Weifei Hu
Cornell University
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Weifei Hu.
Engineering Optimization | 2013
Weifei Hu; Dohyun Park; Dong-Hoon Choi
A composite blade structure for a 2 MW horizontal axis wind turbine is optimally designed. Design requirements are simultaneously minimizing material cost and blade weight while satisfying the constraints on stress ratio, tip deflection, fatigue life and laminate layup requirements. The stress ratio and tip deflection under extreme gust loads and the fatigue life under a stochastic normal wind load are evaluated. A blade element wind load model is proposed to explain the wind pressure difference due to blade height change during rotor rotation. For fatigue life evaluation, the stress result of an implicit nonlinear dynamic analysis under a time-varying fluctuating wind is converted to the histograms of mean and amplitude of maximum stress ratio using the rainflow counting algorithm Miners rule is employed to predict the fatigue life. After integrating and automating the whole analysis procedure an evolutionary algorithm is used to solve the discrete optimization problem.
12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference | 2012
Weifei Hu; Nicholas J. Gaul; Olesya I. Zhupanska
This study presents a methodology that analyzes the fatigue reliability of a composite wind turbine blade considering wind load uncertainty. To facilitate the reliability analysis of wind turbine design, the turbulent random wind field has been simulated and characterized by two random variables, 10-minute mean wind speed and 10-minute turbulence intensity factor. The well-known Weibull distribution of 10-minute mean wind speed has been validated by statistically analyzing measured wind speed data. A log-logistic distribution is first proposed to represent the distribution of 10-minute turbulence intensity factor. By using both the mean wind speed and the turbulence intensity factor, the chaotic characteristic of a random wind field can be accurately rendered. The uncertainties of parameters determining the Weibull and log-logistic distribution are further studied such that the spatiotemporal wind uncertainty can be accurately represented. A hierarchical expanded wind uncertainty representation method is proposed for reliability analysis of wind turbine blades. A comprehensive procedure, including random wind simulation, aerodynamic analysis, composite structural analysis and fatigue damage calculation has been realized to predict the fatigue life of a simulated blade model. The reliability of a 5-MW reference wind turbine blade is evaluated to investigate the effect of the spatiotemporal wind uncertainty towards fatigue life.
32nd ASME Wind Energy Symposium | 2014
Weifei Hu; Olesya I. Zhupanska; James Buchholz; Kyung K. Choi
A fatigue analysis procedure including random wind field simulation, aerodynamic analysis, stress analysis by finite element analysis, and fatigue damage evaluation based on tested fatigue data has been developed for large horizontal axis wind turbine blades. In order to simulate realistic wind loads applied on the blade while maintaining affordable computation time, the sectional surface pressure fields obtained from XFOIL are modified to match the lift, drag, and moment coefficients obtained using NREL’s AeroDyn. Thus the modified pressure distribution includes the effect of the dynamic stall and the wake on the turbine rotor aerodynamics. A high-fidelity finite element blade model, which could easily tailor the design of composite materials in the blade, has been parameterized for the detailed stress analyses. Constant life diagrams based on the tested fatigue data have been constructed for fatigue damage evaluation under multi-axial complex stress states of variable amplitude. Starting from the random wind field simulation, the evaluated fatigue damage is determined by two random variables, 10-minute mean wind speed and 10-minute turbulence intensity factor. Consequently, the effect of mean wind speed and atmospheric turbulence toward blade fatigue can be investigated. The proposed fatigue analysis procedure can facilitate the reliability analysis and reliability-based design optimization of composite wind turbine blades considering wind load uncertainty.
Journal of Applied Meteorology and Climatology | 2018
Weifei Hu; F. Letson; R. J. Barthelmie; S. C. Pryor
AbstractImproved understanding of wind gusts in complex terrain is critically important to wind engineering and specifically the wind energy industry. Observational data from 3D sonic anemometers d...
Structural and Multidisciplinary Optimization | 2016
Weifei Hu; Kyung K. Choi; Hyunkyoo Cho
Structural and Multidisciplinary Optimization | 2016
Weifei Hu; Kyung K. Choi; Olesya I. Zhupanska; James Buchholz
Journal of Wind Engineering and Industrial Aerodynamics | 2018
F. Letson; S. C. Pryor; R. J. Barthelmie; Weifei Hu
대한기계학회 춘추학술대회 | 2009
Weifei Hu; Sang-Joon Yoon; Sang-Chul Park; Donghoon Choi
international conference on fuel cell science engineering and technology fuelcell collocated with asme international conference on energy sustainability | 2017
Weifei Hu; S. C. Pryor; F. Letson; R. J. Barthelmie
international conference on fuel cell science engineering and technology fuelcell collocated with asme international conference on energy sustainability | 2017
Weifei Hu; Yeqing Wang