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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward a persistent event-streaming system for high-performance computing applications

High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications between application components, trading persistence and fault tolerance for speed. Event-driven architectures, as popularized in enterprise contexts, present a compelling middle ground, avoiding the performance cost and API constraints of parallel file systems while retaining persistence and offering impedance matching between application components. However, adapting streaming frameworks to HPC workloads requires addressing challenges unique to HPC systems. This paper investigates the potential for a streaming framework designed for HPC infrastructures and use cases. We introduce Mofka, a persistent event-streaming framework designed specifically for HPC environments. Mofka combines the capabilities of a traditional streaming service with optimizations tailored to the HPC context, such as support for massively multicore nodes, efficient scaling for large producer-consumer workflows, RDMA-enabled high-performance network communications, specialized network fabrics with multiple links per node, and efficient handling of large scientific data payloads. Built using the Mochi suite of HPC data service components, Mofka provides a lightweight, modular, and high-performance solution for persistent streaming in HPC systems. We present the architecture of Mofka and evaluate its performance against Kafka and Redpanda using benchmarks on diverse platforms, including Argonne's Polaris and Oak Ridge's Frontier supercomputers, showing up to 8× improvement in throughput in some scenarios. We then demonstrate its utility in several real-world applications: a tomographic reconstruction pipeline, a workflow for the discovery of metal-organic frameworks for carbon capture, and the instrumentation of Dask workflows for provenance tracking and performance analysis.

HPC↗
NASA NTRS1979

Persistent emission from X-ray burst sources and the nature of galactic bulge X-ray sources

Intrinsic persistent emission from galactic bulge X-ray sources and the ratio of the average persistent X-ray luminosity to the time-averaged burst luminosity associated with Type I burst sources are discussed in the light of the thermonuclear flash model of X-ray burst emission. Values of the ratio between average persistent luminosity and time-averaged burst luminosity for a large collection of SAS 3 sources are presented to confirm the predictions of the burst model of thermonuclear flashes in freshly accreted matter on a neutron star. The model also predicts a critical value of the persistent accretion rate, below which bursts can occur. It is suggested that the galactic bulge X-ray sources represent neutron stars undergoing accretion, with burst sources accounting for a subset in which the accretion rate is below the critical value.

Van Paradijs, J.↗
NASA NTRS1987

Statistics and dynamics of persistent anomalies

Persistent anomalies with recurrent spatial patterns play an important role in the atmosphere's low-frequency variability. A connection between statistical and dynamical methods of description and prediction of persistent anomalies is established by computing and analyzing the empirical orthogonal functions (EOFs) in a simple deterministic model, on the one hand, and in Southern Hemisphere geopotential heights, on the other. The dynamical model is governed by the fully nonlinear, equivalent-barotropic vorticity equation on the sphere, with simplified forcing, dissipation and topography. The Southern Hemisphere data consist in gridded daily maps of 500 mb heights from June 1972 to July 1983. Two types of persistent anomalies appear in this time series, both having a strong wavenumber-three component; they differ by the value of the constant phase of this wave and by the strength of the wavenumber-one component. The first two EOFs bear a striking resemblance to these two patterns. It is concluded that the dynamical interpretation of EOFs is their pointing from the time mean to the most populated regions of the system's phase space. Pursuing this interpretation, a Markov-chain formulation of transitions from one persistent anomaly regime to another is introduced, and the implications for long-range forecasting are discussed.

Mo, Kingtse C.↗
NASA NTRS1993

Unusual features in the persistent emission of the Rapid Burster

Several distinct features in the persistent X-ray emission after long (greater than 30 s) type II bursts from the Rapid Burster were discovered in August 1985. A specific pattern characterized by a 'hump' was observed in the early portion of the persistent emission after type II bursts with integrated fluxes less than about 4.8 x 10 exp -6 erg/sq cm. This hump which typically lasts about 200 s is almost never observed after bursts with fluences greater than this value. The emission during the hump is found to be always harder than the average persistent emission. Quasi-periodic oscillations with frequencies of about 40 mHz observed in 10 cases occur exclusively during a hump. The persistent emission also exhibited sharp 'glitches' and small 'bumps' lasting about 20-100 s. The glitches always occurred at the same phase in the intervals between bursts. In seven cases the glitches were followed by a bump.

Lubin, Lori M.↗
NASA NTRS2010

Diagnosing Intermittent and Persistent Faults using Static Bayesian Networks

Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly, while maintaining strong performance on persistent faults.

Megshoel, Ole Jakob↗
DOE OSTI2025

Persistent Classification: Understanding Adversarial Attacks by Studying Decision Boundary Dynamics

ABSTRACT There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high‐dimensionality of the data, the high codimension in the ambient space of the data manifolds of interest, and that the structure of machine learning models may encourage classifiers to develop decision boundaries close to data points. This article proposes a new framework for studying adversarial examples that does not depend directly on the distance to the decision boundary. Similarly to the smoothed classifier literature, we define a (natural or adversarial) data point to be ( γ , σ)‐stable if the probability of the same classification is at least for points sampled in a Gaussian neighborhood of the point with a given standard deviation . We focus on studying the differences between persistence metrics along interpolants of natural and adversarial points. We show that adversarial examples have significantly lower persistence than natural examples for large neural networks in the context of the MNIST and ImageNet datasets. We connect this lack of persistence with decision boundary geometry by measuring angles of interpolants with respect to decision boundaries. Finally, we connect this approach with robustness by developing a manifold alignment gradient metric and demonstrating the increase in robustness that can be achieved when training with the addition of this metric.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo

Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.

Karamanis, Minas↗
DOE OSTI2025

Persistence of bacterial-mediated anti-rotifer protection in preliminary outdoor cultivation trial for Microchloropsis salina

Outdoor algal cultivation systems are susceptible to a wide variety of deleterious species. In previously published studies, we observed protection using microbial consortia at laboratory scale cultures; Microchloropsis salina in the presence of microbial consortia were protected from grazing from the marine rotifer, Brachionus plicatilis. Our objective for the present work was to determine if this protection conferred by microbial consortia in controlled laboratory experiments would persist in an open, outdoor multi-liter cultivation system. We found that algal protection did persist as evidenced by the presence of fewer motile rotifers and decreased rotifer-associated egg counts for the consortia-treated outdoor cultures. Due to the low temperature and light conditions that reduced growth of the algae outdoors, we performed an indoor laboratory assay which also confirmed the persistence of algal protection. Lastly, the lower numbers of motile rotifers and fewer rotifer-associated eggs in the consortia-treated algal cultures suggests a possible protective mechanism by the consortia through interfering with the rotifer lifecycle or reproduction. Finally, these initial results support the possibility that low cost, prophylactic treatments with microbial consortia can protect algae from deleterious species in outdoor cultivation systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Persistent urinary metabolic signatures in children with type 1 diabetes

There are an estimated 3.7 million people with undiagnosed type 1 diabetes (T1D), living primarily in poor areas of the globe. Therefore, there is a need for non-invasive, affordable tests to provide accurate diagnosis despite the time post-disease onset and fasting state. Here, we studied persistent urinary T1D biomarkers that can be used to develop such tests. Here, we analyzed the urine metabolomes of three independent cohorts of samples collected within 48 h (from Indiana University), and 1 year (from University of Colorado) and 1–10 years (6 years in average) (from Children’s National Medical Center) post-diagnosis. Samples were submitted to gas chromatography-mass spectrometry and machine learning an0alyses to determine diagnostic metabolite panels. The data were also mapped into a metabolic pathway to understand persistently regulated processes in T1D. Seven metabolites showed consistent increases in all three cohorts: d-glucose, d-mannose, myo-inositol, 3-hydroxyisobutyric acid, gluconolactone, d-gluconic acid, and d-glucuronic acid. A combination of machine learning analysis and metabolite ratios as biomarker candidates diagnosed T1D with high sensitivity and specificity across different cohorts and times. Mapping the regulated metabolites into a pathway showed impairment in glycolysis and overflow of glucose towards other pathways in subjects with T1D that was persistent over time. We identified and cross-validated highly specific and sensitive urinary biomarkers. This opens opportunities to develop affordable, robust, and non-invasive tests. The results also show that most of the biomarkers were signatures of dysregulated glucose metabolism.

Type 1 diabetes↗
DOE OSTI2026

Ultranano Titania: Selectively Ridding Water of Persistent Organic Pollutants

Persistent organic pollutants, including the EPA's “dirty dozen”, are difficult to remove from water supplies due to their chemical stability. Here, we report a stable oxide photocatalyst, ultranano titania (d < 2 nm) doped with iron, Fe•TiUNP, that efficiently mineralizes multiple persistent pollutants including aromatic compounds plus common troublesome, difficult-to-oxidize intermediates such as formaldehyde and acetone, netting mineralization of persistent pollutants. Efficiency stems from a direct charge-transfer pathway. The key role of iron doping is to lower the reduction potential of the photogenerated electron so that it is insufficient to reduce water, thus eliminating competition from the hydrogen evolution reaction. The reduction potential of the localized electron is similarly insufficient to reduce quinone, enabling breaking aromaticity. Specific results for degrading acetone, phenol, benzoic acid, and 1,4-benzoquinone are reported.

alcohols↗
DOE OSTI2024

Cosmology with persistent homology: a Fisher forecast

Abstract Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from theQuijotesimulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13–50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data.

Astronomy & Astrophysics↗
DOE OSTI2025

Persistent Current Simulation for CCT Testing Magnet Used in EIC

The Electron-Ion Collider (EIC), a powerful new facility to be built in the United States at the U.S. Department of Energy's Brookhaven National Laboratory in collaboration with Thomas Jefferson National Accelerator Facility, will explore the most fundamental building blocks of nearly all visible matter. Here, there are many different types of superconducting magnets near the interaction region (IR) of EIC. Due to space constraints and special lattice requirements, Tapered CCT (canted-cosine theta) magnets have been used for EIC. At beam injection, the magnetic field is only ~5.5% of the maximum operating field. Considerable field errors will be generated from persistent current in superconducting strands even using very fine filament for those superconductors. A tapered CCT demonstrator magnet has been built and tested successfully at BNL since July 2020 to evaluate the key technologies for future tapered CCT magnets. In October 2023, BNL team also measured the persistent current in this demonstrator magnet. To validate the persistent current simulation methods for CCT magnets in EIC, this paper used a full 3D Opera Model and measured magnetization data from superconducting strand for the simulation. Simulation results showed reasonable agreement with recent measurement results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1983

Development of a persistent chemical agent simulation system

A Persistent Chemical Agent Simulation System was developed (PCASS) to simulate, for force-on-force training exercises, the field environment produced by the presence of persistent chemical agents. Such a simulant system must satisfy several requirements to be of value as a training aid. Specifically, it must provide for realistic training which will generate competency in at least the following areas: (1) detection of the persistent agent presence; (2) proper use of protective equipment and procedures; (3) determination of the extent of contamination; and (4) decontamination of equipment and personnel.

Source record↗
NASA NTRS1986

Persistent anomalies of the extratropical Northern Hemisphere wintertime circulation - Structure

A study identifying horizontal and vertical structures of low patterns occurring with persistent 500 mb height anomalies in the central North Pacific, eastern North Atlantic, and northern Soviet Union regions is presented. The flow patterns of positive and negative anomalies are compared. The relationship between persistent anomalies and small recurrent anomaly patterns is examined. The temporal fluctuations of the persistent patterns are analyzed.

Dole, R. M.↗
NASA NTRS1988

On the relation between X-ray burst properties and the persistent X-ray luminosity

Published data on X-ray bursts is analyzed, assuming that the peak luminosity of X-ray bursts with radius expansion is a standard candle and that the ratio of the anisotropy factors, xi(b) and xi(p) (Sztajno et al., 1987) is the same for all burst sources. It is shown that the effective burst duration, defined as the ratio of burst fluence to maximum burst flux, is strongly anticorrelated with the persistent luminosity. A positive correlation with the persistent luminosity of the ratio of the average persistent flux to the time-averaged burst flux is found. It is concluded that, independent of the accretion rate, after a given waiting time burst sources produce bursts with approximately the same (average) energy. This suggests that continuous stable burning of a sizeable fraction of the nuclear fuel is a general phenomenon on the surface of accreting neutron stars. It is suggested that this fraction is a gradually increasing function of the accretion rate.

Van Paradijs, J.↗
NASA NTRS1992

Persistence and predictability in a perfect model

A realistic two-level GCM is used to examine the relationship between predictability and persistence. Predictability is measured by the average divergence of ensembles of solutions starting from perturbed initial conditions, and persistence is defined in terms of the autocorrelation function based on a single long-term model integration. The average skill of the dynamical forecasts is compared with the skill of simple persistence-based statistical forecasts. For initial errors comparable in magnitude to present-day analysis errors, the statistical forecast loses all skill after about one week, reflecting the lifetime of the lowest frequency fluctuations in the model. Large ensemble mean dynamical forecasts would be expected to remain skillful for about 3 wk. The disparity between the skill of the statistical and dynamical forecasts is greater for the higher frequency modes, which have little memory beyond 1 d, yet remain predictable for about 2 wk. The results are analyzed in terms of two characteristic time scales.

Schubert, Siegfried D.↗
NASA NTRS1993

Path planning by querying persistent stores of trajectory segments

We introduce an algorithm for path planning (long duration) paths of dynamical systems, given a persistent object store containing suitable collections of short duration trajectory segments. We also describe experimental results from a proof-of-concept implementation of the algorithm. The basic idea is to interpret a path planning algorithm as a suitable query on a persistent object store consisting of short duration trajectory segments. The query returns a concatenation of short duration trajectory segments which is close to the desired path. The needed short duration segments are computed by using a divide and conquer algorithm to break up the original path into shorter paths; each shorter path is then matched to a nearby trajectory segment which is part of the persistent object store by using a suitable index function.

Grossman, Robert L.↗
NASA NTRS1994

Simulated life cycles of persistent anticyclonic anomalies over the North Pacific: Role of synoptic-scale eddies

This study examines the role of synoptic-scale eddies during the development of persistent anticyclonic height anomalies over the central North Pacific in a general circulation model under perpetual January conditions. The General Circulation Model (GCM) replicates the basic characteristics of the evolution of the anomaly patterns found in observations. The life cycle is characterized by the rapid establishment of the major anomaly center and considerably longer maintenance and decay phases, which include the development of downstream anomaly centers. The simulation also shows a realistic evolution of synoptic-scale activity beginning with enhanced activity off the east coast of Asia prior to onset, followed by a northward shift of the Pacific storm track, which lasts throughout the maintenance phase. The initial enhancement of synoptic-scale eddy activity is associated with a large-scale cyclonic anomaly that developes over Siberia several days prior to the onset of the main anticyclonic anomaly over the central North Pacific. The observations, however, show considerable interdecadel variability in the details of the composite onset behavior; it is unclear whether this variability is real or whether it reflects differences in the data assimilation systems. The role of the time mean flow and synoptic-scale eddies in the development of the persistent Pacific anomalies is studied within the context of a kinetic energy budget in which the flow is decomposed into the time-mean, low-frequency (timescales longer than 10 days), and synoptic (timescales less than 6 days) components. The budget, which is carried out for the simulation at 500 mb, shows that the initial growth of the persistent anticyclonic anomalies is associated with barotropic conversions of energy, with approximately equal contributions coming from the mean flow and the synoptic-scale eddies. After onset the barotropic conversion from the mean flow dominates, whereas the decay phase is associated with baroclinic processes within the low-frequency flow.

Higgins, R. W.↗