An automated, simulation-based aircraft design process allows for the prediction of unanticipated problems early in the design stage, leading to reduced turn-around time and development cost. Having reliable, and affordable (fast) design tools is crucial to achieving this level of automation in the design process. An example of this is illustrated for a jet trainer aircraft using two aircraft design codes: Jet Designer and CEASIOM which includes Digital DATCOM, a Vortex lattice method, and an Euler flow solver. A set of aerodynamic methods with different degrees of fidelity and computational expense is considered, with the limitations of each method provided. In particular, this paper examines the challenges that CFD-based aircraft design poses to a designer, including: a) the cost of generation of large data tables, b) the automated handling of geometry, c) treating control surface deflections, d) and calculation of dynamic derivatives using CFD. A Kriging-based sampling approach was used for generating aerodynamic tables with a reasonable computational cost compared with a brute-force approach. For Euler calculations, an automated CAD and mesh generation approach from a geometry description was used. It is demonstrated that application of Euler solutions to low fidelity aircraft geometry shows the expected design trends. Also, results show that the wave drag at transonic speeds can be predicted with Euler equations, but not with Vortex lattice or Digital DATCOM. The treatment of control surface deflections was also investigated for the Vortex lattice solver and the Euler code. A transpiration boundary condition was used in the Euler code to model the flap surface movements, although this approach is limited for large deflections. The calculated aero tables form each aero source were used next to study the vehicle flying qualities. Results presented demonstrate the validity and feasibility of the simulation-based approach for aircraft conceptual design.
Nomenclaturelift curve slope, 1/rad C Lq lift derivative with respect to normalized pitch rate, 1/rad C m pitching moment coefficient, m/q ∞ Sc C mα pitching moment slope, 1/rad C mq pitching moment derivative with respect to normalized pitch rate, 1/rad C mδe pitching moment derivative with respect to elevator deflection, 1/rad C Y side-force coefficient, Y /q ∞ S *
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