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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Discrete Recurrent Neural Networks for Grammatical Inference

Recurrent neural networks have recently been shown to have the ability to learn regular and context-free grammars from examples. We show that while conventional analog recurrent networks try to form clusters in activation space to represent discrete states of the grammars during learning, and can be successful in doing so, the clusters so formed tend to become unstable as longer and longer test input strings are presented to the network.

Neural↗
NASA NTRS2019

Forbush Decreases and < 2 Day GCR Flux Non-recurrent Variations Studied with LISA Pathfinder

Non-recurrent short-term variations of the galactic cosmic-ray (GCR) flux above 70 MeV n−1 were observed between 2016 February 18 and 2017 July 3 on board the European Space Agency LISA Pathfinder (LPF) mission orbiting around the Lagrange point L1 at 1.5 × 106 km from Earth. The energy dependence of three Forbush decreases is studied and reported here. A comparison of these observations with others carried out in space down to the energy of a few tens of MeV n−1 shows that the same GCR flux parameterization applies to events of different intensity during the main phase. FD observations in L1 with LPF and geomagnetic storm occurrence are also presented. Finally, the characteristics of GCR flux non-recurrent variations (peaks and depressions) of duration <2 days and their association with interplanetary structures are investigated. It is found that, most likely, plasma compression regions between subsequent corotating high-speed streams cause peaks, while heliospheric current sheet crossing causes the majority of the depressions.

M. Armano↗
NASA NTRS2019

Forbush Decreases and <2 Day GCR Flux Non-Recurrent Variations Studied with LISA Pathfinder

Non-recurrent short-term variations of the galactic cosmic-ray (GCR) flux above 70 MeV n(exp −1) were observed between 2016 February 18 and 2017 July 3 on board the European Space Agency LISA Pathfinder (LPF) mission orbiting around the Lagrange point L1 at 1.5 × 10 (exp 6) km from Earth. The energy dependence of three Forbush decreases is studied and reported here. A comparison of these observations with others carried out in space down to the energy of a few tens of MeV n(exp −1) shows that the same GCR flux parameterization applies to events of different intensity during the main phase. FD observations in L1 with LPF and geomagnetic storm occurrence are also presented. Finally, the characteristics of GCR flux non-recurrent variations (peaks and depressions) of duration <2 days and their association with interplanetary structures are investigated. It is found that, most likely, plasma compression regions between subsequent corotating high-speed streams cause peaks, while heliospheric current sheet crossing causes the majority of the depressions.

Cosmic rays↗
NASA NTRS2023

Recurrent 3he-Rich Solar Energetic Particle Injections Observed By Solar Orbiter at ∼0.5 Au

We report Solar Orbiter observations of six recurrent solar energetic particle injections in 2022 March 3−6 at ∼0.5 au. All but one were associated with jets emanating from a plage near a large sunspot in active region 12 957. We saw large jets in injections with high 3He and Fe enrichments and minor jets in injections with no or lower enrichments. Furthermore, the event with the highest enrichment showed a more compact configuration of the underlying photospheric magnetic field. The higher fluences as well as harder spectra were seen in the event with a simultaneous jet and wider eruption. However, in this case, the energy buildup time in the source might be required to produce such spectra. Extreme-ultraviolet images from Solar Orbiter revealed a number of intersecting loops at the base of jets not seen from 1 au that might be a precondition for the recurrent events.

Sun: particle emission↗
NASA NTRS2016

Cross Recurrence Analysis as a Measure of Pilots' Coordination Strategy

When solving problems, multi-person airline crews can choose whether to work together, or to address different aspects of a situation with a divide and conquer strategy. Knowing which of these strategies is most effective may help airlines develop better procedures and training. This paper concentrates on joint attention as a measure of crew coordination. We report results obtained by applying cross recurrence analysis to eye movement data from two-person crews, collected in a flight simulator experiment. The analysis shows that crews exhibit coordinated gaze roughly 1/6th of the time, with a tendency for the captain to lead the first officer’s visual attention. The degree to which crews coordinate their gaze is not significantly correlated with performance ratings assigned by instructors; further research questions and approaches are discussed.

cross recurrence analysis↗
NASA NTRS2016

Cross Recurrence Analysis as a Measure of Pilots' Coordination Strategy

When solving problems, multi-person airline crews can choose whether to work together, or to address different aspects of a situation with a divide and conquer strategy. Knowing which of these strategies is most effective may help airlines develop better procedures and training. This paper concentrates on joint attention as a measure of crew coordination. We report results obtained by applying cross recurrence analysis to eye movement data from two-person crews, collected in a flight simulator experiment. The analysis shows that crews exhibit coordinated gaze roughly 16th of the time, with a tendency for the captain to lead the first officers visual attention. The degree to which crews coordinate their gaze is not significantly correlated with performance ratings assigned by instructors; further research questions and approaches are discussed.

non-linear models↗
NASA NTRS2022

Predicting Unreinforced Fabric Mechanical Behavior with Recurrent Neural Networks

Unreinforced woven fabrics are widely employed in various high-performance applications, including parachute deployment systems, airbags, and ballistic armor. The analysis of such materials is inherently complex due to the multiscale structure of these materials, and the dependence of macroscale behavior on changes that occur at lower scales. Previously, NASA’s Multiscale Analysis Tool (NASMAT) showed its capability in predicting unreinforced fabric behavior at the macroscale by capturing finite rotations that occur at the mesoscale. Though effective, the tool can face high computational cost for large, complex problems, motivating the need for the development of a surrogate model that can capture the same behavior. A recurrent neural network (RNN) was developed and trained on virtual NASMAT data to mimic the physics-based solutions while improving the computational runtime. The architecture of the RNN to best simulate the fabric behavior was carefully crafted based on heuristic knowledge of predicting physics-based temporal data, manual hyperparameter case studies, and Hyperband optimization.. The resultant model was able to predict a variety of stress-strain curves for fabrics with different mesoscale geometries, and was further validated by comparing to experimental data for the K706 style Kevlar plain-weave fabric, demonstrating the ability of the model to effectively capture the geometric changes in the fabric without explicitly calculating them, as is done in NASMAT. Furthermore, the tool showed its ability to improve on the runtime by a factor of 10 for fabric solutions compared to the multiscale tool, which would further enable the simulation of complex loading scenarios on unreinforced fabrics.

Fabric↗
NASA NTRSDate not supplied

Pilot Workload Rating Predictions Using Image Data and Recurrent Neural Networks

In this work, we augmented existing methods for estimating pilot workload ratings with deep neural networks trained using data from simulated flight tests in the Vertical Motion Simulator (VMS). We used an existing method, Spare Capacity Operations Estimator (SCOPE), along with a recurrent neural network and conducted comparison studies between the two methods individually, and when used together. We found that using both methods together can improve the result over using either approach alone. In our first test case, we achieved an improved linear correlation coefficient of 0.409 over that of SCOPE alone at 0.352 on the training dataset. Through cross validation, we also found that the results may be dependent on the split of training vs. validation data, and that further investigation should be conducted to understand what additional inputs to the neural network model should be made.

Image Data↗
NASA NTRS2023

Drought and Deluge: the Recurrence of Hydroclimate Extremes During the Past 600 Years in Eastern Australia’s Natural Resource Management (NRM) Clusters

Recent extremes of flood and drought across Australia have raised questions about the recurrence of such rare events and highlighted the importance of understanding multi-decadal climate variability. However, instrumental records over the past century are too short to adequately characterise climate variability on multi-decadal and longer timescales or robustly determine extreme event frequencies and their duration. Palaeoclimate reconstructions can provide much-needed information to help address this problem. Here, we use the 600-year hydroclimate record captured in the eastern Australian and New Zealand Drought Atlas (ANZDA) to analyse drought and pluvial frequency trends for East Australian Natural Resource Management (NRM) clusters. This partitioning of the drought atlas grid points into recognised biophysical areas (i.e. NRM clusters) revealed their differences and similarities in drought intensity and pluvial events over time. We find sustained multi-decadal periods of a wet–dry geographic 'seesaw' between eastern to central and southern NRMs (e.g. 1550–1600 CE and 1700–1750 CE). In contrast, other periods reveal spatially consistent wetting (e.g. 1500–1550 CE) or drying (e.g. 1750–1800 CE). Emerging hot spot analysis further shows that some areas that appear naturally buffered from severe drought during the instrumental period have a greater exposure risk when the longer 600-year record is considered. These findings are particularly relevant to management plans when dealing with the impacts of climate extremes developed at regional scales. Our results demonstrate that integrating and extending instrumental records with palaeoclimate datasets will become increasingly important for developing robust and locally specific extreme event frequency information for managing water resources.

Australian hydroclimate↗
NASA NTRS1968

On trinomial recurrences.

Linear recurring sequences polynomial set generation, discussing binomial and trinomial recurrences

Goldstein, R. M.↗