Using Sensor Signals to Analyze Fires

Published

January 23, 2002

Author(s)

William D. Davis, Thomas G. Cleary, Michelle K. Donnelly, S. D. Hellerman

Abstract

Building fire sensors are capable of supplying substantially more information to the fire service than just the simple detection of a possible fire. Nelson, in 1984, recognized the importance of tying all the building sensors to a smart fire panel. In order to accomplish a smart fire panel configuration such as envisioned by Nelson, algorithms must be developed that convert the analog/digital signals received from sensors to the heat release rate (HRR) of the fire. Once the HRR of the fire is known, a multiroom zone fire model can be used to determine smoke layers and temperatures in the other rooms of the building. This information can then be sent to the fire service providing it with an approximate overview of the fire scenario in the building. This paper will describe a ceiling jet algorithm that is being developed to predict the heat release rate (HRR) of a fire using signals from smoke and gas sensors. The prediction of this algorithm will be compared with experiments. In addition, an example of the predictions from a sensor-driven fire model, SDFM, using signals from heat sensors, will be compared with measurements from a full-scale, two-story, flashover townhouse fire.

Proceedings Title

Fire Suppression and Detection Research Application Symposium

Conference Dates

January 23-25, 2002

Conference Location

Tampa, FL

Conference Title

Research and Practice: Bridging the Gap

Pub Type

Conferences

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Keywords

fire suppression, fire detection, fire research, fire safety, fire protection, ceiling jets, fire detectors, experiments, fire models, zone models, fire hazards, flashover

Citation

Davis, W. , Cleary, T. , Donnelly, M. and Hellerman, S. (2002), Using Sensor Signals to Analyze Fires, Fire Suppression and Detection Research Application Symposium, Tampa, FL, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=912278 (Accessed December 16, 2024)