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Adjoint-Based Sensitivity Analysis in High-Temperature Fluid Flows with Paticipating Media

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Modeling, Simulation and Optimization in the Health- and Energy-Sector

Part of the book series: SEMA SIMAI Springer Series ((ICIAM2019SSSS,volume 14))

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Abstract

We present a novel approach to compute adjoint sensitivities in heat transfer problems involving fluid flows and radiation. The method overcomes the traditional adjoint requirement of an exact Jacobian computation across disciplines, and provides efficient means to compute very accurate gradients for optimal design applications. We implement a one-equation P1 radiation model into the open-source multiphysics suite SU2 and couple it to its incompressible Navier-Stokes solver with energy equation. To demonstrate the proposed methodology, we compute the coupled adjoint-based sensitivities and verify their accuracy using finite differences. We demonstrate the applicability of the adjoint method in efficiently computing coupled sensitivities in problems involving absorbing fluid flows and radiation.

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Notes

  1. 1.

    https://su2code.github.io/.

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Acknowledgements

This work has been funded by the Bundesministerium für Bildung und Forschung of the German Government under the project “Energieeffiziente Hochtemperaturprozesse durch Formoptimierung”, grant number 05M18UKA. This economic support is greatly appreciated by the authors. The code that has been developed during this work is freely available at the main SU2 repository https://github.com/su2code/SU2. The authors would also like to acknowledge the technical support from the open-source community of SU2, and particularly from Dr. Thomas Economon for his help in setting the test cases presented.

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  1. Chair for Scientific Computing, TU Kaiserslautern, Paul-Ehrlich-Straße 34 (36-412), Kaiserslautern, Germany

    Ruben Sanchez, Emre Özkaya & Nicolas R. Gauger

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  1. Ruben Sanchez
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  1. Department of Mathematics, Technische Universität Kaiserslautern, Kaiserslautern, Germany

    René Pinnau

  2. Scientific Computing, Technische Universität Kaiserslautern, Kaiserslautern, Germany

    Nicolas R. Gauger

  3. Department of Mathematics, Technische Universität Kaiserslautern, Kaiserslautern, Germany

    Axel Klar

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Sanchez, R., Özkaya, E., Gauger, N.R. (2022). Adjoint-Based Sensitivity Analysis in High-Temperature Fluid Flows with Paticipating Media. In: Pinnau, R., Gauger, N.R., Klar, A. (eds) Modeling, Simulation and Optimization in the Health- and Energy-Sector. SEMA SIMAI Springer Series(), vol 14. Springer, Cham. https://doi.org/10.1007/978-3-030-99983-4_7

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