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A scientometric approach is utilized to investigate the dynamic maps of relationships among researchers, institutes, and countries in the field of Artificial Intelligence for Fluid-flow and Heat-transfer (AIFH). The Web of Science database was searched for related publications during the last 40 years (1982 and 2022). A total of 6151 articles were discovered, which were analyzed in detail. Using a bibliometric analysis, the most relevant and most cited sources of publications were identified. The most active researchers, institutions, and countries leading AIFH were reported. Then, the worldwide dynamic collaboration maps and coupling maps of relationships were reported. The Islamic Azad University (1893 T.C.), the Chinese Academy of Sciences (1374 T.C.), and Beihang University (1266 T.C.) were the most influential institutes in AIFH. The most influential countries were China, the USA, and Iran. The dynamic map of collaborations shows a good worldwide collaboration distribution. The USA and China established the most connection with the rest of the world. ANNs are the most studied topic (19.5% of publications), followed by Machine Learning (17.9%) and Neural Networks (15.4%). Support Vector Machines lag behind at 1.4%. ANNs boast the highest total citations (17,064) and H-index (63). Most ANIF papers were published by Medical Physics (119 T.P.). Half of the articles in AIFH were published by five journals of Medical Physics, Neurocomputing, International Journal of Heat and Mass Transfer, International Journal of Radiation Oncology Biology Physics, and IEEE Access. The International Journal of Heat and Mass Transfer received the most citations in AIFH. [ABSTRACT FROM AUTHOR]