Development and Implementation of a Novel Parametrization Technique for Multidisciplinary Design Initialization

A new parametrization method for aircraft shapes is presented to enhance shape optimization for aircraft design. This parametrization method was implemented in a tool that creates feasible initial solutions for multidisciplinary design optimization problems. The tool combines all aspects of the aerodynamic design process: parametrization, aero-dynamic analysis and optimization. The novel parametrization method presented in this paper makes use of the Class-Shape-Refinement-Transformation (CSRT) method. This method employs a combination of Bernstein polynomials and B-splines to allow for both global and local control of the shape. Additionally, the use of B-splines makes it possible to efficiently handle volume constraints, which are very common in aircraft design. The parametrization method was coupled to two different aerodynamic analysis tools. The commercial panel method code VSAERO was used for the low-speed regime and an in-house Euler code was used for transonic and supersonic flight conditions. Various different optimization schemes were investigated and compared. A number of test cases were performed. For the first set of test cases, a three-dimensional geometry was optimized for subsonic conditions, using VSAERO and various optimization algorithms. For the second set of test cases, an airfoil was optimized for transonic and supersonic conditions, using the in-house Euler solver and a gradient-based optimizer. From this work it can be concluded that a combination of stochastic and gradient-based optimization algorithms works best together with the CSRT method. Additionally, refining the shape using B-splines proved to be an efficient way of increasing the design freedom, while the design space remained smooth enough to employ gradient-based optimization.Aerodynamics, Wind Energy & PropulsionAerospace Engineerin

Aeroelastic Design and Optimization of Unconventional Aircraft Configurations in a Distributed Design Environment

A Multidisciplinary Design and Optimization (MDO) methodology is presented, which uses a physics-based modeling approach for the preliminary structural design of unconventional aircraft configurations. Therein, static as well as dynamic aeroelastic stability constraints are accounted for at the early stage of the design process. A functional parametrization is applied for the description of the aircraft’s geometry. Several physics based analysis modules are orchestrated by an engineering framework to enable distributed multidisciplinary analysis and optimization. The method builds on DLR’s collaborative design environment, which uses the central data model CPACS to provide consistent model information in the analysis workflow. A knowledge based aeroelastic engine is developed to accelerate the integration of the disciplinary models and the subsequent aeroelastic analysis, and to automate the disciplinary couplings. The approach is tested in optimization test cases for a conventional wing design as well as for a Blended Wing Body configuration

A genetic algorithm optimization method for a morphing wing tip demonstrator validated using infra red experimental data

In the present paper an \u2018in-house\u2019 genetic algorithm is described and applied to an optimization problem of improving the aerodynamic performances of an airfoil through upper surface morphing. The results of the optimization of the flow behavior for the airfoil morphing upper-surface problem are validated with experimental transition results obtained with Infra-red Thermography for the CRIAQ MDO 505 wing tip demonstrator, proving that the 2D numerical optimization using the \u2018in-house\u2019 genetic algorithm is an important tool in improving various aspects of a wing\u2019s performancesPeer reviewed: YesNRC publication: Ye