Multi-objective heat transfer optimization of 2D helical micro-fins using NSGA-II
dc.citation | Mann, G. W., & Eckels, S. (2019). Multi-objective heat transfer optimization of 2D helical micro-fins using NSGA-II. International Journal of Heat and Mass Transfer, 132, 1250–1261. https://doi.org/10.1016/j.ijheatmasstransfer.2018.12.078 | |
dc.citation.doi | 10.1016/j.ijheatmasstransfer.2018.12.078 | |
dc.citation.issn | 0017-9310 | |
dc.citation.jtitle | International Journal of Heat and Mass Transfer | |
dc.citation.volume | 132 | |
dc.contributor.author | Mann, Garrett W. | |
dc.contributor.author | Eckels, Steven | |
dc.contributor.authoreid | eckels | |
dc.date.accessioned | 2019-12-23T22:47:25Z | |
dc.date.available | 2019-12-23T22:47:25Z | |
dc.date.issued | 2019-04-01 | |
dc.date.published | 2019 | |
dc.description | Citation: Mann, G. W., & Eckels, S. (2019). Multi-objective heat transfer optimization of 2D helical micro-fins using NSGA-II. International Journal of Heat and Mass Transfer, 132, 1250–1261. https://doi.org/10.1016/j.ijheatmasstransfer.2018.12.078 | |
dc.description.abstract | A numerical simulation of helical micro-fins is implemented in ANSYS Fluent 15. The model is scripted to automatically set up and execute given three input parameters: fin height, helix angle, and number of starts. The simulation results reasonably predict experimental pressure drop and heat transfer for multiple micro-fin geometries. A multi-objective parameter optimization is implemented based on the NSGA-II algorithm to estimate the optimal trade-off (Pareto front) between Nusselt number and friction factor of a micro-fin tube for 0.0006 < e/D < 0.045, 10 < Ns < 70, at Reynolds number of 49,013. The resulting Pareto front is analyzed and compared with several experimental data points. From the optimal results, a distinct difference in flow characteristics was identified between geometries above and below a helix angle of approximately 45°. How the Pareto front can be used to choose micro-fin geometries for different performance evaluation criterion scenarios is demonstrated. Optimal results from various existing correlations are also compared to the optimization results. | |
dc.description.embargo | Version of Record (VoR) | |
dc.identifier.uri | http://hdl.handle.net/2097/40333 | |
dc.relation.uri | https://doi.org/10.1016/j.ijheatmasstransfer.2018.12.078 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.title | Multi-objective heat transfer optimization of 2D helical micro-fins using NSGA-II | |
dc.type | Text |
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