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Flow Control pp 49–78Cite as

A Sensitivity Equation Approach to Shape Optimization in Fluid Flows

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Part of the book series: The IMA Volumes in Mathematics and its Applications ((IMA,volume 68))

Abstract

In this paper we apply a sensitivity equation method to shape optimization problems. An algorithm is developed and tested on a problem of designing optimal forebody simulators for a 2D, inviscid supersonic flow. The algorithm uses a BFGS/Trust Region optimization scheme with sensitivities computed by numerically approximating the linear partial differential equations that determine the flow sensitivities. Numerical examples are presented to illustrate the method.

Supported in part by the Air Force Office of Scientific Research under grant F49620-92-J-0078.

Supported in part by the Air Force Office of Scientific Research under grants F49620-92-J-0078 and F49620-93-1-0280, the National Science Foundation under grant INT-89-22490 and by the National Aeronautics and Space Administration under Contract No. NASI-19480 while the author was a visiting scientist at the Institute for Computer Applications in Science and Engineering (ICASE), NASA Langley Research Center, Hampton, VA 23681-0001.

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References

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Author information

Authors and Affiliations

  1. Interdisciplinary Center for Applied Mathematics, Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, USA

    Jeff Borggaard & John Burns

Authors
  1. Jeff Borggaard
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  2. John Burns
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Interdisciplinary Center for Applied Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061-0531, USA

    Max D. Gunzburger

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© 1995 Springer-Verlag New York, Inc.

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Borggaard, J., Burns, J. (1995). A Sensitivity Equation Approach to Shape Optimization in Fluid Flows. In: Gunzburger, M.D. (eds) Flow Control. The IMA Volumes in Mathematics and its Applications, vol 68. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2526-3_3

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  • DOI: https://doi.org/10.1007/978-1-4612-2526-3_3

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7569-5

  • Online ISBN: 978-1-4612-2526-3

  • eBook Packages: Springer Book Archive

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