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Computational Fluid Dynamics (CFD)

The most advanced and sophisticated fire modelling technique is the use of Computational Fluid Dynamics (CFD) models to predict fire growth and compartment temperatures. CFD models have been shown to be successful in the modelling of smoke movement and have recently been applied to the modelling of fires. They are capable of modelling pre-flashover and localised fires in complex geometries with smoke movement in multi-compartments.

According to Annex D (informative) of BSEN1991-1-2 (2002), typical CFD models analyse systems involving fluid flow, heat transfer and associated phenomena by solving the fundamental equations of the fluid flow. These equations represent the mathematical statements of the conservation laws of physics:

  • the mass of a fluid is conserved;
  • the rate of change of momentum equals the sum of the forces on a fluid particle – the Newton’s second law;
  • the rate of change of energy is equal to the sum of the rate of heat increase and the rate of work done on a fluid particle – the first law of thermodynamics.

Basically, in a CFD model, the partial differential equations of the thermodynamic and aerodynamic variables (Navier-Stokes equations) are solved in a very large number of points in the compartments. Most CFD models for enclosure fires are appropriate for low-speed, thermally-driven flow with an emphasis on smoke and heat transport from fires.

The input requirement for CFD models is very demanding and requires expertise in defining the correct input parameters and assessing the feasibility of the calculated results. On the other hand, the results are given with much greater detail, providing the variables in all points of the compartments, such as temperature, velocity and chemical species concentration.

The examples of CFD models include:

  • FDS from NIST (McGrattan et al. 2002)
  • SMARTFIRE from the University of Greenwich (SMARTFIRE 1998)
  • SOFIE from Cranfield University (Rubini 2000)
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