Effect of varying core density and material on the quasi?static behaviors of sandwich structure with 3D?printed hexagonal honeycomb core

The quasi?static behaviors on sandwich composite of 3D?printed hexagonal honeycomb core structure.Additive manufacturing (AM) involves the development of complex, lightweight sandwich structures for the automotive and aerospace industries. These structures are essential for load bearing and impact resistance. Nevertheless, there is a significant obstacle of failure under compressive loading, e.g. through brittle fractures and crushing. To address this issue, this study evaluates the compressive properties, energy absorption and failure damage in quasi?static tests (flatwise, in?plane, and flexural) of sandwich composites with 3D?printed hexagonal honeycomb cores of different unit cells (6, 8 and 10?mm) and materials (polylactic acid (PLA), PLA?Carbon and PLA?Wood). The results show that increasing the core density enhances compressive strength, modulus, and energy absorption. An 8?mm unit cell absorbs energy optimally for lightweight structures. In PLA flatwise testing, the 8?mm unit cell absorbed 419.49?J more energy than the 10?mm unit cell. Additionally, PLA?Wood has better mechanical performance than PLA?Carbon due to the better filler with the PLA? matrix. In flatwise testing with an 8?mm unit, PLA?Wood absorbs 214.01?J, while PLA?Carbon absorbs 122.49?J. The failure modes vary depending on tests performed. The study highlights the potential of 3D?printed honeycomb core structures for load?bearing applications in various industries, including aerospace and automotive.HighlightsQuasi?static loading behavior of 3D?printed hexagonal honeycomb cores.Increased core density improves compressive stress, modulus, and absorbed energy.An optimal unit cell size for lightweight 3D printed core structures is 8?mm.PLA?Wood performs better in energy absorption due to filler compatibility.The failure modes are related to the type of quasi?static loads applied.

» Publication Date: 22/04/2024

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


                   




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