Abstract Traditional testing algorithm based on pattern matching is impossible to effectively analyze the heat transfer performance of heat pipes filled with different concentrations of nanofluids, so the testing algorithm for heat transfer performance of a nanofluidic heat pipe based on neural network is proposed. Nanofluids are obtained by weighing, preparing, stirring, standing and shaking using dichotomy. Based on this, the heat transfer performance analysis model of the nanofluidic heat pipe based on artificial neural network is constructed, which is applied to the analysis of heat transfer performance of nanofluidic heat pipes to achieve accurate analysis. The experimental results show that the proposed algorithm can effectively analyze the heat transfer performance of heat pipes under different concentrations of nanofluids, and the heat transfer performance of heat pipes is best when the volume fraction of nanofluids is 0.15%.

中文翻译：

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基于神经网络的纳米流体填充热管传热性能测试算法

摘要 传统的基于模式匹配的测试算法无法有效分析填充不同浓度纳米流体的热管的传热性能，提出一种基于神经网络的纳米流体热管传热性能测试算法。使用二分法通过称重、制备、搅拌、静置和摇动获得纳米流体。在此基础上，构建了基于人工神经网络的纳米流体热管传热性能分析模型，应用于纳米流体热管传热性能分析中，实现精确分析。实验结果表明，所提算法能够有效分析不同纳米流体浓度下热管的传热性能，