followed by a further week of directed study/coursework (or equivalent for part-time and distance learning). 

Advanced modules, which enable students to explore some areas in greater depth, are two week (or equivalent for part time) individual mini-projects on an agreed topic in that subject which includes a written report and oral presentation. MSc students must complete a taught phase consisting of eight standard modules, which includes two core modules (Foundations of Modelling and Simulation and Networked and Distributed Simulation), plus four advanced modules, followed by an individual thesis in a relevant topic. 

Individual project

An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.

Thesis topics will be related to problems of specific interest to students and sponsors of local industry wherever possible. PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis. PgCert students must complete the core module (Foundations of Modelling and Simulation) together with five other modules; up to three of these may be advanced modules. Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.

Assessment

Assessment is 50% by coursework, 10% by exam and 40% thesis/dissertation

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 compulsory modules and (where applicable) some elective modules affiliated with this programme which ran in the academic year 2017–2018. There is no guarantee that these modules will run for 2018 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

Introductory Studies

Module Leader
  • Dr John Salt
Aim

    To prepare students mathematically and organisationally to study at CDS on the Defence Simulation and Modelling and Military Operational Research Postgraduate programs.




Syllabus
    Course structure,
    intro to IT (email, VLE, online access),
    library introduction and referencing,
    mathematics: probability, statistics, differentiation, integration and matrices,
    introduction to Matlab,
    introduction to fundamentals of computing.
Intended learning outcomes On successful completion of this module a student should be able to:

explain the DSM and MOR Course Structure, it’s modules and assessments,
understand the facilities available at CDS to support student study -  including Library and IT as well as specialist resources such as the Simulation and Synthetic Environment Laboratory (SSEL),
understand how to search and reference material for future assignments,
understand the process for submitting assignments,
understand the fundamental mathematics required for the DSM and MOR courses,
demonstrate the basic concepts of Matlab including the performance of arithmetic and basic matrices operators, produce simple line plots and save sets of commands.
 

Foundations of Modelling and Simulation

Module Leader
  • John Hoggard
Aim

    To make students aware of the roles, concepts and applications of modelling and simulation in defence, and to understand how to construct simple models.



Syllabus
    The General Principles of Modelling and Simulation

    The verification and validation of defence models and simulations. The acquisition, operation and evolution of defence models and simulations. Hard and soft approaches to modelling. Deterministic and stochastic models. Monte Carlo simulation. The role of modelling and simulation in supporting defence decision-making.

    Continuous and Discrete Event Simulation

    The design and application of simple discrete event simulation models. An introduction to system dynamics models.

    Synthetic Environments

    An introduction to defence synthetic environments. The technologies of live, constructive and virtual simulation and their defence applications.
     
Intended learning outcomes On successful completion of this module a student should be able to:

explain and apply the general principles of modelling and simulation and to explain the importance of modelling and simulation in supporting defence decision-making,
apply the ideas of verification and validation to defence models and explain the issues involved,
design simple simulation models using different approaches,
explain the technologies of live, constructive and virtual simulation and their defence applications.
 

Networked and Distributed Simulation

Module Leader
  • Jonathan Searle
Aim
    To enable students to appreciate the main ways in which defence simulation systems make use of networking technology. The emphasis of the module is on the use by simulations of TCP/IP style LANs (Local Area Networks) and WANs (Wide Area Networks) with particular reference to the design, construction, integration, testing, operation and use of integrated and interoperable networks of fully distributed systems and components which form the basis of Live Virtual Constructive (LVC) defence Synthetic Environments.
Syllabus
    Fundamentals of computer communications, networking, LANs and WANs,
    main hardware components of computer networks,
    ISO-OSI Architecture and network protocols (eg TCP/IP),
    features and facilities of TCP/IP and their relevance to simulation systems,
    networked and distributed simulation architectures,
    simulation, interoperability and composability,
    the design, management, configuration and testing of distributed simulation components, systems and networks,
    networking interoperability standards in defence simulation (eg DIS, HLA),
    practical experiments and case studies.
Intended learning outcomes On successful completion of this module a student should be able to:

• recognise and recommend network strategies and architectures appropriate to the needs of a particular simulation system,
• carry out simple network configuration and testing functions using standard network tools,
• demonstrate an understanding of the issues and processes of simulation interoperability,
• appreciate and explain the issues in the design and application of Synthetic Environments in the defence arena.

Discrete and Continuous Simulation

Module Leader
  • Dr Ken McNaught
Aim

    The aim of the course is to provide students with a good understanding of the principles underlying both discrete event simulation (DES) and continuous simulation, focusing, in the latter case, on System Dynamics (SD) modelling.



Syllabus

    Simulation modelling paradigms,
    conceptual models (activity cycle diagrams, causal loop diagrams and stock/flow diagrams),
    input modelling (the selection and fitting of appropriate probability distributions for stochastic simulations),
    output analysis (methods for comparing and analysing the results of simulation experiments),
    discrete event simulation principles and types of software,
    developing and experimenting with Discrete Event Simulation models using an appropriate software package (currently SIMUL8),
    system dynamics principles,
    developing and experimenting with system dynamics models using an appropriate software package (currently Vensim).

     

     

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

describe the origins and the main principles underlying both DES and SD,
develop conceptual models of systems prior to their simulation,
identify feedback loops within an SD model and understand the effects of positive and negative feedback,
distinguish between the different types of variables commonly used in SD models,
develop an SD model from an appropriate diagram,
select appropriate probability distributions for use in stochastic simulations,
develop a DES model of a simple system,
perform appropriate experiments, policy analysis and output analysis with the completed simulation model.
 

War Gaming and Combat Modelling

Module Leader
  • Jeremy Smith
Aim
    To provide students with a general knowledge of the techniques used in wargaming, combat simulations and analytical battle models.
Syllabus
    Introduction: An introduction to the methods used in combat modelling and their application in support of defence decision making and training.

    Combat Simulation: The basic principles of discrete event Monte Carlo simulations of combat illustrated through the use of a simple engagement model. Extension of the concepts to allow more realistic representation of the battlefield. Aggregated models of combat.

    Lanchester’s Equations: The deterministic and stochastic Lanchester equations for direct and indirect fire as used for both homogeneous and heterogeneous forces. The application of Lanchester’s equations in current models of combat.

    War Gaming/lnteractive Simulation: The underlying principles of war gaming and the interactive simulation of combat as used for the assessment, testing and training of military forces and their equipment. The synthetic battlefield. Synthetic Environments: Constructive, virtual and live simulations of combat. Manual Combat Wargames. Other gaming techniques.

    War Gaming and Combat Modelling Practicals: The practical application of war gaming and combat modelling with issues such as : data and scenarios, terrain modelling, com- bat algorithms (attrition and movement), the representation of human factors, measures of effectiveness, the verification and validation of combat models, automated forces, simulation for training and distributed simulation.
     

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

critically appraise the full range of wargames and combat simulations and apply them to defence problems,
use the deterministic and stochastic Lanchester equations to represent combat between both homogeneous and heterogeneous forces,
use interactive computer based representations of military operations,
explain how the different methods of representing the operations of military forces are used in the training, testing and assessment of those forces and their equipment.
 

Computer Graphics

Module Leader
  • John Hoggard
Aim
    To enable students to gain an understanding of the methods and applications of 3D computer graphics.
Syllabus
    Coordinate systems and transforms,
    geometric modelling,
    rendering techniques,
    graphics application programming,
    real-time virtual environments,
    graphics hardware and architectures,
    serious games technologies,
    applications of computer graphics.
Intended learning outcomes On successful completion of this module a student should be able to:

demonstrate an understanding of the fundamental representations, techniques and processes underpinning 3D computer graphics,
describe the role of graphics programming libraries,
discuss the different techniques for creating and rendering scenes, and identify those relevant to given applications,
demonstrate an understanding of the issues in specifying and designing real- time computer graphics systems, with particular reference to interactive virtual environments,
demonstrate an understanding of the tools and methods used in creating scene content, including 3D object and terrain modelling,
discuss uses of computer graphics relevant to student’s area of interest.
 

Experimentation Analysis and Trials for Simulation

Module Leader
  • Jeremy Smith
Aim

    To provide students with the skills to design, manage, analyse and assess simulation based trials in support of training, experimentation and acquisition.

Syllabus

    Experimental design including sampling and ethical considerations,
     methodology and analysis of statistical data (inference, ANOVA and regression),
     definition, execution, analysis, present and critical assessment of simulation based experimentation and trials reports,
     visiting speakers from MOD and defence industry to include:
    o Operational Analysis (OA),  o Integrated Test Evaluation and Acceptance,  o Simulation Experimentation.

     




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

describe the place and utility of simulation based experimentation and trials within Defence Core Business,
critically assess the design, planning and execution of simulation based experimentation and trials and the analysis of results,
critically assess the impact of experimentation and trial constraints on the data collection and analysis methods used,
using simple Operational Research techniques, calculate appropriate ways to combine or balance multiple variables and benefits in a simulation based experimentation and trials context,
appropriately quantify and graph the results of an experiment or trial and statistically analyse these results in relatively simple cases,
develop effective methods to design, perform, analyse and report a simulation based experiment or trial.
 

Weapon System Performance Assessment

Module Leader
  • Jeremy Smith
Aim

    To enable students to understand the application of operational research techniques to the assessment of weapon systems.

Syllabus
    Concepts of performance and effectiveness measures,
    dispersion of fire,
    accuracy, consistency and precision,
    calculation of single shot kill probability for direct fire weapons,
    modelling of area effect weapons (eg shells, grenades) including using the damage function,
    modelling of minefields and calculation of stopping power,
    assessment of direct fire systems examples,
    methods for modelling of land, sea and air targets,
    approaches to the analysis of various other weapon systems,
    force effectiveness comparisons,
    practical exercises to illustrate the theories,
    cost effectiveness principles.
Intended learning outcomes On successful completion of this module a student should be able to:

describe the cycle of weapon assessment studies and the measures of performance and effectiveness,
demonstrate the application of statistics to weapon delivery errors,
discuss the nature of direct fire weapons and demonstrate how to calculate their performance,
review the nature of area weapons and demonstrate the use of the damage function and lethal area in the analysis of their effects,
use a technique for the analysis of anti- tank minefields,
appreciate the different emphasis in the study of guided weapon systems,
review the special nature of other weapon systems and the ideas involved in their assessment,
evaluate the need and collection methods, for data in models,
explain the issues surrounding practical weapon assessment projects including force effectiveness and cost effectiveness analyses.
 

Intelligent Systems

Module Leader
  • Dr Venkat Sastry
Aim

    The aim of this module is to provide students with basic knowledge of intelligent systems techniques that can be applied in a variety of disciplines.



Syllabus
    Overview of Intelligent Systems; basic approaches to developing intelligent systems,
    problem spaces and architectures,
    case studies in rule based programming,
    cognitive architectures – overview of SOAR,
    classical inference techniques; reasoning under uncertainty,
    fuzzy reasoning,
    Bayesian networks,
    Introduction to artificial Neural Networks,
    hebbian learning,
    supervised learning – perceptrons and multilayer perceptrons; basics of perceptron learning algorithm; analysis of back propagation learning algorithm and its modifications,
    unsupervised learning – Kohonen maps; Associative memories; Hopfield networks,
    Neural Networks for classification and prediction,
    application to time series,
    review of comparable statistical techniques.
Intended learning outcomes On successful completion of this module a student should be able to:

develop an application of intelligent systems using either rule-based or Neural Network or Bayesian Belief Networks or a combination of techniques
assess the performance of developed systems
appreciate the role of data pre-processing and representation.

Networked and Distributed Simulation Exercise

Module Leader
  • Jonathan Searle
Aim
    The module will allow students who have completed the Networked and Distributed Simulation (NDS) module to design, setup and conduct a basic battlespace Synthetic Environment (SE) exercise employing local- and wide-area network (LAN and WAN) distributed simulation technology.
Syllabus
    • A group project to design, set up and conduct a basic distributed battlespace exercise using both Distributed Interactive Simulation (DIS) and High Level Architecture (HLA) systems.
    • An individual written report on the project including a detailed description of the Synthetic Environment (SE) and the experiments that were conducted, an explanation and analysis of the results obtained and a critical technical appraisal of the project.
Intended learning outcomes On successful completion of the module the student will be able to:

  • Apply the principles of modelling and simulation and the technologies of networked and distributed simulation in the context of a specific project
  • Design, set up and conduct a basic battlespace exercise using a DIS/HLA based synthetic environment
  • Communicate and discuss the results of their experimentation orally and in writing.

Advanced Module 1

Aim

    The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree.


Syllabus

    A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one or more already completed standard taught modules in that degree.

    Part-time students will typically complete their work over a 10-week period, one such block of 10 weeks being offered in each academic term.



Intended learning outcomes On successful completion of the module a diligent student will be able, within the individual topic agreed, to:

  • Plan, organise and undertake an individual, open-ended research activity with appropriate supervision
  • Demonstrate an ability to acquire, organise, discuss, assess and apply relevant knowledge
  • Demonstrate an ability to gather and critically appraise data and to utilise it within the appropriate context
  • Critically apply appropriate methods, tools, techniques, processes and knowledge to the topic selected
  • Communicate findings in the form of both a written deliverable and an oral presentation.


Advanced Module 2

Aim

    The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree.


Syllabus

    A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one or more already completed standard taught modules in that degree.

    Part-time students will typically complete their work over a 10-week period, one such block of 10 weeks being offered in each academic term.



Intended learning outcomes On successful completion of the module a diligent student will be able, within the individual topic agreed, to:

  • Plan, organise and undertake an individual, open-ended research activity with appropriate supervision
  • Demonstrate an ability to acquire, organise, discuss, assess and apply relevant knowledge
  • Demonstrate an ability to gather and critically appraise data and to utilise it within the appropriate context
  • Critically apply appropriate methods, tools, techniques, processes and knowledge to the topic selected
  • Communicate findings in the form of both a written deliverable and an oral presentation.


Advanced Module 3

Aim

    The aim of this module is to allow students to conduct an in-depth study in an area of particular personal interest or relevance to them, in the context of their degree.


Syllabus

    A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one or more already completed standard taught modules in that degree.

    Part-time students will typically complete their work over a 10-week period, one such block of 10 weeks being offered in each academic term.



Intended learning outcomes On successful completion of the module a diligent student will be able, within the individual topic agreed, to:

  • Plan, organise and undertake an individual, open-ended research activity with appropriate supervision
  • Demonstrate an ability to acquire, organise, discuss, assess and apply relevant knowledge
  • Demonstrate an ability to gather and critically appraise data and to utilise it within the appropriate context
  • Critically apply appropriate methods, tools, techniques, processes and knowledge to the topic selected
  • Communicate findings in the form of both a written deliverable and an oral presentation.


Fees and funding

European Union students applying for university places in the 2019 to 2020 academic year will still have access to student funding support. Please see the UK Government’s announcement (24 July 2018).

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 £21,000
MSc Part-time £21,000 *
PgDip Full-time £17,200
PgDip Part-time £17,200 *
PgCert Full-time £10,350
PgCert Part-time £10,350 *
  • * Fees can be paid in full up front, or in equal annual instalments. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2019 and 31 July 2020.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • For self-funded applicants a non-refundable £500 deposit is payable on offer acceptance and will be deducted from your overall tuition fee.
  • Additional fees for extensions to the agreed registration period 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 Isle of Man) pay Overseas fees.

MSc Full-time £22,500
MSc Part-time £22,500 *
PgDip Full-time £17,200
PgDip Part-time £17,200 *
PgCert Full-time £10,350
PgCert Part-time £10,350 *
  • * Fees can be paid in full up front, or in equal annual instalments. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2019 and 31 July 2020.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • For self-funded applicants a non-refundable £500 deposit is payable on offer acceptance and will be deducted from your overall tuition fee.
  • Additional fees for extensions to the agreed registration period 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 Isle of Man) pay Overseas fees.

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.

There are a number of MOD funded places each year.

For any further funding enquiries please contact studentfunding@cranfield.ac.uk for more information on funding.





Entry requirements

Normally a first or second class Honours degree or equivalent in science, engineering or mathematics. Alternatively, a lesser qualification together with appropriate work experience may be acceptable.

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:

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.

Security clearance for Shrivenham

Some Cranfield University courses are delivered at the Defence Academy of the United Kingdom, Shrivenham which is a Ministry of Defence (MOD) site. All applicants to courses that are wholly or partially delivered at Shrivenham must complete the BPSS (HMG Baseline Personnel Security Standard V4 April 2014) prior to registration on the course or must already hold a security clearance to this level or higher.

Please visit our security clearance page for further information.



Your career

This qualification will equip you for simulation-specific appointments within the armed forces or government, or in the defence related activities of commercial organisations.

How to apply

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