Flexible parametric FEA modeling for product family based on script fragment grammar

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Date: Oct. 2019
From: Computers in Industry(Vol. 111)
Publisher: Elsevier B.V.
Document Type: Report
Length: 287 words

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Abstract :

Keywords Parametric FEA; Ontology; SFG; FEA script generation engine (SGE) Highlights * Flexible parametric finite element analysis (FEA) model using scripts is addressed. * FEA processes are modelled as an ontology. * A script fragment grammar is obtained by instantiating FEA ontology. * A method of automatically generating parametric FEA scripts based on derivation of the script fragment grammar is proposed. * The method is applied to develop an automatically generating FEA script software for an air separator product family. Abstract The flexible finite element analysis (FEA) modeling process is addressed within the framework of scripting programming language such as ANSYS Parametric Design Language(APDL). Resorting to recently proposed upper ontology and specific ontology, the FEA modeling processes are expressed as the entities and relations among entities in an ontology tree. An algorithm to obtain a script fragment grammar (SFG) that describe the combination rules of script fragments by instantiating FEA ontology tree is provided. In addition, a method of automatically generating FEA parametric scripts based on SFG derivations is proposed. Then, the whole procedure is applied to develop an automatically generating FEA script software for an air separator product family. The proposed method can effectively reduce repetitive operations in the parametric FEA modeling process, which thereby improves the overall efficiency of the FEA modeling process. Author Affiliation: (a) College of Mechanical Engineering, ZheJiang University of Technology, HangZhou, ZheJiang, 310032, China (b) College of Computer Science and Technology and College of Software Engineer, ZheJiang University of Technology, HangZhou, ZheJiang, 310032, China * Corresponding author. Article History: Received 30 January 2019; Revised 13 May 2019; Accepted 17 June 2019 Byline: Xuesong Xu (a), Gang Xiao (a,b), Gonghui Lou (a), Jiawei Lu (b), Jun Yang (a), Zhenbo Cheng [czb@zjut.edu.cn] (b,*)

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Gale Document Number: GALE|A599181987