Defence Simulation and Modelling

Full-time/Part-time

  • Emphasis on practical application
  • Suitable for military, government and industry
  • Modular structure - Full or part-time study
MSc Defence Simulation and Modelling

The 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.



Course overview

The modular form of the course, consisting of a compulsory core and a selection of standard and advanced modules, enables each student to select the course of study most appropriate to their particular requirements.

Standard modules normally comprise a week of teaching (or equivalent for distance learning) 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 and distance learning) 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. 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.

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.

Modules

Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.
Advanced Modules, which typically comprise individual self-study, can be selected to follow on from any standard modules that have been chosen.
Standard Modules, which typically involve traditional classroom instruction and/or VLE-based delivery, can be chosen from the following:

Core

  • Foundations of Modelling and Simulation
    Module LeaderMr John Hoggard - Lecturer in Defence Simulation
    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 outcomesOn successful completion of the module the student will 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 LeaderMr Jonathan Searle - Senior Lecturer
    Syllabus
    • Fundamentals of computer communications, networking, Local Area Networks and Wide Area Networks
    • Main hardware components of computer networks
    • The International Standards Organisation's Open Systems Interconnection (OSI) Architecture and network protocols
    • The features and facilities of network protocols Transmission Control Protocol and Internet Protocol (TCP/IP) and their relevance to simulation systems
    • Networked and distributed simulation architectures
    • Interoperability and composability
    • The design, management, configuration and testing of distributed simulation systems and networks
    • Networking standards in defence simulation, e.g. Distributed Interactive Simulation, High Level Architecture
    • Practical experiments and case studies in the application of Networked and Distributed Simulation technologies.

    Intended learning outcomesOn successful completion of the module the student will 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 LeaderDr Ken McNaught - Senior Lecturer
    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 outcomesOn successful completion of the module the student will be able to:
    • Describe the origins and the main principles underlying both Discrete Event Simulation and System Dynamics
    • Develop conceptual models of systems prior to their simulation
    • Identify feedback loops within an System Dynamics model and understand the effects of positive and negative feedback
    • Distinguish between the different types of variables commonly used in System Dynamics models
    • Develop an System Dynamics model from an appropriate diagram
    • Select appropriate probability distributions for use in stochastic simulations
    • Develop a Discrete Event Simulation model of a simple system
    • Perform appropriate experiments, policy analysis and output analysis with the completed simulation model.
  • War Gaming and Combat Modelling
    Module LeaderMr Jeremy Smith - Senior Lecturer
    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, combat 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 outcomesOn successful completion of the module you will 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 LeaderMr Jonathan Searle - Senior Lecturer
    Syllabus
    • Coordinate systems and transforms
    • Geometric modelling
    • Rendering techniques
    • Graphics application programming
    • Scientific visualisation
    • Real-time Virtual Environments
    • Graphics hardware and architectures
    • Serious Games technologies
    • Applications of computer graphics.
    Intended learning outcomesOn successful completion of the module the student will be able to:
    • Demonstrate an understanding, appropriate to the student’s degree, 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
    • Discuss the use of graphics as a means of data visualisation
    • 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 the student’s degree
    • Develop appropriate computer graphics components or software.
  • Logistics Modelling
    Module LeaderMr Mark Lewis - Lecturer in Defence Simulation
    Syllabus
    • Logistics methodologies
    • Modelling distribution networks with Linear Programming approaches
    • Inventory control
    • Reliability, availability and maintenance modelling
    • Simulation of logistics systems.
    Intended learning outcomesOn successful completion of the module the student will be able to:
    • Describe the most important logistical methodologies such as Just In Time (JIT), Integrated Logistic Support (ILS) and Material Requirement Planning (MRP)
    • Describe the similarities and differences between commercial and military logistics systems
    • Perform simple reliability and replacement calculations
    • Calculate the optimum level of spare parts to hold in some simple settings
    • Derive and apply the Economic Order Quantity formula in inventory control
    • Describe various inventory control systems and understand their strengths and weaknesses
    • Perform a Pareto analysis of an organisation’s stockholding
    • Formulate and solve simple shortest-path, assignment, transportation and transshipment problems
    • Perform a set of MRP calculations
    • Describe the role of simulation in designing logistical systems.
  • Statistical Analysis and Trials
    Module LeaderDr Trevor Ringrose - Lecturer
    Syllabus

    Pre-Course reading including topics marked*

    • Principles of data collection, organisation, analysis and interpretation*
    • Graphing and summarising data, exploratory data analysis*
    • Probability*
    • Probability distributions
    • Confidence intervals and significance tests for large and small samples
    • Tests of consistency and goodness of fit
    • Non-parametric methods
    • Introduction to experimental/trials design
    • Regression and analysis of variance for the analysis of experimental data
    • Statistical aspects of simulation modelling.
    Intended learning outcomes

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

    • Calculate probabilities from distributions such as the binomial, Poisson and normal
    • Perform z and t tests and construct z and t confidence intervals, and know when they are appropriate
    • Perform simple non-parametric tests and know when they are appropriate
    • Appreciate the basic principles of experimental design, such as randomisation and factorial designs
    • Analyse data using simple linear regression and one- and two-way analysis of variance, and assess when these are appropriate
    • Set up a simple Markov chain.
  • Weapon System Performance Assessment
    Module LeaderMr Jeremy Smith - Senior Lecturer
    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 outcomesOn successful completion of the module the student will 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 LeaderDr Venkat Sastry - Head of Group
    Syllabus
    • Review of intelligent systems
    • Problem spaces and architectures
    • Classical inference techniques
    • Review of search algorithms
    • Reasoning under uncertainty
    • Fuzzy reasoning
    • Bayesian networks
    • Rule based programming.
    Intended learning outcomes

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

    • Develop a simple application using rule based programming
    • Develop simple applications using fuzzy inference and Bayesian network techniques
    • Assess available architectures and techniques for a practical problem under consideration.
  • Decision Analysis
    Module LeaderDr Ken McNaught - Senior Lecturer
    Syllabus
    • Introduction – The role and scope of decision analysis in supporting decision making.
    • Pay-off Matrices – Structuring decision problems using a pay-off matrix to represent the value or utility of each option for each possible state of nature. Analysing the pay-off matrix under conditions of uncertainty and risk. Sensitivity/robustness of decisions to the inputs.
    • Decision Trees – Structuring and analysing decision problems using a decision tree to represent sequential decision making under conditions of risk and uncertainty. The application of Bayes' Theorem to update probabilities in the light of new information. The calculation of the value of perfect and imperfect information.
    • Bayesian Networks and Influence Diagram Decision Networks – These modern tools are examples of probabilistic graphical models which offer a powerful framework for reasoning and decision-making under risk and uncertainty. Modelling assumptions and development, example applications and software.
    • Game Theory – Classical two-person zero-sum game theory and its application to decision making under conditions of competition or conflict. Extensions of the classical theory to non zero-sum games.
    • Judgmental Methods – The elicitation and analysis of individual judgements as part of the decision making process: the strategy to task technique, the Delphi technique, the analytic hierarchy process and an associated consensus methodology.
    • Soft Systems Methods – A review and brief introduction to some of the "softer" methods used to support decision-makers. The topics covered will include Checkland's soft systems methodology, hypergames and metagames, robustness analysis and approaches to strategic decision making.
    • Multiple Criteria Decision Analysis – A review of the different approaches used in multiple criteria decision analysis where several, often conflicting, criteria are important to a decision-maker: aggregate value methods to permit trade-offs in multiple attribute decision making and mathematical programming methods in multiple objective decision making.
    • Software for Decision Analysis – Throughout the course reference will be made to the application of decision analysis software to help support the decision making process, including demonstrations and hands-on practicals.
    Intended learning outcomesOn successful completion of the module the student will be able to:
    • Structure decision problems using a pay-off matrix and analyse the pay-off matrix under conditions of uncertainty, risk and competition
    • Structure and analyse sequential decision problems using a decision tree
    • Structure and analyse decision problems using Bayesian networks and influence diagram decision networks
    • Structure and analyse decision problems based on using expert judgments
    • Explain and apply the different approaches used in multiple criteria decision analysis
    • Explain how the different methods of representing decision problems can be used to support defence decision-making.
  • Networked and Distributed Simulation Exercise
    Module LeaderMr Jonathan Searle - Senior Lecturer
    Syllabus
    • A group project to design, setup 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 outcomesOn 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, setup 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
    Syllabus

    A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one 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 outcomesOn 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
    Syllabus

    A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one 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 outcomesOn 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
    Syllabus

    A self-study ‘mini-project’ conducted over two weeks, on an individually selected and agreed topic, which must follow on from one 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 outcomesOn 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.

Assessment

Continuous assessment, written examinations, oral vivas and (MSc only) thesis.

Proportions of different assessment types will vary according to programme and modules taken. For an MSc these might typically comprise 15-24% continuous assessment (written and oral), 36-45% written examinations and 40% thesis/dissertation.

Start date, duration and location

Start date: Full-time: annually in September. Part-time: by arrangement

Duration: MSc: One year full-time, up to 5 years part-time. PgDip: 40 weeks full-time, up to 4 years part-time. PgCert: 20 weeks full-time, Up to 3 years part-time

(For MOD status students the duration may vary, subject to annual review.)

Teaching location: Shrivenham

Overview

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.

  • 10 places are normally available for the full-time cohort. 
  • The course is suitable for both military and civilian personnel, including those from defence industry and government departments.

Informed by industry

The aim of the Industrial Advisory Panel, which is common to all components of the AMOR Postgraduate Suite, 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 program has members on it from both Defence Industry (including Cassidian, BAE Systems and AWE) and the MOD.

Your teaching team

External speakers from industry and defence (due to frequency of post changes it is not practical to include names).







Facilities and resources

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

Students whose first language is not English must attain an IELTS score of 6.5.

Fees

Home EU Student Fees

MSc Full-time - £16,250

MSc Part-time - £16,250 *

PgDip Full-time - £13,900

PgDip Part-time - £13,900 *

PgCert Full-time - £6,950

PgCert Part-time - £6,950 *

Overseas Fees

MSc Full-time - £16,250

MSc Part-time - £16,250 *

PgDip Full-time - £13,900

PgDip Part-time - £13,900 *

PgCert Full-time - £6,950

PgCert Part-time - £6,950 *

*

Students will be offered the option of paying the full fee up front, or to pay in four equal instalments at six month intervals (i.e. the full fee to be paid over the first two years of their registration). 

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2016 and 31 July 2017.
  • 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.

Application Process

Career opportunities

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



Related areas