Integrated design and manufacturing for the high speed civil transport (a combined aerodynamics/propulsion optimization study)

Abstract

This report documents the efforts of a Georgia Tech High Speed Civil Transport (HSCT) aerospace student design team in completing a design methodology demonstration under NASA's Advanced Design Program (ADP). Aerodynamic and propulsion analyses are integrated into the synthesis code FLOPS in order to improve its prediction accuracy. Executing the integrated product and process development (IPPD) methodology proposed at the Aerospace Systems Design Laboratory (ASDL), an improved sizing process is described followed by a combined aero-propulsion optimization, where the objective function, average yield per revenue passenger mile (/RPM),isconstrainedbyflightstability,noise,approachspeed,andfieldlengthrestrictions.Primarygoalsincludesuccessfuldemonstrationoftheapplicationoftheresponsesurfacemethodolgy(RSM)toparameterdesign,introductiontohigherfidelitydisciplinaryanalysisthannormallyfeasibleattheconceptualandearlypreliminarylevel,andinvestigationsofrelationshipsbetweenaerodynamicandpropulsiondesignparametersandtheireffectontheobjectivefunction,/RPM), is constrained by flight stability, noise, approach speed, and field length restrictions. Primary goals include successful demonstration of the application of the response surface methodolgy (RSM) to parameter design, introduction to higher fidelity disciplinary analysis than normally feasible at the conceptual and early preliminary level, and investigations of relationships between aerodynamic and propulsion design parameters and their effect on the objective function, /RPM. A unique approach to aircraft synthesis is developed in which statistical methods, specifically design of experiments and the RSM, are used to more efficiently search the design space for optimum configurations. In particular, two uses of these techniques are demonstrated. First, response model equations are formed which represent complex analysis in the form of a regression polynomial. Next, a second regression equation is constructed, not for modeling purposes, but instead for the purpose of optimization at the system level. Such an optimization problem with the given tools normally would be difficult due to the need for hard connections between the various complex codes involved. The statistical methodology presents an alternative and is demonstrated via an example of aerodynamic modeling and planform optimization for a HSCT

    Similar works