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modeling + simulation.

Modelling and simulation is a discipline which bring together elements of art, science, engineering and design to produce computerised replications of real-world scenarios. These models can be used for a wide range of applications, from constraints mapping to scenario testing. The term “model” refers to the theoretical framework developed representing a system or process, including specification of the conceptualisation and the underlying assumptions and constraints.

In a simulation, a set of input parameters is run through a model to produce a number of results. In essence, the model is the representation of the physical system, and the simulation is the use of the model to produce results for a certain scenario.

The concept of modelling and simulation, and in particular techniques such as Complex Systems Modelling or Whole Systems Analysis, is a field which has expanded significantly in the past 10 years due to the rapid increase in available computing power. World leading institutes such as the Santa Fe Institute for Complex Systems have developed departments dedicated to developing techniques for modelling increasingly complicated systems.

Combined with the global context of rapid urbanisation and increasingly strained urban infrastructure worldwide, there has been significant interest in creating models to provide insight into how cities work and developing solutions to some of the problems they face.

In the context of cities, modelling and simulation involves three key steps:



Creating a digital prototype of the city system or

sub-system to various changes in parameters. 



Use the resulting model to determine the reaction of the system to various changes in parameters.



Determine and forecast real-world outcomes and recommend optimal strategies.

The key advantage of modelling and simulation is that it can facilitate understanding of a city system or sub-system without real-world testing or prototyping. If the model is accurate and the underlying assumptions and constraints are understood, invaluable insights into the future of a city can be gleaned. The availability of rapid computing capability in recent years has enabled the use of simulation for scenario testing and numerical optimisation, a computing technique which tests millions of different scenarios within a model to determine the optimal solution. Modelling and simulation allows city systems to be explored in a way which would otherwise be too risky, expensive or even impossible.

The applications of modelling and simulation to city systems is almost boundless, limited only by the complexity of the model and the availability of data to test and validate it.

Potential uses of modelling and simulation in the context of cities include:

  • Analysis of future development plans to determine constraints and choke-points, and identify optimal design solutions. 

  • Modelling infrastructure systems (energy. transport, roading, etc) to test resilience to external factors such as increased demand or natural disaster.

  • Forecasting population growth and distribution throughout the city.


  • Understanding the effects of land developments on the systems present in the surrounding city. 

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