This module can only be taken as part of the Systems Engineering MSc and applicants must have completed the Introduction to Systems and Systems Engineering module before undertaking the course. 
 

This module is designed to equip you with a sound understanding of the dynamic modelling of complex systems through the use of the System Dynamics methodology.

 
 

 

At a glance

  • Duration5 days
  • LocationCranfield campus

What you will learn

On successful completion of the course you will be able to:

 

  • Relate complex system behaviour to system structure, appreciating considerations such as cause and effect, feedback and delay within systems.
  • Develop convincing and compelling qualitative models of problem systems and use them for beneficial communication with system stakeholders.
  • Use computational modelling and simulation to explore the consequences of such models and to develop useful policy interventions to improve system behaviour.
  • Combine the dual aspects of qualitative and quantitative system dynamics to study suitable problem systems and to make recommendations for system improvement.

Core content

Unit 1

The System Dynamics Approach. Dynamical systems, complexity and change. Closed systems and their behaviour. Structure as a driver of dynamic behaviour. Building candidate understanding models and testing them. Reference modes. The "twin pillars" of SD – feedback thinking and computational modelling. SD as a paradigm to support systems thinking.

Unit 2

Qualitative SD. Seeing complexity as an emergent consequence of cause and effect. Visualising the interdependencies within complex systems using feedback structures and causal loop diagrams. Considering policy interventions as points of leverage. Developing understanding of complex systems and communicating it usefully. Relationship to other soft methods.

Unit 3

Quantitative SD. Simulating feedback systems. First order, second order and higher order feedback systems. Suggesting and testing policy interventions for behavioural improvement. Theoretical underpinnings of SD modelling, including its background in control theory. Introducing delays. Formulating equations, using data and estimating parameters. Relationship to other computational simulation methods.

Unit 4

Implementing the SD approach. Building useful models. Verification and validation of simulation models. Case studies and a detailed modelling exercise.

Location and travel

Situated close to Milton Keynes and Bedford, the Cranfield campus is situated in Wharley End, very close to Cranfield village, and is about 10 minutes from the M1 motorway.  There is rail and road access to most major airports as well as coach and train stations. Cranfield campus also has its own airport for private executive business travel.

Download a visitor guide including map, directions and health and safety information.

Campus address

College Road
Cranfield
Bedfordshire
MK43 0AL


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