(Georgia Institute of Technology, 2001)
Roth, Bryce Alexander; German, Brian Joseph; Mavris, Dimitri N.; Macsotai, Noel I.
This paper describes a method to assist in selecting technology concepts from amongst a pool of candidates such that the resulting concepts yield the best compromise between conflicting sign performance and technology risk. The heart of
this method is a unique technology impact forecasting
environment that is used in conjunction with a genetic
algorithm as a tool to efficiently explore the technology
combinatorial space. The technique is applied to a
commercial turbofan engine technology selection
problem of practical interest. A pool of forty technology
concepts is proposed and evaluated, the objective being
to determine which subset of technologies is the best
candidate to go forward into development given
conflicting objectives on performance, engine
manufacturing cost, and design risk (i.e. cumulative
technology readiness).
Introduction
manufacturing cost, design risk, etc.
School of Aerospace, Georgia Tech. Member, AIAA.
Director, ASDL. Associate Fellow, AIAA.