Performance enhancement of a C-shaped printed circuit heat exchanger in supercritical CO2 Brayton cycle: A machine learning-based optimization study Article Swipe
Muhammad Saeed
,
Abdallah S. Berrouk
,
Yasser F. Al Wahedi
,
Munendra Pal Singh
,
Ibragim Abu Dagga
,
Imran Afgan
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.csite.2022.102276
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.csite.2022.102276
The present work is focused on enhancing the overall thermo-hydraulic performance of a previously proposed C-shaped printed circuit heat exchanger (PCHEs) using Machine Learning (ML) Algorithms. In this context, CFD analysis is carried out on 81 different channel configurations of the C-shaped channel geometry, and computed data is used to train three ML algorithms. Later, C-shaped channel geometry is optimized by coupling the trained ML model with the multi-objective genetic algorithm (MOGA). Finally, the optimized channel geometry (called optimizedML) is investigated numerically for a wide range of Reynolds numbers. Its performance is compared with the zigzag geometry, C-shaped base geometry, and previously optimized C-shape channel geometry using response surface methodology (RSM). The findings showed that the multilayered approach combining MOGA, CFD, and machine learning techniques is beneficial to accomplish a robust and realistic optimized solution. Comparing the thermo-hydraulic characteristics of the optimizedML channel geometry with zigzag channel geometry shows that the former is up to 1.24 times better than the latter based on the performance evaluation criteria (PEC). Furthermore, the overall performance of the optimizeML channel geometry was found up to 21% and 16% higher than the optimized RSM geometry on the cold and hot sides, respectively.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.csite.2022.102276
- https://ars.els-cdn.com/content/image/1-s2.0-S2214157X22005226-ga1_lrg.jpg
- OA Status
- gold
- Cited By
- 56
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4292996395
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Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4292996395Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.csite.2022.102276Digital Object Identifier
- Title
-
Performance enhancement of a C-shaped printed circuit heat exchanger in supercritical CO2 Brayton cycle: A machine learning-based optimization studyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-08-08Full publication date if available
- Authors
-
Muhammad Saeed, Abdallah S. Berrouk, Yasser F. Al Wahedi, Munendra Pal Singh, Ibragim Abu Dagga, Imran AfganList of authors in order
- Landing page
-
https://doi.org/10.1016/j.csite.2022.102276Publisher landing page
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https://ars.els-cdn.com/content/image/1-s2.0-S2214157X22005226-ga1_lrg.jpgDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://ars.els-cdn.com/content/image/1-s2.0-S2214157X22005226-ga1_lrg.jpgDirect OA link when available
- Concepts
-
Hydraulic diameter, Zigzag, Geometry, Heat exchanger, Reynolds number, Context (archaeology), Brayton cycle, Channel (broadcasting), Materials science, Mechanical engineering, Computer science, Mechanics, Mathematics, Engineering, Physics, Paleontology, Biology, Computer network, TurbulenceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
56Total citation count in OpenAlex
- Citations by year (recent)
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2025: 20, 2024: 24, 2023: 12Per-year citation counts (last 5 years)
- References (count)
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58Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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