International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Doctoral Thesis | Material Science and Engineering | India | Volume 11 Issue 5, May 2022


Performance Probability Prediction of a Sandwich Panel with Honeycomb Core Structure

Nagalingeshwara V | S K Maharana


Abstract: Composite sandwich panels have been increasingly used in aerospace industry for various applications such as floor panels, comportment partitions, bulkheads, and even the skin and wings. It is important to design light weight structure for aircraft operations. The sandwich panel serves this requirement. The sandwich composites are multilayered materials made by bonding stiff, high strength skin facings to low density core material. In this study, composite sandwich panels are created, tested, and assessed under various load conditions employing finite element analysis and experimental equipment. These load situations include edge wise and flat wise loading, where edgewise loads applied in the plane of the sandwich panel and flat wise loads are applied normal to the plane of the sandwich panel. The number of layers in the face sheet and core thickness are optimized without compromising strength.The designed and built sandwich panel with hexacore honeycomb structure has a 53 percent chance of being allowed for usage under severe compressive stress conditions with a 50 percent chance of core height change. With an R-squared value of 0.85, the compressive load has a fairly significant association with the side length of the hexacore. The novel methodology, Monte Carlo Simulation, was used in conjunction with both numerical and experimental methods to compute the required performance parameters, validate them, and estimate the likelihood of those values occurring during the unknown conditions of use in aerospace applications.


Keywords: Sandwich structures, honeycomb core, composites, design of sandwich, probability prediction


Edition: Volume 11 Issue 5, May 2022,


Pages: 53 - 60


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