F
Faisal Khan
Researcher at Memorial University of Newfoundland
Publications - 785
Citations - 28657
Faisal Khan is an academic researcher from Memorial University of Newfoundland. The author has contributed to research in topics: Risk assessment & Risk analysis. The author has an hindex of 70, co-authored 705 publications receiving 21281 citations. Previous affiliations of Faisal Khan include Royal Hobart Hospital & Australian Maritime College.
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Landfarming operation of oily sludge in arid region--human health risk assessment.
TL;DR: Volatilization is observed as the main process of hydrocarbon degradation, which can cause significantly high concentration of airborne volatile organic compounds (VOCs) in the atmosphere leading to serious human health risk to the onsite workers.
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Analysis on accident-causing factors of urban buried gas pipeline network by combining DEMATEL, ISM and BN methods
TL;DR: The effectiveness and applicability of the proposed model has been validated in a case study, which indicates that the model is plausible in providing explicit risk information to support better safety management by prioritizing actions to prevent interrelated accidents.
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An integrated method for human error probability assessment during the maintenance of offshore facilities
Rouzbeh Abbassi,Faisal Khan,Vikram Garaniya,Shuhong Chai,Christopher Chin,Khandoker Abul Hossain +5 more
TL;DR: A novel approach for Human Error Probability (HEP) assessment is presented by integrating the Success Likelihood Index Method (SLIM) with the Technique of Human Error Rate Prediction (THERP) to generate the nominal HEP data when it is unavailable.
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Accident modeling approach for safety assessment in an LNG processing facility
TL;DR: In this article, the authors developed an accident modeling approach, SHIPP (System Hazard Identification, Prediction and Prevention), which identifies possible causal factors and potential consequences and provides quantitative results by combining fault and event tree analyses.
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An integrated approach for fire and explosion consequence modelling
TL;DR: In this paper, the authors proposed a novel approach to model the entire sequences involved in a potential accident using liquid and gas release incidents as two test cases using Computational Fluid Dynamics (CFD) codes FLACS and FDS.