Technical Programme

Session: T24Machine Learning for Reliability, Maintenance and Safety


Application of an Unvalidated ProcessModel to Define Operational Functional Failures
M. Schwarz, P. Schepers, J. Van Boggelen, R. Loendersloot and T. Tinga


Machine Learning for Risk Ranking Automation in IRSN Level 2 PSA
Guillaume Kioseyian and Marine Marcilhac-Fradin


Pipe Drift Estimation Based on the Measurements of Geometrical Parameters from a Single Pipe
Luca Bellani, Michele Compare, Enrico Zio Gustavo Almeida and Pedro Filgueiras


Meta-learning Potential to Assess Uncertainties in Dynamic Risk Management
Elena Stefana and Nicola Paltrinieri


Development of a Bivariate Machine-Learning Approach for Decision-Support in Offshore Drilling Operations
Surbhi Bansal, Nejm Saadallah, Jon T. Selvik and Eirik B. Abrahamsen


Bayesian Model Updating of Reliability Parameters using Transitional Markov Chain Monte Carlo with Slice Sampling
Adolphus Lye, Alice Cicirello and Edoardo Patelli


Adaptive Monte Carlo Simulation for Detecting Critical Regions in Accident Analyses
Martina Kloos, Nadine Berner and Joerg Peschke


Lessons from Past Hazardous Events: Data Analytics for Severity Prediction
Nicola Paltrinieri, Riccardo Patriarca, Michael Pacevicius and Pierluigi Salvo Rossi


Increasing Safety at Smart Elderly Homes by Human Fall Detection from Video Using Transfer Learning Approaches
Zahra Kharazian, Mahmoud Rahat, Emad Fatemizadeh and Ali Motie Nasrabadi


Deep Learning Approach for Short-Term Storm Forecasting
François-Xavier Ferlande and Guillaume Hochard


Research on Nonlinear Hysteresis of the Flight Control System
Yihan Guo, Cunbao Ma, Haotian Niu, Zhiyu She and Yan Liang


Audio-Visual and Heart Signals for Attention and Emotion Analysis
Ilyes Bendjoudi, Denis Hamad, Frédéric Vanderhaegen and Fadi Dornaika


A Physics-Informed Deep Learning Approach for Fatigue Crack Propagation
Sergio Cofre-Martel, Enrique Lopez Droguett and Mohammad Modarres


Optimizing Replacement of Power Distribution Network Cables with Graph Computing and Machine Learning
Jeremie Merigeault, Sebastien Folleville and Odilon Faivre


Knowledge-Enabled Machine Learning for Predictive Diagnostics: A Case Study for an Automotive Diesel Particulate Filter
Aleksandr Doikin, Felician Campean, Daniel Neagu, Martin Priest, Morteza Soleimani and Chunxing Lin


Graphical Models for Missing Data Analysis in Reliability
Vimal.V and S K Chaturvedi


Theory-Guided Machine Learning For Licensee Event Reports of U.S. Nuclear Power Plants to Quantify Organizational Factors in Probabilistic Risk Assessment
Justin Pence, Jaemin Yang, Pegah Farshadmanesh, Tatsuya Sakurahara, Seyed Reihani and Zahra Mohaghegh


Localizing Cliff-Edge Effects in Accident Analyses Via an Adaptive Gauss Process Sampling Approach
Nadine Berner, Martina Kloos and Joerg Peschke