Predicting the specific heat capacity of alumina/ethylene glycol nanofluids using support vector regression model optimized with Bayesian algorithm
Nanofluids are now considered the most essential constituent of solar thermal collector due to their superior thermal performance over conventional fluids. An accurate determination of the thermal efficiency of the solar collector depends on the value of the specific heat capacity of the nanofluid. So far...
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| 主要な著者: | , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Elsevier
2019
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/81784/1/20201028%20-%20Predicting%20the%20specific%20heat%20capacity%20of%20alumina_ethylene%20glycol%20nanofluids%20using%20support%20vector%20regression%20model%20optimized%20with%20Bayesian%20algorithm%20.pdf http://psasir.upm.edu.my/id/eprint/81784/ https://www.sciencedirect.com/science/article/abs/pii/S0038092X19301860 |
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