T he U.S. Air Force's aircraft inventory is old and getting older. Aircraft, such as the B-52 and KC-135, were designed and manufactured more than 60 years ago but remain critical elements of the Air Force's force structure. At the same time, newer aircraft, such as the F-22 and RQ-4, rely on more-complex technologies, materials, and software, potentially creating new operational and sustainment challenges. The aging of certain fleets and increasing complexity of newer military aircraft, coupled with continued overseas operations and a fluctuating budget environment, have led some to worry that the Air Force's inventory is likely to be more prone to incidents that result in a loss of aircraft or, worse, life.These concerns were elevated following a March 15, 2018, HH-60 loss in Iraq that resulted in seven fatalities and a May 2, 2018, WC-130 loss in Savannah, Georgia, that resulted in nine fatalities and contributed to Congress establishing the National Commission on Military Aviation Safety as part of the 2019 National Defense Authorization Act. 1 To investigate concerns over mishaps and support the commission, we assembled and analyzed mishap data from the Air Force Safety Center for 55 different aircraft types in operation since 1950. 2 A mishap is an "unplanned event or series of events resulting in death, injury, occupational illness, or damage to or loss of equipment or property, or damage to the environment." 3 Our analysis focuses on three types of mishap events, defined as follows: 4
The processing conditions during solvent-based fabrication of thin film organic electronics significantly determine the ensuing microstructure. The microstructure, in turn, is one of the key determinants of device performance. In recent years, one of the foci in organic electronics has been to identify processing conditions for enhanced performance. This has traditionally involved either trial-and-error exploration, or a parametric sweep of a large space of processing conditions, both of which are time and resource intensive. This is especially the case when the process → structure and structure → property simulators are computationally expensive to evaluate. In this work, we integrate an adaptive-sampling based, gradient-free, Bayesian optimization routine with a phase-field morphology evolution framework that models solvent-based fabrication of thin film polymer blends (process → structure simulator) and a graph-based morphology characterization framework that evaluates the photovoltaic performance of a given morphology (structure → property simulator). The Bayesian optimization routine adaptively adjusts the processing parameters to rapidly identify optimal processing configurations, thus reducing the computational effort in process → structure → property explorations. This serves as a modular, parallel 'wrapper' framework that facilitates swapping-in other process simulators and device simulators for general process → structure → property optimization. We showcase this framework by identifying two processing parameters, the solvent evaporation rate and the substrate patterning wavelength, in a model system that results in a device with enhanced photovoltaic performance evaluated as the shortcircuit current of the device. The methodology presented here provides a modular, scalable and extensible approach towards the rational design of tailored microstructures with enhanced functionalities.
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