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首页> 外文期刊>International Journal of Heat and Mass Transfer >Neural network analysis of boiling hat transfer enhancement using additives
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Neural network analysis of boiling hat transfer enhancement using additives

机译：使用添加剂增强沸腾帽转移的神经网络分析

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摘要

A model was developed to evaluate and predict boiling heat transfer enhancement using additives. The model is based on the molecular structures of the additives and uses artificial neural network technology. The effects of 30 additives tested by the authors and other researchers on the augmentation of boiling heat transfer were analyzed with the model. The results show that the evaluation of all 30 additives is consistent with the experimental data, which means that the training accuracy of the model is 100/100. In addition, the boiling heat transfer enhancement with sodium oblate and 11 other additives was also predicted, with a prediction accuracy of over 90/100 since the calculated results for 10 of the 11 additives were in agreement with the experimental results.
机译：开发了用于评估和预测使用添加剂的沸腾传热增强的模型。该模型基于添加剂的分子结构，并使用人工神经网络技术。使用该模型分析了作者和其他研究人员测试的30种添加剂对沸腾传热的增强作用。结果表明，对全部30种添加剂的评价与实验数据吻合，表明该模型的训练精度为100/100。此外，还预测了使用扁酸钠和其他11种添加剂的沸腾传热增强，由于11种添加剂中10种的计算结果与实验结果一致，因此预测精度超过90/100。

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