Search NASA⌕ Search

SEARCH · Search NASA

Results for “recurrence”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Recurrence times and periodicities in 4U 1608-52 as observed by Vela 5B

We report on the Vela 5B 10 year history of the soft X-ray transient 4U 1608-52, and on the characteristics of its soft X-ray outbursts. The Vela 5B satellite observed the four known outbursts in 1975, 1977, and 1979, and four new outbursts in 1970 and 1971, altering the recurrence pattern of outbursts from this source. One of the 1970 outbursts is symmetric in its intensity profile, while the two outbursts in 1971 have short exponential profiles separated by 80 days. Despite suggestive recurrence periods of approximately 85 and approximately 150 days evident in the time intervals between the outbursts, there is no single statistically significant recurrence time on which the outbursts recur consistently. In the 1970 symmetric event, there is evidence for a period of either 4.10 or 5.19 days. Drawing upon the analogy with SU Ursa Majoris dwarf novae, we suggest that the short period is orbital and any longer period would be associated with a precession period of the accretion disk.

Lochner, James C.↗
NASA NTRS2012

Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network

The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis

Yao, Weigang↗
NASA NTRS2016

Recurrence Rate and Magma Effusion Rate for the Latest Volcanism on Arsia Mons, Mars

Magmatism and volcanism have evolved the Martian lithosphere, surface, and climate throughout the history of Mars. Constraining the rates of magma generation and timing of volcanism on the surface clarifies the ways in which magma and volcanic activity have shaped these Martian systems. The ages of lava flows on other planets are often estimated using impact crater counts, assuming that the number and size-distribution of impact craters per unit area reflect the time the lava flow has been on the surface and exposed to potential impacts. Here we show that impact crater age model uncertainty is reduced by adding stratigraphic information observed at locations where neighboring lavas abut each other, and demonstrate the significance of this reduction in age uncertainty for understanding the history of a volcanic field comprising 29 vents in the 110-kilometer-diameter caldera of Arsia Mons, Mars. Each vent within this caldera produced lava flows several to tens of kilometers in length; these vents are likely among the youngest on Mars, since no impact craters in their lava flows are larger than 1 kilometer in diameter. First, we modeled the age of each vent with impact crater counts performed on their corresponding lava flows and found very large age uncertainties for the ages of individual vents, often spanning the estimated age for the entire volcanic field. The age model derived from impact crater counts alone is broad and unimodal, with estimated peak activity in the field around 130Ma (megaannum, 1 million years). Next we applied our volcano event age model (VEAM), which uses a directed graph of stratigraphic relationships and random sampling of the impact crater age determinations to create alternative age models. Monte Carlo simulation was used to create 10,000 possible vent age sets. The recurrence rate of volcanism is calculated for each possible age set, and these rates are combined to calculate the median recurrence rate of all simulations. Applying this approach to the 29 volcanic vents, volcanism likely began around 200-300Ma then first peaked around 150Ma, with an average production rate of 0.4 vents per Myr (million years). The recurrence rate estimated including stratigraphic data is distinctly bimodal, with a second, lower peak in activity around 100Ma. Volcanism then waned until the final vents were produced 10-90Ma. Based on this model, volume flux is also bimodal, reached a peak rate of 1-8 cubic kilometers per million years by 150Ma and remained above half this rate until about 90Ma, after which the volume flux diminished greatly. The onset of effusive volcanism from 200-150Ma might be due to a transition of volcanic style away from explosive volcanism that emplaced tephra on the western flank of Arsia Mons, while the waning of volcanism after the 150Ma peak might represent a larger-scale diminishing of volcanic activity at Arsia Mons related to the emplacement of flank apron lavas.

Richardson, Jacob A.↗
NASA NTRS2016

M31N 2008-12a-The Remarkable Recurrent Nova in M31-Panchromatic Observations of the 2015 Eruption

The Andromeda Galaxy recurrent nova M31N 2008-12a had been observed in eruption 10 times, including yearly eruptions from 2008 to 2014. With a measured recurrence period of Prec = 351+/-13 days (we believe the true value to be half of this) and a white dwarf very close to the Chandrasekhar limit, M31N 2008-12a has become the leading pre-explosion supernova type Ia progenitor candidate. Following multi-wavelength follow-up observations of the 2013 and 2014 eruptions, we initiated a campaign to ensure early detection of the predicted 2015 eruption, which triggered ambitious ground- and space-based follow-up programs. In this paper we present the 2015 detection, visible to near-infrared photometry and visible spectroscopy, and ultraviolet and X-ray observations from the Swift observatory. The LCOGT 2 m (Hawaii) discovered the 2015 eruption, estimated to have commenced at August 28.28 +/- 0.12 UT. The 2013-2015 eruptions are remarkably similar at all wavelengths. New early spectroscopic observations reveal short-lived emission from material with velocities approx. 13,000 km/s, possibly collimated outflows. Photometric and spectroscopic observations of the eruption provide strong evidence supporting a red giant donor. An apparently stochastic variability during the early supersoft X-ray phase was comparable in amplitude and duration to past eruptions, but the 2013 and 2015 eruptions show evidence of a brief flux dip during this phase. The multi-eruption Swift/XRT spectra show tentative evidence of high-ionization emission lines above a high-temperature continuum. Following Henze et al. (2015a), the updated recurrence period based on all known eruptions is Prec 174 +/- 10 days, and we expect the next eruption of M31N 2008-12a to occur around 2016 mid-September.

cataclysmic variables – stars: individual (M31N ↗
DOE OSTI2025

Physics-Informed Recurrent Neural Networks to Predict Reactor Operations of the AGN-201 Nuclear Reactor

4 page paper submitted to ANS Student conference. Summary of paper similar to the following abstract: The ability to predict how a reactor will operate, understand when anomalous conditions arise, and ensure a reactor is being operated as expected is crucial for deploying new nuclear facilities. Digital twins serve as a unique solution to recognizing reactor behavior; however, they require data to be useful. For next-generation reactors, this data may not currently be available. To explore how synthetic physics-informed reactor data can be used to predict reactor operations, a recurrent neural network was implemented for the Idaho State University AGN-201 digital twin. The goal of this work is to determine how synthetic data can be used to train a recurrent neural network model for predicting the reactor power of the AGN-201. The recurrent neural network was validated using both synthetic and real operational data. We envision this approach will help bridge the gap between the virtual and physical sides of a digital twin, where reactor physics models based on as-built data can be corrected for actual operating parameters to ensure the virtual model mirrors reality.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗
NASA NTRS1998

T wave alternans as a predictor of recurrent ventricular tachyarrhythmias in ICD recipients: prospective comparison with conventional risk markers

INTRODUCTION: The current standard for arrhythmic risk stratification is electrophysiologic (EP) testing, which, due to its invasive nature, is limited to patients already known to be at high risk. A number of noninvasive tests, such as determination of left ventricular ejection fraction (LVEF) or heart rate variability, have been evaluated as additional risk stratifiers. Microvolt T wave alternans (TWA) is a promising new risk marker. Prospective evaluation of noninvasive risk markers in low- or moderate-risk populations requires studies involving very large numbers of patients, and in such studies, documentation of the occurrence of ventricular tachyarrhythmias is difficult. In the present study, we identified a high-risk population, recipients of an implantable cardioverter defibrillator (ICD), and prospectively compared microvolt TWA with invasive EP testing and other risk markers with respect to their ability to predict recurrence of ventricular tachyarrhythmias as documented by ICD electrograms. METHODS AND RESULTS: Ninety-five patients with a history of ventricular tachyarrhythmias undergoing implantation of an ICD underwent EP testing, assessment of TWA, as well as determination of LVEF, baroreflex sensitivity, signal-averaged ECG, analysis of 24-hour Holter monitoring, and QT dispersion from the 12-lead surface ECG. The endpoint of the study was first appropriate ICD therapy for electrogram-documented ventricular fibrillation or tachycardia during follow-up. Kaplan-Meier survival analysis revealed that TWA (P < 0.006) and LVEF (P < 0.04) were the only significant univariate risk stratifiers. EP testing was not statistically significant (P < 0.2). Multivariate Cox regression analysis revealed that TWA was the only statistically significant independent risk factor. CONCLUSIONS: Measurement of microvolt TWA compared favorably with both invasive EP testing and other currently used noninvasive risk assessment methods in predicting recurrence of ventricular tachyarrhythmias in ICD recipients. This study suggests that TWA might also be a powerful tool for risk stratification in low- or moderate-risk patients, and needs to be prospectively evaluated in such populations.

Non-NASA Center↗
DOE OSTI2024

Saturation and Recurrence of Quantum Complexity in Random Local Quantum Dynamics

Quantum complexity is a measure of the minimal number of elementary operations required to approximately prepare a given state or unitary channel. Recently, this concept has found applications beyond quantum computing—in studying the dynamics of quantum many-body systems and the long-time properties of anti–de Sitter black holes. In this context, Brown and Susskind [] conjectured that the complexity of a chaotic quantum system grows linearly in time up to times exponential in the system size, saturating at a maximal value, and remaining maximally complex until undergoing recurrences at doubly exponential times. In this work, we prove the saturation and recurrence of complexity in two models of chaotic time evolutions based on (i) random local quantum circuits and (ii) stochastic local Hamiltonian evolution. Our results advance an understanding of the long-time behavior of chaotic quantum systems and could shed light on the physics of black-hole interiors. From a technical perspective, our results are based on establishing new quantitative connections between the Haar measure and high-degree approximate designs, as well as the fact that random quantum circuits of sufficiently high depth converge to approximate designs. Published by the American Physical Society 2024

Oszmaniec, Michał (ORCID:0000000249466835)↗
DOE OSTI2026

VRN3P: Variational Recurrent Neural Network Based Net-Load Prediction under High Solar Penetration

This is the final technical report for the SETO-funded VRN3P project (PNNL# 76914). The goal of this project, led by Pacific Northwest National Laboratory (PNNL), in collaboration with Lawrence Livermore National Laboratory (LLNL) and Portland General Electric (PGE), was to develop and validate a deep variational recurrent neural network-based net-load prediction (VRN3P) framework for probabilistic time-series forecasting of day-ahead net-load under high solar penetration scenarios. The project team reports successful design of a novel probabilistic net-load forecasting architecture, comprising of a variational autoencoder and a recurrent neural network, which demonstrates 30% improvement in forecast performance, 60% improvement in training time, and consumes 44% less memory, when compared with conventional baseline models. The team tested the VRN3P model performance on GridLAB-D test-cases representing varying BTM solar penetration levels of 20%, 30%, and 50%, with integrated time-series net-load profiles provided by the utility partner (PGE). The VRN3P model demonstrate <2% hourly MAPE (averaged over the year) for day- ahead net-load forecast on the test scenario with 20% BTM solar. Transfer learning extension of the VRN3P model has demonstrated 8.33× speed-up in training, while still achieving acceptable forecast performance of 2.24% hourly MAPE on the 30% BTM solar penetration test-scenario. A preliminary version of the VRN3P GridAPPS-D™has been developed, along with a web-based interactive user-interface (named ‘Forte’) which has made available on GitHub for public use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Exceedance Probabilities and Recurrence Intervals for Extended Power Outages in the United States

This report provides estimates of recurrence intervals and conditional exceedance probabilities for major power outages by U.S. region between 2015 and 2021. Additionally, we provide estimates for grid management, particularly outages caused by California’s public safety power shutoffs (PSPS), and for natural outages caused by major hurricanes. Outage recurrence intervals are the average number of years between outage events, and conditional exceedance probabilities are the likelihoods that a customer who experiences a major power outage will experience an outage exceeding a given duration. Major outage events are those that affect 10,000 or more customers, as defined by the U.S. Department of Energy’s (DOE’s) Electric Emergency Incident and Disturbance Report, called OE-417 (DOE 2020). These results can be applied to determine the likelihood of experiencing long-duration outages, which can be integrated into cost-benefit analyses of resilience solutions and broader energy resilience studies.

Ericson, Sean [National Renewable Energy Laborator↗
NASA NTRS1976

The causes of recurrent geomagnetic storms

The causes of recurrent geomagnetic activity were studied by analyzing interplanetary magnetic field and plasma data from earth-orbiting spacecraft in the interval from November 1973 to February 1974. This interval included the start of two long sequences of geomagnetic activity and two corresponding corotating interplanetary streams. In general, the geomagnetic activity was related to an electric field which was due to two factors: (1) the ordered, mesoscale pattern of the stream itself, and (2) random, smaller-scale fluctuations in the southward component of the interplanetary magnetic field Bz. The geomagnetic activity in each recurrent sequence consisted of two successive stages. The first stage was usually the most intense, and it occurred during the passage of the interaction region at the front of a stream. These large amplitudes of Bz were primarily produced in the interplanetary medium by compression of ambient fluctuations as the stream steepened in transit to 1 A.U. The second stage of geomagnetic activity immediately following the first was associated with the highest speeds in the stream.

Burlaga, L. F.↗
NASA NTRS1981

Ultraviolet spectroscopy of the recurrent nova U Scorpii during outburst

Observations of the recurrent nova U Sco during the 1979 outburst are presented, and the spectral evolution is found to differ from that of other recurrent novas. Spectra are dominated by emission lines, and the strong forbidden-line emission characteristic is conspicuously absent. A method to determine masses of nova shells is outlined, and an analysis of the emission lines shows an enrichment in N relative to C and O, and that the nova ejecta are rich in He relative to H. Optical spectra of U Sco obtained following its return to quiescence show predominantly He II emission lines, which suggests an enrichment of the preoutburst gas in He, and thus the presence of a highly evolved companion.

Williams, R. E.↗
NASA NTRS1984

Innovative approaches to recurrent training

Innovative approaches to recurrent training for regional airline aircrews are explored. Guidelines for recurrent training programs which include in corporation of cockpit resource management are discussed. B.W.

Noon, H.↗
NASA NTRS1984

Gamma-ray burster recurrence timescales

Three optical transients have been found which are associated with gamma-ray bursters (GRBs). The deduced recurrence timescale for these optical transients (tau sub opt) will depend on the minimum brightness for which a flash would be detected. A detailed analysis using all available data of tau sub opt as a function of E(gamma)/E(opt) is given. For flashes similar to those found in the Harvard archives, the best estimate of tau sub opt is 0.74 years, with a 99% confidence interval from 0.23 years to 4.7 years. It is currently unclear whether the optical transients from GRBs also give rise to gamma-ray events. One way to test this association is to measure the recurrence timescale of gamma-ray events tau sub gamma. A total of 210 gamma-ray error boxes were examined and it was found that the number of observed overlaps is not significantly different from the number expected from chance coincidence. This observation can be used to place limits on tau sub gamma for an assumed luminosity function. It was found that tau sub gamma is approx. 10 yr if bursts are monoenergetic. However, if GRBs have a power law luminosity function with a wide dynamic range, then the limit is tau sub gamma 0.5 yr. Hence, the gamma-ray data do not require tau sub gamma and tau sub opt to be different.

Schaefer, B. E.↗
NASA NTRS1985

Latitude variation of recurrent fluxes in the outer solar system

Recurrent low energy (greater than or = to 0.5 MeV) proton flux enhancements, reliable indicators of corotating plasma interaction regions, were observed on the Voyager 1 and 2 and Pioneer 11 spacecraft in the heliographic latitude range 2 deg S to 23 N and the heliocentric radial range 11 to 20 AU. After a period of rather high correlation between fluxes at different latitudes in early 1983, distinct differences developed in the fluxes during an overall flux decrease. The flux intensities returned to higher levels in early 1984 and differences in both the recurrence frequency and flux intensity persisted into 1985, as Voyager 1 traveled to 23 AU and 25 N latitude. Intercomparison of data from the three spacecraft indicates that the flux differences are most likely due to latitudinal rather than radial or temporal variations.

Christon, S. P.↗
NASA NTRS1984

Recurrent mass ejections observed in H-alpha and CIV

Time sequences of recurrent mass ejections have been observed during a coordinated SMY program (Sept. 1, 1980 - Sept. 23, 1980 - Oct. 2, 1980). Comparison of the temporal evolution of H-alpha and CIV brightnesses shows a weak phase lag between H-alpha and CIV maxima, in the case of homologous flares, with CIV brightness maxima preceding H-alpha maxima. The analysis of the variation of the ejection velocities is expected to lead to the determination of an energy balance. Such recurrent ejections could be due to periodic energy storage and periodic reorganization of magnetic field as envisaged to occur for flares, but at lower energy levels.

Schmieder, B.↗
NASA NTRS1987

Localization, time histories, and energy spectra of a new type of recurrent high-energy transient source

The detection of a recurrent high-energy transient source which is neither a classical X-ray nor a gamma-ray burster, but whose properties are intermediate between the two, is reported. The energy spectra of 12 recurrent events are found to be soft, characterized by kT's of 34-56 keV. The time histories are short with rise and fall times as fast as about 10 ms. The source location is a 0.12 sq deg region about 10 deg from the Galactic center.

Atteia, J.-L.↗
NASA NTRS1988

Evolution of recurrent solar wind structures between 14 AU and the termination shock

The solar wind conditions observed from Voyager 2 at approximately 14 AU are extrapolated to the region of the outer heliosphere bounded by the termination shock, using an MHD simulation model. Results from two simulation studies are presented for two sets of nearly recurrent solar wind interaction regions, with initial conditions generated from plasma and magnetic field data observed on March 1984 at 13.8 AU, and on November 1984 at 15.4, respectively. Each simulation describes an idealized recurrent solar wind structure in the supersonic region of the outer heliosphere out to the termination shock far beyond the present reaches of the Pioneer and Voyager spacecraft. It is shown that a collision between the forward shock and the reverse shock occurs approximately every 40 AU. When a forward shock interacts with the termination shock, the latter is weakened and moves outward; the termination shock is strengthened and moves inward when a reverse shock interacts with it.

Whang, Y. C.↗