Shu Dai^1,*, Bert Sweetman²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09687

Abstract Short-term wind process is normally assumed to be a Gaussian distribution, such as TurbSim, the widely used 3D wind field tool. Nowadays, newest researches indicate that non-Gaussian wind model is believed to be more accurate according to the field observation data. A new numerical method is proposed to generate non-Gaussian wind filed using translation process theory and spectral representation method. This study presents a comprehensive investigation on power production and blades fatigue damage of floating offshore wind turbines (FOWTs) to the non-Gaussian wind field. The comparisons of Gaussian and non-Gaussian simulation results indicate that the More >

Hang Meng^1,*, Jiaxing Wu¹, Guangxing Wu¹, Kai Long¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09685

Abstract Wind energy is one of the most promising renewable energies in the world. To generate more electricity, the wind turbines are getting larger and larger in recent decades [1]. With the wind turbine size growing, the length of the blade is getting slender. The large deflections of slender wind turbine blade will inevitably lead to geometric nonlinearities [2], e.g. nonlinear coupling between torsion and deflection, which complicates the governing equations of motion. To simplify the solution of the nonlinear equations, in the current research, a novel finite-difference method was proposed to solve the nonlinear equations… More >

Chunxiu Ji¹, Dan Xie^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010329

Abstract Blade flutter is a complex phenomenon that can lead to serious damage or failure of turbomachinery systems. Predicting and mitigating blade flutter is therefore an important aspect of the design and analysis of these systems[1]. In this paper, we present a comparative study of two representative methods for blade flutter predictions: the energy method and the computational fluid dynamics/computational structural dynamics (CFD/CSD) coupled time-domain method. The energy method is a decoupled approach that uses a simplified model of the blade and fluid-structure interaction to calculate the stability boundaries of the system[2]. The time-domain method, on… More >

Jin Wang¹, Zhen Liu^1,*, Ying Wang¹, Caifeng Wen^2,3, Jianwen Wang^2,3

Energy Engineering, Vol.120, No.5, pp. 1149-1162, 2023, DOI:10.32604/ee.2023.025209 - 20 February 2023

Abstract Analyzing the strain signal of wind turbine blade is the key to studying the load of wind turbine blade, so as to ensure the safe and stable operation of wind turbine in natural environment. The strain signal of the wind turbine blade under continuous crosswind state has typical non-stationary and unsteady characteristics. The strain signal contains a lot of noise, which makes the analysis error. Therefore, it is very important to denoise and extract features of measured signals before signal analysis. In this paper, the joint algorithm of ensemble empirical mode decomposition (EEMD) and wavelet… More >

Yuxing Yang, Peng Zhang^*, Meng Lv

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1397-1409, 2023, DOI:10.32604/fdmp.2023.024916 - 30 January 2023

Abstract The performances of turbine blades have a significant impact on the energy conversion efficiency of vertical solar power plants. In the present study, such a relationship is assessed by considering two kinds of airfoil blades, designed by using the Wilson theory. In particular, numerical simulations are conducted using the SST K − ω model and assuming a wind speed of 3–6 m/s and seven or eight blades. The two airfoils are the NACA63121 (with a larger chord length) and the AMES63212; It is shown that the torsion angle of the former is smaller, and its wind drag More > Graphic Abstract

Ling Yuan¹, Zhenggang Liu^2,*, Li Li³, Ming Lin¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1129-1141, 2023, DOI:10.32604/fdmp.2023.023538 - 30 November 2022

Abstract The blades of large-scale wind turbines can obviously deform during operation, and such a deformation can affect the wind turbine’s output power to a certain extent. In order to shed some light on this phenomenon, for which limited information is available in the literature, a bidirectional fluid-structure interaction (FSI) numerical model is employed in this work. In particular, a 5 MW large-scale wind turbine designed by the National Renewable Energy Laboratory (NREL) of the United States is considered as a testbed. The research results show that blades’ deformation can increase the wind turbine’s output power by More > Graphic Abstract

Ying He, Yongshuang Wen^*, Xuemei Huang, Leian Zhang, Rujun Song, Chang Li

Energy Engineering, Vol.120, No.2, pp. 445-459, 2023, DOI:10.32604/ee.2022.022223 - 28 November 2022

Abstract In order to study the mechanical properties of the heterogeneous core plate of the wind turbine blade, a modeling method of the core plate based on displacement field variables is proposed. Firstly, the wind turbine blade core plate was modeled according to the theory of modeling heterogeneous material characteristics. Secondly, the three-point bending finite element model of the wind turbine blade core plate was solved by the display dynamic equation to obtain the deformation pattern and force-deformation relationship of the core plate. Finally, the three-point bending static test was conducted to compare with the finite More >

Hong Zhang¹, Lukai Song^1,2,*, Guangchen Bai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1871-1897, 2023, DOI:10.32604/cmes.2022.021880 - 20 September 2022

Abstract

The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like high-nonlinearity, multi-failure regions, and small failure probability, which brings in unacceptable computing efficiency and accuracy of the current analysis methods. In this case, by fitting the implicit limit state function (LSF) with active Kriging (AK) model and reducing candidate sample pool with adaptive importance sampling (AIS), a novel AK-AIS method is proposed. Herein, the AK model and Markov chain Monte Carlo (MCMC) are first established to identify the most probable failure region(s) (MPFRs), and the adaptive kernel density estimation (AKDE) importance sampling

More >

Linchuan Liu¹, Jian Wu², Zhongwei Hu², Xiaochao Jin^1,*, Pin Lu¹, Tao Zhang², Xueling Fan^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1219-1236, 2023, DOI:10.32604/cmes.2022.022221 - 31 August 2022

Abstract A virtual wall thickness method is developed to simulate the temperature field of turbine blades with thermal barrier coatings (TBCs), to simplify the modeling process and improve the calculation efficiency. The results show that the virtual wall thickness method can improve the mesh quality by 20%, reduce the number of meshes by 76.7% and save the calculation time by 35.5%, compared with the traditional real wall thickness method. The average calculation error of the two methods is between 0.21% and 0.93%. Furthermore, the temperature at the blade leading edge is the highest and the average… More >

Tingshun Li¹, Jiaohui Xu^1,*, Zesan Liu², Dadi Wang², Wen Tan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 767-782, 2023, DOI:10.32604/cmes.2022.020702 - 31 August 2022

Abstract The blades of wind turbines located at high latitudes are often covered with ice in late autumn and winter, where this affects their capacity for power generation as well as their safety. Accurately identifying the icing of the blades of wind turbines in remote areas is thus important, and a general model is needed to this end. This paper proposes a universal model based on a Deep Neural Network (DNN) that uses data from the Supervisory Control and Data Acquisition (SCADA) system. Two datasets from SCADA are first preprocessed through undersampling, that is, they are… More >