Development of CNC Micro-milled Leaf-Pattern Micro-channel Heat Sink (LP-MCHS) and Testing Using Nanofluids

• Published in: IOP conference series. Materials Science and Engineering Vol. 810; no. 1; pp. 12025 - 12038
• Main Authors: Itankar, S R, Mohite, S S, Gaikwad, V P, Parmar, H
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.03.2020
• Subjects: Aluminum oxide; Base fluid (bf); Confined spaces; Copper oxides; Deionized water (DI); Flow velocity; Fluid dynamics; Fluid flow; Heat flux; Heat sinks; Leaf pattern micro-channel heat sink (LP-MCHS); Machine tools; Machining centres; Micro-channel Heat Sink (MCHS); Microchannels; Milling (machining); Nanofluid (nf); Nanofluids; Nusselt Number (Nu); Performance evaluation; Performance Evaluation Criterion (PEC); Pressure drop; Pressure drop (ΔP); Reynolds number (Re); Silicon dioxide; Silicon oxides; Working fluids
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/810/1/012025

Micro-channel heat sinks (MCHS) have attracted the attention of researchers because of their compact design and wide range of applications. MCHS is mostly used to dissipate heat where large amount of heat is generated in a confined space. In this work, leaf pattern MCHS is fabricated on pure copper block by micro-milling on CNC machining center and is tested for its thermal performance and fluid flow behaviour using pure water as well as various nanofluids such as Copper Oxide(CuO), Aluminium Oxide(Al2O3)and Silicon Oxide(SiO2). The volume concentration of nanofluids was kept constant, i.e., 0.3% volume fraction and the experiments were carried out for heat flux ranging from 65 W/cm2 to 200 W/cm2 and flow rate from 100 ml/min to 900 ml/min. The results of experiments indicate that these nanofluids, as a working fluid, enhance the heat transfer by 35% and Nusselt Number by up to 37%, however, increases the pressure drop by 18% which increases the pumping power. From the performance evaluation analysis, it was found that the SiO2 nanofluid with leaf pattern MCHS gives optimal performance.