Optimization, finite element analysis, and investigation of the fatigue behavior of asymmetric face-sheet aluminum honeycomb sandwich panels
Abstract (EN)
This study investigated the effects of adhesive type, adhesive amount, core thickness, and face sheet asymmetry resulting from the thickness difference between the upper and lower face sheets on the three-point bending performance of honeycomb sandwich composite panels. The experimental study was planned using a design of experiments (DOE) approach, and the results were evaluated by analysis of variance (ANOVA). In the first stage, the panel strength was evaluated based on the maximum load-carrying capacity. Subsequently, optimization was performed by considering strength, weight, and cost simultaneously. The optimum configuration with strength as the primary objective consisted of a 20 mm core thickness, a 2 mm upper face sheet, a 1 mm lower face sheet, and 15 g of polyurethane adhesive, achieving a maximum load-carrying capacity of 4.01 kN. Finite element analysis was performed to support the experimental results. The analyses showed that the load was primarily transferred in the Z direction, the highest equivalent stresses were concentrated in the honeycomb cell walls, and face sheet asymmetry significantly affected the stress distribution and plastic deformation.Fatigue tests were conducted on the two configurations that exhibited the best static performance. Specimens bonded with epoxy adhesive exceeded 1,000,000 cycles at 65% of the failure load, whereas those bonded with polyurethane adhesive achieved more than 1,000,000 cycles even at the higher load level of 90%. Consequently, polyurethane adhesive provided superior fatigue performance under high loading conditions.
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Osman Mert Küçükgöze (Doctorate thesis). Optimization, finite element analysis, and investigation of the fatigue behavior of asymmetric face-sheet aluminum honeycomb sandwich panels, 2026, pp. 1-124, Erzincan Binali Yıldırım University, Makine Mühendisliği Bölümü, DOI: https://doi.org/10.71008/ebyu.thesis.2026.170.
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