期刊
THEORETICAL AND APPLIED MECHANICS LETTERS
卷 8, 期 6, 页码 361-365出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.taml.2018.06.004
关键词
Data-driven computational mechanics; Model-free method; Nonparametric method; Kernel regression; Nadaraya-Watson estimator
类别
资金
- JSPS KAKENHI [17K06633, 18K18898]
- Grants-in-Aid for Scientific Research [17K06633, 18K18898] Funding Source: KAKEN
This paper presents a simple nonparametric regression approach to data-driven computing in elasticity. We apply the kernel regression to the material data set, and formulate a system of nonlinear equations solved to obtain a static equilibrium state of an elastic structure. Preliminary numerical experiments illustrate that, compared with existing methods, the proposed method finds a reasonable solution even if data points distribute coarsely in a given material data set. (c) 2018 The Authors. Published by Elsevier Ltd on behalf of The Chinese Society of Theoretical and Applied Mechanics. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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