Framework of airfoil max lift-to-drag ratio prediction using hybrid feature mining and Gaussian process regression-Reference-Cited by-同舟云学术

Framework of airfoil max lift-to-drag ratio prediction using hybrid feature mining and Gaussian process regression

Published:2021-09 Issue: Volume:243 Page:114339
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Chen Yaoran,Dong Zhikun,Su Jie,Wang Yan,Han Zhaolong,Zhou Dai,Zhao Yongsheng,Bao Yan

Funder

Shanghai Municipal Natural Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference42 articles.

1. Challenges of grid integration of wind power on power system grid integrity: A review;Ayodele;World,2020

2. Sogukpinar H, Bozkurt I. Numerical calculation of aerodynamics wind turbine blade S809 airfoil and comparison of theoretical calculations with experimental measurements and confirming with NREL data. In: Conference Numerical calculation of aerodynamics wind turbine blade S809 airfoil and comparison of theoretical calculations with experimental measurements and confirming with NREL data, vol. 1935. AIP Publishing LLC, p. 020004.

3. Experimental and numerical icing penalties of an S826 airfoil at low Reynolds numbers;Hann;Aerospace,2020

4. Aerodynamic performance of a 5-metre-diameter Darrieus turbine with extruded aluminum NACA-0015 blades;Sheldahl;National Technical Information Service USA,1980

5. Unsteady thrust on an oscillating wind turbine: Comparison of blade-element momentum theory with actuator-line CFD;Apsley;Journal of Fluids and Structures,2020

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning and numerical simulation research on specific energy consumption for gradated coarse particle two-phase flow in inclined pipes;Physics of Fluids;2024-09-01

2. Power demand estimation techniques applied to microgrid;International Journal of Ambient Energy;2024-01-25

3. A boom damage prediction framework of wheeled cranes combining hybrid features of acceleration and Gaussian process regression;Measurement;2023-11

4. Surrogate models for twin-VAWT performance based on Kriging and artificial neural networks;Ocean Engineering;2023-04

5. A fusion framework for lithium-ion batteries state of health estimation using compressed sensing and entropy weight method;ISA Transactions;2023-04