[HTML][HTML] Physics-informed machine learning: a comprehensive review on applications in anomaly detection and condition monitoring

Y Wu, B Sicard, SA Gadsden - Expert Systems with Applications, 2024 - Elsevier
Condition monitoring plays a vital role in ensuring the reliability and optimal performance of
various engineering systems. Traditional methods for condition monitoring rely on physics …

Physics-informed machine learning and its structural integrity applications: state of the art

SP Zhu, L Wang, C Luo… - … of the Royal …, 2023 - royalsocietypublishing.org
The development of machine learning (ML) provides a promising solution to guarantee the
structural integrity of critical components during service period. However, considering the …

[HTML][HTML] AK-MDAmax: Maximum fatigue damage assessment of wind turbine towers considering multi-location with an active learning approach

C Ren, Y Xing - Renewable Energy, 2023 - Elsevier
Lifetime fatigue damage prediction plays a key factor in wind turbine structure's reliability
assessment. However, the damage estimation of wind turbines requires thousands of …

A prediction method for blade deformations of large-scale FVAWTs using dynamics theory and machine learning techniques

W Deng, L Liu, Y Dai, H Wu, Z Yuan - Energy, 2024 - Elsevier
There is renewed interest in floating vertical axis wind turbines (FVAWTs) as offshore wind
turbines progressively increase in size and move into deeper waters. To explore the …

Real-time monitoring, fault prediction and health management for offshore wind turbine systems

Z Gao, P Odgaard - Renewable Energy, 2023 - Elsevier
Compared with on-shore wind turbines, off-shore wind turbines are installed in sea, which
can harvest more consistent and stronger winds. Faster wind speeds offshore mean more …

Efficient layout optimization of offshore wind farm based on load surrogate model and genetic algorithm

X Zhang, Q Wang, S Ye, K Luo, J Fan - Energy, 2024 - Elsevier
Wind farm layout optimization (WFLO) has become a significant approach to enhancing the
efficiency of wind energy utilization. However, load also represents a critical factor that must …

[HTML][HTML] Predictive model for fatigue evaluation of floating wind turbines validated with experimental data

F Pimenta, D Ribeiro, A Román, F Magalhães - Renewable Energy, 2024 - Elsevier
Estimating internal forces and corresponding fatigue damage plays a central role in the
definition of operation strategies of any wind turbine, particularly in offshore scenarios …

Multi-objective parameter optimization of large-scale offshore wind Turbine's tower based on data-driven model with deep learning and machine learning methods

B Cheng, Y Yao, X Qu, Z Zhou, J Wei, E Liang… - Energy, 2024 - Elsevier
The tower plays a crucial role in wind turbine systems. However, the design and optimization
of configuration parameters have traditionally been lacking in intelligent methods. This study …

[HTML][HTML] Offshore renewable energies: A review towards Floating Modular Energy Islands—Monitoring, Loads, Modelling and Control

E Marino, M Gkantou, A Malekjafarian, S Bali… - Ocean engineering, 2024 - Elsevier
Abstract Floating Modular Energy Islands (FMEIs) are modularized, interconnected floating
structures that function together to produce, store, possibly convert and transport renewable …

Machine learning based prediction models for uniaxial ratchetting of extruded AZ31 magnesium alloy

X Deng, Y Hu, B Hu, Z Wang, G Kang - Extreme Mechanics Letters, 2024 - Elsevier
The detrimental effect of ratchetting on the fatigue life of materials requires precise prediction
models to guarantee the safety of engineering structures. This study focuses on predicting …