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Fire Detector Performance Predictions in a Simulated Multi-Room Configurtion.

pdf icon Fire Detector Performance Predictions in a Simulated Multi-Room Configurtion. (380 K)
Cleary, T. G.; Donnelly, M. K.; Mulholland, G. W.; Farouk, B.

NIST SP 965; February 2001.

International Conference on Automatic Fire Detection "AUBE '01", 12th. Proceedings. National Institute of Standards and Technology. March 25-28, 2001, Gaithersburg, MD, Beall, K.; Grosshandler, W. L.; Luck, H., Editor(s)(s), 455-469 pp, 2001.


fire detection; fire detection systems; detector response; heat release rate


Modeling fire detector performance requires detailed information on the environment surrounding the detector, the species transport (heat, smoke, gas) from the surrounding to the sensing surface or volume, and the sensor response. The species transport to the sensing surface or volume and the sensor response can be determined through experiments or modeled if sufficient detailed information on a particular detector exists. Here, a fire model (the Fire Dynamics Simulator, FDS) was used to predict the environment at multiple detector locations, and the fire emulator/detector evaluator was used to reproduce the modeled environment at selected location. FDS was used to compute velocity, temperature, smoke and CO gas concentrations at detector locations in each room of a simulated commercial-sized three-room configuration fire scenario. The simulated fire consisted of a flaming fire that starts out with a heat release rate similar to the EN54 TF4 flaming polyurethane foam mat fire. It transitions to a "medium t2 fire" after the mat fire reaches its peak output. The smoke and CO emission are typical of what would be expected from a flaming plastics fire. The environment was simulated for 500 seconds, and the output data were used to program the FE/DE such that it reproduced the environment, (i.e. temporal values of temperature, velocity, smoke and CO concentration) at each detector location. An analog output photo-ion-thermal multi-sensor detector was placed in the test section along with an electrochemical CO sensor and the sensor responses to the emulated conditions were recorded. Sensor outputs obtained in this manner could be used to develop or verify multi-sensor, multi-criteria detection algorithms, be used as input data for the inverse fire model development, or to predict performance of existing or new conventional designs or performance-based designs that have been modeled.