Fire Suppression Modeling & Simulation Framework for Ground Vehicles

Paper #:
  • 2017-01-1351

Published:
  • 2017-03-28
DOI:
  • 10.4271/2017-01-1351
Citation:
Korivi, V., McCormick, S., and Hodges, S., "Fire Suppression Modeling & Simulation Framework for Ground Vehicles," SAE Int. J. Trans. Safety 5(1):58-67, 2017, https://doi.org/10.4271/2017-01-1351.
Pages:
10
Abstract:
The US Army Tank Automotive Research, Development and Engineering Center (TARDEC) has developed a unique physics based modeling & simulation (M&S) capability using Computational Fluid Dynamics (CFD) techniques to optimize automatic fire extinguishing system (AFES) designs and complement vehicle testing for both occupied and unoccupied spaces of military ground vehicles.The modeling techniques developed are based on reduced global kinetics for computational efficiency and are applicable to fire suppressants that are being used in Army vehicles namely, bromotrifluoromethane (Halon 1301), heptafluoropropane (HFC-227ea, trade name FM200), sodium-bicarbonate (SBC) powder, water + potassium acetate mixture, and pentafluoroethane (HFC-125, trade name, FE-25). These CFD simulations are performed using High Performance Computers (HPC) that enable the Army to assess AFES designs in a virtual world at far less cost than physical-fire tests.This methodology is applied to vehicle crew compartments for multiple scenarios using HFC227e + SBC powder which is the suppressant combination used in most US combat and tactical vehicles with crew fire protection systems. Predicted and test results match qualitatively very well for overall suppression time as well as for soldier survivability from thermal injury, blast overpressure and inhalation toxicity risks.After gaining confidence with crew compartment simulations, this fire suppression modeling methodology is now being applied to the geometrically-more-complex military vehicle engine compartments with HFC-125 fire suppressant that is widely used for unoccupied spaces. Challenges associated with the fire suppression simulations are discussed along with future developments that are being proposed to enhance the overall accuracy of the simulation methodology.
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