Multipoint High-Fidelity Aerostructural Optimization of a Transport Aircraft Configuration

Abstract

This paper presents multi-point high-fidelity aerostructural optimizations of a long-range wide-body transonic transport aircraft configuration. The aerostructural analysis employs Euler CFD with a 2 million cell mesh and a structural finite element model with 300 000 degrees of freedom. The coupled adjoint sensitivity method is used to efficiently compute gradients, enabling the use of gradient-based optimization with respect to hundreds of aerodynamic shape and structural sizing variables. The NASA Common Research Model is used as the baseline configuration, together with a wingbox structure that was designed for this study. Two design optimization problems are solved: one where takeoff gross weight is minimized, and another where fuel burn is minimized. Each optimization uses a multi-point formulation with 5 cruise conditions and 2 maneuver conditions. Each of the optimization problems have 476 design variables, including wing planform, airfoil shape, and structural thickness variables. Optimized results are obtained within 36 hours of wall time using 435 processors. The resulting optimal configurations are discussed and analyzed for the aerostructural trade-offs resulting from each objective. The takeoff gross weight minimization results in a 4.2% reduction in takeoff gross weight with a 6.6% fuel burn reduction, while the fuel-burn optimization resulted in an 11.2% fuel burn reduction with no significant change in the takeoff gross weight.

Aerostructural optimization of the Common Research Model configuration

“…Optimality refers to how closely the current point satisfies the first-order Karush-Kuhn-Tucker (KKT) conditions [29]. Approximately 2 orders of magnitude reduction in the optimality are achieved, which is similar to previous aerostructural [1] and aerodynamic optimizations [28]. A complete overview of optimized configuration with the initial design is shown in Figure 10.…”

“…There has been some recent interest in using the CRM configuration as a model for aerostructural (static aeroelastic) analysis and design [1,10]. For aerostructural analysis the "built in" 1 g deflections are now problematic.…”

“…The optimization problem can be best described as a complete wing redesign for the CRM. Based on previous work by the authors [15,1] we know that a fuel burn minimization problem places more emphasis on reducing drag, at the expense of increased structural weight, and tends to produce very flexible wing designs. We make an effort to simplify the optimization problem as much as possible, both in an effort to reduce the computational expense, and also to more fully understand the trade-offs in the optimization.…”

“…An example of how missing physics in an optimization problem can be seen in previous optimization results by the authors [1]. In that work, multipoint optimization problems were solved with fuel burn and take-off gross weight (TOGW) as the objective functions.…”

Geometry and Structural Modeling for High-Fidelity Aircraft Conceptual Design Optimization

“…Approach MOTIVATION The motivation for this project is the success and promise shown by modern high-fidelity MDO algorithms [4,5]. For instance, Kenway and Martins' recently developed algorithm performed multi-point aerostructural optimization of the NASA Common Research Model (CRM) wing-body-tail configuration involving computational fluid dynamics (CFD) and finite element analysis (FEA) [4]. This algorithm coupled the Euler equations discretized on a 2 million cell mesh with a shell-element structure with 300,000 degrees of freedom, with nearly 500 aerodynamic shape and structural sizing design variables.…”