Detalhes

TÓPICOS ESPECIAIS II - MODELAGEM BAYESIANA EM ENGENHARIA DE CONFIABILIDADE

Nome da Disciplina: TÓPICOS ESPECIAIS II - MODELAGEM BAYESIANA EM ENGENHARIA DE CONFIABILIDADE
Carga Horária: 60
Créditos: 3
Obrigatória: Não
EMENTA
Interpretações de probabilidade. Axiomas de probabilidade. Teorema de Bayes. Inferência Bayesiana e modelos hierárquicos. Árvore de Falhas Bayesiana. Árvore de Eventos Bayesianas. Modelagem de Árvore de Falhas (estática e dinâmica) via Redes Bayesianas. Modelagem de Árvore de Eventos via Redes Bayesianas. Atualização de informações. É FORTEMENTE RECOMENDADO QUE OS ALUNOS DESTA DISCIPLINA JÁ TENHAM CURSADO CONFIABILIDADE ANTERIORMENTE.
BIBLIOGRAFIA
Hamada, M. S., Wilson, A. G., Reese, C. S., & Martz, H. F. (2009). Bayesian Reliability. In: The Elements of Statistical Learning (Vol. 27). https://doi.org/10.1007/b94608 Kelly, D., & Smith, C. (2011). Bayesian Inference for Probabilistic Risk Assessment: A Practitioner’s Guidebook. Springer. Singpurwalla, N. D. (2015). Reliability and Risk Models. In Reliability and Risk Models. https://doi.org/10.1002/9781118873199 Yu, H., Khan, F., & Veitch, B. (2017). A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents. Risk Analysis, 37(9), 1668–1682. https://doi.org/10.1111/risa.12736 Cai, B., Liu, Y., Fan, Q., Zhang, Y., Yu, S., Liu, Z., & Dong, X. (2013). Performance evaluation of subsea BOP control systems using dynamic Bayesian networks with imperfect repair and preventive maintenance. Engineering Applications of Artificial Intelligence, 26(10), 2661–2672. https://doi.org/10.1016/j.engappai.2013.08.011 Cai, B., Liu, Y., Zhang, Y., Fan, Q., & Yu, S. (2013). Dynamic Bayesian network-based performance evaluation of subsea blowout preventers in presence of imperfect repair. Expert Systems with Applications, 40(18), 7544–7554. https://doi.org/10.1016/j.eswa.2013.07.064 Liu, Z., Liu, Y., Cai, B., Zhang, D., & Zheng, C. (2015). Dynamic Bayesian network modeling of reliability of subsea blowout preventer stack in presence of common cause failures. Journal of Loss Prevention in the Process Industries, 38, 58–66. https://doi.org/10.1016/j.jlp.2015.09.001 Cai, B., Liu, Y., Liu, Z., Tian, X., Dong, X., & Yu, S. (2012). Using Bayesian networks in reliability evaluation for subsea blowout preventer control system. Reliability Engineering & System Safety, 108, 32–41. https://doi.org/10.1016/j.ress.2012.07.006 Cai, B., Liu, Y., & Fan, Q. (2016). A multiphase dynamic Bayesian networks methodology for the determination of safety integrity levels. Reliability Engineering and System Safety, 150, 105–115. https://doi.org/10.1016/j.ress.2016.01.018 Cai, B., Liu, Y., Zhang, Y., Fan, Q., Liu, Z., & Tian, X. (2013). A dynamic Bayesian networks modeling of human factors on offshore blowouts. Journal of Loss Prevention in the Process Industries, 26(4), 639–649. https://doi.org/10.1016/j.jlp.2013.01.001


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