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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Parametric studies of stream instability-induced higher harmonics in plasma ionization breakdown near an emissive dielectric surface

Here, in this work, we comprehensively investigate the generation of higher harmonic (HH) electric fields normal to the applied rf electric field in multipactor-coexisting plasma breakdown by fully kinetic particle-in-cell (PIC) simulations and a theoretical model. Firstly, a base case at driving frequency 1 GHz, transverse rf electric field amplitude 3 MV m –1 , and background gas pressure 0.2 Torr, is studied in detail. The enhanced harmonic frequency observed is around ten times the fundamental rf frequency, significantly lower than the Langmuir frequency. A theoretical model reveals that the fundamental mechanism of HHs generation is stream–plasma instability, which originates from stream-like secondary electron emission interacting with plasma. The resulting HH frequency and the growth rate of its oscillating amplitude from the theoretical model, agree well with the PIC simulations. With increasing pressure, the HH oscillations are found to be significantly reduced. This is because at higher pressure the gas ionization rate is higher, which causes a more rapidly increasing plasma density, leaving less time for the growth of instability. Furthermore, the parameter space in terms of background gas pressure and rf field amplitude within which the HHs appear is revealed. Finally, the effect of the driving rf frequency on HHs is also investigated, and it is found that the instability-induced oscillating HHs field remains when the driving frequency is increased to 2 GHz, however, it is highly reduced at higher driving frequency of 5 GHz, as oscillations at the fundamental frequency start playing a more important role.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Cosmological Perturbation Theory for streams of relativistic particles

Motion equations describing streams of relativistic particles and their properties are explored in detail in the framework of Cosmological Perturbation Theory. Those equations, derived in any metric both in the linear and nonlinear regimes, express the matter and momentum conservation. In this context we extend the setup of adiabatic initial conditions—that was initially performed in the conformal Newtonian gauge—to the synchronous gauge. The subhorizon limit of the nonlinear motion equations written in a generic perturbed Friedmann-Lemaître metric is then derived and analyzed. We show in particular that the momentum field P{sub i}(x) is always potential in the linear regime and remains so at subhorizon scales in the nonlinear regime. Finally the equivalence principle is exploited to highlight invariance properties satisfied by such a system of equations, extending that known for streams of non-relativistic particles, namely the extended Galilean invariance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗
DOE OSTI2025

Efficient Streaming Dynamic Mode Decomposition

We propose a reformulation of the streaming dynamic mode decomposition method that requires maintaining a single orthonormal basis, thereby reducing computational redundancy. The proposed efficient streaming dynamic mode decomposition method results in a constant-factor reduction in computational complexity and memory storage requirements. Numerical experiments on representative canonical dynamical systems show that the enhanced computational efficiency does not compromise the accuracy of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

System Modeling and Simulation of In-Stream Hydrokinetic Turbines for Power Management and Control

Electricity generation from moving currents without using dams (i.e., in-stream hydrokinetic electricity) has the potential to introduce multiple GW of renewable power to U.S. grids. Here this study evaluates a control system designed to regulate the generator rotor rate (rpm) to improve power production from in-stream hydrokinetic turbines. The control algorithm is evaluated using numerical models of both a rigidly mounted tidal turbine (TT) and a moored ocean current turbine (OCT) coupled to an induction electric machine model. The moored simulation utilizes an innovative approach for coupling a multiple degrees-of-freedom (DOF) nonlinear hydrodynamic/mechanical turbine model with a nonlinear electromechanical generator model. Based on the turbine torque-speed characteristic, as well as the asynchronous machine features, a proportional–integral (PI) controller is used to generate a correction term for the frequency of the three-phase sinusoidal voltages that are supplied to the asynchronous generator. The speed control of the induction generator through the supply frequency is accomplished by a simplified voltage source inverter (VSI). The simplified VSI consists of control voltage sources (CVSs), while the comparison with a real VSI using diodes and transistors, which are controlled by pulse width modulation (PWM) technique, is also presented. Simulations are used to evaluate the developed algorithms showing that rpm fluctuations are around 0.02 for a tidal turbine operating in a wave field with a 6 m significant wave height and around 0.005 for a moored ocean current turbine operating in a wave field with a 2 m significant wave height.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Climate mediates continental scale patterns of stream microbial functional diversity

Understanding the large-scale patterns of microbial functional diversity is essential for anticipating climate change impacts on ecosystems worldwide. However, studies of functional biogeography remain scarce for microorganisms, especially in freshwater ecosystems. Here we study 15,289 functional genes of stream biofilm microbes along three elevational gradients in Norway, Spain and China. We find that alpha diversity declines towards high elevations and assemblage composition shows increasing turnover with greater elevational distances. These elevational patterns are highly consistent across mountains, kingdoms and functional categories and exhibit the strongest trends in China due to its largest environmental gradients. Across mountains, functional gene assemblages differ in alpha diversity and composition between the mountains in Europe and Asia. Climate, such as mean temperature of the warmest quarter or mean precipitation of the coldest quarter, is the best predictor of alpha diversity and assemblage composition at both mountain and continental scales, with local non-climatic predictors gaining more importance at mountain scale. Under future climate, we project substantial variations in alpha diversity and assemblage composition across the Eurasian river network, primarily occurring in northern and central regions, respectively. We conclude that climate controls microbial functional gene diversity in streams at large spatial scales; therefore, the underlying ecosystem processes are highly sensitive to climate variations, especially at high latitudes. This biogeographical framework for microbial functional diversity serves as a baseline to anticipate ecosystem responses and biogeochemical feedback to ongoing climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Levoglucosan data from five coastal streams impacted by the 2020 CZU Lightning Complex Fires, California, United States

This dataset includes levoglucosan data for five coastal California (United States) streams impacted by the 2020 CZU Lightning Complex Fires which burned from August 16th through September 22nd. Levoglucosan is a highly soluble and biolabile fraction of pyrogenic carbon. The five watersheds (San Lorenzo River, Pescadero Creek, Majors Creek, Laguna Creek, and Scott Creek) were impacted by the fires with watersheds experiencing a range of burn severity and extents. Grab samples were collected from each stream between October 2020 and May 2021, targeting both baseflow and event flow hydrologic conditions. Additional biogeochemistry data (i.e., organic and black carbon concentrations) can be found in a separate data package (https://doi.org/10.4211/hs.421c0226bb38460c8393d67fe0c4f802). This data package consists of one main data folder that contains (1) readme; (2) file-level metadata; (3) data dictionary; (4) field metadata with international generic sample numbers (IGSN); (5) methods codes; and (6) levoglucosan data. All files are .csv or .pdf.

2020 CZU Lightning Complex Fires↗
DOE OSTI2022

Technology Overview: Side Stream Filtration for Cooling Towers

The Federal Energy Management Program (FEMP) identified cooling tower side stream filtration as a technology that offers key benefits to the federal sector, including the potential to reduce energy and water use, decrease operating costs, and extend cooling equipment life. This overview provides agencies with key information to deploy side stream filtration systems that may otherwise be overlooked.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

SPRUCE S1 Bog Porewater, Groundwater, and Stream Chemistry Data: 2011-2013

This data set reports the chemistry of S1 bog porewater, outlet stream water, and groundwater from upland wells from 2011 through 2013. These data provide information for studies of the biogeochemical status of the bog and surrounding groundwater aquifer. Porewater samples were collected from one nest of 6 piezometers installed in a hollow in the south end of the S1 bog to characterize solute chemistry depth profiles. Peat porewater was collected from piezometers that opened at 0, 0.3, 0.5, 1, 2, and 3 m depths below hollow surfaces. Samples were collected weekly (2011) or monthly (2012 & 2013) when the samplers were not frozen (typically June – November). Stream water was sampled weekly (2011-2013) from the outlet of the S1 bog (located on the southern edge of the bog). Four groundwater wells located in the uplands of the S1 watershed were sampled monthly in 2013. Bog water level data are also reported for the S1 bog. Water samples were analyzed for pH, specific conductivity, nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), cation concentrations (calcium, potassium, magnesium, sodium, aluminum, iron, manganese, silicon, strontium), anion concentrations (chloride, sulfate), and total organic carbon concentrations. The experimental work is to be conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

UNBOUND DEBRIS STREAMS AND REMNANTS RESULTING FROM THE TIDAL DISRUPTIONS OF STARS BY SUPERMASSIVE BLACK HOLES

The kinetic energy of a star in orbit about a supermassive black hole is a significant fraction of its rest mass energy when its periapse is comparable to its tidal radius. Upon its destruction, a fraction of this energy is extracted and injected into the stellar debris, half of which becomes unbound from the black hole, with the fastest material moving at ∼0.03c. In this paper, we present a formalism for determining the fate of these unbound debris streams (UDSs) as they depart from the black hole and interact with the surrounding gas. As the density and velocity varies along the length of a UDS, we find that hydrodynamical drag quickly shapes UDSs into loop-like structures, with the densest portions of the streams leading portions of lower density. As UDSs travel outwards, their drag against the ISM increases quadratically with distance, which causes UDSs to deposit their momentum and energy into the ambient medium before the surrounding shocked ISM has a chance to cool. This sudden injection of ∼10{sup 50} erg into the ambient medium generates a Sedov-like unbound debris remnant (UDR) that mimics supernova remnants (SNRs) in energetics and appearance, accelerates particles which will produce cosmic rays and synchrotron emission, and provides momentum feedback into the molecular clouds surrounding a black hole. We estimate that a few of these UDRs might be present within a couple degrees of the Galactic Center masquerading as SNRs, and that the UDR scenario is a plausible explanation for Sgr A east.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

GALACTIC COSMIC-RAY INTENSITY MODULATION BY COROTATING INTERACTION REGION STREAM INTERFACES AT 1 au

We present a new model that couples galactic cosmic-ray (GCR) propagation with magnetic turbulence transport and the MHD background evolution in the heliosphere. The model is applied to the problem of the formation of corotating interaction regions (CIRs) during the last solar minimum from the period between 2007 and 2009. The numerical model simultaneously calculates the large-scale supersonic solar wind properties and its small-scale turbulent content from 0.3 au to the termination shock. Cosmic rays are then transported through the background, and thus computed, with diffusion coefficients derived from the solar wind turbulent properties, using a stochastic Parker approach. Our results demonstrate that GCR variations depend on the ratio of diffusion coefficients in the fast and slow solar winds. Stream interfaces inside the CIRs always lead to depressions of the GCR intensity. On the other hand, heliospheric current sheet (HCS) crossings do not appreciably affect GCR intensities in the model, which is consistent with the two observations under quiet solar wind conditions. Therefore, variations in diffusion coefficients associated with CIR stream interfaces are more important for GCR propagation than the drift effects of the HCS during a negative solar minimum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Estimate of the Mass and Radial Profile of the Orphan–Chenab Stream's Dwarf-galaxy Progenitor Using MilkyWay@home

We fit the mass and radial profile of the Orphan–Chenab Stream's (OCS) dwarf-galaxy progenitor by using turnoff stars in the Sloan Digital Sky Survey and the Dark Energy Camera to constrain N-body simulations of the OCS progenitor falling into the Milky Way on the 1.5 PetaFLOPS MilkyWay@home distributed supercomputer. We infer the internal structure of the OCS's progenitor under the assumption that it was a spherically symmetric dwarf galaxy composed of a stellar system embedded in an extended dark matter halo. We optimize the evolution time, the baryonic and dark matter scale radii, and the baryonic and dark matter masses of the progenitor using a differential evolution algorithm. The likelihood score for each set of parameters is determined by comparing the simulated tidal stream to the angular distribution of OCS stars observed in the sky. We fit the total mass of the OCS's progenitor to (2.0 ± 0.3) × 10 7 M ⊙ with a mass-to-light ratio of γ = 73.5 ± 10.6 and (1.1 ± 0.2) × 10 6 M ⊙ within 300 pc of its center. Within the progenitor's half-light radius, we estimate a total mass of (4.0 ± 1.0) × 10 5 M ⊙ . We also fit the current sky position of the progenitor's remnant to be (α, δ) = ((166.0 ± 0.9)°, (–11.1 ± 2.5)°) and show that it is gravitationally unbound at the present time. The measured progenitor mass is on the low end of previous measurements and, if confirmed, lowers the mass range of ultrafaint dwarf galaxies. Our optimization assumes a fixed Milky Way potential, OCS orbit, and radial profile for the progenitor, ignoring the impact of the Large Magellanic Cloud.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The GD-1 Stellar Stream Perturber as a Core-collapsed Self-interacting Dark Matter Halo

The GD-1 stellar stream exhibits spur and gap structures that may result from a close encounter with a dense substructure. When interpreted as a dark matter subhalo, the perturber is denser than predicted in the standard cold dark matter (CDM) model. In self-interacting dark matter (SIDM), however, a halo could evolve into a phase of gravothermal collapse, resulting in a higher central density than its CDM counterpart. We conduct high-resolution controlled N-body simulations to show that a collapsed SIDM halo could account for the GD-1 perturber's high density. We model a progenitor halo with a mass of 3 × 10 8 M ⊙ , motivated by a cosmological simulation of a Milky Way analog, and evolve it in the Milky Way's tidal field. For a cross section per mass of σ/m ≈ 30–100 cm 2 g −1 at ${V}_{{\rm{\max }}}\unicode{x0007E}10\,{\rm{km}}\,{{\rm{s}}}^{-1}$, the enclosed mass of the SIDM halo within the inner 10 pc can be increased by more than 1 order of magnitude compared to its CDM counterpart, leading to a good agreement with the properties of the GD-1 perturber. Our findings indicate that stellar streams provide a novel probe into the self-interacting nature of dark matter.

dark matter↗
DOE OSTI2024

Kernelized approaches to streaming compression of scientific data

In this paper three algorithms are developed for the streaming compression of scientific data. The algorithms presented are reliant on the theory of vector-valued reproducing kernel Hilbert spaces and operator valued kernel. Further, the scientific data is modeled as a snapshot of time dependent vector field F(x, t) over a manifold M and the recovery of the data is framed as a learning problem. These processes are then appropriately modified and ana lyzed for the streaming scenario in which data is generated without the ability to revisit past entries.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1962

Pressure Distribution Induced on a Flat Plate at a Free-Stream Mach Number of 1.39 by Rockets Exhausting Upstream and Downstream

An experimental investigation was made of the pressures induced on a flat plate at a free-stream Mach number of 1.39 by a supersonic rocket jet exhausting upstream and downstream. Measurements of the pressure distribution on a flat plate were made at zero angle of attack for 11 different locations of the jet exhaust nozzle beneath the wing. Measurements were made at ratios of rocket-exit total pressure to freestream static pressure from 6 to 60 and at a Reynolds number per foot of approximately 10 x 10 6 . The rocket when exhausted upstream produced a strong shock that moved further upstream with increasing rocket-exit total-pressure ratio. Positive incremental normal-force coefficients were obtained at all test positions. Data at 11 test positions are tabulated for rocket-on and rocket-off pressure coefficients as well as for incremental pressure coefficients for the 48 orifices of the flat plate for the range of ratio of rocket-exit total pressure to free-stream static pressure of the investigation. Changing the location of the model with respect to the plate had a negligible effect when the rocket was varied in the chordwise direction, but the pressure coefficients were reduced as the rocket was lowered away from the flat-plate wing.

Supersonic jet↗