Faisal Khan

TL;DR: In this paper, a probabilistic model is developed for predicting the long-term pitting corrosion depth of steel structures in marine environment using Bayesian network, which combines an understanding of corrosion phenomenological model and empirical model calibrated using real-world data.

TL;DR: Wang et al. as discussed by the authors analyzed the current status and challenges of university laboratory safety in China and presented future directions to reduce accidents using engineering and administrative controls, and performed a descriptive statistical analysis of 110 publicly reported university laboratory accidents in mainland China since 2000.

TL;DR: In this article, the authors provide a systematic review of risk analysis research to enhance the safety performance of autonomous underwater vehicles (AUVs) and identify critical risk factors and causal relationships of AUV operations.

TL;DR: A Bayesian network-based model able to handle evolving conditions of the barriers, their failure dependence and, also uncertainty in the data is presented, which is explained and tested on a case study from the Elgin platform's well plugging and abandonment failure.

TL;DR: It was observed that given the same training, people used different sets of attributes to make decisions on the egress route, which can help to diagnose causes of poor performance and to design adaptive training lessons.