Publication: An interactive environment for supporting the transition from simulation to optimization
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An interactive environment for supporting the transition from simulation to optimization

- Article in a journal -
 

Author(s)
C. H. Bischof , H. M. Bücker , B. Lang , A. Rasch

Published in
Scientific Programming

Year
2003

Abstract
Numerical simulation is a powerful tool in science and engineering, and it is also used for optimizing the design of products and experiments rather than only for reproducing the behavior of scientific and engineering systems. In order to reduce the number of simulation runs, the traditional ``trial and error″ approach for finding near-to-optimum design parameters is more and more replaced with efficient numerical optimization algorithms. Done by hand, the coupling of simulation and optimization software is tedious and error-prone. In this note we report on a new version of a software environment that facilitates and speeds up this task by doing much of the required work automatically. Our framework includes support for automatic differentiation providing the derivatives required by many optimization algorithms. We describe the process of integrating the widely used computational fluid dynamics package FLUENT and a MINPACK-1 least squares optimizer into our environment and follow a sample session solving a data assimilation problem.

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BibTeX
@ARTICLE{
         Bischof2003Aie,
       author = "C. H. Bischof and H. M. B{\"u}cker and B. Lang and A. Rasch",
       title = "An interactive environment for supporting the transition from simulation to
         optimization",
       journal = "Scientific Programming",
       pages = "263--272",
       abstract = "Numerical simulation is a powerful tool in science and engineering, and it is also
         used for optimizing the design of products and experiments rather than only for reproducing the
         behavior of scientific and engineering systems. In order to reduce the number of simulation runs,
         the traditional ``trial and error'' approach for finding near-to-optimum design parameters
         is more and more replaced with efficient numerical optimization algorithms. Done by hand, the
         coupling of simulation and optimization software is tedious and error-prone. In this note we report
         on a new version of a software environment that facilitates and speeds up this task by doing much of
         the required work automatically. Our framework includes support for automatic differentiation
         providing the derivatives required by many optimization algorithms. We describe the process of
         integrating the widely used computational fluid dynamics package \mbox{FLUENT} and a MINPACK-1
         least squares optimizer into our environment and follow a sample session solving a data assimilation
         problem.",
       ad_theotech = "General",
       year = "2003",
       volume = "11",
       number = "4",
       url = "http://iospress.metapress.com/link.asp?id=dyye5nwjkc68cf73"
}


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