The Collaborative Optimization Of Composite Laminated Surface Honeycomb Sandwich Structure

Composite sandwich structure is widely used in modern industrial field ofaerospace and high-speed train, for it has meet the requirement of low weight, high strengthand stiffness ratio. Through the collaborative optimization design in the aspects of macro andmicro to achieve the lightweight of composite sandwich structure, it can further save theenergy and materials.This paper studies the collaborative optimization of composite laminated surfacehoneycomb sandwich structure. At the beginning, it has reviewed the research progress ofthe composite sandwich structure and structural optimization theory and given the coplanarproperty, non coplanar property and equivalent density of the composite honeycombsandwich structure. Equivalent elastic parameters of the honeycomb core considering theeffect of extension or contraction deformation, shear deformation and flexural deformationare been presented. The accuracy of the formulas has been verified by the knownexperimental data. Analysis of the influence of equivalent elastic modulus to differentgeometrical parameters. Then, it has derived the equivalent bending elastic parameter ofregular bias layer laminate composite and the mechanical properties of honeycombsandwich structure, analyzed the composite laminated surface sandwich structurecalculation model and based on the three equivalent theory of honeycomb sandwichstructure to find the equivalent parameters. Finally, it has established the multi-constraintoptimization design model of single and laminated surface honeycomb sandwich structureand discussed with the different ratio of torsion stiffness and bending stiffness, therelationship between the weight of the honeycomb laminated sandwich structure. Throughthe collaborative optimization design in the aspects of macro and micro to achieve therelationships of the weight with the thickness of honeycomb sandwich layer and the plyangle of composite laminate.It has found the optimal solutions in ANSYS.