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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Disturbance of hibernating bats due to researchers entering caves to conduct hibernacula surveys

Estimating population changes of bats is important for their conservation. Population estimates of hibernating bats are often calculated by researchers entering hibernacula to count bats; however, the disturbance caused by these surveys can cause bats to arouse unnaturally, fly, and lose body mass. We conducted 17 hibernacula surveys in 9 caves from 2013 to 2018 and used acoustic detectors to document cave-exiting bats the night following our surveys. We predicted that cave-exiting flights (i.e., bats flying out and then back into caves) of Townsend’s big-eared bats (Corynorhinus townsendii) and western small-footed myotis (Myotis ciliolabrum) would be higher the night following hibernacula surveys than on nights following no surveys. Those two species, however, did not fly out of caves more than predicted the night following 82% of surveys. Nonetheless, the activity of bats flying out of caves following surveys was related to a disturbance factor (i.e., number of researchers × total time in a cave). We produced a parsimonious model for predicting the probability of Townsend’s big-eared bats flying out of caves as a function of disturbance factor and ambient temperature. That model can be used to help biologists plan for the number of researchers, and the length of time those individuals are in a cave to minimize disturbing bats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The structures of ordered defects in thiocyanate analogues of Prussian Blue

We report the structures of six new divalent transition metal hexathiocyanatobismuthate frameworks with the generic formula $\Big\{ M[Bi(SCN)_6]_\frac{2+x}{3} \Big\}$ $\{guest\}^{x+}$, M = Mn, Co, Ni and Zn. These frameworks are defective analogues of the perovskite-derived trivalent transition metal hexathiocyanatobismuthates M III [Bi(SCN) 6 ]. The defects in these new thiocyanate frameworks order and produce complex superstructures due to the low symmetry of the parent structure, in contrast to the related and more well-studied cyanide Prussian Blue analogues. Despite the close similarities in the chemistries of these four transition metal cations, we find that each framework contains a different mechanism for accommodating the lowered transition metal charge, making use of some combination of Bi(SCN) 6 3- vacancies, M Bi antisite defects, water substitution for thiocyanate, adventitious extra-framework cations and reduced metal coordination number. These materials provide an unusually clear view of defects in molecular framework materials and their variety suggests that similar richness may be waiting to be uncovered in other hybrid perovskite frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Rapid early gas accretion for the inner Galactic disc: A case for short accretion timescale

Recent observations of the Milky Way and galaxies at high redshifts suggest that galaxy discs were already in place soon after the Big Bang. While the gas infall history of the Milky Way in the inner disc has long been assumed to be characterised by a short accretion timescale, this has not been directly constrained using observations. Using data for the inner regions of the Milky Way recently produced by APOGEE and Gaia and of unprecedented quantity and quality, we aim to derive strong constraints on the infall history of the inner (< 6 kpc) Galaxy (with a focus on stars between 4 and 6 kpc, which we show is an appropriate proxy for the entire inner disc). We implemented gas infall into a chemical evolution model of the Galaxy disc, and used a Schmidt–Kennicutt law to connect the infall to the star formation. We explore a number of models, and two different formulations of the infall law. In one formulation, the infall is non-parametric, and in the other the infall has an explicitly exponential form. We fit the model parameters to the time–[Si/Fe] distribution of solar vicinity stars, and the metallicity and [Si/Fe] distribution function of stars with a galactocentric radius of between 4 and 6 kpc from APOGEE. Our results point to a fast, early gas accretion, and an upper limit on the accretion timescale of around 2 Gyr in the inner disc of the Milky Way. This suggests that at least half the baryons were in place within 2–3 Gyr of the Big Bang, and that half the stars of the inner disc formed within the first 5 Gyr, during the thick disc formation phase. This implies that the stellar mass of the inner disc is dominated by the thick disc, supporting our previous work, and that the gas accretion onto the inner disc was rapid and early.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Non-oscillatory no-scale inflation

We propose a non-oscillatory no-scale supergravity model of inflation (NO-NO inflation) in which the inflaton does not oscillate at the end of the inflationary era. Instead, the Universe is then dominated by the inflaton kinetic energy density (kination). During the transition from inflation to kination, the Universe preheats instantly through a coupling to Higgs-like fields. These rapidly annihilate and scatter into ultra-relativistic matter particles, which subsequently dominate the energy density, and reheating occurs at a temperature far above that of Big Bang Nucleosynthesis. After the electroweak transition, the inflaton enters a tracking phase as in some models of quintessential inflation. The model predictions for cosmic microwave background observables are consistent with Planck 2018 data, and the density of gravitational waves is below the upper bound from Big Bang Nucleosynthesis. Furthermore, we also find that the density of supersymmetric cold dark matter produced by gravitino decay is consistent with Planck 2018 data over the expected range of supersymmetric particle masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Time variability of ultra fast BAL outflows using SALT: C IV equivalent width analysis

We study the time variability (over ≤7.3 yr) of ultra fast outflows (UFOs) detected in a sample of 64 C IV broad absorption line (BAL) quasars (with 80 distinct BAL components) monitored using the Southern African Large Telescope. By comparing the properties of the quasar in our sample with those of a control sample of non-BAL quasars, we show that the distributions of black hole mass are different and the bolometric luminosities and optical photometric variations of UFO BAL quasars are slightly smaller compared to that of non-BAL quasars. The detection fraction of C IV equivalent width (W) variability (∼95 per cent), the fractional variability amplitude $\left(\frac{\Delta W}{W}\right)$ and the fraction of ‘highly variable’ BAL (i.e. $\big|$$\frac{\Delta W}{W}$$\big|$ > 0.67) components (∼33 per cent) are higher in our sample compared to the general BAL population. The scatter in $\frac{\Delta W}{W}$ and the fraction of ‘highly variable’ BALs increase with the time-scale probed. The $\frac{\Delta W}{W}$ distribution is asymmetric at large time scales. We attribute this to the BAL strengthening time-scales being shorter than the weakening time-scales. The BAL variability amplitude correlates strongly with the BAL properties compared to the quasar properties. BALs with low W, high-velocity, shallow profiles, and low-velocity width tend to show more variability. When multiple BAL components are present, a correlated variability is seen between low- and high-velocity components with the latter showing a larger amplitude variations. We find an anticorrelation between the fractional variations in the continuum flux and W. While this suggests photoionization induced variability, the scatter in continuum flux is much smaller than that of W.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Clustering and runaway merging in a primordial black hole dominated universe

If primordial black holes (PBHs) are present in the early Universe, their contribution to the energy budget grows relative to that of radiation and generically becomes dominant unless the initial abundance is exponentially small. This black hole domination scenario is largely unconstrained for PBHs with masses ≲ 10 9 g, which evaporate prior to big bang nucleosynthesis. However, if the era of PBH domination is sufficiently long, the PBHs form clusters and can merge appreciably within these objects. We calculate the population statistics of these clusters within the Press-Schechter formalism and find that, for a wide range of PBH masses and Hubble rates at the onset of PBH domination, the mergers within PBH clusters can exhibit runaway behavior, where the majority of the cluster will eventually form a single black hole with a mass much greater than the original PBH mass. Finally, these mergers can dramatically alter the PBH mass distribution and leave behind merged relic black holes that evaporate after big bang nucleosynthesis and yield various observational signatures, excluding parameter choices previously thought to be viable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evolution of decaying particles and decay products in various scenarios for the future expansion of the Universe

We examine nonrelativistic particles that decay into relativistic products in big rip, little rip, and pseudorip models for the future evolution of the Universe. In contrast to decays that occur in standard ΛCDM, the evolution of the ratio r of the energy density of the relativistic decay products to the energy density of the initially decaying particles can decrease with time in all of these models. In big rip and little rip models, r always goes to zero asymptotically, while this ratio evolves to infinity or a constant in pseudorip models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Signatures of primordial energy injection from axion strings

Axion strings are horizon-size topological defects that may be produced in the early Universe. Ultralight axion-like particles may form strings that persist to temperatures below that of big bang nucleosynthesis. Such strings have been considered previously as sources of gravitational waves and cosmic microwave background (CMB) polarization rotation. In this work we show, through analytic arguments and dedicated adaptive mesh refinement cosmological simulations, that axion strings deposit a subdominant fraction of their energy into high-energy Standard Model (SM) final states, for example, by the direct production of heavy radial modes that subsequently decay to SM particles. This high-energy SM radiation is absorbed by the primordial plasma, leading to novel signatures in precision big bang nucleosynthesis, the CMB power spectrum, and gamma-ray surveys. In particular, we show that CMB power spectrum data constrains axion strings with decay constants f a ≲ 10 12 GeV , up to model dependence on the ultraviolet completion, for axion masses m a ≲ 10 − 29 eV ; future CMB surveys could find striking evidence of axion strings with lower decay constants. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Simulations of multicomponent relativistic thermalization

Multicomponent relativistic fluids have been studied for decades. However, simulating the dynamics of the particles and fluids in such a mixture has been a challenge due to the fact that such simulations are computationally expensive in three spatial dimensions. Here, we report on the development and application of a multidimensional relativistic Monte Carlo code to explore the thermalization process in a relativistic multicomponent environment in a computationally inexpensive way. As an illustration we simulate the fully relativistic three-dimensional Brownian-motion-like solution to the thermalization of a high-mass particle (proton) in a bath of relativistic low-mass particles (electrons). Here, we follow the thermalization and ultimate equilibrium distribution of the Brownian-like particle as can happen in the cosmic plasma during big-bang nucleosynthesis. We also simulate the thermalization of energetic particles injected into the plasma as can occur, for example, by the decay of massive unstable particles during the big bang.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Enabling discovery data science through cross-facility workflows

Experimental and observational instruments for scientific research (such as light sources, genome sequencers, accelerators, telescopes and electron microscopes) increasingly require High Performance Computing (HPC) scale capabilities for data analysis and workflow processing. Next-generation instruments are being deployed with higher resolutions and faster data capture rates, creating a big data crunch that cannot be handled by modest institutional computing resources. Often these big data analysis pipelines also require near real-time computing and have higher resilience requirements than the simulation and modeling workloads more traditionally seen at HPC centers. While some facilities have enabled workflows to run at a single HPC facility, there is a growing need to integrate capabilities across HPC facilities to enable cross-facility workflows, either to provide resilience to an experiment, increase analysis throughput capabilities, or to better match a workflow to a particular architecture. In this paper we describe the barriers to executing complex data analysis workflows across HPC facilities and propose an architectural design pattern for enabling scientific discovery using cross-facility workflows that includes orchestration services, application programming interfaces (APIs), data access and co-scheduling.

Antypas, Katerina B.↗
DOE OSTI2021

Creating a Tools Ecosystem for Cross-Discipline Environmental Data Reuse

Reusing data is difficult even within well-defined science communities and only gets worse when combining data from multiple communities and disciplines. Through the lens of current work on constructing an environmental epidemiological data set from multiple disciplinary sources, we demonstrate the need for a new tool ecosystem to support heterogeneous Big Data science. Extending existing community standards for schemas and/or data formats through human auditing and wrangling of the data is not feasible at scale. This work therefore suggests new approaches for the multi-disciplinary communities to build a shared tool ecosystem for big data. We discuss both the larger context of data wrangling of epidemiological data sets for novel artificial intelligence algorithms and the specific lessons from working with these multi-disciplinary data sets. Adopting a more model-driven, automatable approach promises not only better efficiency but also removes key sources of human-generated errors and promotes reuse and reproducibility of science data.

Logan, Jeremy↗
DOE OSTI2021

Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.

consistent stream ordering↗
DOE OSTI2023

Traction Motor Design Trade-Offs with Additively Manufactured Anisotropic Bonded Magnets

Extrusion based big area additive manufacturing (BAAM) has been previously demonstrated for the fabrication of dense anisotropic bonded magnets. This paper reports on design trade-offs when such magnets are employed in a motor designed for electric vehicle applications. An external rotor fractional slot permanent magnet synchronous machine designed with sintered dysprosium free magnets rated for 100kW peak and 50kW continuous power is used as the baseline. The impact of using the bonded BAAM magnets on the motor and inverter volumes, motor loss and cooling systems as well as demagnetization margins is evaluated. It is found that although the motor power density reduces due to the lower energy product of the BAAM magnets, there are other system level benefits including reductions in the cooling system requirement, lower inverter rating and volume, decrease in short circuit current and improved demagnetization marains.

additive manufacturing↗
DOE OSTI2024

DICER: Data Intensive Computing Environment and Runtime for Evaluating Unprecedented Scale of Geospatial-Temporal Human Mobility Data

With the significant increase in sources and volume of human mobility data through commercial data vendors as well as microsimulation of cities, the scale of geospatial-temporal data to analyze and assess for mobility characterization has grown to the level of Big Data. There are mobility related commercial organizations deploying scalable computing, but often the system architecture, workflow, and intermediate processing components are not fully disclosed in relevant scope. Current research literature has a notable lack of studies demonstrating architectures and workflows for human mobility analytics that are implemented on a TeraByte scale of geospatial-temporal data. In this context, this paper presents a hyperscale-level system solution named DICER (Data Intensive Computing Environment and Runtime) for processing and analytics of geospatial-temporal data at big data scale. Although the cluster computing architecture of DICER with Apache Spark job running on Kubernetes cluster is not new, there are innovations in the workflow, hierarchical processing logic, and a wide range of intermediate preprocessing and mobility metrics calculation. We have performed case studies to validate the effectiveness of DICER system solution by performing detailed analytics and assessment of human mobility microsimulation output at three different scopes and scale, including a usecase with 16.97 TeraByte and 259.2 Billion rows of data. In addition, we have presented another case study of utilizing DICER to perform the same mobility processing and comparative analytics on large-scale commercially available geospatial-temporal data. All these case studies validate the efficiency and usefulness of DICER in computing population mobility characteristics from geospatial-temporal trajectory data at an unprecedented scale (not only just data volume, but also combination of: number of user entities, temporal frequency, spatial resolution, data duration).

De, Debraj↗
DOE OSTI2020

A Survey of Singular Value Decomposition Methods for Distributed Tall/Skinny Data

The Singular Value Decomposition (SVD) is one of the most important matrix factorizations, enjoying a wide variety of applications across numerous application domains. In statistics and data analysis, the common applications of SVD inclue Principal Components Analysis (PCA) and regression. Usually these applications arise on data that has far more rows than columns, so-called "tall/skinny" matrices. In the big data analytics context, this may take the form of hundreds of millions to billions of rows with only a few hundred columns. There is a need, therefore, for fast, accurate, and scalable tall/skinny SVD implementations which can fully utilize modern computing resources. To that end, we present a survey of three different algorithms for computing the SVD for these kinds of tall/skinny data layouts using MPI for communication. We contextualize these with common big data analytics techniques. Finally, we present both CPU and GPU timing results from the Summit supercomputer, and discuss possible alternative approaches.

Schmidt, Drew↗
DOE OSTI2024

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Braneworld cosmological effect on freeze-in dark matter density and lifetime frontier

In the 5-dimensional braneworld cosmology, the Friedmann equation of our 4-dimensional universe on a brane is modified at high temperatures while the standard Big Bang cosmology is reproduced at low temperatures. Based on two well-known scenarios, the Randall–Sundrum and Gauss–Bonnet braneworld cosmologies, we investigate the braneworld cosmological effect on the relic density of a non-thermal dark matter particle whose interactions with the Standard Model particles are so weak that its relic density is determined by the freeze-in mechanism. For dark matter production processes in the early universe, we assume a simple scenario with a light vector-boson mediator for the dark matter particle to communicate with the Standard Model particles. We find that the braneworld cosmological effect can dramatically alters the resultant dark matter relic density from the one in the standard Big Bang cosmology. As an application, we consider a right-handed neutrino dark matter in the minimal B – L extended Standard Model with a light B – L gauge boson (Z') as a mediator. We find an impact of the braneworld cosmological effect on the search for the long-lived Z' boson at the planned/proposed Lifetime Frontier experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest.We conduct the evaluations on two climate use cases – one targeting small-scale, node features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.

Gong, Qian↗