Determination of System Feasibility and Viability Employing a Joint Probabilistic Formulation
Mavris, Dimitri N.
DeLaurentis, Daniel A.
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The present paper outlines a method for probabilistic multi-criteria decision making. Recognizing the limitations of traditional probabilistic methods in accounting for multiple decision criteria in conceptual or preliminary design, this new method combines probabilistic treatment of uncertain information with a multi-criteria decision making technique. The paper describes how the method addresses a need in Multi-Disciplinary Optimization and Analysis as well as the advanced technology selection process in conceptual and preliminary design. The mathematical foundations of a general joint probabilistic formulation are outlined. Two specific functions are introduced that compute the joint probability: the joint empirical distribution function and the joint probability model. The utility of both functions is demonstrated in a proof of concept study for two criteria, applying both functions to a challenging aircraft design problem, the High Speed Civil Transport. This example application addresses two pressing issues: the identification of a feasible design space for a given design concept and the evaluation of viability of a given aircraft design. Finally, the advantages and limitations of the empirical distribution function method as well as the joint probability model are summarized.