摘要
纳米流体热物性的研究作为一门新兴交叉学科一直受到关注,然而至今仍没有理论能够准确解释AuH2O这类体积分数极低的纳米流体导热系数极大增强的现象。因此,在前人理论的基础上,提出一种新的算法模型:利用分形理论模拟纳米颗粒分布来解释团聚物对纳米流体导热系数的影响;利用微对流模型以及颗粒扩散修正因子来还原导热系数的动态项。该算法模型充分考虑了团聚、颗粒分布、布朗运动形成的微对流、温度对颗粒和基液分子布朗运动的影响以及颗粒扩散等因素对纳米流体导热系数的影响,能够准确预测出Au-H2O纳米流体导热系数增强的趋势,理论预测值与绝大部分现有实验数据最大偏差不超过1.5%。研究发现,对这类极低浓度纳米流体而言,温度对其影响大于体积分数和粒径的影响,且呈指数形式增长。
The heat transfer of nanofluids has been studied as an emergent interdisciplinary. However, there is no theory that can explain the enormous enhancement of TC of gold nanofluids compare to its extremely low volume fraction. Therefore, we present a brand new algorithm/model, which has fully taken clusters, distribution and diffu sion of particles, Brownian motion, temperature into consideration, to explain the effect of the clusters by simulating the distribution of nanoparticles with fractal theory and calculate the TC caused by Brownian motion of nanoparticles using micro-heat convection model and a modifying factor. This model is able to predict the enhancement of TC of gold nanofluids with its deviation from experimental date less than 1.5%. We have discovered that, as for this kind of nanofluids with extremely low volume fraction, TC was affected greater by temperature, increasing in exponent, than by both the volume fraction and particle size.
基金
"高等学校学科创新引智计划"(X99974)
关键词
Au—H2O
纳米流体
极低体积分数
布朗运动
导热机理
Au-H2O nanofluids
extremely low volume fraction
Brownian motion
mechanism of thermal con-ductivity