Dynamic Risk Analysis in the Chemical and Petroleum Industry 2016
DOI: 10.1016/b978-0-12-803765-2.00015-9
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Human Reliability Analysis in the Petroleum Industry

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Cited by 15 publications
(11 citation statements)
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“…According to Paltrinieri, N., & Khan, F. I. ( 2016), an investment will break even at a given rate when the present value of all future cash flows equals the initial investment, which is called the internal rate of return (IRR) [2]. Financial managers prefer it since it is expressed in percentage terms, they can simply make a comparison between the IRR and the required rate of return, in other words, to estimate the potential profitability of an investment project [3].…”
Section: The Irr Investment Theorymentioning
confidence: 99%
“…According to Paltrinieri, N., & Khan, F. I. ( 2016), an investment will break even at a given rate when the present value of all future cash flows equals the initial investment, which is called the internal rate of return (IRR) [2]. Financial managers prefer it since it is expressed in percentage terms, they can simply make a comparison between the IRR and the required rate of return, in other words, to estimate the potential profitability of an investment project [3].…”
Section: The Irr Investment Theorymentioning
confidence: 99%
“…A detailed integration is necessary for industrial applications. For instance, accurate human reliability indicators may be integrated by the SPAR-H (standardized plant analysis risk-human reliability analysis) method to estimate human error probabilities in the petroleum industry [77][78][79].…”
Section: Peer Reviewmentioning
confidence: 99%
“…More collaboration among companies and academia and authorities can also be seen. The second trend is concerned with making risk assessments less static and more dynamic (Paltrinieri and Khan, 2016). Dynamic risk analyses include advanced mathematical-based techniques being developed in the academia including Markov chains (Shu and Zhao, 2014), Event sequence diagrams (Zhou et al, 2016), Petri-nets (Zhou and Reniers, 2016a,b,c), and Bayesian Networks Khakzad, 2015;Khakzad and Reniers, 2016;Khakzad and Reniers, 2015a).…”
Section: Current Evolutionary Trends To Improve Safety (And Security)...mentioning
confidence: 99%
“…During the past decade, the attempts in the field of dynamic risk assessment have been made to address factors such as dynamic procedures for atypical scenario identification (including black swan and grey swan events), dynamic hazard identification (as a substitute for conventional static techniques such as FMEA, HAZOP, etc. ), reactive and proactive approaches for probability updating using leading and lagging risk indicators, which in turn would result in a more effective uncertainty modeling, dynamic consequence analysis so as to consider temporal variations of contributing parameters such as vulnerability, economic conditions, etc., and dynamic risk management (for a detail discussion see Paltrinieri and Khan, 2016). Despite remarkable innovations in the field of quantitative risk analysis (QRA) as a tool to improve safety, design, licensing, and operational processes, still methods for uncertainty handling and, more importantly, validation and verification of QRA results are lacking.…”
Section: Safety Innovation and Dynamic Risk Assessmentsmentioning
confidence: 99%