Dynamic and educational economic of truncated nanocomposite conical shells based on artificial intelligence method

This paper presents a new attempt to explore the dynamic behavior and its economic implications for truncated nanocomposite conical shells concerning educational infrastructures using techniques of artificial intelligence. The main theme of the research work is dynamics buckling of carbon nanotube-reinforced composite shells, which find extensive application in space environments and may have potential adaptations to ensure economical, eco-friendly educational settings. Material properties of the nanocomposites are calculated using Mori-Tanaka model and, then, equations of motion are extracted utilizing first order shear deformation theory (FSDT), Hamilton's principle, and energy approach. For the analysis of the dynamic instability region (DIR), a hybrid model incorporating diffrential quadrature method (DQM) and Bolotin's method is used. Furthermore, AI can be employed to optimize design parameters such as geometrical configurations and nanotube volume fractions for improved structural performance and cost efficiency in educational settings. The findings have revealed that the DIR increases with the increase of the higher frequencies by increasing the amount of CNT, which demonstrates that there is some scope for dynamic stability and economic feasibility of the design in educational buildings, which can be further optimized with the help of AI.