Article | Proceedings of the 8th International Modelica Conference; March 20th-22nd; Technical Univeristy; Dresden; Germany | Auto-Extraction of Modelica Code from Finite Element Analysis or Measurement Data Linköping University Electronic Press Conference Proceedings
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Title:
Auto-Extraction of Modelica Code from Finite Element Analysis or Measurement Data
Author:
The-Quan Pham: OptiY e.K., Aschaffenburg, Germany Alfred Kamusella: Technische Universität Dresden, Institute of Electromechanical and Electronic Design, Germany Holger Neubert: Technische Universität Dresden, Institute of Electromechanical and Electronic Design, Germany
DOI:
10.3384/ecp11063668
Download:
Full text (pdf)
Year:
2011
Conference:
Proceedings of the 8th International Modelica Conference; March 20th-22nd; Technical Univeristy; Dresden; Germany
Issue:
063
Article no.:
074
Pages:
668-672
No. of pages:
5
Publication type:
Abstract and Fulltext
Published:
2011-06-30
ISBN:
978-91-7393-096-3
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


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This paper presents a new approach to extract Modelica codes from finite element analysis or measurement data automatically. The finite element model or the real system on the test bench is adaptively sam-pled while applying the Gaussian process with a few number of model calculations or measurement points. Based on these support points; a meta- or surrogate model of the system is built. Thus; Modelica codes can be generated automatically. These algorithms are implemented in the multidisciplinary design software OptiY®. Its application is demonstrated on the example of an electromagnetic actuator.

Keywords: Gaussian Process; Kriging; Surrogate Modeling; Meta Modeling

Proceedings of the 8th International Modelica Conference; March 20th-22nd; Technical Univeristy; Dresden; Germany

Author:
The-Quan Pham, Alfred Kamusella, Holger Neubert
Title:
Auto-Extraction of Modelica Code from Finite Element Analysis or Measurement Data
DOI:
http://dx.doi.org/10.3384/ecp11063668
References:

[1] Rasmussen C. E.; Williams C. K. I.: Gaus-sian Process for Machine Learning. MIT Press 2006.

[2] Santner; T. J.; Williams; B. J.; Notz; W. I.: The Design and Analysis of Computer Experiment. Springer New York 2003. doi: 10.1007/978-1-4757-3799-8.

[3] Sacks J.; Welch W. J.; Mitchell T. J.; Wynn H. P.: Design and Analysis of Computer Experiments. Statistical Science 4; pp. 409-435; 1989. doi: 10.1214/ss/1177012413.

[4] Jones; R. D.: A Taxonomy of Global Optimization Methods Based on Response Surfaces. Journal of Global Optimization 21: 345-383; 2001. doi: .

[5] Xiong; Y.; Chen; W; and Tsui; K.: A New Variable Fidelity Optimization Framework Based on Model Fusion and Objective-Oriented Sequential Sampling. ASME Jour-nal of Mechanical Design ; 130 (11); 2008

[6] Antuolas; A. C.: Approximation of Large-Scale Dynamical Systems. SIAM 2005

[7] OptiY Software and Documentation. www.optiy.eu

[8] http://www.optiyummy.de/index.php/Software:_FEM_-_Tutorial_-_Magnetfeld; see Kennfeld-Export als Modelica-Code

[9] SimulationX Software and Documentation. www.iti.de

[10] FEMM Software and Documentation. www.femm.info

Proceedings of the 8th International Modelica Conference; March 20th-22nd; Technical Univeristy; Dresden; Germany

Author:
The-Quan Pham, Alfred Kamusella, Holger Neubert
Title:
Auto-Extraction of Modelica Code from Finite Element Analysis or Measurement Data
DOI:
https://doi.org10.3384/ecp11063668
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