ARTICLE
28 April 2026
Teaching Design of Thermodynamics and Fluid Mechanics Empowered by Digital Intelligence: A Case Study of Bernoulli’s Equation
Yuexia Lv Sa Li Yunqian Ma Mingdong Yi Jin Du Lili Zhang
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1 Faculty of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, Shandong, China,
2 Teaching Affairs Office, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, Shandong, China,
3 College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Science), Jinan 250353, Shandong, China,
IEF 2026 , 4(4), 98–106; https://doi.org/10.26689/ief.v4i4.14882
© 2026 by the Authors. Licensee: Bio-Byword Scientific Publishing Pty Ltd, Australia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

Bernoulli’s equation is a fundamental principle in Thermodynamics and Fluid Mechanics, which has been extensively applied in engineering scenarios. However, traditional teaching approaches are often encountered with challenges that restrict students’ deep conceptual understanding and practical application capabilities. To address these issues, this study proposes a digital intelligence empowered teaching model that integrates artificial intelligence technologies throughout the entire instructional process. A four-dimensional framework named “theoretical foundation, AI empowerment, ideological guidance, and advanced extension” is developed to enhance the visualization, interaction, and adaptability of teaching. AI-driven simulation platforms, intelligent tutoring systems, and learning analytics are incorporated to facilitate personalized learning and provide real-time feedback. Furthermore, engineering scenarios are embedded to effectively bridge the gap between theoretical knowledge and practical application. The results of teaching practice demonstrate that the proposed model significantly improves students’ engagement, conceptual understanding, and engineering application abilities, which also promotes higher-order thinking and innovation capacity.

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