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Article Citation - WoS: 2Citation - Scopus: 2Large Deflection Analysis of Functionally Graded Reinforced Sandwich Beams With Auxetic Core Using Physics-Informed Neural Network(Taylor & Francis inc, 2025) Nopour, Reza; Fallah, Ali; Aghdam, Mohammad MohammadiThis paper aims to investigate the large deflection behavior of a sandwich beam reinforced with functionally graded (FG) graphene platelets (GPL) together with an auxetic core, rested on a nonlinear elastic foundation. The nonlinear governing equations of the problem are derived using Hamilton's principle based on the Euler-Bernoulli beam theory for large deflections. Five different distributions are considered to describe the dispersion of GPL in the top and bottom faces of the sandwich beam. The Physics-Informed Neural Network (PINN) method is employed to model the nonlinear deflection of the beam under various boundary conditions. This study highlights the effectiveness of PINN in handling the complexities of nonlinear structural analyses. The findings underscore the impact of the core auxeticity, GPL amount and distribution, and elastic foundation coefficient on the nonlinear deflection of the sandwich beam under different loading scenarios. For instance, using Type I configuration can reduce the deflection of the beam by nearly half compared to using Type IV. Furthermore, a nonlinear foundation with a unit coefficient results in a 48% reduction in deflection compared to the scenario without an elastic foundation.Article Citation - WoS: 1Citation - Scopus: 14D-Printed Continuous Fiber-Reinforced PLA/TPU Auxetic Composites: Mechanical Performance, Energy Absorption, Shape Recovery, and Reusability Evaluation(SpringerNature, 2025) Alkan, Atakan; Ranjbar Aghjehkohal, Amin; Fallah, Ali; Koc, BahattinThis study explores the mechanical performance, energy absorption, shape recovery, and reusability of 4D-printed continuous carbon fiber-reinforced auxetic composite structures based on PLA/TPU blends, designed for load-bearing applications. PLA-TPU mixtures with different TPU content were developed to optimize the balance between flexibility and strength, with carbon fibers incorporated to enhance the mechanical properties of the resulting composites. Thermo-mechanical characterization of the blends was conducted, followed by a detailed evaluation of the structures' mechanical behavior and energy absorption capacity under room temperature conditions, simulating practical industrial scenarios. The shape recovery performance of these composite structures was also investigated. To assess reusability, the programming-recovery cycle was repeated five times, analyzing the retention of mechanical properties and shape recovery over multiple cycles to determine durability. Results revealed that TPU integration provided sufficient flexibility for cold programming, while carbon fiber reinforcement significantly enhanced stiffness and strength. The 4D-printed composites exhibited consistent shape recovery and maintained mechanical integrity after five cycles, confirming their reusability. These findings demonstrate the potential of 4D-printed PLA/TPU-based carbon fiber-reinforced composites as smart, durable materials for load-bearing applications in industries such as biomedical engineering, automotive, and aerospace.
