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Aerospace Systems Design Laboratory (ASDL)
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ItemGenerating Dynamic Models Including Uncertainty for Use in Aircraft Conceptual Design(Georgia Institute of Technology, 1997-08) DeLaurentis, Daniel A. ; Mavris, Dimitri N. ; Calise, Anthony J. ; Schrage, Daniel P.Accurate stability and control derivative information is essential to the configuration designer. As new, non-conventional aircraft are being designed, however, the trusted stability and control estimates usually used in conceptual design may no longer be useful. Using sophisticated analysis to compute every derivative in the highly iterative design environment is not a viable approach either. This paper proposes a method for addressing this dilemma by combining experimental design techniques for model building with vortex lattice aerodynamics for analysis. The careful implementation of this method results in parametric regression equations for three important derivatives as a function of the variables of most interest to the designer (e.g. wing, tail geometry, center of gravity location, etc.). These equations are based on actual analysis and not historical trends. Finally, uncertainty associated with this method is introduced and an initial technique for analyzing the effect of such uncertainty is presented.
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ItemReduced Order Guidance Methods and Probabilistic Techniques in Addressing Mission Uncertainty(Georgia Institute of Technology, 1996-09) DeLaurentis, Daniel A. ; Mavris, Dimitri N. ; Calise, Anthony J. ; Schrage, Daniel P.Recognizing that vehicle synthesis fulfills the role of integrator of the mutually interacting disciplines, difficulties persist in intelligently implementing disciplinary analysis into this synthesis process. This paper develops and describes analytical and statistical approximation techniques used to create design-oriented analyses which are implementable in the process. Specifically, techniques related to the vehicle guidance discipline are examined. The ultimate goal is to investigate the economic viability of an aerospace system in the face of uncertainty at the system and discipline design levels. The notion of a requirement is replaced by a modeling of mission variability, since future aircraft will likely fly a variety of missions. Aircraft guidance laws are key components in the mission analysis portion of an aircraft sizing code, and thus they must be included in the investigation. Through the use of statistical modeling techniques, a link between mission uncertainty, optimal guidance, wing planform, and economic objectives is obtained. This linkage allows for the investigation of guidance and mission effects on such quantities as gross weight and ticket price (on a per mile basis). Further, the resulting solutions are robust since they are obtained by choosing control parameters which maximize the probability of meeting a target while simultaneously assuring that appropriate constraints (which are also probabilistic) are met.
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ItemSystem Synthesis in Preliminary Aircraft Design Using Statistical Methods(Georgia Institute of Technology, 1996-09) DeLaurentis, Daniel A. ; Mavris, Dimitri N. ; Schrage, Daniel P.This paper documents an approach to conceptual and early preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically Design of Experiments (DOE) and Response Surface Methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an Overall Evaluation Criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in a innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting in solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a High Speed Civil Transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabilistic designs (and eventually robust ones).
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ItemA New Approach to Integrated Wing Design in Conceptual Synthesis and Optimization(Georgia Institute of Technology, 1996-09) DeLaurentis, Daniel A. ; Cesnik, Carlos Eduardo Stolf ; Lee, Jae-Moon ; Mavris, Dimitri N. ; Schrage, Daniel P.Design-oriented analysis has become increasingly important as more and more problems traditionally solved in isolation are being approached from a multidisciplinary point of view. One such problem is the aeroelastic optimization of supersonic transport wings. Whereas simplified analytical techniques may not be sophisticated enough, and complex numerical models may be too cumbersome, this paper puts forward a new approach to achieving a balance between modeling fidelity and required accuracy. Higher fidelity analysis techniques, usually associated with design stages where key geometric variables have been fixed, are used to model a design space consisting of these important geometric variables. This is accomplished through the combined use of a Design of Experiment/Response Surface Method technique and parametric analysis tools (including an automated finite element grid generation procedure). The result is a prediction method for the structural weight of an aeroelastically optimized wing for use in an Integrated Product and Process Development environment, where cost, performance, and manufacturing trades can be accomplished. The technique is to be demonstrated on the aeroelastic design of a wing for a generic High Speed Civil Transport, based on a select set of planform and airfoil design variables. Finally, a framework for evaluating new technologies within the aeroelastic optimization is outlined.