Preparing digital mock-ups (DMUs) for finite element analyses (FEAs) is currently a long and tedious task requiring many interactive CAD model transformations. Functional information about components appears to be very useful to speed this preparation process. The purpose of this paper is to shows how DMU components can be automatically enriched with some functional information.
DMUs are widespread and stand as reference model for product description. However, DMUs produced by industrial CAD systems essentially contain geometric models, which lead to tedious preparation of finite element Models (FEMs). Analysis and reasoning approaches are developed to automatically enrich DMUs with functional and kinematic properties. Indeed, geometric interfaces between components form a key starting point to analyze their behaviors under reference states. This is a first stage in a reasoning process to progressively identify mechanical, kinematic as well as functional properties of components.
Inferred semantics adds up to the pure geometric representation provided by a DMU and produce also geometrically structured components. Functional information connected to a structured geometric model of a component significantly improves FEM preparation and increases its robustness because idealizations can take place using components’ functions and components’ structure helps defining sub-domains of FEMs.
Future research will carry on improving algorithms for geometric interfaces identification, processing a wider range of component functions, which will contribute to a formalization of the concept of functional consistency of a DMU.
Simulation engineers benefit from this automated enrichment of DMUs with functional information to speed up the preparation of FEAs of large assemblies.
This work is carried out in the framework of the ANR project ROMMA and the authors thank the ANR for its financial support.
Shawan, A., Léon, J., Foucault, G. and Fine, L. (2015), "Functional restructuring of CAD models for FEA purposes", Engineering Computations, Vol. 32 No. 1, pp. 155-176. https://doi.org/10.1108/EC-03-2013-0088Download as .RIS
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