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- W3118367153 abstract "Rotorcraft components experience different stress levels based on the flight parameters and intensity of the rotorcraft mission. The stress history experienced by a mechanical component can have significant effect on the wear and tear of a given component, which in turn dictates the maintenance schedule as well as life expectancy for the component. In order to improve the resilience of a rotorcraft to successfully and safely complete a mission, the rotorcraft’s maneuvers can be designed to minimize the stress experienced by critical mechanical components. This paper discusses a methodology for the optimization of rotorcraft flight parameters to minimize stress on critical mechanical components based on their current and predicted states while satisfying the operational constraints. A digital twin approach is pursued in order to support probabilistic prognosis, diagnosis, and optimization. Comprehensive rotorcraft analysis is used to estimate the loading on the rotorcraft under particular flight conditions and a finite element model is used to predict the corresponding stress in the component of interest. A surrogate model is constructed to increase the efficiency of the uncertainty and optimization analyses. Diagnostic information is collected after every flight, and this information is used to estimate the discrepancy in the damage prognosis model. The updated prognosis model is used to estimate the state of the component for a specified future mission. Then the optimal flight parameters for the future mission are identified by considering the predicted future state of the component, the set of feasible maneuvers and by minimizing the stress in the component under uncertainty. The proposed methodology is demonstrated using numerical experiments." @default.
- W3118367153 created "2021-01-18" @default.
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- W3118367153 date "2021-01-04" @default.
- W3118367153 modified "2023-09-27" @default.
- W3118367153 title "A digital twin approach for rotorcraft flight parameter optimization to enhance component life" @default.
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- W3118367153 doi "https://doi.org/10.2514/6.2021-0899" @default.
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