UAS Integration in the NAS: Airspace Concept Evaluation System (ACES) Simulation Studies
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A Python direct-mode interface to OpenDSS, a distribution system simulator for electric power systems.
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Power system resilience is an emerging topic and plays an essential role in helping power industry understand and respond to the increasing threats of extreme weather events. The first step of power system resilience analysis is to introduce metrics to quantify the resilience reasonably. Existing resilience metrics are typically restrained by the limited data for extreme event modeling and fall short in terms of physical interpretation and comparability. This paper develops novel quantitative metrics to evaluate power system resilience in pre- and post-event contexts. The developed metrics illustrate clear physical meanings and can be effectively used to compare resilience across different systems under different extreme events. Moreover, the developed metrics can be applied to both transmission and distribution systems. Simulation on a distribution system is employed to validate the effectiveness of the proposed resilience metrics and resilience evaluation approach.
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This extended abstract briefly summarizes ongoing research activity on the evaluation and experimental validation of physics methods for photon and electron transport. The analysis includes physics models currently implemented in Geant4 as well as modeling methods used in other Monte Carlo codes, or not yet considered in general purpose Monte Carlo simulation systems. The validation of simulation models is performed with the support of rigorous statistical methods, which involve goodness-of-fit tests followed by categorical analysis. All results are quantitative, and are fully documented. (authors)
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Realization of the expected proliferation of Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) depends on the development and validation of performance standards for UAS Detect and Avoid (DAA) Systems. The RTCA Special Committee 228 is charged with leading the development of draft Minimum Operational Performance Standards (MOPS) for UAS DAA Systems. NASA, as a participating member of RTCA SC-228 is committed to supporting the development and validation of draft requirements for DAA alerting system performance. A recent study conducted using NASA's ACES (Airspace Concept Evaluation System) simulation capability begins to address questions surrounding the development of draft MOPS for DAA alerting systems. ACES simulations were conducted to study the performance of an alerting scheme proposed by the SC-228 DAA Alerting sub-group. Analysis included but was not limited to: 1) correct alert (and their timeliness), 2) false alert (and their severity and duration), 3) missed alert, and 4) probability of an alert type at the time of loss of well clear. The results will be used by SC-228 to inform decisions about the alerting aspect of UAS DAA systems and future requirements development and validation efforts.
The generalized fractional reaction–diffusion equations which exist in the form of noninteger order partial differential equations have now found wide application for illustrating important and useful physical phenomena, such as subdiffusive and superdiffusive scenarios. The space fractional derivatives are defined in the Riesz sense on the intervals 0 < α < 1 and 1 < α ≤ 2. We propose robust numerical techniques, such as a spectral representation of the fractional Laplacian operator in conjunction with the exponential time differencing method, and present the equivalent relationship between the Riesz fractional derivative and fractional Laplacian operator. We apply these techniques to numerically solve a range of chaotic processes, such as the Chua’s equations, Rössler system, Lorenz and Lorenz-type systems. Simulation results revealed various complex and spatiotemporal chaos, spiral chaos, intermittent chaos and spots patterns in two-dimensional space fractional reaction–diffusion problems.
A system and method for simulation of fluid flow. The system being configured to remove loops in a vortex filament in a simulation model and reconnect the filament. The system may also be configured to model fluid flow in relation to a moving object and to correct errors in surface vorticity.