Heat transfer optimisation using novel biomorphic pin-fin heat sinks - An integrated approach - design for manufacturing, numerical simulation, and machine learning

Aug 5, 2026

Advanced manufacturing enables non-conventional, bio-inspired biomorphic geometries that can improve heat transfer performance. This study evaluates thermal and flow behavior of novel biomorphic scutoid pin fins with different volumes and top configurations. Reynolds numbers in the range 5500–13500 were simulated using four hybrid designs, and the effect of top geometry on heat transfer coefficient was assessed by combining CFD, experimental data, and machine learning. The new fins reduce volume/material by 6.3–14.3% while increasing heat transfer by about 1.5–1.7 times, yielding more uniform velocity and temperature fields.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages21

Reading Time53 min

AccessFree to download

Introduction

Thermal challenge in miniaturized electronics

Biomorphic pin-fin concept and motivation

Thermal Science and Engineering Progress 51 (2024) 102606 Contents lists available at ScienceDirect Thermal Science and Engineering Progress journal [homepage:](homepage: www.sciencedirect.com/journal/thermal-science-and-engineering-progress)[ www.sciencedirect.com/journal/thermal-science-and-engineering-progress](homepage: www.sciencedirect.com/journal/thermal-science-and-engineering-progress) | Heat transfer optimisation using novel biomorphic pin-fin heat sinks: An integrated approach via design for manufacturing, numerical simulation, and machine learning
Mohammad Harris a, *, Hongwei Wu a, *, Anastasia Angelopoulou b, Wenbin Zhang c, Zhuohuan Hud, Yongqi Xiee
a School of Physics, Engineering and Computer Science, University of Hertfordshire, College Lane Campus, Hatfield AL10 9AB, UK b School of Computer Science and Engineering, University of Westminster, 115 New Cavendish Street, London W1W 6UW, UK c School of Science & Technology, Nottingham Trent University, Clifton Lane, Clifton, Nottingham NG11 8NS, UK
d School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China e School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China | | | | --- | --- | --- | | A R T I C L E I N F O | | A B S T R A C T | | Keywords:
Heat transfer enhancement Biomorphic pin fins
Mini and microchannels Machine learning Numerical simulation | | With the availability of advanced manufacturing techniques, non-conventional shapes and bio-inspired/ biomorphic designs have shown to provide more efficient heat transfer. Consequently, this research investigates the heat transfer performance and fluid flow characteristics of novel biomorphic scutoid pin fins with varying volumes and top geometries. Numerical simulations were conducted using four hybrid designs for Reynolds Number 5500–13500. The impact of pin fin ’top’ geometrical features on the heat transfer coefficient (HTC) was evaluated by combining computational fluid dynamics (CFD), experimental data, and machine learning. The results highlighted that the new pin fins saved 6.3 % to 14.3 % volume/material usage but produced around 1.5 to 1.7 times more heat transfer than conventional square/rectangular fins. Also, manipulating pin fins via the top geometrical properties can lead to more uniform velocity and temperature distributions while demonstrating the potential for increased thermal efficiency with reduced thermal resistance. Furthermore, six machine learning models accurately predict HTC using volume and surface area as key variables, achieving less than 5 % mean absolute percentage error (MAPE). Overall, this research introduces innovative biomorphic designs with unconventional geometries, emphasising resource optimisation and efficient HTC prediction using machine learning. It simplifies design processes, supports agile product development, calls for re-evaluation of conventional heat sink geometries, and provides promising directions for future research. | Nomenclature Latin Symbols A Area,m2 Cp Specific heat capacity,J/kgˆA⋅K D Diameter,m Dh Hydraulic diameter,m h Heat transfer coefficient,W/m2K H Height, m K Thermal conductivity,W/mˆA⋅K L Length,m m˙ Mass flow rate,kg/s Nu Nusselt number, no unit (continued on next column) Nomenclature (continued ) Q˙ Heat energy rate,W/m2 R Thermal resistance, K/W Re Reynolds number, no unit SA Surface area, m2 T Temperature,C U,V,W Dimensionless parameter u,v,w Directional velocity,m/s V Volume,m3 W Width,m x,y,z Directional vectors X,Y,Z Dimensionless parameter Greek Symbols η Efficiency, dimensionless (continued on next page) * Corresponding authors. E-mail [addresses:](addresses: m.harris8@herts.ac.uk)[ m.harris8@herts.ac.uk](addresses: m.harris8@herts.ac.uk) (M. Harris), [h.wu6@herts.ac.uk](h.wu6@herts.ac.uk) (H. Wu). [https://doi.org/10.1016/j.tsep.2024.102606](https://doi.org/10

FAQs

What is the focus of this research on biomorphic pin-fin heat sinks?

It investigates heat transfer performance and fluid flow characteristics of novel biomorphic scutoid pin fins, emphasizing how geometry variations influence thermal behavior.

How were the heat transfer results evaluated in the study?

The work uses numerical simulations over Reynolds numbers 5500–13500 and evaluates the influence of top geometries by integrating CFD, experimental data, and machine learning models.

What performance improvements were reported compared with conventional fins?

The optimized biomorphic pin fins used 6.3% to 14.3% less volume/material and delivered about 1.5 to 1.7 times more heat transfer than conventional square or rectangular fins.

Aug 5, 2026

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