Benchmark Composite Wing Design Including Joint Analysis and Optimization.

摘要

A composite wing panel software package, named WING Joint OpTimization and Analysis (WINGJOTA) featuring bolted joint analysis, is created and presented in this research. Three areas of focus were the development of an analytic composite bolted joint analysis suitable for fast evaluation; a more realistic wing design than what has been considered in the open literature; and the application of two optimization algorithms for composite wing design. Optimization results from 14 wing load cases applied to a composite wing panel with joints are presented.;The composite bolted joint analysis consists of an elasticity solution that provides the stress state at a characteristic distance away from the bolt holes. The stresses at the characteristic distance are compared to a failure criterion on a ply-by-ply basis that not only determines first ply failure but also the failure mode. The loads in the multi-fastener joints used in this study were determined by an iterative scheme that provides the bearing-bypass loads to the elasticity analysis.;A preliminary design of a composite subsonic transport wing was developed, based around a mid-size, twin-aisle aircraft. The benchmark design includes the leading and trailing edge structures and the center box inside the fuselage. Wing masses were included as point loads, and fuel loads were incorporated as distributed loads. The side-of-body boundary condition was modeled using high stiffness springs, and the aerodynamic loads were applied using an approximate point load scheme. The entire wing structure was modeled using the finite element code ANSYS to provide the internal loads needed as boundary conditions for the wing panel analyzed by WINGJOTA.;The software package WINGJOTA combines the composite bolted joint analysis, a composite plate finite element analysis, a wing aeroelastic cycle, and two optimization algorithms to form the basis of a computer code for analysis and optimization. Both the Improving Hit-and-Run (IHR) and the Multi-Particle Simulated Annealing (MPSA) algorithms were coded and used as the optimization routines in WINGJOTA. It was found that MPSA was able to find panel designs with lighter weights than IHR; however, the computation time was longer.