The eighth edition of the International Conference on System Reliability and Safety (ICSRS 2024) www.icsrs.org, a landmark event for the international scientific community in the field of system reliability and safety, was held in Sicily from 20 to 22 November 2024. The conference was co-sponsored by the IEEE Reliability Society (Italy Chapter) and was attended by experts from all over the world. Among the topics covered: artificial intelligence and advanced simulation for reliability, safety, resilience of complex systems.

Key roles in the conference

Several lecturers from the Systems Analysis Laboratory for Reliability, Risk and Resilience Analysis (LASAR³ – www.lasar.polimi.it ) of the Department of Energy had key roles in organising the event:

• Prof. Enrico Zio – Conference General Chair
• Prof. Piero Baraldi – Technical Program Chair
• Prof. Francesco Di Maio – Local Organizing Chair

Session Chair and Keynote Lecture

The Department’s lecturers and researchers also coordinated and chaired several thematic sessions:

• Prof. Francesco Di Maio – Session Chair Risk Assessment 1
• Prof. Masoud Naseri – Session Chair Risk Assessment 2
• Dott. Ali Hosseini – Session Chair Safety Analysis in the Energy Sector
• Dott. Luca Pinciroli – Session Chair Methods for Anomaly Detection
• Dott. Dario Valcamonico – Session Chair Safety Analysis

Oral presentations and scientific contributions

Among the most relevant speeches presented by members of the Department:

• Prof. Francesco Di Maio
  • “ARtificial Intelligence and STOchasTic Simulation for the rEsiLience of Critical InfrastructurES (ARISTOTELES)”
  • “Simulation-based Probabilistic Risk Assessment (SIMPRA) of Integrated Road-Power Infrastructures Travelled by EVs and ICVs”
• Prof. Ibrahim Ahmed – Oral Presentation:
  • “Critical Heat Flux Prediction by Physics-informed Neural Networks”
• Dott. Ali Hosseini – Oral Presentation:
  • “A Dynamic Bayesian Network for the Performance Assessment of Nuclear Waste Repositories Undergoing Chemical Degradation due to Climate Change”

• Dott. Luca Pinciroli – Oral Presentation:
  • “Anomaly Detection of Renewable Energy Systems by Unsupervised Graph Neural Networks”

Contributions of STEN doctoral students

In addition to the lecturers and researchers of the LASAR³ research group (www.lasar.polimi.it ), the students of the Energy and Nuclear Science and Technology – STEN PhD course of the Department of Energy who presented their scientific work are:

• Mudi Jiang – Bayesian Deep Learning Framework with Variational Inference for Uncertainty Quantification in RUL Prediction

• Haoran Liu – Analysis of Three-dimensional (3-D) Warranty Data Considering Fluctuated Sales and Heterogeneous Failures

• Stefano Marchetti – A Deep Reinforcement Learning method for finding the risk-based optimal prescriptive maintenance policy of degrading safety barriers

• Giovanni Roma – Severe Accident Management of Nuclear Power Plants by A Condition-Informed Dynamic Bayesian Network

• Santiago Taguado Menza – Artificial Intelligence (AI) – Accelerated Stochastic Simulation for the Resilience Assessment of Critical Energy Infrastructures

• Zongyao Wang – A Sample Synthesis Method for Railway Track Circuit Fault Diagnosis Based on Variational Autoencoder and Improved SMOTEENN

• Weijun Xu – Uncertainty-Aware Prediction of Remaining Useful Life

• Yike Zhao – Deep Neural Network based on Domain Adaptation for the Prediction of Critical Parameters in Hazardous Plants

• Shiyu Chen – Production Planning Optimization of Energy Supply Chain based on the Agent-based Cooperative Framework

• Maria Valentina Clavijo Mesa – Inoperability Assessment of Interdependent Critical Infrastructures by Minimal Inoperability Sets Analysis

• Thomas Coscia – Probabilistic Safety Assessment of Nuclear Power Plants under Climate Change

• Mijie Du – Power Network Vulnerability Assessment Considering Spatial Heterogeneity Demand

• Giovanni Floreale – Improving the Performance of PHM Models by Post-hoc Explainable Artificial Intelligence (XAI) with Automatic Processing of Explanations

• Juan Pablo Futalef – A Classification Problem Formulation for the Reliability Assessment of End-To-End Communication among Cyber Devices of Cyber-Physical Systems