Assessment of micro-scale heat exchangers efficiency using lattice Boltzmann method and design of experiments
•Micro-scale cavity heat exchangers efficiency is assessed and optimized.•Box-Behnken table map of 4 factors of 3 levels is used to specify runs.•LB method is used to perform the experiments (27 trials/runs) accordingly.•Multi-responses DOE optimization is adopted to enhance Nu and reduce Sgen.•Opti...
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Veröffentlicht in: | Energy and built environment 2024-12, Vol.5 (6), p.840-852 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Micro-scale cavity heat exchangers efficiency is assessed and optimized.•Box-Behnken table map of 4 factors of 3 levels is used to specify runs.•LB method is used to perform the experiments (27 trials/runs) accordingly.•Multi-responses DOE optimization is adopted to enhance Nu and reduce Sgen.•Optimized results agree credibility test and non-linear correlations are given.
The study is focused on the use of nanofluids in a micro-open tall cavity, which is a type of micro heat exchanger (MHE). The cavity is heated from the bottom sidewall in a sinusoidal pattern, and the effects of four input parameters (Ra, Ha, Kn, and Vf) on heat transfer and irreversibility are investigated using numerical simulations based on Lattice Boltzmann Method (LBM). The findings of the study suggest that the local heat transfer on the bottom sidewall is strongly influenced by Ra and Ha, while the surface distribution of entropy generation is mainly dependent on Kn. The study also shows that the optimization of the magnitude and wavelength of the sinusoidal temperature can improve both local heat transfer and surface distribution of entropy generation. The results of the study provide valuable insights into the design of micro heat exchangers and suggest that the optimization of micro-porous geometries using DOE could lead to increased energy efficiency. The study contributes to our understanding of the complex interactions between input parameters in micro heat exchangers and highlights the importance of considering multiple parameters in the design process.
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ISSN: | 2666-1233 2666-1233 |
DOI: | 10.1016/j.enbenv.2023.06.011 |