Capturing simulation intent in an ontology: CAD and CAE integration application

ABSTRACT

Computational simulation is critical in the modern engineering design process. Currently, the use of simulation is limited by the time-consuming process of converting CAD assemblies into FEA models which are efficient to run and yet sufficiently accurate. In addition to the geometric representation of components, analysts require additional knowledge to describe the complete 3D simulation model. To speed up the generation of CAE models from CAD assemblies, we propose to capture high-level modelling and idealisation decisions, characterising the simulation intent, into a knowledge-based CAE model. In this framework, a simulation intent ontology formalises and structures the analysis parameters, the modelling and idealisation decisions. The ontological concepts and relations required to incorporate two of the key capabilities, cellular modelling and equivalencing, are described. Cellular modelling introduces the concept of cells, which subdivide the 3D space, and to which simulation attributes can be attached. Equivalencing maintains the link between different representations of the cells required for different analyses throughout the analysis lifecycle. Illustrative examples show how the knowledge-based CAE model is used to manage the idealisation decisions and to apply inference rules replicating current modelling practices.

KEYWORDS:

• Simulation intent
• finite element modelling
• cellular modelling
• ontologies
• CAD/CAE integration

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Flavien Boussuge http://orcid.org/0000-0002-1407-898X

Christopher M. Tierney http://orcid.org/0000-0003-3341-6902

Harold Vilmart http://orcid.org/0000-0002-7849-8211

Trevor T. Robinson http://orcid.org/0000-0002-6595-6308

Cecil G. Armstrong http://orcid.org/0000-0001-8695-5016

Declan C. Nolan http://orcid.org/0000-0002-9388-6183

Jean-Claude Léon http://orcid.org/0000-0003-3337-081X

Federico Ulliana http://orcid.org/0000-0002-9192-9573

Additional information

Funding

This work was supported by the European Commission [grant number 704557], MUMPS, Next Generation Digital Mock-Ups for Multi-Physics Simulation, a H2020-MSCA-IF-2015 founding scheme.