Application of Probabilistic Methods for the Determination of an Economically Robust Hsct Configuration

This paper outlines an approach for the determination of economically viable robust design solutions using the High Speed Civil Transport (HSCT) as a case study. Furthermore, the paper states the advantages of a probability based aircraft design over the traditional point design approach. It also proposes a new methodology called Robust Design Simulation (RDS) which treats customer satisfaction as the ultimate design objective. RDS is based on a probabilistic approach to aerospace systems design, which views the chosen objective as a distribution function introduced by so called noise or uncertainty variables. Since the designer has no control over these variables, a variability distribution is defined for each one of them. The cumulative effect of all these distributions causes the overall variability of the objective function. For cases where the selected objective function depends heavily on these noise variables, it may be desirable to obtain a design solution that minimizes this dependence. The paper outlines a step by step approach on how to achieve such a solution for the HSCT case study and introduces an evaluation criterion which guarantees the highest customer satisfaction. This customer satisfaction is expressed by the probability of achieving objective function values less than a desired target value. † Member, AIAA ¥ Graduate Student Member, AIAA Paper presented at the AIAA/USAF/NASA/ISSMO Multidisciplinary Analysis and Optimization Conference, September 1996, Bellevue, Washington. Introduction The work presented in this paper describes elements of an overall aerospace system design methodology that proposes the use of probabilistic methods to meet some of the modern challenges in aircraft design. This methodology has been motivated by demands for future aircraft, like the High Speed Civil Transport (HSCT), to become economically competitive with current long range subsonic transports. Hence, the economic viability of modern aircraft is an essential although not the only concern of this methodology. Recognizing the presence of uncertainty in the assumptions made as to the number of paying passengers, fluctuations in fuel price, or travel distance, more emphasis has been put on replacing "point" by probabilistic estimates that account and quantify uncertainty of the prediction outcome. In order to implement this objective, a methodology called Robust Design Simulation (RDS), that is based on a Concurrent Engineering (CE)/Integrated Product and Process Development (IPPD) approach has been introduced. The procedure for conducting this IPPD approach employs the use of a Design of Experiments (DOE) to facilitate the development of Response Surface Equations (RSEs) which approximate sophisticated, computationally intense disciplinary analyses tools with second (or higher) order polynomial equations. Furthermore, under this new way of thinking the design focus has shifted from optimizing to ‘compromising’. Compromising describes a decision process that yields a robust solution i.e. a design that is insensitive to the variation of those parameters that are difficult or impossible to control. Such a design might be preferable to a true optimum which exhibits low confidence of achieving that optimum consistently.