Experimental Investigation and Modeling of Bubble Departure Frequency for Pool-Boiling Heat Transfer

被引：2

作者：

Hamzekhani, Samane ^{[1
]}

Shahraki, Farhad ^{[1
]}

Mohebbi-Kalhori, Davood ^{[1
,2
]}

Fardinpour, Mohammad Reza ^{[2
]}

机构：

[1] Univ Sistan & Baluchestan, Dept Chem Engn, Zahedan 98164161, Iran

[2] Islamic Azad Univ, Mahshahr Branch, Fac Chem Engn, POB 6351977439, Mahshahr, Iran

来源：

CHEMICAL ENGINEERING & TECHNOLOGY | 2022年 / 45卷 / 11期

关键词：

Artificial neural networks; Bubble departure frequency; Pool boiling; Pure liquids; Response surface methodology; ENHANCEMENT; DIAMETER; FLUX; OPTIMIZATION; NANOFLUIDS; SURFACE;

D O I：

10.1002/ceat.202100624

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

The artificial neural network (ANN) method and response surface methodology (RSM) were used to predict the bubble departure frequency for the pool-boiling heat transfer of pure liquids, by using experimental data. The effects of vapor-liquid density difference, vapor-liquid viscosity difference, surface tension, thermal conductivity, and heat flux on the departure frequency of vapor bubbles were investigated by RSM and ANN. The results showed that the outputs of the ANN and RSM had a suitable overlap with the experimental data, but the RSM model was more accurate than the ANN model.

引用

页码：2049 / 2060

页数：12

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