期刊
ACS OMEGA
卷 5, 期 48, 页码 30826-30835出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsomega.0c04497
关键词
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资金
- Government of the Russian Federation [A03.21.0011]
- Ministry of Science and Higher Education of the Russian Federation [FENU-2020-0019]
This investigation is conducted to study the integration of the artificial intelligence (AI) method with computational fluid dynamics (CFD). The case study is hydrodynamic and heat-transfer analyses of water flow in a metal foam tube under a constant wall heat flux (i.e., 55 kW/m(2)). The adaptive network-based fuzzy inference system (ANFIS) is an AI method. A 3D CFD model is established in ANSYS-FLUENT software. The velocity of the fluid in the x-direction (Ux) is considered as an output of the ANFIS. The x, y, and z coordinates of the node's location are added to the ANFIS step-by-step to achieve the best intelligence. The number and type of membership functions (MFs) are changed in each step. The training process is done by the CFD results on the tube cross-sections at different lengths (i.e., z = 0.1, 0.2, 0.3, 0.4, 0.6, 0.7, 0.8, and 0.9), while all data (including z = 0.5) are selected for the testing process. The results showed that the ANFIS reaches the best intelligence with all three inputs, five MFs, and gbellmf-type MF. At this condition, the regression number is close to 1.
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