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Review of Artificial Neural Networks for Wind Turbine Fatigue Prediction

Structural Durability & Health Monitoring 2024年第6期18卷 707-737页

作者： Husam AlShannaq aly mousaad aly Windstorm Impact Science and Engineering(WISE)Research LabLouisiana State UniversityBaton RougeLA 70803USA

Wind turbines have emerged as a prominent renewable energy source *** monitoring and detection methods are crucial to enhance their operational effectiveness,particularly in identifying fatigue-related *** review focuses on leveraging artificial neural networks(ANNs)for wind turbine monitoring and fatigue detection,aiming to provide a valuable reference for researchers in this domain and related *** various ANN techniques,including General Regression Neural Network(GRNN),Support Vector Machine(SVM),Cuckoo Search Neural Network(CSNN),Backpropagation Neural Network(BPNN),Particle Swarm Optimization Artificial Neural Network(PSO-ANN),Convolutional Neural Network(CNN),and nonlinear autoregressive networks with exogenous inputs(NARX),we investigate the impact of average wind speed on stress transfer function and fatigue damage in wind turbine *** findings indicate significant precision levels exhibited by GRNN and SVM,making them suitable for practical *** demonstrates superiority over BPNN and PSO-ANN in predicting blade fatigue life,showcasing enhanced accuracy,computational speed,precision,and convergence rate towards the global ***,CNN and NARX models display exceptional accuracy in classification *** results underscore the potential of ANNs in addressing challenges in wind turbine monitoring and fatigue ***,it’s important to acknowledge limitations such as data availability and model *** research should explore integrating real-time data and advanced optimization techniques to improve prediction accuracy and applicability in real-world *** summary,this review contributes to advancing the understanding of ANNs’efficacy in wind turbine monitoring and fatigue detection,offering insights and methodologies that can inform future research and practical applications in renewable energy systems.

关键词： Wind turbine fatigue prediction artificial neural network

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Assessing aerodynamic loads on low-rise buildings considering Reynolds number and turbulence effects: a review

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Advances in Aerodynamics 2022年第1期4卷 512-544页

作者： Md Faiaz Khaled aly mousaad aly Windstorm Impact Scienceand Engineering(WISE)Research LaboratoryDepartment of Civil and Environmental EngineeringLouisiana State UniversityBaton RougeUSA

This paper presents an extensive review of existing techniques used in estimating design wind pressures considering Reynolds number and turbulence effects,as well as a case study of a reference building investigated *** shed light on the limitations of current aerodynamic testing techniques,provisions in design standards,and computational fluid dynamics(CFD)methods to predict wind-induced *** paper highlights the reasons for obstructing the standardization of the wind tunnel ***,we introduce improved experimental and CFD techniques to tackle the identified *** provides superior and efficient performance by employing wall-modeled large-eddy simulation(WMLES)and hybrid RANS-LES *** addition,we tested a large-scale building model and compared the results with published small-scale *** findings reinforce our hypothesis concerning the scaling issues and Reynolds number effects in aerodynamic testing.

关键词： Atmospheric boundary layer Low-rise buildings Reynolds number Turbulence modeling LES Wind tunnel testing Open-jet testing Hybrid RANS-LES

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Experimental investigation of the aerodynamics of a large industrial building with parapet

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Advances in Aerodynamics 2021年第1期3卷 455-476页

作者： aly mousaad aly Matthew Thomas Hamzeh Gol-Zaroudi Windstorm Impact Science and Engineering(WISE)LaboratoryDepartment of Civil and Environmental EngineeringCollege of EngineeringLouisiana State University3230H Patrick F.Taylor HallBaton RougeLA 70803USA

The aerodynamic performance of a roof depends significantly on its shape and size,among other *** instance,large roofs of industrial low-rise buildings may behave differently compared to those of residential *** main objective of this study is to experimentally investigate how perimeter solid parapets can alter the flow pattern around a low-rise building with a large aspect ratio of width/height of about 7.6,the case of industrial buildings/shopping *** parapets of varied sizes are added to the roof and tested in an open-jet simulator in a comparative study to understand their impact on roof pressure *** pressures were measured in the laboratory for cases with and without parapets under different wind direction angles(representative of straight-line winds under open terrain conditions).The results show that using a parapet can alter wind pressures on large *** can modify the flow pattern around buildings and change the mean and peak *** mean pressure pattern shows a reduction in the length of the separation bubble due to the *** parapet of 14%of the building’s roof height is the most efficient at reducing mean and peak pressures compared to other parapet heights.

关键词： Aerodynamics Open-jet testing Turbulence Pressure measurement Lowrise buildings Parapet

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