Determining New System Design Requirements to Optimize Fleet Level Metrics under Uncertainty
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Traditional approaches to design and optimize a new system often do not consider how the operator will use this new system alongside the other existing systems. This ﾓhand-offﾔ between the designs of the new system and how this new system operates with the group of systems, leads to the sub-optimal performance of the new system when measured with respect to system-level objective. In the case of aircraft design, choices made to meet a set of requirements dictate the performance of the aircraft, and this aircraft performance in turn influences how the operator might use the aircraft. Further, the presence of uncertainties in predictions of the new aircraft performance and costs and uncertainties in the amount of payload / passenger to transport further exacerbate the problem of determining these requirements. Recent efforts have posed approaches to address this problem, but generally with a deterministic perspective. This research improves upon prior work by extending a prior developed subspace decomposition framework to enable capability that addresses multi-domain uncertainties. The framework addresses uncertainties arising in one domain and its propagation to the next connected domain. The framework employs a Reliability-Based Design Optimization (RBDO) approach to address the uncertainties arising from the aircraft design optimization subspace and employs an Interval Robust Counterpart (IRC) formulation to address the uncertainty propagation from the design subspace to the allocation subspace. The research adopts a previously developed subspace decomposition approach and integrates features from robust / reliability based optimization to address the uncertainties and solves two application problems ﾖ a military and a commercial airline application. The military application involves an Air Mobility Command (AMC) fleet problem, and, the commercial airline applications reflects typical operations of a US based carrier. The framework demonstrates its ability to acceptably handle uncertainties arising from various domains. Results of application also demonstrates the ability of the framework to identify the design requirements for the new aircraft, and a posterior analysis indicates that the framework acceptably handles the uncertainties.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
NPS Report NumberPUR-AM-17-208
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