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Optimization of Large-Scale Reacting Flows using MPSalsa and Sequential Quadratic Programming

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Large-Scale PDE-Constrained Optimization

Abstract

An rSQP optimization algorithm has been linked to the MPSalsa parallel reacting flows code. The goal is to developSAND (Simultaneous Analysis aNd Design) methods for use with large-scale PDE simulations. MPSalsa is a unstructured grid finite element code that uses a fully coupled Newton method to solve the PDEs governing fluid flow, heat transfer, and non-dilute mass transfer. In this paper, we present results for optimization of a Chemical Vapor Deposition reactor for growing thin films of Gallium Nitride. In particular, we address issues of inexactness in the Jacobian matrix and of solution multiplicity.

Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed-Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000.

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© 2003 Springer-Verlag Berlin Heidelberg

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Salinger, A.G. et al. (2003). Optimization of Large-Scale Reacting Flows using MPSalsa and Sequential Quadratic Programming. In: Biegler, L.T., Heinkenschloss, M., Ghattas, O., van Bloemen Waanders, B. (eds) Large-Scale PDE-Constrained Optimization. Lecture Notes in Computational Science and Engineering, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55508-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-55508-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-05045-2

  • Online ISBN: 978-3-642-55508-4

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