'Feathers in Storms' - intelligent sensor-actuator arrays for control of turbulence and optimization of performance including fuel management

摘要

Quantized transitions between turbulence states that are characterized by high degrees of non-linear stochastic dynamics suggests that there may be techniques for improving both the predictability and control of such states, particularly the highly critical transitions that can create extreme vehicle stress and compromise vehicle safety and integrity. Investigations into meta-stable structures within dynamic flows create limits and bounds on transitions from one behavioral condition into another, thus providing a type of "quantization" between states that are characterized by high degrees of turbulent and chaotic internal dynamics. Such flows can be detected and measured through localized, cell-like neighborhoods that comprise networks of communicating asynchronous sensor-actuator processing elements. This leads to the prospect of designing externally tunable algorithms for control systems (including both human and autonomous piloting systems) within a variety of aircraft and airborne machines. Analysis of probable interactions and consequences from interactions between an aircraft and various upcoming turbulence situations -both natural (e.g., weather formations) and man-made (e.g., intentional actions and countermeasures including incoming ballistics) - can potentially yield realtime solutions for altering an airborne vehicle's path, dynamics, or execution of effective airborne countermeasures. In addition to improving survivability and aircraft durability, this can also aid fuel efficiency. Improved understanding of how specific turbulence states can and cannot transform into different and more manageable states, or into less turbulent conditions, can be valuable in the design of diverse types of airborne vehicles and their control systems.