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Fire Protection Systems for Rail Transportation of Class A Explosives. Interim Report.

pdf icon Fire Protection Systems for Rail Transportation of Class A Explosives. Interim Report. (6834 K)
Bukowski, R. W.

NBSIR 80-2170; 30 p. November 1980.


Department of Transportation, Washington, DC

Available from:

National Technical Information Service (NTIS), Technology Administration, U.S. Department of Commerce, Springfield, VA 22161.
Telephone: 1-800-553-6847 or 703-605-6000;
Fax: 703-605-6900; Rush Service (Telephone Orders Only) 800-553-6847;
Order number: PB81-153975


bombs (ordnance); computer models; fire detection systems; fire suppression; large scale fire tests; heat transfer; railroad accidents; small scale fire tests; thermal protection


As a result of several accidents involving fire induced detonation of military explosive during rail shipment, a research project, funded by the Federal Railroad Administration (FRA), was initiated at the Center for Fire Research (CFR) at the National Bureau of Standards (NBS). This project was initiated to evaluate various methods of protection of Class A explosives from fire, and to identify one or more cost-effective approaches which could be explored in greater detail in later studies. Active systems (detection, notification, and extinguishment) and passive systems (thermal insulating barriers) were evaluated regarding cost, feasibility and level of protection provided for the major hazard scenarios involved in rail shipment of explosives. The passive, thermal barrier approach was selected as the most reliable and less costly of the options studied while providing an acceptable level of protection. Small-scale and full-scale tests were conducted to obtain performance data on one specific thermal barrier material. Based on this data, a computer model was developed which can predict temperatures of the boxcar floor, top surface temperature of a thermal barrier, and casing/explosive interface temperature of a wood-pallet mounted bomb for a range of fire sizes. The model predications compare favorably with measured results from a limited number of experiments. Further experimental data are needed to refine the model and establish an acceptable confidence level in the predicted values. The proposed work necessary to provide this refinement and verification is described.