The impact of tube corrugation within the multi-disciplinary design optimization of a charge air cooler
The impact of tube corrugation within the multi-disciplinary design optimization of a charge air cooler
The following paper explores the impact of corrugated tubes within a charge air cooler (CAC) on overall cooler performance, cost and size, for the first time. Corrugated tubes have been demonstrated to perform better in terms of heat transfer, when compared to a smooth tube, however they have not been optimized in the context of a CAC. In this study, a CAC with corrugated tubes is compared against a similar system comprising of smooth tubes as a baseline design. Both CACs have common design parameters, such as number of tubes per rows, number of rows, number of passes, fins per meter, fin material, and tube material, while two additional design parameters exist i.e., groove depth, and pitch for the CAC with corrugated tubes, that characterizes the helical corrugation. These two systems are optimized to minimize manufacturing cost where cost is a function of cooler dimensions and material selection. Feasible designs are then obtained by satisfying dimension, pressure, weight, performance and vibrations based constraints. A vibration constraint introduced here is an addition to the current state of the art, making this approach, a multi-disciplinary one and the first of its kind. Finally, the optimum is compared which signifies the importance of a multi-disciplinary analysis for both
cooler configurations.
Machine Learning, genetic algorithm NSGA-II, Heat Exchangers, Machine Learning Applications, optimisation, optimisation techniques, Optimization methods
Singh, Atul Udaivir
29f1143c-7c70-4145-afa5-805104dda130
Toal, David
dc67543d-69d2-4f27-a469-42195fa31a68
Richardson, Edward
a8357516-e871-40d8-8a53-de7847aa2d08
Jose, Kevin
62171012-92ec-4338-91a4-94b45cdd8645
Bhaskar, Atul
d4122e7c-5bf3-415f-9846-5b0fed645f3e
Ibsen, Claus
113fbc28-4a7d-4e09-8100-bac244b63d42
5 June 2022
Singh, Atul Udaivir
29f1143c-7c70-4145-afa5-805104dda130
Toal, David
dc67543d-69d2-4f27-a469-42195fa31a68
Richardson, Edward
a8357516-e871-40d8-8a53-de7847aa2d08
Jose, Kevin
62171012-92ec-4338-91a4-94b45cdd8645
Bhaskar, Atul
d4122e7c-5bf3-415f-9846-5b0fed645f3e
Ibsen, Claus
113fbc28-4a7d-4e09-8100-bac244b63d42
Singh, Atul Udaivir, Toal, David, Richardson, Edward, Jose, Kevin, Bhaskar, Atul and Ibsen, Claus
(2022)
The impact of tube corrugation within the multi-disciplinary design optimization of a charge air cooler.
8th European Congress on Computational Methods in Applied Sciences and Engineering, , Oslo, Norway.
05 - 09 Jun 2022.
12 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The following paper explores the impact of corrugated tubes within a charge air cooler (CAC) on overall cooler performance, cost and size, for the first time. Corrugated tubes have been demonstrated to perform better in terms of heat transfer, when compared to a smooth tube, however they have not been optimized in the context of a CAC. In this study, a CAC with corrugated tubes is compared against a similar system comprising of smooth tubes as a baseline design. Both CACs have common design parameters, such as number of tubes per rows, number of rows, number of passes, fins per meter, fin material, and tube material, while two additional design parameters exist i.e., groove depth, and pitch for the CAC with corrugated tubes, that characterizes the helical corrugation. These two systems are optimized to minimize manufacturing cost where cost is a function of cooler dimensions and material selection. Feasible designs are then obtained by satisfying dimension, pressure, weight, performance and vibrations based constraints. A vibration constraint introduced here is an addition to the current state of the art, making this approach, a multi-disciplinary one and the first of its kind. Finally, the optimum is compared which signifies the importance of a multi-disciplinary analysis for both
cooler configurations.
Text
Eccomas_paper
- Author's Original
More information
Accepted/In Press date: 2022
Published date: 5 June 2022
Venue - Dates:
8th European Congress on Computational Methods in Applied Sciences and Engineering, , Oslo, Norway, 2022-06-05 - 2022-06-09
Keywords:
Machine Learning, genetic algorithm NSGA-II, Heat Exchangers, Machine Learning Applications, optimisation, optimisation techniques, Optimization methods
Identifiers
Local EPrints ID: 467372
URI: http://eprints.soton.ac.uk/id/eprint/467372
PURE UUID: 06f4dd7f-1c41-4d9a-ad8d-036fd179a791
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Date deposited: 07 Jul 2022 17:07
Last modified: 16 Apr 2024 01:56
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Contributors
Author:
Atul Udaivir Singh
Author:
Kevin Jose
Author:
Claus Ibsen
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