On the measurement of the aerodynamic features of composite structures under subsonic airflow using mathematical modeling and machine learning method
•Presenting transient aerodynamic features of FG-TPMS doubly curved panel under subsonic airflow.•Implementation Hamilton’s principle, and parabolic shear deformation theory for extracting the motion equations.•Introducing machine learning algorithm for transient problems using the presented mathema...
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Veröffentlicht in: | Measurement : journal of the International Measurement Confederation 2024-10, Vol.238, p.115246, Article 115246 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Presenting transient aerodynamic features of FG-TPMS doubly curved panel under subsonic airflow.•Implementation Hamilton’s principle, and parabolic shear deformation theory for extracting the motion equations.•Introducing machine learning algorithm for transient problems using the presented mathematical modeling datasets.•Presenting some recommendations to improve the transient dynamic response of presented structure under external excitation.
This study investigates the aerodynamic features of functionally graded triply periodic minimal surface (FG-TPMS) structures under subsonic airflow using a combination of mathematical modeling and machine learning methods. The modified supersonic piston theory of Krumhaar is used to quantify the aerodynamic stiffness and damping matrices. Using characteristics and six distinct patterns of volume distribution of FG-TPMS materials in terms of their mechanical qualities, Hamilton’s principle, and parabolic shear deformation theory are used to extract the governing equations of the presented composite structure. After that, the differential quadrature method at the discrete places and Lagrange interpolated polynomials and Kronecker product are used to solve the governing equations in the numerical domain. This study highlights the potential of integrating advanced computational techniques with machine learning to address complex engineering problems. The findings provide valuable insights into the aerodynamic optimization of sandwich structures, paving the way for their more efficient and effective design in aerospace engineering. As an important outcome for related industries, the displacement field along with the Z direction increases by increasing the angle of airflow by approximately 9 % while this value for the X, and Y directions are 7 %, and 6 %, respectively. The proposed methodology offers a powerful tool for engineers and researchers seeking to optimize the performance of advanced composite materials under subsonic airflow conditions. |
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ISSN: | 0263-2241 |
DOI: | 10.1016/j.measurement.2024.115246 |