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.
|Journal||Journal of Engineering Design|
|Early online date||17 Jun 2019|
|Publication status||Published - Nov 2019|
- Simulation intent
- finite element modelling
- cellular modelling
- CAD/CAE integration
FingerprintDive into the research topics of 'Capturing simulation intent in an ontology: CAD and CAE integration application'. Together they form a unique fingerprint.