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首页> 外文期刊>Numerical Heat Transfer, Part B. Fundamentals: An International Journal of Computation and Methodology >Identification of the key variables on thermal conductivity of CuO nanofluid by a fractional factorial design approach
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Identification of the key variables on thermal conductivity of CuO nanofluid by a fractional factorial design approach

机译：通过分数阶乘设计方法确定CuO纳米流体导热系数的关键变量

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摘要

Seven important parameters (temperature, concentration, average primary particle size, pH of nanofluid, density of nanoparticle, elapsed time, and sonication time) which are responsible for the change of the thermal conductivity of nanofluids were experimentally investigated on CuO/water nanofluid and were statistically surveyed by a factorial design method. In order to investigate the main effects and their interactions on the thermal conductivity ratio, a 2~(7-4) _IIIfractional factorial design (FFD) with three other experiments at the center of the design for analysis of variance were applied. Also, the factorial model was statistically validated by analysis of variance (ANOVA). The predicted responses was compared with the experimental ones. Generally, the predicted values were in reasonable agreement with the experimental data, further confirming the high predictability of the models.
机译：在CuO /水纳米流体上，通过实验研究了七个重要参数（温度，浓度，平均初级粒径，纳米流体的pH，纳米颗粒的密度，经过时间和超声处理时间），这些参数决定了纳米流体的导热系数的变化。通过析因设计方法进行统计调查。为了研究主要影响及其相互作用对导热系数的影响，采用了2〜（7-4）_III分数阶乘设计（FFD），并在设计的中心进行了另外三个实验，用于分析方差。此外，通过方差分析（ANOVA）在统计学上验证了阶乘模型。将预测的响应与实验响应进行比较。通常，预测值与实验数据合理吻合，进一步证实了模型的高度可预测性。

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