Integration of artificial intelligence and triple integral in aerodynamic analysis
Received: 2025-05-07
Published: 2025-11-03
Abstract
This article examines the possibilities of spatial analysis of airflow based on triple integrals and the effective use of artificial intelligence tools in this process. The distribution of air density and velocity fields in three-dimensional space is expressed through mathematical modeling, and calculations are performed quickly and visually using artificial intelligence. The article highlights the interactive and practical approach of engineering education through the integration of modern technologies in solving aerodynamic problems, in particular AI (Artificial intelligence) algorithms, into the educational process. The research results propose new approaches to the modeling of real systems through automated solutions of spatial integral analysis.
Keywords
List of references
-
Anderson, J. D. (1991). Fundamentals of Aerodynamics (2nd ed.). McGraw-Hill.
-
Versteeg, H. K., & Malalasekera, W. (2007). An Introduction to Computational Fluid Dynamics: The Finite Volume Method (2nd ed.). Pearson Education.
-
Zhang, Y., Wang, L., & Li, H. (2020). AI-based simulation of aerodynamic flows: Integrating machine learning with CFD. Journal of Computational Physics, 419, 109676. https://doi.org/10.1016/j.jcp.2020.109676
-
Wolfram Research, Inc. (2024). Wolfram Language & System Documentation Center. Retrieved from
-
OpenFOAM Foundation. (2023). OpenFOAM User Guide. Retrieved from https://www.openfoam.com/documentation
-
MathWorks. (2023). MATLAB & Simulink Documentation. Retrieved from https://www.mathworks.com/help/.