SpaRibs Geometry Parameterization for Wings with Multiple Sections using Single Design Space

摘要

The development of additive manufacturing techniques like Electron Beam Free Form Fabrication (EBF3) has made it feasible to manufacture aircraft wings with curvilinear spars and ribs (SpaRibs). The SpaRibs topology, for aerospace structures such as wings, has a significant effect on structural behavior and stability as well as flutter performance. In this article, a new global-local optimization framework for wings with multiple sections using curvilinear SpaRibs is described. The SpaRibs are parameterized using a single design space rather than using separate design spaces for each wing section. A broad range of SpaRibs topologies using limited number of parameters is created. Both Co and Ci continuity have been satisfied at the junction of two wing sections. Mesh continuity between all structural components is also ensured. This method of creating geometry using limited number of parameters is significantly advantageous in complex multi-disciplinary optimization due to its potential to reduce the computational cost. For the global-local size optimization the panels are generated by a new algorithm which relies on using set operations on the connectivity matrix data. The proposed algorithm is independent of both the coordinates of the nodes of the finite element model (FEM) and the order in which the elements are distributed in the FEM, thus can be used for a broad range of aircraft wings. The satisfaction of buckling and stress constraint after size optimization is ensured by another algorithm which finds out and stiffens the panels vulnerable to buckling. This algorithm can be integrated with Particle Swarm Algorithm to optimize SpaRibs topology. The code has been verified by optimizing the NASA CRM wing model under stress and buckling constraints at trim condition at Mach number equal to 0.85 for five different angles of attack (-2°, 0°,2°,4° and 6°). The weight of the best design is 18479 lb which is 8.43 % less than that of the baseline model.