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An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

: Khawli, T.A.; Gebhardt, S.; Eppelt, U.; Hermanns, T.; Kuhlen, T.; Schulz, W.


Simos, T. ; European Society of Computational Methods in Sciences and Engineering -ESCMSE-:
International Conference on Numerical Analysis and Applied Mathematics, ICNAAM 2015 : Rhodes, Greece, 22-28 September 2015
Melville/NY: AIP Publishing, 2016 (AIP Conference Proceedings 1738)
ISBN: 978-0-7354-1392-4
Art. 370003, 6 pp.
International Conference on Numerical Analysis and Applied Mathematics (ICNAAM) <2015, Rhodes>
Conference Paper
Fraunhofer ILT ()

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels.