Concurrent optimization of multiple heat transfer surfaces using adjoint-based optimization with a CAD-based parametrization

Heat exchangers are key components of thermal energy conversion systems, however, their optimal design is still based on reduced order models relying on semi-empirical heat transfer correlations. CFD-based design optimization emerged as a viable method to provide a significant improvement in performance at an affordable cost. This study presents a framework to optimize multiple heat transfer surfaces concurrently using the adjoint method. The heat transfer surfaces are parametrized using a CAD-based parametrization method, and their performance is evaluated using a RANS solver complemented by its discrete adjoint counterpart for gradient computation. The optimization framework is applied to minimize the pressure drop across a bare-tube heat exchanger while constraining the heat transfer rate. Two variants of the same optimization problem are formulated: in the first one, the sensitivities are averaged and the tubes are constrained to maintain the same shape, while in the second variant, the shape of the tubes can vary, resulting in an optimum solution with non-identical tube shapes. The results show that the optimized geometry reduces the pressure drop by 19% if the tube shapes are identical, and by 25% in the case of non-identical shapes, compared to the baseline. To identify the physical mechanisms contributing to the fluid-dynamic losses, entropy generation along the flow path was investigated. The results reveal that the major loss reduction observed for the case of non-identical tube shapes is due to the better thermo-hydraulic performance of the first and last tubes. • An adjoint-based optimization framework is applied to a tubular heat exchanger. • The tube surfaces are parametrized via a CAD-based method and simultaneously optimized. • The pressure drop across the tubes is minimized while the heat transfer rate is constrained. • Non-identical tube shapes allow for higher performance by accounting for entrance and exit effects.

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Publication Details

Journal
International Journal of Heat and Mass Transfer
Published
2024-10-02
DOI
https://doi.org/10.1016/j.ijheatmasstransfer.2024.126230
Citations
6
Primary Topic
Heat Transfer and Optimization
Type
article
Field-Weighted Citation Impact
1.28

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article

Concurrent optimization of multiple heat transfer surfaces using adjoint-based optimization with a CAD-based parametrization

Praharsh Pai Raikar, Carlo De Servi, Matteo Pini, Nitish Anand
6 citations
International Journal of Heat and Mass Transfer
Heat Transfer and Optimization
1.28
article

Concurrent optimization of multiple heat transfer surfaces using adjoint-based optimization with a CAD-based parametrization

Praharsh Pai Raikar, Carlo De Servi, Matteo Pini, Nitish Anand
article en
6 citations

Abstract

Heat exchangers are key components of thermal energy conversion systems, however, their optimal design is still based on reduced order models relying on semi-empirical heat transfer correlations. CFD-based design optimization emerged as a viable method to provide a significant improvement in performance at an affordable cost. This study presents a framework to optimize multiple heat transfer surfaces concurrently using the adjoint method. The heat transfer surfaces are parametrized using a CAD-based parametrization method, and their performance is evaluated using a RANS solver complemented by its discrete adjoint counterpart for gradient computation. The optimization framework is applied to minimize the pressure drop across a bare-tube heat exchanger while constraining the heat transfer rate. Two variants of the same optimization problem are formulated: in the first one, the sensitivities are averaged and the tubes are constrained to maintain the same shape, while in the second variant, the shape of the tubes can vary, resulting in an optimum solution with non-identical tube shapes. The results show that the optimized geometry reduces the pressure drop by 19% if the tube shapes are identical, and by 25% in the case of non-identical shapes, compared to the baseline. To identify the physical mechanisms contributing to the fluid-dynamic losses, entropy generation along the flow path was investigated. The results reveal that the major loss reduction observed for the case of non-identical tube shapes is due to the better thermo-hydraulic performance of the first and last tubes. • An adjoint-based optimization framework is applied to a tubular heat exchanger. • The tube surfaces are parametrized via a CAD-based method and simultaneously optimized. • The pressure drop across the tubes is minimized while the heat transfer rate is constrained. • Non-identical tube shapes allow for higher performance by accounting for entrance and exit effects.

International Journal of Heat and Mass TransferVol. 236
Flemish Institute for Technological Research (BE), Delft University of Technology (NL)
Vlaamse Instelling voor Technologisch Onderzoek
Affordable and clean energy
Openalex Percentile: Top 23%
Heat Transfer and Optimization
1.28
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