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 preflashover and localised fires in complex
geometries with smoke movement in multicompartments.
According to Annex D (informative) of BSEN199112
(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 (NavierStokes
equations) are solved in a very large number of points in the compartments.
Most CFD models for enclosure fires are appropriate for lowspeed,
thermallydriven 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)
