Machine learning for risk and resilience assessment in structural engineering: Progress and future trends

X Wang, RK Mazumder, B Salarieh… - Journal of Structural …, 2022 - ascelibrary.org
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …

A comprehensive review and comparison of the fragility curves used for resilience assessments in power systems

A Serrano-Fontova, H Li, Z Liao, MR Jamieson… - IEEE …, 2023 - ieeexplore.ieee.org
Over the years, power systems have been severely affected by extreme events. This
situation has worsened given that climate change has proven to exacerbate their frequency …

An integrated methodology for dynamic risk prediction of thermal runaway in lithium-ion batteries

H Meng, Q Yang, E Zio, J Xing - Process Safety and Environmental …, 2023 - Elsevier
The risk of thermal runaway in lithium-ion battery (LIB) attracts significant attention from
domains of society, industry, and academia. However, the thermal runaway prediction in the …

Wind-induced failure analysis of a transmission tower-line system with long-term measured data and orientation effect

W Bi, L Tian, C Li, Z Ma, H Pan - Reliability Engineering & System Safety, 2023 - Elsevier
This paper proposes a comprehensive wind-induced performance evaluation framework for
transmission tower-line systems (TTLSs) from both structural safety and normal operation …

Predicting wind-caused floater intrusion risk for overhead contact lines based on Bayesian neural network with spatiotemporal correlation analysis

J Wang, S Gao, L Yu, D Zhang, C Ding, K Chen… - Reliability Engineering & …, 2022 - Elsevier
Wind-caused floater intrusion has posed enormous threats to the safety and resilience of
overhead contact lines (OCLs) of electrified railway. In this paper, a Bayesian neural network …

A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network

J Wang, S Gao, L Yu, C Ma, D Zhang, L Kou - Reliability Engineering & …, 2023 - Elsevier
Due to completely working under open-air conditions without backup equipment, the
overhead contact lines (OCLs) are suffering from external extreme weather conditions …

Spatial–temporal resilience assessment of distribution systems under typhoon coupled with rainstorm events

W Zhang, C Zhang, Q Zhou, J Li, L Zhu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
This article proposes a novel spatial–temporal resilience assessment scheme for the
distribution system (DS) to address the issue of overoptimistic and potentially misleading …

Machine learning for power outage prediction during hurricanes: An extensive review

K Fatima, H Shareef, FB Costa, AA Bajwa… - … Applications of Artificial …, 2024 - Elsevier
The surge of machine learning (ML) applications and increasing usage of data driven
approach for resilience enhancement provide great opportunities for applying ML …

A hybrid physics-based and data-driven model for power distribution system infrastructure hardening and outage simulation

W Hughes, W Zhang, D Cerrai, A Bagtzoglou… - Reliability Engineering & …, 2022 - Elsevier
Power outages caused by severe storms produce enormous economic losses and societal
disruptions. Infrastructure hardening for a more resilient power grid can reduce weather …

An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclones

X Huang, N Wang - Reliability Engineering & System Safety, 2024 - Elsevier
High winds from tropical cyclones can cause significant damages to power transmission
system and lead to widespread power outages resulting in tangible socio-economic losses …