A time-dependent probabilistic model for fire accident analysis

2020 ◽  
Vol 111 ◽  
pp. 102891 ◽  
Author(s):  
Ruochen Yang ◽  
Faisal Khan ◽  
Mohammed Taleb-Berrouane ◽  
Depeng Kong
2019 ◽  
Vol 26 (4) ◽  
pp. 322-335 ◽  
Author(s):  
Paulina Urban ◽  
Vahid Rezaei ◽  
Grzegorz Bokota ◽  
Michał Denkiewicz ◽  
Subhadip Basu ◽  
...  

2019 ◽  
Vol 9 (20) ◽  
pp. 4265 ◽  
Author(s):  
Jang ◽  
Min

Failure mode and effect analysis (FMEA) is a structured technique for identifying risks that may occur during a given stage of a system’s life cycle. However, the use of the risk priority number (RPN) in traditional FMEA results in difficulties with regard to quantification of the degree of risk in the hierarchical failure structure. This study proposes the use of a hierarchical time-dependent FMEA approach to overcome the limitations encountered during the implementation of traditional FMEA approaches. In place of the RPN, a probabilistic loss model is developed under a hierarchical structure considering the elapsed time from the failure-cause (FC) to the system failure. By assuming exponential and case functions for each occurrence and detection time instant, the expected loss corresponding to each FC can be evaluated. As a result of the practical application of the time-dependent probabilistic model through the numerical example, we could reasonably evaluate the risk from the cause of failure in the hierarchical structure in terms of economic loss.


2013 ◽  
Vol 361-363 ◽  
pp. 1315-1318
Author(s):  
Xiao Hui Xia ◽  
Yang He

A large number of design, construction and maintenance measures may be selected by bridge engineers to help ensure safe and durable service. In the present paper an improved model is developed for time-dependent reliability estimation of RC bridge decks subject to general and localized corrosion. The preliminary model developed is improved by considering weakening of the bond interface between concrete and reinforcement as a result of reinforcement corrosion and serviceability limit states in the time-dependent reliability analysis. A probabilistic model is developed that relates loss of reinforcement area to a non-linear bond stressstrain relationship.


Data in Brief ◽  
2019 ◽  
Vol 25 ◽  
pp. 104243
Author(s):  
Alessandro Mancuso ◽  
Michele Compare ◽  
Ahti Salo ◽  
Enrico Zio

Author(s):  
Andrew Francis ◽  
Chas Jandu

Stress corrosion cracking (SCC) poses a threat to integrity of buried pipelines in many parts of the world. In North America there is now a requirement that integrity management plans should address SCC and a direct assessment methodology, SCCDA, for managing the threat due to SCC, is now becoming established. Like general corrosion or fatigue, SCC is a time dependent deterioration process that leads to progressive weakness of the pipe wall eventually causing failure as a leak or rupture, if not managed. There are indeed two known forms of SCC; High-pH and near neutral-pH SCC. The focus of this paper is on High-pH SCC. High-pH SCC involves a number of phases including incubation, initiation, anodic growth, coalescence, mechanical growth and final failure. Factors affecting these processes include temperature, static and cyclic stress, soil conditions, type of coating and level of Cathodic Protection. Some of these factors may vary seasonally. The temporal development of SCC damage is thus both complex and subject to significant uncertainty. The purpose of this paper is to describe a detailed probabilistic model that addresses the various phases of High-pH SCC taking account of uncertainty in the relevant influencing factors. The model determines the likely times to coalescence and to grow to a critical size thus providing a time dependent probability of failure. The model gives a clear indication of which parameters should be managed in order to reduce the likelihood of failure to an acceptable level. The model provides the basis of a powerful decision making tool for the purpose of managing High pH SCC. Consequently, the model can be used in conjunction with relevant in-line inspection data and/or above ground survey data to provide an effective SCC integrity management tool. The model is illustrated through a numerical example and the use of the model as an integrity management tool is clearly demonstrated.


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