Improved Tornado Optimizer with Coriolis Force for Aero-Structural Wing Design

This paper investigates the aero-structural optimization of the NASA Common Research Model (CRM) wing using OpenAeroStruct, focusing on the recently proposed Tornado Optimizer with Coriolis Force (TOC). The optimization problem is formulated to minimize a composite objective function combining structural mass and fuel burn, subject to nonlinear aerodynamic and structural constraints. The design vector consists of five twist control points, three structural spar thickness parameters, and the angle of attack, with constraints on stress failure, lift-weight balance, and geometric feasibility. TOC is benchmarked against two established population-based algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to provide comparative context, while a gradient-based OpenAeroStruct run serves as the baseline reference. Results show that TOC achieves smooth and stable convergence with competitive reductions in structural mass and fuel burn, GA delivers the highest lift-to-drag ratio, and PSO exhibits the fastest convergence with strong efficiency. These findings highlight TOC's potential as a robust and stable optimizer for early-stage aircraft design, complementing GA and PSO within aero-structural optimization workflows.