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contributor authorHuang, Zhanchao
contributor authorLi, Chunjiang
contributor authorHuang, Zhilong
contributor authorWang, Yong
contributor authorJiang, Hanqing
date accessioned2022-02-06T05:35:48Z
date available2022-02-06T05:35:48Z
date copyright6/14/2021 12:00:00 AM
date issued2021
identifier issn0021-8936
identifier otherjam_88_10_101006.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4278359
description abstractThe simplified governing equations of applied mechanics play a pivotal role and were derived based on ingenious assumptions or hypotheses regarding the displacement fields for specific problems. In this paper, we introduce a data-driven method by the name AI-Timoshenko in honor of Timoshenko, father of applied solid mechanics, to automatically discover simplified governing equations for applied mechanics problems directly from discrete data simulated by the three-dimensional (3D) finite element method. The simplified governing equations are in variational form, which is compact and advantageous for data-driven discovery. AI-Timoshenko liberates applied mechanicians from burdensome labor, including assumptions, derivation, and trial and error. The simplified governing equations for Euler–Bernoulli and Timoshenko beam theories are successfully rediscovered using the present AI-Timoshenko method, which shows that this method is capable of discovering simplified governing equations for applied mechanics problems.
publisherThe American Society of Mechanical Engineers (ASME)
titleAI-Timoshenko: Automatedly Discovering Simplified Governing Equations for Applied Mechanics Problems From Simulated Data
typeJournal Paper
journal volume88
journal issue10
journal titleJournal of Applied Mechanics
identifier doi10.1115/1.4051334
journal fristpage0101006-1
journal lastpage0101006-12
page12
treeJournal of Applied Mechanics:;2021:;volume( 088 ):;issue: 010
contenttypeFulltext


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