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Potential of adaptive neuro-fuzzy methodology for investigation of heat transfer enhancement of a minichannel heat sink

机译:适应性神经模糊方法的潜力,用于调查Miniocannel散热器的传热增强

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In this paper, the potential of adaptive neuro fuzzy inference system (ANFIS) was appraised for investigation of thermal performances of a minichannel heat sink for cooling of electronics using nanofluid coolant instead of pure water. The process, which simulates the thermal performances with ANFIS network, was constructed. The developed ANFIS network was with three neurons in the input layer, and one neuron (thermal performances) in the output layer. Since there are three thermal performances investigated, three ANFIS networks are created. The inputs were flow rate, as well as the Reynolds number. The third input represents the nanofluid concentration. The Al2O3-H2O nanofluid including the volume fraction was used as a coolant. Obtained experimental results showed the higher improvement of the thermal performances using nanofluid instead of pure distilled water. ANFIS results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach for heat sink base temperature prediction. (C) 2019 Elsevier B.V. All rights reserved.
机译:在本文中,评估了适应性神经模糊推理系统(ANFIS)的潜力,用于研究Miniocannel散热器的热性能,用于使用纳米流体冷却剂而不是纯水冷却电子器件。构建了模拟与ANFIS网络的热性能的过程。开发的ANFIS网络在输入层中有三个神经元,以及输出层中的一个神经元(热性能)。由于调查了三种热性能,因此创建了三个ANFIS网络。输入是流速,以及雷诺数。第三输入代表纳米流体浓度。使用包括体积分数的Al 2 O 3-H 2 O纳米流体用作冷却剂。获得的实验结果表明,使用纳米流体代替纯蒸馏水的热性能更高。 ANFIS结果表明,通过用于散热器基础温度预测的ANFIS方法,可以实现预测准确度和泛型能力的提高。 (c)2019 Elsevier B.v.保留所有权利。

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