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6CCVD Research

A novel case of honeycomb shaped pin fin heat sink - CFD-data driven machine learning models for thermal performance prediction

At a Glance

Section titled ā€œAt a Glanceā€
MetadataDetails
Publication Date2024-09-01
JournalCase Studies in Thermal Engineering
AuthorsKazi Masuk Elahi, Nabil Mohammad Chowdhury, Mohammad Rejaul Haque, Md. Mamunur Rashid, Md Meraj Hossain
Citations18

Abstract

Section titled ā€œAbstractā€

This research explores a useful thermal engineering application utilizing novel honeycomb-shaped pin fins heat sink (PFHS). 3D incompressible flow and heat transfer are examined using standard k-Ō‘ turbulence model for Reynolds numbers (Re) ranging from 8547 to 21367. Using the PFHS with 1.5 mm side length and pitch arrangement of (S =25 Ɨ 25), the Nusselt Number (Nu) increased by 171 % at a Re of 21367. Furthermore, Cu-Diamond composite material raises Hydrothermal performance factor (HTPF) to 3.304. At a Re of 8547, honeycomb heat sink has 200 % greater HTPF than the baseline. Predictive modeling of HTPF, Nu, and pressure drop (Ī”P) was done using Artificial Neural Network (ANN), Multiple Linear Regression (MLR), Extreme Gradient Boosting Regression (XGBR), and Light Gradient Boosting Machine Regression (LGBMR). The four models with the highest R2 and lowest MRE on the test dataset performed best. Both models were implemented using Keras and Sklearn. XGBR and MLR have superior HTPF prediction accuracy (R2test = 0.977, MRE (%) = 1.1 and 0.924, MRE (%) = 2.1). XGBR and MLR predicted the Nu well with R2test values of 0.979 and MRE percentages of 1.9 and 3.9. R2test of 0.999 and MRE (%) of 0.3 indicate that XGBR predicts pressure reduction.

Tech Support

Section titled ā€œTech Supportā€

Original Source

Section titled ā€œOriginal Sourceā€

References

Section titled ā€œReferencesā€
  1. 2014 - Optimum design of a radial heat sink with a fin-height profile for high-power LED lighting applications [Crossref]
  2. 2022 - Optimization design by evolutionary computation for minimizing thermal stress of a thermoelectric generator with varied numbers of square pin fins [Crossref]
  3. 2017 - Experimental investigation of n-eicosane based circular pin-fin heat sinks for passive cooling of electronic devices [Crossref]
  4. 2017 - Numerical and experimental analysis of cooling performance of single-phase array microchannel heat sinks with different pin-fin configurations [Crossref]
  5. 2009 - Numerical analysis of turbulent convection heat transfer from an array of perforated fins [Crossref]
  6. 2011 - Investigation of effects of heat sinks on thermal performance of microelectronic package
  7. 2019 - Effects of a pyramidal pin fins on CPU heat sink performances
  8. 2022 - CFD studies on thermal performance augmentation of heat sink using perforated twisted, and grooved pin fins [Crossref]
  9. 2022 - Numerical investigation of heat transfer performance for rectangular, elliptical, and airfoil shaped pin fin heatsinks through the novel combination of perforation and bulge inserts [Crossref]

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