Research on the model development of untenable conditions and egress failure in compartment firs

• Main Author: 周柏年
• Other Authors: 林元祥
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/whmces

碩士 === 中央警察大學 === 消防科學研究所 === 99 === Abstract This research focuses on developing “the fire and smoke growth model” to simulate the time to the untenable conditions, including smoke layer temperature, visibility, carbon monoxide concentration, fractional incapacitating dose, and radiation heat flux in a room with less than 200 square meters, and building “the egress behavior model” to simulate an individual required safety egress time in a room. Moreover, reliability-based design and structure function are incorporated into above mentioned models to construct ”the assessment model of egress failure in a room fire.” After the model construction, the input parameters and the probability distributions are assumed. Random numbers of parameters are generated by Monte Carlo simulation. After several simulations, the failure probability of an individual egress due to any one of untenable conditions is obtained. Furthermore, random samples are generated by Bernoulli trials, then the estimate of the failure probability of egress system and confidence interval are constructed. Finally, a commercial premises is taken as an example. Under the conditions of identical room area, room height, and without smoke exhaust equipment, four experimental samples are categoried by considering with/without the automatic fire alarm equipments or with/without resrtriction on the number of occupant accommodation. To conclude, in order to reduce the failure probability of an individual fails to evacuate due to untenable conditions and the estimate of the failure probability of egress system. Research results show that the resrtriction on the number of occupant accommodation is more effective than installation of the automatic fire alarm equipments. Keywords: the fire and smoke growth model, the time to the untenable conditions, Monte Carlo simulation method.