Yiming Zhou¹, Jinhua Zhang^2,3, Kai Long^2,*, Ayesha Saeed², Yutang Chen², Rongrong Geng², Tao Tao⁴, Xiaohui Guo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1743-1761, 2025, DOI:10.32604/cmes.2025.063034 - 30 May 2025

Abstract The jacket structure and transition piece comprise the supporting structure of a bottom-fixed offshore wind turbine (OWT) connected to the steel tower, which determines the overall structural dynamic performance of the entire OWT. Ideally, optimal performance can be realized by effectively coordinating two components, notwithstanding their separate design processes. In pursuit of this objective, this paper proposes a concurrent design methodology for the jacket structure and transition piece by exploiting topology optimization (TO). The TO for a three-legged jacket foundation is formulated by minimizing static compliance. In contrast to conventional TO, two separated volume fractions… More >

Md. Mahbub Alam^*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.4, pp. 657-695, 2025, DOI:10.32604/fdmp.2025.060942 - 06 May 2025

Abstract Wind turbines play a vital role in renewable energy production. This review examines advancements in wind turbine blade morphing technologies aimed at enhancing power coefficients, reducing vibrations, and minimizing noise generation. Efficiency, vibration, and noise levels can be optimized through morphing techniques applied to the blade’s shape, leading edge, trailing edge, and surface. Leading-edge morphing is particularly effective in improving efficiency and reducing noise, as flow attachment and separation at the leading edge significantly influence lift and vortex generation. Morphing technologies often draw inspiration from bionic designs based on natural phenomena, highlighting the potential of More > Graphic Abstract

Wenhai Zhao¹, Wanrun Li^1,2,*, Ximei Li^1,2, Shoutu Li³, Yongfeng Du^1,2

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 593-611, 2025, DOI:10.32604/sdhm.2024.057759 - 03 April 2025

Abstract Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies, as well as the inability to achieve precise full-field monitoring, this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion. Firstly, the Lucas-Kanade Tomasi (LKT) optical flow method and a multi-region of interest (ROI) monitoring structure are employed to track pixel displacements, which are subsequently subjected to band pass filtering and resampling operations. Secondly, the actual displacement time history is derived through double integration of the acquired acceleration data and… More >

Tingrui Liu¹, Qinghu Cui^1,2, Dan Xu^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.1, pp. 1-36, 2025, DOI:10.32604/fdmp.2024.058444 - 24 January 2025

Abstract With the gradual increase in the size and flexibility of composite blades in large wind turbines, problems related to aeroelastic instability and blade vibration are becoming increasingly more important. Given their impact on the lifespan of wind turbines, these subjects have become important topics in turbine blade design. In this article, first aspects related to the aeroelastic (structural and aerodynamic) modeling of large wind turbine blades are summarized. Then, two main methods for blade vibration control are outlined (passive control and active control), including the case of composite blades. Some improvement schemes are proposed More > Graphic Abstract

Ryan Randall¹, Chunmei Chen^1,*, Mesfin Belayneh Ageze^2,3, Muluken Temesgen Tigabu⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2657-2691, 2024, DOI:10.32604/fdmp.2024.058169 - 23 December 2024

Abstract Vertical Axis Wind Turbines (VAWTs) offer several advantages over horizontal axis wind turbines (HAWTs), including quieter operation, ease of maintenance, and simplified construction. Surprisingly, despite the prevailing belief that HAWTs outperform VAWTs as individual units, VAWTs demonstrate higher power density when arranged in clusters. This phenomenon arises from positive wake interactions downstream of VAWTs, potentially enhancing the overall wind farm performances. In contrast, wake interactions negatively impact HAWT farms, reducing their efficiency. This paper extensively reviews the potential of VAWT clusters to increase energy output and reduce wind energy costs. A precise terminology is introduced More >

Baohua Li, Yi Ye, Yuanjun Dai^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2809-2842, 2024, DOI:10.32604/fdmp.2024.054011 - 23 December 2024

Abstract A linear microporous blade tip structure is designed in order to reduce the aerodynamic noise of a wind turbine during operations. Various structures of such a kind are considered and the related aerodynamic noise is determined in the framework of large vortex simulation and acoustic array test methods. The findings demonstrate that various blade tip designs can enhance the vortex trajectory in the tip region and lessen the pressure differential between the blade’s upper and lower surfaces. In particular, the wind turbine’s maximum linear velocity at the blade tip can be increased by 10%–23% while More > Graphic Abstract

Jianyong Ao¹, Yanping Li¹, Shengqing Hu¹, Songyu Gao², Qi Yao^2,*

Energy Engineering, Vol.121, No.12, pp. 3825-3841, 2024, DOI:10.32604/ee.2024.055250 - 22 November 2024

Abstract Blades are essential components of wind turbines. Reducing their fatigue loads during operation helps to extend their lifespan, but it is difficult to quickly and accurately calculate the fatigue loads of blades. To solve this problem, this paper innovatively designs a data-driven blade load modeling method based on a deep learning framework through mechanism analysis, feature selection, and model construction. In the mechanism analysis part, the generation mechanism of blade loads and the load theoretical calculation method based on material damage theory are analyzed, and four measurable operating state parameters related to blade loads are… More >

Dattu Ghane^*, Vishnu Wakchaure

Energy Engineering, Vol.121, No.11, pp. 3199-3220, 2024, DOI:10.32604/ee.2024.050952 - 21 October 2024

Abstract Wind energy provides a sustainable solution to the ever-increasing demand for energy. Micro-wind turbines offer a promising solution for low-wind speed, decentralized power generation in urban and remote areas. Earlier researchers have explored the design, development, and performance analysis of a micro-wind turbine system tailored for small-scale renewable energy generation. Researchers have investigated various aspects such as aerodynamic considerations, structural integrity, efficiency optimization to ensure reliable and cost-effective operation, blade design, generator selection, and control strategies to enhance the overall performance of the system. The objective of this paper is to provide a comprehensive design… More >

Shuang Kang¹, Yinchao He^1,2, Wenwen Li^1,*, Sen Liu²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 933-949, 2024, DOI:10.32604/cmc.2024.056614 - 15 October 2024

Abstract To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect… More >

Husam AlShannaq, Aly Mousaad Aly^*

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 707-737, 2024, DOI:10.32604/sdhm.2024.054731 - 20 September 2024

Abstract Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This 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 areas. Employing 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… More >