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Transportation of flammable liquefied gas in tunnels presents a significant risk of an accidental loss of containment leading to an explosion with major consequences. Possible scenarios include a BLEVE, a non-reactive gas expansion explosion and a reactive gas explosion. Quantification of the risk and consequences associated with such events is central in the design of tunnels and routing of dangerous goods. TNO previously developed a Quantitative Risk Analysis (QRA) method, which combines a probability assessment with state-of-the-art explosion effect and consequence models. The current article extends this model to combine the dispersion of a flammable cloud with its probability of ignition and the resulting physical effects such as overpressure. The model assumes an increasing probability of ignition with both the number and the duration of vehicles present within the flammable cloud. Various case studies are considered to illustrate the effect of different ignition probability parameters. These cases deal with instantaneous and continuous LPG releases with varying release rates including the effect of ventilation. They clearly show the capability to quantify the ignition probabilities and gas explosion load. The combination of the gas dispersion, gas explosion and ignition probability models are needed to derive design loads for tunnels, to perform tunnel risk assessments, and to develop safety measures. These models form the backbone for quantitative risk assessments. [ABSTRACT FROM AUTHOR]

Reported in this paper is a novel application of statistical analysis of structural fire hazards that were found in heritage housing stock in a metropolitan area. The structural fire hazards in terms of non-compliances to the building regulations are digitised and then subjected to statistical analysis to obtain estimates of probabilities of occurrence under various conditions. The concepts of Hamming distance, Jaccard distance, virtual distance and pairwise Phi correlation coefficients are employed in the analysis to estimate the association between the fire hazards. Estimates of the probability distribution over the number of joint occurrence of hazards and pairwise joint probabilities are also obtained. In addition the 3-tuple and 4-tuple joint probabilities are analysed. Finally, logistic regression models are established to correlate each fire hazard with the others. The results show that not only the probability of occurrence of structural fire hazards is high, but probability of multiple occurrence is also significant. There are indications that some structural fire hazards are correlated. The findings of this study may assist certifying authorities, building surveyors, fire safety engineers and fire services in identifying fire hazards in heritage buildings and developing alleviating and effective strategies or solutions to protect life safety of building occupants as well as the cultural heritage values of the relevant building stock. [ABSTRACT FROM AUTHOR]