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Modeling, Simulation and Optimization of Complex Processes pp 255–272Cite as

Numerical Methods for Nonlinear Experimental Design

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Summary

Nonlinear experimental design leads to a challenging class of optimization problems which occur in the procedure of the validation of process models. This paper discusses the formulation of such problems for a general class of underlying process models, presents numerical methods for the solution and shows their successful application to industrial processes.

This work was supported by the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (BMBF).

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Author information

Authors and Affiliations

  1. Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, D-69120, Heidelberg, Germany

    Stefan Körkel & Ekaterina Kostina

Authors
  1. Stefan Körkel
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  2. Ekaterina Kostina
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Editor information

Editors and Affiliations

  1. Interdisziplinäres Zentrum für Wissenschaftliches Rechnen (IWR), Universität Heidelberg, Im Neuenheimer Feld 368, 69120, Heidelberg, Germany

    Hans Georg Bock  & Ekaterina Kostina  & 

  2. Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), 18 Hoang Quoc Viet Road, 10307, Hanoi, Vietnam

    Hoang Xuan Phu

  3. Institut für Angewandte Mathematik, Universität Heidelberg, Im Neuenheimer Feld 294, 68120, Heidelberg, Germany

    Rolf Rannacher

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© 2005 Springer-Verlag Berlin Heidelberg

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Körkel, S., Kostina, E. (2005). Numerical Methods for Nonlinear Experimental Design. In: Bock, H.G., Phu, H.X., Kostina, E., Rannacher, R. (eds) Modeling, Simulation and Optimization of Complex Processes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27170-8_20

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