Thermal Buckling Analysis of Axially Layered Aluminium Zirconia Functionally Graded Beam

This study investigates the thermal buckling behavior of functionally graded material (FGM) thin beams with potential applications in automotive structures. The FGM beam is comprised of four axially layered sections, where the volume fraction of metal and ceramic varies across the thickness. The buckling analysis is conducted under three different boundary conditions: clamped-clamped, simply-supported-simply-supported, and clamped-simply-supported. The primary objective is to identify the optimal thermal buckling temperature of the FGM thin beam using the Taguchi optimization method. The beam configurations are designed based on a Taguchi L9 orthogonal array and analyzed using finite element software (ANSYS). Layers 1-4 of the axially layered beam are considered process parameters, while the thermal buckling temperature is the response parameter. Minitab software performs an Analysis of Variance (ANOVA) at a 95% confidence level to determine the most significant layer and its relative contribution to the buckling temperature. The results, confirmed by a separate test, indicate that Layer 2 significantly influences the critical buckling temperature within the beam. Finally, the optimal critical buckling temperature is predicted based on the 95% confidence interval of the confirmation analysis and population data. This research provides valuable insights into optimizing the thermal performance of FGM thin beams for automotive applications, where lightweight structures with high thermal stability are crucial. Engine Hood A non-uniformly heated engine hood can buckle and warp, affecting aesthetics and potentially causing fitment issues with fenders or compromising safety features like hood latches. The findings can guide the design and development of vehicle heat-resistant components, potentially leading to improved fuel efficiency and safety. Keywords: Beam, thermal buckling, functionally graded material, Engine Hood, Taguchi method, Optimization, ANOVA, ANSYS.