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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Comment on 'Determining the yield of the Trinity nuclear device using gamma-ray spectroscopy' [Am. J. Phys. 63(5), 411-413 (1995)] and 'Trinitite redux...' [Am. J. Phys. 65(11), 1110-1112 (1997)]
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Comparative Risk-Benefit Profiles of Individual Devices for Graft Fixation in Anterior Cruciate Ligament Reconstruction: A Systematic Review and Network Meta-analysis
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A Dual Neural Network Approach to Topology Optimization for Thermal-Electromagnetic Device Design
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A thin-film modeling approach for analysis of carbon capture sorbent-based devices
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Paper-based devices for rapid diagnostics and testing sewage for early warning of COVID-19 outbreak
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Oblique microchannel merged with circle micro pin-fin as a novel hybrid heat sink for cooling of electronic devices
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Design considerations for next-generation sorbent-based atmospheric water-harvesting devices
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Energy savings and thermal comfort evaluation of a novel personal conditioning device
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Modelling the spectral influence on photovoltaic device performance using the average photon energy and the depth of a water absorption band for improved forecasting
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Multi-device study of temporal characteristics of magnetohydrodynamic modes initiating disruptions
Disruptions in tokamaks are often preceded by magnetohydrodynamic (MHD) instabilities that can rotate or become locked to the wall. Measurements from magnetic diagnostics in the presence of MHD mode precursors to disruptions can yield potentially valuable input to the plasma control system, with a view to disruption avoidance, prediction and mitigation. This report presents an exploratory analysis of the growth of MHD modes and corresponding time scales on the basis of magnetic measurements in multiple tokamaks. To this end, a database was compiled using disruptive discharges from COMPASS, ASDEX Upgrade, DIII-D and JET, manually classified according to disruption root cause, and characterized by a great diversity of operational conditions and mode dynamics. The typical time during which a mode can be detected using saddle coils and the duration of the locked mode phase in the database both extend over several orders of magnitude, but generally the time scales increase with plasma size. Several additional factors are discussed that can influence these durations, including the disruption root cause. A scaling law for the locked phase duration was estimated, yielding predictions toward ITER of the order of hundreds of milliseconds or even seconds. In addition, a scaling law for the mode amplitude at the disruption onset, proposed earlier by de Vries et al. (2016), is applied to the database, and its predictive capabilities are assessed. Despite significant uncertainty on the predictions from both scaling laws, encouraging trends are observed of the fraction of disruptions that may be detected with sufficient warning time to allow mitigation or even avoidance, based solely on observations of MHD mode dynamics. When combined with similar analysis of measurements from diagnostics that are sensitive to other disruption precursors, our analysis methods and results may contribute to the reliability, robustness and generalization of disruption warning schemes for ITER.
Machine learning-based system for vacuum leakage detection in EAST fusion device
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