Multi-level systems modeling and optimization for novel aircraft
This research combines the disciplines of system-of-systems (SoS) modeling, platform-based design, optimization and evolving design spaces to achieve a novel capability for designing solutions to key aeronautical mission challenges. A central innovation in this approach is the confluence of multi-level modeling (from sub-systems to the aircraft system to aeronautical system-of-systems) in a way that coordinates the appropriate problem formulations at each level and enables parametric search in design libraries for solutions that satisfy level-specific objectives. The work here addresses the topic of SoS optimization and discusses problem formulation, solution strategy, the need for new algorithms that address special features of this problem type, and also demonstrates these concepts using two example application problems - a surveillance UAV swarm problem, and the design of noise optimal aircraft and approach procedures. This topic is critical since most new capabilities in aeronautics will be provided not just by a single air vehicle, but by aeronautical Systems of Systems (SoS). At the same time, many new aircraft concepts are pressing the boundaries of cyber-physical complexity through the myriad of dynamic and adaptive sub-systems that are rising up the TRL (Technology Readiness Level) scale. This compositional approach is envisioned to be active at three levels: validated sub-systems are integrated to form conceptual aircraft, which are further connected with others to perform a challenging mission capability at the SoS level. While these multiple levels represent layers of physical abstraction, each discipline is associated with tools of varying fidelity forming strata of 'analysis abstraction'. Further, the design (composition) will be guided by a suitable hierarchical complexity metric formulated for the management of complexity in both the problem (as part of the generative procedure and selection of fidelity level) and the product (i.e., is the mission best achieved via a large collection of interacting simple systems, or a relatively few highly capable, complex air vehicles). The vastly unexplored area of optimization in evolving design spaces will be studied and incorporated into the SoS optimization framework. We envision a framework that resembles a multi-level, mult-fidelity, multi-disciplinary assemblage of optimization problems. The challenge is not simply one of scaling up to a new level (the SoS), but recognizing that the aircraft sub-systems and the integrated vehicle are now intensely cyber-physical, with hardware and software components interacting in complex ways that give rise to new and improved capabilities. The work presented here is a step closer to modeling the information flow that exists in realistic SoS optimization problems between sub-contractors, contractors and the SoS architect.
DeLaurentis, Purdue University.
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