Integration of a case-based reasoning and an ontological know ledge base in the system of intelligent support of finite element analysis

Authors

  • Peter Wriggers Leibniz University Hannover
    Germany
  • Marina Siplivaya Volgograd State University of Architectural and Civil Engineering
    Russia
  • Irina Zhukova Volgograd State Technical University
    Russia
  • Alexander Kapysh Volgograd State Technical University
    Russia
  • Anton Kultsov Volgograd State Technical University
    Russia

Keywords:

artificial intelligence, case-based reasoning, ontologies, finite element analysis

Abstract

The process of engineering analysis, especially its preprocessing stage, comprises some knowledge-based tasks which influence the quality of the results greatly, require considerable level of expertise from an engineer; the support for these tasks by the contemporary CAE systems is limited. Analysis of the knowledge and reasoning involved in solving these tasks shows that the appropriate support for them by an automated system can be implemented using case-based reasoning (CBR) technology and ontological knowledge representation model. In this paper the knowledge-based system for intelligent support of the preprocessing stage of engineering analysis in the contact mechanics domain is presented which employs the CBR mechanism. The knowledge representation model is formally represented by the OWL DL ontology. Case representation model, case retrieval and adaptation algorithms for this model and the automated system are described.

References

[1] B. Bartsch-Spurl, M. Lenz, A. Hubner. Case-based reasoning - Survey and future directions. XPS-99: Knowledge-Based Systems: Survey and Future Directions: Proceedings of the Fifth Biannual German Conference on Knowledge-Based Systems, Wurzburg, Germany, 1999.
[2] R. Bergman. On the relations between structural case-based reasoning and ontology-based knowledge management. Proceedings of International Conference ICCBR2003, Trondheim, Norway, 2003.
[3] S. Bogaerts, D. Leake. Facilitating CBR for Incompletely-Described Cases: Distance Metrics for Partial Problem Descriptions, Lindley Hall, 2004.
[4] S. Bruninghaus, K.D. Ashley. Reasoning with Textual Cases. ICCBR2005, 2005.
[5] A. Broad. Case-Based Reasoning. CS3411 essay, Department of Computer Science, University of Manchester, Manchester, UK, 1998.

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Published

2022-08-17

Issue

pp. 753-765

Section

Articles

How to Cite

Wriggers, P., Siplivaya, M., Zhukova, I., Kapysh, A., & Kultsov, A. (2022). Integration of a case-based reasoning and an ontological know ledge base in the system of intelligent support of finite element analysis. Computer Assisted Methods in Engineering and Science, 14(4), 753-765. https://cames3.ippt.pan.pl/index.php/cames/article/view/810