Estimating forces from cross-sectional data in the wake of flows past a plate using theoretical and data-driven models

doi:10.1063/5.0125374

CORC > 力学研究所 > 中国科学院力学研究所 > 非线性力学国家重点实验室

	Estimating forces from cross-sectional data in the wake of flows past a plate using theoretical and data-driven models
	Tong, Wenwen 4; Wang SZ(王士召)2,3; Yang, Yue 1,4
刊名	PHYSICS OF FLUIDS
	2022-11-01
卷号	34 期号:11 页码:19
ISSN号	1070-6631
DOI	10.1063/5.0125374
通讯作者	Yang, Yue()
英文摘要	We report a comparative study of theoretical and data-driven models for estimating forces from velocity data in the wake of three-dimensional flows past a plate. The datasets with a range of angles of attack are calculated using the immersed boundary method. First, we develop a theoretical model to estimate forces on a flat plate from cross-sectional velocity data in the far wake. This algebraic model incorporates the local momentum deficit and pressure variation. Second, we develop several data-driven models based on the convolutional neural network (CNN) for force estimation by regarding the velocity field on a series of cross sections as images. In particular, we design three CNN architectures for integrating physical information or attention mechanism, and use different training datasets for interpolation and extrapolation tasks. The model performances indicate that the optimized CNN can identify important flow regions and learn empirical physical laws. The theoretical and CNN models are assessed by multiple criteria. In general, both models are accurate (with errors less than 10%), robust, and applicable to complex wake flows. The theoretical model is superior to the CNN model in terms of the completeness, cost, and interpretability, and the CNN model with the appropriate training data and optimized CNN architecture has better description and accuracy. Published under an exclusive license by AIP Publishing.
分类号	一类/力学重要期刊
资助项目	National Natural Science Foundation of China[91952108] ; National Natural Science Foundation of China[11925201] ; National Natural Science Foundation of China[11988102] ; National Numerical Wind Tunnel Project[NNW2021ZT6-B36] ; National Key R&D Program of China[2020YFE0204200] ; Xplore Prize
WOS关键词	FLUID DYNAMIC FORCES ; VELOCITY-FIELDS ; FREE-FLIGHT ; PERFORMANCE ; BODIES ; LIFT ; BAT
WOS研究方向	Mechanics ; Physics
语种	英语
WOS记录号	WOS:000880314400002
资助机构	National Natural Science Foundation of China ; National Numerical Wind Tunnel Project ; National Key R&D Program of China ; Xplore Prize
其他责任者	Yang, Yue
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/90774]
专题	力学研究所_非线性力学国家重点实验室
作者单位	1.Peking Univ, HEPDS CAPT, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China; 3.Chinese Acad Sci, Inst Mech, LNM, Beijing 100190, Peoples R China; 4.Peking Univ, Coll Engn, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China;
推荐引用方式 GB/T 7714	Tong, Wenwen,Wang SZ,Yang, Yue. Estimating forces from cross-sectional data in the wake of flows past a plate using theoretical and data-driven models[J]. PHYSICS OF FLUIDS,2022,34(11):19.
APA	Tong, Wenwen,王士召,&Yang, Yue.(2022).Estimating forces from cross-sectional data in the wake of flows past a plate using theoretical and data-driven models.PHYSICS OF FLUIDS,34(11),19.
MLA	Tong, Wenwen,et al."Estimating forces from cross-sectional data in the wake of flows past a plate using theoretical and data-driven models".PHYSICS OF FLUIDS 34.11(2022):19.