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Design of heat exchangers via a bioinspired topology optimization framework with physics-informed underlying fields

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Abstract

A topology optimization framework with physics-informed fields is presented to bridge the gap between implicit and explicit bioinspired techniques. The methodology takes advantage of the reduced optimization space unique to the explicit analysis while intelligently adjusting the topologies through underlying fields. A heat exchanger design problem was used to illustrate the effectiveness of the proposed methodology. The objective was to minimize the average temperature while remaining below the pressure drop of a traditional parallel channel design. Pressure and velocity fields from an open cavity design domain were used to control the length scale and orientation, respectively, of the topology generation process. This resulted in designs that had a minimal pressure drop while following the natural flow path of the heat exchanger. The Darcy flow model was used to permit a rapid analysis during the optimization routine, while the final designs were validated using a high-fidelity RANS model. Four different design cases were run to observe the effect that the underlying fields had on the optimization process. The cases ranged from no underlying fields and a three-parameter optimization space to two underlying fields and a five-parameter optimization space. A Bayesian optimization model was used to explore and exploit each parameter space. Ultimately, the two-field design case highlighted the value of the physics-informed fields as it produced the top performing heat exchanger design. Compared to the traditional parallel channel design, it reduced the average temperature by 68% while maintaining a similar pressure drop.

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Funding

This work was funded by Wyoming NASA Space Grant Consortium, NASA Grant #80NSSC20M0113.

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Authors and Affiliations

  1. Department of Mechanical Engineering, University of Wyoming, Laramie, WY, 82071, USA

    Sarah N. Hankins & Ray S. Fertig III

Authors
  1. Sarah N. Hankins
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  2. Ray S. Fertig III
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Corresponding author

Correspondence to Ray S. Fertig III.

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The authors have no competing interests to declare that are relevant to the content of this article.

Replication of results

The optimized parameter settings were used to generate the heat exchanger designs for each of the following design cases:

  1. 1.

    – case: \(f=0.02406806, k= 0.05164529, {D}_{U}=5.99331\bullet {10}^{-6}.\)

  2. 2.

    \({{\varvec{\phi}}}_{1}\) case: \(f=0.02719727, k= 0.05332128, {D}_{U}=1.57355\bullet {10}^{-6}, \alpha =6.435584.\)

  3. 3.

    \({{\varvec{\phi}}}_{2}\) case: \(=0.0314231, k= 0.05517635, {D}_{U}=5.27411\bullet {10}^{-6}, \beta =2.079748.\)

  4. 4.

    \({{\varvec{\phi}}}_{1}+{{\varvec{\phi}}}_{2}\) case: \(f=0.03180928, k= 0.05558959, {D}_{U}=4.21952\bullet {10}^{-6}, \alpha =4.999685, \beta =2.042737.\)

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Hankins, S.N., Fertig, R.S. Design of heat exchangers via a bioinspired topology optimization framework with physics-informed underlying fields. Struct Multidisc Optim 66, 157 (2023). https://doi.org/10.1007/s00158-023-03615-8

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  • DOI: https://doi.org/10.1007/s00158-023-03615-8

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