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Intelligent support of the preprocessing stage of engineering analysis using case-based reasoning

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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. In this paper the automated 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 case representation model is proposed which is centered on the structured qualitative model of a technical object. The model is formally represented by the Ontology Web Language Description Logics (OWL DL) ontology. Case retrieval and adaptation algorithms for this model are described which according to the initial tests perform better in the chosen domain then the known prototypes. The automated system is described and a sample problem-solving scenario from the contact mechanics domain is presented. Use of such system can potentially lower costs of engineering analysis by reducing the number of inappropriate decisions and analysis iterations and facilitate knowledge transfer from research into industry.

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References

  1. Wriggers P (2004) Computational contact mechanics. Springer, Berlin-Heidelberg, Germany

    Google Scholar 

  2. Wriggers P (1995) Finite element algorithms for contact problems. IM TH Darmstadt, Darmstadt

    Google Scholar 

  3. Bartsch-Spurl B, Lenz M, Hubner A (1999) Case-based reasoning––survey and future directions. XPS-99: knowledge-based systems: survey and future directions. In: Proceedings of the fifth biannual German conference on knowledge-based systems, Wurzburg, Germany

  4. Bogaerts S, Leake D (2004) Facilitating CBR for incompletely-described cases: distance metrics for partial problem descriptions. Lindley Hall, Chien

    Google Scholar 

  5. Broad A (1998) Case-based reasoning. CS3411 essay, Department of Computer Science. University of Manchester, Manchester

    Google Scholar 

  6. Gomez-Albarran M, Gonzales-Calero P, Diaz-Agudo B, Fernandez-Conde C (1999) Modeling the CBR life cycle using description logics. Lecture notes in computes science, vol 1650. Springer, Berlin, pp 719–720

  7. Forbus KD, Ferguson RW, Usher JM (2000) Towards a computational model of sketching. In: Proceedings of the international conference on intelligent user interfaces, Sante Fe, NM

  8. Kuipers B (2001) Qualitative simulation. MIT, Cambridge

    Google Scholar 

  9. Wriggers P, Tarnow N (1989) Interactive control of nonlinear finite element calculations by an expert system. IBNM, University of Hannover, Hannover

    Google Scholar 

  10. Hsiung CH (2002) A reusable engineering analysis preprocessing methodology to support design-analysis integration. Doctoral Thesis, Georgia Institute of Technology, Atlanta

  11. Pokojski J (2004) IPA: concepts and applications in engineering. Springer, Berlin, Heidelberg

    Google Scholar 

  12. McMahon CA, Liu Y, Crossland R, Brown D, Leal D, Devlukia J (2004) A best practice advice system to support automotive engineering analysis processes. Engineering with Computers 19:271–283

    Article  Google Scholar 

  13. Purvis L, Pearl P (1998) COMPOSER: a case-based reasoning system for engineering design. Robotica 16:285–295

    Article  Google Scholar 

  14. Grosse I, Milton-Benoit J, Wileden J (2005) Ontologies for supporting engineering analysis models. Artif Intell Eng Des Anal Manuf 19:1–18

    Google Scholar 

  15. Nikolaychuk O, Yurin A (2008) Computer-aided identification of mechanical system’s technical state with the aid of case-based reasoning. Expert Syst Appl 34:635–642. doi:10.1016/j.eswa.2006.10.001

    Article  Google Scholar 

  16. Bichindaritz I (2006) Me´moire: a framework for semantic interoperability of case-based reasoning systems in biology and medicine. Artif Intell Med 36:177–192

    Article  Google Scholar 

  17. Ceccaroni L, Cortes U, Sanchez-Marre M (2004) OntoWEDSS: augmenting environmental decision-support systems with ontologies. Environ Model Softw 3:25–51

    Google Scholar 

  18. Bello-Tomás J, González-Calero P, Díaz-Agudo B (2004) JColibri: an object-oriented framework for building CBR systems. In: Proceedings of ECCBR 2004, advances in case-based reasoning, Springer, Berlin, Heidelberg, pp 32–46

  19. Konter A (2000) How to––undertake a contact and friction analysis. NAFEMS Ltd., Manchester

    Google Scholar 

  20. Feng Q, Prinja NK (2002) NAFEMS benchmark tests for finite element modelling of contact, gapping and sliding. NNC Ltd, Manchester

    Google Scholar 

  21. Gonzales-Calero P, Diaz-Agudo B, Gomez-Albarran M (2000) Applying DLs for retrieval in case-based reasoning

  22. Petrovic S, Kendall G, Yang Y (2002) A Tabu search approach for graph-structured case retrieval. In: STarting artificial intelligence researches symposium, Lyon, France

  23. Konter A (2005) Advanced finite element contact benchmarks: a FENET report. NAFEMS Ltd., Manchester

    Google Scholar 

  24. Zavarise G, Wriggers P, Nackenhorst U (2006) A report of Leonardo project NUFRIC. TCN, Bergamo

    Google Scholar 

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Acknowledgments

The authors would like to thank Alexander Kapysh and Anton Kultsov, Master students of Volgograd State Technical University, for participation in development of ISFEA.

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Authors and Affiliations

  1. Institute of Computational Mechanics, University of Hannover, Appelstrasse 9a, 30167, Hannover, Germany

    Peter Wriggers

  2. IST Department, Volgograd State University of Architecture and Civil Engineering, Akademicheskaya 1, 400074, Volgograd, Russia

    Marina Siplivaya

  3. CAD Department, Volgograd State Technical University, Lenina 28, 400131, Volgograd, Russia

    Irina Joukova & Roman Slivin

Authors
  1. Peter Wriggers
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  2. Marina Siplivaya
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  3. Irina Joukova
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  4. Roman Slivin
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Corresponding author

Correspondence to Marina Siplivaya.

Additional information

The work is financially supported by the ‘Mikhail Lomonosow’ grants of DAAD and Ministry of Education and Science of Russia.

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Wriggers, P., Siplivaya, M., Joukova, I. et al. Intelligent support of the preprocessing stage of engineering analysis using case-based reasoning. Engineering with Computers 24, 383–404 (2008). https://doi.org/10.1007/s00366-007-0079-5

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  • DOI: https://doi.org/10.1007/s00366-007-0079-5

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