微通道
纳米流体
材料科学
散热片
合金
石墨烯
复合材料
热的
工作液
水力直径
冶金
机械工程
机械
纳米技术
热力学
雷诺数
工程类
纳米颗粒
湍流
物理
作者
Puurnaraj Nadarajah,Khairudin Mohamed,Jamaluddin Abdullah,Mutharasu Devarajan
标识
DOI:10.1088/1361-6439/ad2304
摘要
Abstract Microchannel heat sinks (MCHS) are known for providing enhanced cooling performance but their fabrication requires complex and multi step processes. The recent development of additive manufacturing has enabled the fabrication of state-of-art monolithic structures that had been impossible to build using conventional methods. In this work, a monolithic cross-flow triangular cross-section microchannel heat sink was fabricated from aluminum alloy (AlSi 10 Mg) using the Direct Metal Laser Sintering (DMLS) process. The microchannel wall surface roughness was measured and the cross-section shrinkage of the microchannels was compared with the initial design hydraulic diameter of 500 µm - 1 000 µm., The MCHS with an initial design hydraulic diameter of 750 µm possessed a relative wall surface roughness, R a of 7.7%. The triangular cross-section hydraulic diameter underwent a shrinkage of 15.2% and 5.3% in terms of the reduction in angle between adjacent side alloys. Experiments were conducted for Reynolds numbers between 50 and 275 with nanofluids containing graphene and Al 2 O 3 nanoparticles in water/water +10% ethylene glycol; these were compared with their respective base fluids. For this range of Reynolds numbers, with water as coolant, the rough wall surface elevated the friction factor to least double that of smooth microchannels. The Poiseuille number indicated that flow was laminar developed with base fluid and laminar developing with nanofluid as coolant. Despite providing the lowest thermal resistance, the graphene nanoparticles in water created the greatest pressure drop leading to a reduced performance coefficient. Al 2 O 3 nanoparticles in water/water +10% Ethylene glycol were found to have 7.7% and 20% better performance coefficients than their respective base fluids.
科研通智能强力驱动
Strongly Powered by AbleSci AI