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The full potential of carbon-fiber and aluminum-honeycomb sandwich panels and structures has been limited by the huge property mismatch between the high-stiffness carbon fiber and low-stiffness aluminum honeycomb. In this study, an orthogrid structure was added into the sandwich structure to raise the stiffness of soft honeycomb and therefore reduce the interfacial mismatch. The core then became an aluminum orthogrid structure filled with aluminum-honeycomb blocks. Three point bending tests were conducted to compare carbon fiber sandwiches with different types of core: (1) aluminum-honeycomb core; (2) aluminum-plate orthogrid core; and (3) aluminum-plate orthogrid core filled by aluminum-honeycomb blocks. The honeycomb filled orthogrid core sandwich was a bit heavier than the honeycomb or grid sandwich, but the critical load, specific strength and energy absorption ability were all improved. The results indicated that the honeycomb filled orthogrid core sandwich with carbon fiber face sheet could provide improved structural properties for thin walled engineering structures. [ABSTRACT FROM AUTHOR]

Abstract: Critical local and global buckling loads of grid-stiffened carbon-fiber thin-shell structures, such as advanced grid-stiffened (AGS) conical shells relevant to aviation and aerospace applications, under uniform external transverse pressure were determined analytically using an equivalent stiffness model considering the influence of non-uniform grid distribution and the minimum potential energy principle. Experiments and finite-elements analysis have been carried out to assess the reliability of this analytical model. To maximize the buckling resistance for optimal design of the AGS conical shells, a hybrid genetic algorithm combining the genetic approach with a simulated annealing algorithm was developed, which considers the characteristics of multi-constraints and mixed discrete–continuous design variables. Comparisons between the benchmark results from the traditional genetic algorithm and simulated annealing algorithm confirmed the validity and efficiency of the hybrid genetic algorithms. Numerical examples show that the local-buckling constraint is a key factor for weight optimization of the AGS carbon-fiber conical. [Copyright &y& Elsevier]