Application of tensor factorisation for CAE model preparation from CAD assembly models. (November 2022)
- Record Type:
- Journal Article
- Title:
- Application of tensor factorisation for CAE model preparation from CAD assembly models. (November 2022)
- Main Title:
- Application of tensor factorisation for CAE model preparation from CAD assembly models
- Authors:
- Boussuge, Flavien
Armstrong, Cecil G.
Tierney, Christopher M.
Robinson, Trevor T. - Abstract:
- Abstract: Generating fit-for-purpose CAE models from complex CAD assemblies is time consuming and error-prone. Tedious tasks include identifying and isolating the components of interest, removing duplicate components, and correcting inconsistent component interfaces. In this paper a new approach to help engineers identify similar features and analyse the consistency of CAD assembly models is proposed. The method utilises a tensor factorisation technique developed for relational machine learning and applies it to B-Rep topological and geometrical relations. The model considers globally all the input relations to identify which entities in the assembly are similar (within a user-defined threshold) to a selected input entity. It is shown that a hierarchical clustering method can group entities, based on the similarities of their attributes and relationships with adjacent components. It is shown how some unsuspected CAD modelling errors show up as features which should be similar, but which are not. It is demonstrated how the technique can be used to support the, currently highly manual, task of decomposing a volume representing an internal fluid network into sub-volumes and features of significance. Highlights: Application of relational learning tensor factorisation to B-Rep models. New approach to analyse the consistency of large CAD assemblies. Usage scenario for CAD/CAE integration: Finding similar features in an assembly. Hierarchical clustering of similar CAD parts in anAbstract: Generating fit-for-purpose CAE models from complex CAD assemblies is time consuming and error-prone. Tedious tasks include identifying and isolating the components of interest, removing duplicate components, and correcting inconsistent component interfaces. In this paper a new approach to help engineers identify similar features and analyse the consistency of CAD assembly models is proposed. The method utilises a tensor factorisation technique developed for relational machine learning and applies it to B-Rep topological and geometrical relations. The model considers globally all the input relations to identify which entities in the assembly are similar (within a user-defined threshold) to a selected input entity. It is shown that a hierarchical clustering method can group entities, based on the similarities of their attributes and relationships with adjacent components. It is shown how some unsuspected CAD modelling errors show up as features which should be similar, but which are not. It is demonstrated how the technique can be used to support the, currently highly manual, task of decomposing a volume representing an internal fluid network into sub-volumes and features of significance. Highlights: Application of relational learning tensor factorisation to B-Rep models. New approach to analyse the consistency of large CAD assemblies. Usage scenario for CAD/CAE integration: Finding similar features in an assembly. Hierarchical clustering of similar CAD parts in an assembly. Industrial use case: Finding airflow features between parts in a complex assembly. … (more)
- Is Part Of:
- Computer aided design. Volume 152(2022)
- Journal:
- Computer aided design
- Issue:
- Volume 152(2022)
- Issue Display:
- Volume 152, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 152
- Issue:
- 2022
- Issue Sort Value:
- 2022-0152-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-11
- Subjects:
- CAD/CAE integration -- Relational learning -- Computer aided-design -- Assembly representation
Computer-aided design -- Periodicals
Engineering design -- Data processing -- Periodicals
Computer graphics -- Periodicals
Conception technique -- Informatique -- Périodiques
Infographie -- Périodiques
Computer graphics
Engineering design -- Data processing
Periodicals
Electronic journals
620.00420285 - Journal URLs:
- http://www.journals.elsevier.com/computer-aided-design/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cad.2022.103372 ↗
- Languages:
- English
- ISSNs:
- 0010-4485
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3393.520000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23339.xml