Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets
Fountains injected into homogeneous fluids, characterized by combined temperature and concentration effects, are common in both natural and environmental settings. In this study, the capacities of several machine learning models, including support vector regression, multi-layer perceptron, random fo...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2025-01-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0243565 |
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| _version_ | 1832542766006009856 |
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| author | Yaowen Xia Wenfeng Gao Qiong Li Banglong Wu Jia Xie Shuting Yang |
| author_facet | Yaowen Xia Wenfeng Gao Qiong Li Banglong Wu Jia Xie Shuting Yang |
| author_sort | Yaowen Xia |
| collection | DOAJ |
| description | Fountains injected into homogeneous fluids, characterized by combined temperature and concentration effects, are common in both natural and environmental settings. In this study, the capacities of several machine learning models, including support vector regression, multi-layer perceptron, random forests, XGBoost, CatBoost, AdaBoost, and LightGBM, were investigated to clarify the transient flow behavior of fountains. The results indicated that the multi-layer perceptron was superior to the other models as it provided improved coefficient of determination, root mean squared error, and mean absolute error. This study confirmed that the machine learning techniques have great potential to study the transient flow behavior of fountains. |
| format | Article |
| id | doaj-art-04b74026da1f43d9805a86730b11f656 |
| institution | Kabale University |
| issn | 2158-3226 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj-art-04b74026da1f43d9805a86730b11f6562025-02-03T16:40:42ZengAIP Publishing LLCAIP Advances2158-32262025-01-01151015039015039-810.1063/5.0243565Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jetsYaowen Xia0Wenfeng Gao1Qiong Li2Banglong Wu3Jia Xie4Shuting Yang5School of Information Science and Technology, Yunnan Normal University, Kunming 650500, ChinaKey Laboratory of Rural Energy Engineering of Yunnan, Kunming, Yunnan 650500, ChinaKey Laboratory of Rural Energy Engineering of Yunnan, Kunming, Yunnan 650500, ChinaSouthwest United Graduate School, Kunming, Yunnan 650092, ChinaSouthwest United Graduate School, Kunming, Yunnan 650092, ChinaSouthwest United Graduate School, Kunming, Yunnan 650092, ChinaFountains injected into homogeneous fluids, characterized by combined temperature and concentration effects, are common in both natural and environmental settings. In this study, the capacities of several machine learning models, including support vector regression, multi-layer perceptron, random forests, XGBoost, CatBoost, AdaBoost, and LightGBM, were investigated to clarify the transient flow behavior of fountains. The results indicated that the multi-layer perceptron was superior to the other models as it provided improved coefficient of determination, root mean squared error, and mean absolute error. This study confirmed that the machine learning techniques have great potential to study the transient flow behavior of fountains.http://dx.doi.org/10.1063/5.0243565 |
| spellingShingle | Yaowen Xia Wenfeng Gao Qiong Li Banglong Wu Jia Xie Shuting Yang Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets AIP Advances |
| title | Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets |
| title_full | Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets |
| title_fullStr | Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets |
| title_full_unstemmed | Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets |
| title_short | Machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets |
| title_sort | machine learning predicting the transport mechanisms and entrainment characteristics of negative buoyant jets |
| url | http://dx.doi.org/10.1063/5.0243565 |
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