Technical Programme

Session: T24Machine Learning for Reliability, Maintenance and Safety

T24-01

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

T24-02

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

T24-03

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

T24-04

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

T24-05

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

T24-06

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

T24-07

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

T24-08

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

T24-09

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

T24-10

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

T24-11

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

T24-12

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

T24-13

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

T24-14

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

T24-15

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

T24-16

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

T24-18

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

T24-19

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