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Sensor-Driven Inverse Zone Fire Model



William D. Davis, Glenn P. Forney


As sensor use in buildings becomes more wide spread, it is possible to use this information as input to an inverse fire model in order to enhance the value of the information available from sensors in both fire and non-fire conditions. Typical fire models use the heat release rate (HRR) of the fire as an input and sensor outputs are calculated. An inverse fire model uses sensor signals as inputs in order to estimate the HRR of the fire. An inverse zone fire model is being developed at NIST to be used in conjunction with the NIST Virtual Cybernetic Building Testbed to investigate the feasibility of such a model. Version 1.1 of this model uses ceiling jet algorithms for temperature and smoke concentration to convert the signals from heat and smoke detectors to HRR. A version of CFAST is then used to obtain layer temperatures and depths for the room of fire origin as well as surrounding rooms. Details of the ceiling jet algorithms for smoke concentration and temperature will be discussed and an example of the predictive capabilities of the inverse zone fire model will be demonstrated.
Proceedings Title
Fire Protection Research Foundation
Conference Dates
February 23-25, 2000
Conference Location
Orlando, FL
Conference Title
Research and Practice: Bridging the Gap. Fire Suppression and Detection Research Application Symposium


fire suppression, predictive models, fire detection, fire research, fire safety, fire protection, zone models, fire models, sensors, heat release rate, ceiling jets, temperature, smoke, fire hazards


Davis, W. and Forney, G. (2000), Sensor-Driven Inverse Zone Fire Model, Fire Protection Research Foundation, Orlando, FL (Accessed April 23, 2024)
Created February 23, 2000, Updated February 19, 2017