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A hybrid and automated approach to adapt geometry model for CAD/CAE integration

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Abstract

Traditional adaption of CAD geometry, which plays an important role in generating effective and fit-for-purpose finite element models, is usually carried out manually and optionally with excessive dependence on engineer’s experience. Automatic and efficient geometry modification before simulation evidently improves design efficiency and quality, and cuts down product life cycle. This paper represents an automatic approach to generate simplified and idealized geometry models for CAE simulation, which consists of hybrid model simplification criteria, feature-based model simplification, and simulation intent driven geometry modification. Hybrid adaption criteria takes detailed features geometric dimension, geometry topology, design intent into consideration synthetically. Simulation intent-driven modification with the help of virtual topology operators helps to deal with geometry at a higher level to get an ameliorative boundary for mesh without perturbing the original design model with constructing history for down-stream manufacture-oriented application, such as machining feature recognition and process planning. Development of plug-in toolkit guarantees automation of the simplification process and helps generate simulation-fitted geometry for subsequent analysis and simulation process. Prototype system and cases are implemented to demonstrate the result and efficiency of the proposed approach.

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Authors and Affiliations

  1. National Engineering Research Center of Die and Mold CAD, Shanghai Jiao Tong University, 1954 Hua Shan Road, Shanghai, 200030, China

    Qingqing Feng, Xionghui Zhou & Junjie Li

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  1. Qingqing Feng
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  2. Xionghui Zhou
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  3. Junjie Li
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Correspondence to Xionghui Zhou.

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Feng, Q., Zhou, X. & Li, J. A hybrid and automated approach to adapt geometry model for CAD/CAE integration. Engineering with Computers 36, 543–563 (2020). https://doi.org/10.1007/s00366-019-00713-4

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  • DOI: https://doi.org/10.1007/s00366-019-00713-4

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