Leveraging feature generalization and decomposition to compute a well-connected midsurface

Computer-aided design (CAD) models of thin-walled parts, such as sheet metal or plastic parts, are often represented by their corresponding midsurfaces for computer-aided engineering (CAE) analysis. The reason being, 2D surface elements, such as “shell” elements, which need to be placed on the midsu...

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Veröffentlicht in:Engineering with computers 2017, Vol.33 (1), p.159-170
Hauptverfasser: Kulkarni, Yogesh H., Sahasrabudhe, Anil, Kale, Mukund
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description Computer-aided design (CAD) models of thin-walled parts, such as sheet metal or plastic parts, are often represented by their corresponding midsurfaces for computer-aided engineering (CAE) analysis. The reason being, 2D surface elements, such as “shell” elements, which need to be placed on the midsurface, provide fairly accurate results, while requiring far lesser computational resources time compared to the analysis using 3D solid elements. Existing approachesof midsurface computation are not reliable and robust. They result in ill-connected midsurfaces having missing patches, gaps, overlaps, etc. These errors need to be corrected, mostly by a manual and time-consuming process, requiring from hours to even days. Thus, an automatic and robust technique for computation of a well-connected midsurface is the need of the hour. This paper proposes an approachwhich, instead of working on the complex final solid shape, typically represented by B-rep (boundary representation), leverages feature information available in the modern CAD models for techniques such as defeaturing, generalization, and decomposition. Here, first, the model is defeaturedby removing irrelevant features, generating a simplified shape called “gross shape”. The remaining features are then generalizedto their corresponding generic loft-feature equivalents. The model is then decomposed into sub-volumes, called “cells” having respective owner loft features. A graph is populated, with the cells at the graph nodes. The nodes are classified into midsurface patch-generating nodes (called ‘solid cells’ or sCell s) and interaction-resolving nodes (called ‘interface cells’ or iCell s). Using owner loft feature’s parameters, sCell s compute their own midsurface patches. Using a generic logic, the patches then get connected appropriately in the iCell s, resulting in a well-connected midsurface. The efficacy of the approach is demonstrated by computing well-connected midsurfaces of various real-life sheet metal parts.
doi_str_mv 10.1007/s00366-016-0466-x
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Here, first, the model is defeaturedby removing irrelevant features, generating a simplified shape called “gross shape”. The remaining features are then generalizedto their corresponding generic loft-feature equivalents. The model is then decomposed into sub-volumes, called “cells” having respective owner loft features. A graph is populated, with the cells at the graph nodes. The nodes are classified into midsurface patch-generating nodes (called ‘solid cells’ or sCell s) and interaction-resolving nodes (called ‘interface cells’ or iCell s). Using owner loft feature’s parameters, sCell s compute their own midsurface patches. Using a generic logic, the patches then get connected appropriately in the iCell s, resulting in a well-connected midsurface. 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subjects Boundary representation
CAD
CAE
CAE) and Design
Calculus of Variations and Optimal Control
Optimization
Classical Mechanics
Computation
Computer aided design
Computer aided engineering
Computer Science
Computer-Aided Engineering (CAD
Control
Decomposition
Math. Applications in Chemistry
Mathematical and Computational Engineering
Mathematical models
Metal sheets
Original Article
Patches (structures)
Product design
Robustness (mathematics)
S parameters
Systems Theory
title Leveraging feature generalization and decomposition to compute a well-connected midsurface
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