Validation of Space Weather Data using LISA Pathfinder historical sensor records [Slides]
LANL missions can be affected by space weather.
79 ASTRONOMY AND ASTROPHYSICS↗
SEARCH · Engineering Papers
Results for “LISA data”
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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Prospects for fundamental physics with LISA
In this paper, which is of programmatic rather than quantitative nature, we aim to further delineate and sharpen the future potential of the LISA mission in the area of fundamental physics. Given the very broad range of topics that might be relevant to LISA,we present here a sample of what we view as particularly promising fundamental physics directions. We organize these directions through a “science-first” approach that allows us to classify how LISA data can inform theoretical physics in a variety of areas. For each of these theoretical physics classes, we identify the sources that are currently expected to provide the principal contribution to our knowledge, and the areas that need further development. Overall, the classification presented here should not be thought of as cast in stone, but rather as a fluid framework that is amenable to change with the flow of new insights in theoretical physics.
79 ASTRONOMY AND ASTROPHYSICS↗
Reconstructing the dark sector interaction with LISA
We perform a forecast analysis of the ability of the LISA space-based interferometer to reconstruct the dark sector interaction using gravitational wave standard sirens at high redshift. We employ Gaussian process methods to reconstruct the distance-redshift relation in a model independent way. We adopt simulated catalogues of standard sirens given by merging massive black hole binaries visible by LISA, with an electromagnetic counterpart detectable by future telescopes. The catalogues are based on three different astrophysical scenarios for the evolution of massive black hole mergers based on the semi-analytic model of E. Barausse, Mon. Not. Roy. Astron. Soc. 423 (2012) 2533. We first use these standard siren datasets to assess the potential of LISA in reconstructing a possible interaction between vacuum dark energy and dark matter. Then we combine the LISA cosmological data with supernovae data simulated for the Dark Energy Survey. We consider two scenarios distinguished by the time duration of the LISA mission: 5 and 10 years. Using only LISA standard siren data, the dark sector interaction can be well reconstructed from redshift z ∼1 to z ∼3 (for a 5 years mission) and z ∼1 up to z ∼5 (for a 10 years mission), though the reconstruction is inefficient at lower redshift. When combined with the DES datasets, the interaction is well reconstructed in the whole redshift region from 0 z ∼ to z ∼3 (5 yr) and z ∼0 to z ∼5 (10 yr), respectively. Massive black hole binary standard sirens can thus be used to constrain the dark sector interaction at redshift ranges not reachable by usual supernovae datasets which probe only the z ∼< 1.5 range. Gravitational wave standard sirens will not only constitute a complementary and alternative way, with respect to familiar electromagnetic observations, to probe the cosmic expansion, but will also provide new tests to constrain possible deviations from the standard ΛCDM dynamics, especially at high redshift.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Cascades/Aleutian Play Fairway Analysis: Data and Map Files
Contains Excel data files used to quantifiably rank the geothermal potential of each of the young volcanic centers of the Cascade and Aleutian Arcs using world power production volcanic centers as benchmarks. Also contains shapefiles used in play fairway analysis with power plant, volcano, geochemistry and structural data.
15 GEOTHERMAL ENERGY↗
Adaptation of fan motor and VFD efficiency correlations using Bayesian inference
Energy performance contracts (EPC) are types of agreements in which a service provider guarantees that customers’ buildings will achieve a specified energy performance (i.e., minimum energy savings) to reduce the risk of their investment in energy efficiency improvements. EPC requires prediction of future energy consumption of the building, at the design stage, before construction or major retrofit. To this end, building energy simulations taking into account all the major energy-using components are performed. In particular, fans can contribute significantly to the total building consumption. The overall efficiency of fans is the combination of three factors: mechanical, motor, and variable frequency drive (VFD). Manufacturers usually provide fan mechanical efficiency curves for a broad operating range. In contrast, motor and VFD efficiencies are generally given at rating conditions only. To represent part-load conditions, correlations are typically used to estimate motor and VFD efficiency variations, to evaluate the overall electricity consumption. The first aim of this study is to evaluate existing correlations for motor and VFD efficiency as a function of load and speed, by comparison with manufacturer data, for a vendor that has shared its detailed test data. While VFD efficiency correlations from the literature provide reasonable accuracy against real data, motor correlations under predict actual motor efficiency at low loads. Finally, the second aim of the paper is to improve such correlations using Bayesian inference to fit the available data.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Semisupervised Learning for Seismic Monitoring Applications
The impressive performance that deep neural networks demonstrate on a range of seismic monitoring tasks depends largely on the availability of event catalogs that have been manually curated over many years or decades. However, the quality, duration, and availability of seismic event catalogs vary significantly across the range of monitoring operations, regions, and objectives. Semisupervised learning (SSL) enables learning from both labeled and unlabeled data and provides a framework to leverage the abundance of unreviewed seismic data for training deep neural networks on a variety of target tasks. We apply two SSL algorithms (mean-teacher and virtual adversarial training) as well as a novel hybrid technique (exponential average adversarial training) to seismic event classification to examine how unlabeled data with SSL can enhance model performance. In general, we find that SSL can perform as well as supervised learning with fewer labels. We also observe in some scenarios that almost half of the benefits of SSL are the result of the meaningful regularization enforced through SSL techniques and may not be attributable to unlabeled data directly. Lastly, the benefits from unlabeled data scale with the difficulty of the predictive task when we evaluate the use of unlabeled data to characterize sources in new geographic regions. Finally, in geographic areas where supervised model performance is low, SSL significantly increases the accuracy of source-type classification using unlabeled data.
58 GEOSCIENCES↗
Cost of Saving Electricity Through Efficiency Programs Funded by Customers of Publicly Owned Utilities: 2012–2017
This report finds that energy efficiency programs for customers of publicly owned utilities saved electricity at an average cost of 2.4 cents per kilowatt-hour (kWh) from 2012 to 2017. Utilities use such cost performance metrics to assess effectiveness of efficiency program portfolios, determine what programs to offer customers, and, more broadly, ensure electricity system reliability at the most affordable cost as part of electric utility resource adequacy planning and resource procurement processes. The study analyzed efficiency program data reported by 111 program administrators for 219 publicly owned utilities in 14 states — about 90 percent of the municipal utilities and public utility districts that report the data to the Energy Information Administration (EIA). The data represent 88 percent of all spending and 75 percent of all savings that publicly owned utilities reported to EIA in those years. Berkeley Lab used data from several sources, including data provided directly by American Public Power Association members, publicly available annual reports and regional data collections.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Laser-Induced Spectrochemical Assay for Uranium Enrichment (LISA-UE)
Uranium hexafluoride (UF6) is the uranium compound typically involved in uranium enrichment process. As the first line of defense against nuclear proliferation, accurate determinations of the uranium enrichment ratio in UF6 are critical for materials verification, accounting and safeguards. Shipping gaseous UF6 samples off-site for analysis with mass spectrometry is cumbersome and costly, and results are not available for some time (months). In-field UF6 enrichment assay has the potential to substantially reduce the time, logistics and expense of sample handling. At present, COMPUCEA is the only accepted method for UF6 enrichment assay in the field. Laser-Induced Spectrochemical Assay for Uranium Enrichment (LISA-UE) is an all-optical (based on laser induced plasma emission) analytical technique intended for fieldable, accurate, precise and rapid UF6 enrichment assay. In its operation, laser induced plasma is created directly in the gaseous UF6 sample. Because different U isotopes emit at slightly different wavelengths, the isotopic information of the UF6 sample is inherently encoded in the atomic emission from the plasma. Isotopic emissions from 235U and 238U are measured simultaneously, which eliminate correlated noise from the laser induced plasma. Isotopic information of the UF6 sample can be extracted from the acquired spectrum with theoretical multi-variable non-linear spectral fitting. To date, advances made by the LISA-UE research team include optimization of the spectral window for direct gaseous UF6 enrichment assay with laser induced plasma, development of data reduction algorithms, and demonstrations of the LISA-UE technique with gaseous UF6 samples. In this presentation, the technical aspect of LISA-UE will be overviewed, the data reduction algorithm will be described, and performance of the technique will be discussed.
Chan, George↗
Monitoring DUNE Data Streaming Efficiency
Explore the source record for details and available documents.
Paton, Lisa↗
SANS of AlxCoCrFeNi Series of High Entropy Alloy
SANS data for study of AlxCoCrFeNi high entopy alloys. We will also include the magnetization data.
36 MATERIALS SCIENCE↗
Comparing Multipollutant Emissions-Based Mobile Source Indicators to Other Single Pollutant and Multipollutant Indicators in Different Urban Areas
A variety of single pollutant and multipollutant metrics can be used to represent exposure to traffic pollutant mixtures and evaluate their health effects. Integrated mobile source indicators (IMSIs) that combine air quality concentration and emissions data have recently been developed and evaluated using data from Atlanta, Georgia. IMSIs were found to track trends in traffic-related pollutants and have similar or stronger associations with health outcomes. In the current work, we apply IMSIs for gasoline, diesel and total (gasoline + diesel) vehicles to two other cities (Denver, Colorado and Houston, Texas) with different emissions profiles as well as to a different dataset from Atlanta. We compare spatial and temporal variability of IMSIs to single-pollutant indicators (carbon monoxide (CO), nitrogen oxides (NOx) and elemental carbon (EC)) and multipollutant source apportionment factors produced by Positive Matrix Factorization (PMF). Across cities, PMF-derived and IMSI gasoline metrics were most strongly correlated with CO (r = 0.31–0.98), while multipollutant diesel metrics were most strongly correlated with EC (r = 0.80–0.98). NOx correlations with PMF factors varied across cities (r = 0.29–0.67), while correlations with IMSIs were relatively consistent (r = 0.61–0.94). In general, singlepollutant metrics were more correlated with IMSIs (r = 0.58–0.98) than with PMF-derived factors (r = 0.07–0.99). A spatial analysis indicated that IMSIs were more strongly correlated (r > 0.7) between two sites in each city than single pollutant and PMF factors. These findings provide confidence that IMSIs provide a transferable, simple approach to estimate mobile source air pollution in cities with differing topography and source profiles using readily available data.
mobile sources↗
Spurious solar-wind effects on acceleration noise in LISA Pathfinder
Spurious solar-wind effects are a potential noise source in future Laser Interferometer Space Antenna (LISA) measurements. One noise coupling mechanism is constrained by estimating solar-wind effects on acceleration noise in LISA Pathfinder (LPF). While LISA is designed for drag-free differential measurement, predicting the realistic impact both bounds the operational environment and assesses whether LISA could provide serendipitous space-weather observations. Data from NASA's Advanced Composition Explorer (ACE), situated at the L1 Lagrange point, serves as a reliable source of solar-wind data. The data sets are compared over the 114 d time period from 1 March 2016 to 23 June 2016. This period gives the longest readily-available open data set, without interference from other commissioning activities. To evaluate space weather effects, the data from both satellites are formatted, gap-filled/interpolated, and fast-Fourier transformed for amplitude spectral density and coherence comparisons. Solar wind effects are not seen in a coherence plot between LPF and ACE; modest coherence in the planned LISA observational frequency band can be attributed to chance. This result indicates that measurable correlation due to solar-wind acceleration noise over 3 month timescales will be a negligible noise source. LISA is unlikely to inform solar wind measurements routinely. Another source of noise from the Sun, solar radiation pressure, is estimated to impart greater acceleration noise, but has yet to be analyzed.
79 ASTRONOMY AND ASTROPHYSICS↗
Testing modified gravity at cosmological distances with LISA standard sirens
Modifications of General Relativity leave their imprint both on the cosmic expansion history through a non-trivial dark energy equation of state, and on the evolution of cosmological perturbations in the scalar and in the tensor sectors. Specifically, the modification in the tensor sector gives rise to a notion of gravitational-wave (GW) luminosity distance, different from the standard electromagnetic luminosity distance, that can be studied with standard sirens at GW detectors such as LISA or third-generation ground based experiments. Here, we discuss the predictions for modified GW propagation from some of the best studied theories of modified gravity, such as Horndeski or the more general degenerate higher order scalar-tensor (DHOST) theories, non-local infrared modifications of gravity, bigravity theories and the corresponding phenomenon of GW oscillation, as well as theories with extra or varying dimensions. We show that modified GW propagation is a completely generic phenomenon in modified gravity. We then use a simple parametrization of the effect in terms of two parameters (Ξ 0 , n ), that is shown to fit well the results from a large class of models, to study the prospects of observing modified GW propagation using supermassive black hole binaries as standard sirens with LISA. We build mock source catalogs and perform detailed Markov Chain Monte Carlo studies of the likelihood obtained from LISA standard sirens alone, as well as by combining them with CMB, BAO and SNe data to reduce the degeneracies between cosmological parameters. We find that the combination of LISA with the other cosmological datasets allows one to measure the parameter Ξ 0 that characterizes modified GW propagation to the percent level accuracy, sufficient to test several modified gravity theories. LISA standard sirens can also improve constraints on GW oscillations induced by extra field content by about three orders of magnitude relative to the current capability of ground detectors. We also update the forecasts on the accuracy on H 0 and on the dark-energy equation of state using more recent estimates for the LISA sensitivity.
79 ASTRONOMY AND ASTROPHYSICS↗
Materials Data Management at LANL and across the Nuclear Security Enterprise [Slides]
Abstract not provided.
36 MATERIALS SCIENCE↗
Gravitational waves from supercooled phase transitions in conformal Majoron models of neutrino mass
We study supercooled first-order phase transitions above the QCD scale in a wide class of conformal Majoron-like U(1)′ models that explain the totality of active neutrino oscillation data and produce a detectable stochastic gravitational wave background (SGWB) at LIGO, LISA and ET. We place constraints on the U(1)′ breaking scale and gauge coupling using current LIGO-Virgo-Kagra data. We find that strong supercooling can be ruled out in large regions of parameter space if a SGWB is not detected by these experiments. A null signal at LIGO and ET will disfavor a type-I seesaw scale above 10 14 GeV, while a positive signal is a signature of heavy right-handed neutrinos. On the other hand, LISA will be sensitive to seesaw scales as low as a TeV, and could detect a SGWB even if the right-handed neutrinos are decoupled.
early universe particle physics↗
Superhard Materials: Advances in the Search and Synthesis of New Materials
Materials with superior hardness can be categorized as ultrahard (Vickers hardness, H v ≥ 80 GPa) and superhard (H v ≥ 40 GPa). These materials are commonly used as cutting tools and abrasives in the machining and manufacturing industries. With its extreme hardness, diamond is the best known and most used ultrahard material for industrial applications. However, it is ineffective at cutting and drilling ferrous alloys due to diamond's high reactivity with iron and poor thermal stability in air. Additionally, the synthesis of diamond requires both high pressure (HP) and high temperature, making it an expensive process. These limitations have driven the search for alternative superhard materials that are capable of cutting steels and other materials at lower costs. This article reviews the concept of hardness and summarizes advancements in the synthesis and mechanical properties of hard materials. It begins with a review of methods to measure hardness, adding HP diffraction methods to more conventional hardness measurements. It then considers new ultrahard materials that exist within the B–C–N ternary system, with hardness approaching diamond but improved chemical stability. Finally, it surveys superhard nitrides, oxides, and borides as potential alternative materials, focusing on transition metal boride systems where the synthesis can be readily achieved at ambient pressure and scaled for industrial applications. We hope that this article serves as an overview of hard materials and guide for the comparison of data reported in the literature.
36 MATERIALS SCIENCE↗
pnnl/archive-sprinter
The Archive Sprinter tool is designed to efficiently process synchrophasor measurements from electric power grids and export data signatures that summarize the grid's behavior. Parallel processing will allow data to be processed quickly to enable practical analyses of archives spanning years. The grid's behavior will be summarized using a wide-array of signatures calculated from the input data.
Follum, Jim↗
EMSL-Computing/nmRanalysis
R package that serves as wrapper for rDolphin, an open-source R package that performs semiautomated quantification of metabolites represented within Nuclear Magnetic Resonance (NMR) spectral data
Winans, Natalie↗