Fire growth prediction

FIRAC is a computer code designed to estimate radioactive and chemical source-terms as.sociaied with a fire and predict fire-induced flows and thermal and material transport within facilities, especially transport through a ventilation system. It includes a fire compartment module based on the FIRIN computer code, which calculates fuel mass loss rates and energy generation rates within the fire compartment. A second fire module, FIRAC2, based on the CFAST computer code, is in the code to model fire growth and smoke transport in multicompartment stmetures. 

FIRE SIMULATOR predicts the effects of fire growth in a 1-room, 2-vent compartment with sprinkler and detector. It predicts temperature and smoke properties (Oj/CO/COj concentrations and optical densities), heat transfer through room walls and ceilings, sprinkler/heat and smoke detector activation time, heating history of sprinkler/heat detector links, smoke detector response, sprinkler activation, ceiling jet temperature and velocity history (at specified radius from the flre i, sprinkler suppression rate of fire, time to flashover, post-flashover burning rates and duration, doors and windows which open and close, forced ventilation, post-flashover ventilation-limited combustion, lower flammability limit, smoke emissivity, and generation rates of CO/CO, pro iri i post-flashover. 

Probably the best way of assessing fire hazard is by calculations via mathematical fire growth and transport models, such as HAZARD I [58], FAST [59], HARVARD [60] or OSU [61]. These models predict times to reach untenable situations. They are often combined with fire escape models and will, then, yield times to escape. 

Convective heating in fire conditions is principally under natural convection conditions where for turbulent flow, a heat transfer coefficient of about 10 W/m2 K is typical. Therefore, under typical turbulent average flame temperatures of 800 °C, we expect convective heat fluxes of about 8 kW/m2. Consequently, under turbulent conditions, radiative heat transfer becomes more important to fire growth. This is one reason why fire growth is not easy to predict. 

Gas-Phase Physics Required to Predict Fire Growth.552... 

GAS-PHASE PHYSICS REQUIRED TO PREDICT FIRE GROWTH... 

In the context of fire CFD, it is sometimes appropriate to distinguish between flame and fire spread simulations. Flame spread simulation usually means the ability to predict the fire growth starting from a small initial fire or ignition point, where all the three subprocesses are important but the second subprocess dominates the heat transfer. Fire spread, in turn, means the ignition of solid surfaces in the presence of a relatively large initial fire dominating the heat transfer by radiation. In practice,... 

Typically, a fire growth model is evaluated by comparing its calculations (predictions) of large-scale behavior to experimental HRR measurements, thermocouple temperatures, or pyrolysis front position. The overall predictive capabilities of fire growth models depend on the pyrolysis model, treatment of gas-phase fluid mechanics, turbulence, combustion chemistry, and convective/radiative heat transfer. Unless simulations are truly blind, some model calibration (adjusting various input parameters to improve agreement between model calculations and experimental data) is usually inherent in published results, so model calculations may not truly be predictions. 

The first test series evaluated the flammability characteristics of small format Li-ion batteries and the FM Global standard cartoned commodities in a three-tier high, single row, open frame, rack storage array. All tests conducted were free burn tests. In each test, cartoned commodity was only located in a portion of the rack where the initial fire growth was expected to lead to sprinkler operation (i.e., at the flues). The first test series was used to estimate the fire hazard from the cartoned commodity present at the time of the predicted first sprinkler operation. 

Table 3.4 Predicted quick response sprinkler link operation time and corresponding fire growth characteristics (courtesy of FM Global)...

This predicted burn time of 1.3 minutes is most likely shorter than will actually occur. In reality, there will be additional time associated with the growth period of the fire and the pool fire may take minutes before reaching a steady-state burning rate. This time also does not account for secondary materials igniting and burning. 

However, current CFD cannot provide good predictions of HRR evolution (i.e., hre growth) in real complex enclosures/scenarios. Fire modeling is not yet able to predict the HRR, and research efforts need to be tailored toward this issue. However, hre environments for hre safety design can still be calculated using CFD, if the HRR is an input data to the design process. This is because, current CFD tools provide good predictions of the effects of a hre (e.g., temperature held, smoke movements, etc.) once the HRR is provided. 

Coen and Clark [128] has coupled a fire model into a three-dimensional non-hydrostatic terrain-following numerical mesoscale model developed at the US National Center for Atmospheric Research, Boulder, CO. The model includes rain and cloud physics. Calculations predict the growth and spread of a fire line moving across a two dimensional small Gaussian hill (height 200 m, half-width 300 m) for a wind speed of 3 m/s, and a stable atmospheric lapse rate (10°C/km). The head of the fire propagated quickly uphill in the direction of the environmental wind. Once the fire reaches the top of the hill, the updrafts tend to inhibit the forward movement of the fire front, and the fire spreads faster laterally in the lee of the hill. 

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