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Dynamic risk assessment of inherently safer chemical processes: An accident precursor approach

Posted on:2008-06-20Degree:Ph.DType:Thesis
University:University of PennsylvaniaCandidate:Meel, AnjanaFull Text:PDF
GTID:2441390005951238Subject:Health Sciences
Abstract/Summary:
Accidents in chemical plants potentially involve the loss of human lives, huge economic losses, and legal complications. These consequences have inspired the development of techniques in this thesis to improve the inherent safety and perform dynamic risk assessment, as vital ingredients in the planning, design, and operation of chemical plants.; Initially, multi-objective process designs using Game theory are developed to increase their inherent safety, thereby resulting in lower frequencies of abnormal events. Extended bifurcation diagrams are introduced to provide an improved understanding of processes having instability and non-minimum-phaseness. Applications of the proposed method to an isothermal, continuous, stirred-tank reactor (CSTR), an exothermic CSTR, and an anaerobic fermentor, are presented.; In spite of inherently safer designs, the occurrence of abnormal events is inevitable in chemical operations. Consequently, methods are developed for plant-specific, dynamic, risk assessment using Bayesian analysis with copulas that analyze abnormal events. More specifically, three analyzers are developed: (i) a forecasting analyzer that predicts the frequencies of occurrence of abnormal events, (ii) a reliability analyzer that predicts the failure probabilities of safety systems involving equipments and human actions, and (iii) an accident closeness analyzer that predicts the proximity of a current plant state to a failure or disaster, through the use of accident precursor data. In addition, the propagations of abnormal events through the safety systems are modeled in real-time for a continuous ethyl-benzene process.; Furthermore, the role of consequences, with their frequencies, in risk estimation led to the development of a fast-Fourier transform-based method to estimate the capital-at-risk within an industry utilizing frequency and loss-severity distributions. The model has been tested using data in the National Response Center database for companies in Harris County, Texas.; Finally, the importance of human behavior on plant safety is examined. A framework to estimate the impacts of management and engineering decisions, operator performance, and equipment operations, on the failure state is introduced. Also, a game-theoretic model is developed to balance the advantages and disadvantages of having a Near-miss Management System with different sophistication levels.
Keywords/Search Tags:Chemical, Risk assessment, Accident, Abnormal events, Analyzer that predicts, Dynamic, Developed
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