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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Improve Learning from Crowds via Generative Augmentation

Crowdsourcing provides an efficient label collection schema for supervised machine learning. However, to control annotation cost, each instance in the crowdsourced data is typically annotated by a small number of annotators. This creates a sparsity issue and limits the quality of machine learning models trained on such data. In this paper, we study how to handle sparsity in crowdsourced data using data augmentation. Specifically, we propose to directly learn a classifier by augmenting the raw sparse annotations. We implement two principles of high-quality augmentation using Generative Adversarial Networks: 1) the generated annotations should follow the distribution of authentic ones, which is measured by a discriminator; 2) the generated annotations should have high mutual information with the ground-truth labels, which is measured by an auxiliary network. Extensive experiments and comparisons against an array of state-of-the-art learning from crowds methods on three real-world datasets proved the effectiveness of our data augmentation framework. It shows the potential of our algorithm for low-budget crowdsourcing in general.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Magnetism of single crystalline breathing pyrochlore spinel AgInCr 4 ⁢S 8

Single crystals of Ag⁢In⁢Cr 4⁢ S 8 are grown by chemical vapor transport and crystallographic ordering of Ag/In that results in a breathing pyrochlore motif of Cr 3+ is verified by x-ray and neutron diffraction. Long-range antiferromagnetic order is observed below a Néel temperature of 𝑇 N ≈ 9.6 K. The magnetic properties are characterized using ac and dc magnetization, specific heat capacity, and single crystal neutron diffraction measurements. The specific heat data are characterized by a small lambda anomaly near 9.5 K and the estimated magnetic entropy reaches ≈ $\frac{1}{3}$ of the expected value by 3⁢𝑇 N , suggesting significant short-range order in the paramagnetic phase. Single crystal neutron diffraction evidences an incommensurate spin structure with propagation vector 𝒌 = (0,0,𝛿) and 𝛿 = 0.343 at 5 K. The minimal model that accounts for the data consists of ferromagnetic layers of Cr atoms, with magnetic moments lying in the plane of the layers and modulating in the perpendicular direction to form a helical structure propagating along 𝒌. Furthermore, this study represents a rare investigation of single crystals within the family of breathing pyrochlore materials.

Frustrated magnetism↗
DOE OSTI2024

MONTE CARLO CROSS SECTION LOOKUP KERNEL FOR THE CEREBRAS WSE-2 IN CSL

This is a small kernel that was used to collect data for an upcoming paper. We would like to have the code be open source so that the reviewers (and then readers) of the paper can see the whole code, and can reproduce/verify our results. This is not a fully featured application, it cannot produce any useful simulation results, it just executes a small abstracted kernel using synthetic data. The purpose of the kernel is to understand the basic performance characteristics of an HPC kernel on novel AI accelerator architectures. The main kernel is written in the CSL coding language for use with the Cerebras WSE-2 AI accelerator. The kernel represented is the Monte Carlo cross section lookup kernel, which is a small kernel used by the Monte Carlo neutral particle transport algorithm. There is also a baseline kernel written in CUDA that we will include in the repository to form a basis for comparing the WSE-2 to GPU.

Tramm, John↗
DOE OSTI2021

Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

Beyond ΛCDM, physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analysed assuming ΛCDM. Here, we present an application of internal consistency tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of ΛCDM. We find that the DES Y1 data have an acceptable goodness of fit to ΛCDM, with a probability of finding a worse fit by random chance of p = 0.046. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5 per cent) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the p-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Local order of orthorhombic weberite-type Y 3 TaO 7 as determined by neutron total scattering and density functional theory calculations

Weberite-type oxides are a family of oxides with A 3 BO 7 stoichiometry that can adopt different space groups depending on chemical composition. There is a discrepancy in previous studies as to whether Y 3 TaO 7 is the orthorhombic C222 1 or the Ccmm space group. Here, we describe the short- and long-range structural properties of weberite-type Y 3 TaO 7 using neutron total scattering data, which has a high sensitivity to the oxygen sublattice. Simultaneous analysis of both short- and long-range structural data via conventional Rietveld and small box modelling demonstrates that Y 3 TaO 7 is best modeled as C222 1 . While the Ccmm describes equally well the long-range structure, pair distribution function analysis revealed that the local atomic configuration can be best modelled as C222 1 . This is corroborated by first-principles calculations that confirm the energetic preference of the C222 1 over Ccmm. Further, neutron total scattering data are reported for the first time for the Y 3 TaO 7 weberite-type ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage

The goal of this project is to develop advanced methods for day-ahead net-load forecasting, by leveraging the state-of-the-art machine learning techniques. The developed models produce both point and probabilistic forecasts for a variety of use cases, and are versatile to work with different types of data sets. The innovation lies in the novel design of the architectures, leveraging the most recent advances in machine learning that have not been explored in power systems, accompanied by techniques in the broader artificial intelligence fields such as fuzzy systems. This project has achieved the following accomplishments: (1) preprocessing of over 10 data sets covering varying geographical regions, time horizons, and system levels, which form a robust foundation for training and evaluating forecasting models across a wide range of realistic grid scenarios; (2) development of an interactive web app that enables exploratory analysis of load and generation data, and supports better understanding of data trends, anomalies, and correlations, facilitating model development and stakeholder engagement; (3) implementation of over 10 benchmark models for point and probabilistic forecasting, which include a mix of conventional machine learning methods and state-of-the-art deep learning approaches, providing a comprehensive baseline for performance comparison and validation of the proposed models; (4) development of a fuzzy system based gradient boosting model, tailored for small (less than 3 years) data sets, which achieves a mean absolute percentage error (MAPE) of 4% for point forecasting and a 20% improvement in average pinball loss for probabilistic forecasting; (5) development of a Transformer (a state-of-the-art deep learning architecture) based neural network model, tailored for large (3 years or more) data sets, which achieves a MAPE of 2% for point forecasting and a 20% improvement in average pinball loss for probabilistic forecasting; (6) development of a methodology for quantifying DR potential, and extensions of the previous models for multi-target forecasting of net load and DR potential, which achieve a MAPE of 10% for DR potential.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Columnar data analysis with ATLAS analysis formats

Future analysis of ATLAS data will involve new small-sized analysis formats to cope with the increased storage needs. The smallest of these, named DAOD_PHYSLITE, has calibrations already applied to allow fast downstream analysis and avoid the need for further analysis-specific intermediate formats. This allows for application of the "columnar analysis" paradigm where operations are applied on a per-array instead of a per-event basis. We will present methods to read the data into memory, using Uproot, and also discuss I/O aspects of columnar data and alternatives to the ROOT data format. Furthermore, we will show a representation of the event data model using the Awkward Array package and present proof of concept for a simple analysis application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High-Mileage Courier Fleet Vehicle On-road Logger Data

This dataset describes the performance and fuel efficiency of AVTA test vehicles operating in commercial courier fleets the Phoenix, AZ metro area between 2010 and 2016. Aftermarket data loggers were installed in two to four vehicles of each of 30+ distinct year/make/models (see reference ["INL Advanced Vehicle Testing Activity: On-road Logger and Laboratory Battery Pack Testing Vehicle List"](https://avt.inl.gov/sites/default/files/pdf/reports/DatasetVehicleList.pdf) for full list of vehicles). Loggers recorded vehicle operation as they were driven up to 160,000 miles in up to three years of fleet testing. Parameters were logged at 1-second intervals, including - vehicle speed, - engine and/or electric motor speed, - fuel and/or electricity consumption, and - ambient temperature. This dataset includes both raw second-by-second data and trip-level metrics. (This dataset will be shared by API; a small sample of the vehicle and logger data has been extracted and is available for download while the API is being developed.)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

BAWLD-CH 4 : a comprehensive dataset of methane fluxes from boreal and arctic ecosystems

Methane (CH 4 ) emissions from the boreal and arctic region are globally significant and highly sensitive to climate change. There is currently a wide range in estimates of high-latitude annual CH 4 fluxes, where estimates based on land cover inventories and empirical CH 4 flux data or process models (bottom-up approaches) generally are greater than atmospheric inversions (top-down approaches). A limitation of bottom-up approaches has been the lack of harmonization between inventories of site-level CH 4 flux data and the land cover classes present in high-latitude spatial datasets. Here we present a comprehensive dataset of small-scale, surface CH 4 flux data from 540 terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakes and ponds), compiled from 189 studies. The Boreal–Arctic Wetland and Lake Methane Dataset (BAWLD-CH 4 ) was constructed in parallel with a compatible land cover dataset, sharing the same land cover classes to enable refined bottom-up assessments. BAWLD-CH 4 includes information on site-level CH 4 fluxes but also on study design (measurement method, timing, and frequency) and site characteristics (vegetation, climate, hydrology, soil, and sediment types, permafrost conditions, lake size and depth, and our determination of land cover class). The different land cover classes had distinct CH 4 fluxes, resulting from definitions that were either based on or co-varied with key environmental controls. Fluxes of CH 4 from terrestrial ecosystems were primarily influenced by water table position, soil temperature, and vegetation composition, while CH 4 fluxes from aquatic ecosystems were primarily influenced by water temperature, lake size, and lake genesis. Models could explain more of the between-site variability in CH 4 fluxes for terrestrial than aquatic ecosystems, likely due to both less precise assessments of lake CH 4 fluxes and fewer consistently reported lake site characteristics. Analysis of BAWLD-CH 4 identified both land cover classes and regions within the boreal and arctic domain, where future studies should be focused, alongside methodological approaches. Overall, BAWLD-CH 4 provides a comprehensive dataset of CH 4 emissions from high-latitude ecosystems that are useful for identifying research opportunities, for comparison against new field data, and model parameterization or validation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Feasibility of Using Fourier Neural Operators for 3D Elastic Seismic Simulations

Seismic simulations in three-dimensional (3D) Earth models are important in many of the seismological applications related to our lab’s mission, however, accurate high-fidelity simulations are computationally costly. We investigated the capabilities of the newly developed Fourier Neural Operator (FNO) to solve the 3D elastic wave equations for seismic simulations. We generated simulation data for training the FNO model, and analyzed its performance on various test cases, such as the performance with different number of training data, different resolutions, and on more canonical structures. We found the FNO model can reproduce 3D seismic simulations with high accuracy and ~169 times faster on a small spatial grid size of 16 x 16 x16. When applied on higher resolution data, we found that transfer learning with fine-tuning on a small amount of data achieves reasonable results. This feasibility study showed promising results for using FNO’s for 3D seismic simulations and represents the foundation of further research to develop this into a more mature approach for different seismological applications. The potential impact of this project will provide techniques for large-scale or real-time applications of solving PEDs in support of national lab’s programs.

58 GEOSCIENCES↗
DOE OSTI2021

PBX9012 Tracker Gauge Data

Five shock-to-detonation transition (SDT) gas gun experiments for PBX 9012 were performed by Burns and Chiquete [2020]. The data from the experiments is available on the small-scale database. Here we focus on the tracker gauge data for the lead shock trajectory, x(t). In order to determine the shock speed U s (t) and the detonation transition point, a least squared fit to the shock trajectory is used based on a pair of ODEs with a fitting form for the shock acceleration developed by Hill and Gustavsen [2002].

42 ENGINEERING↗
DOE OSTI2023

Search for light Higgs bosons from supersymmetric cascade decays in $\text {pp}$ collisions at $\sqrt{s}=13\,\textrm{TeV}$

A search is reported for pairs of light Higgs bosons (H 1 ) produced in supersymmetric cascade decays in final states with small missing transverse momentum. A data set of LHC pp collisions collected with the CMS detector at $\sqrt{s}$ = 13 TeV and corresponding to an integrated luminosity of 138 fb -1 is used. The search targets events where both H 1 bosons decay into $\text{b}\bar{\text{b}}$ pairs that are reconstructed as large-radius jets using substructure techniques. No evidence is found for an excess of events beyond the background expectations of the standard model (SM). Results from the search are interpreted in the next-to-minimal supersymmetric extension of the SM, where a “singlino” of small mass leads to squark and gluino cascade decays that can predominantly end in a highly Lorentz-boosted singlet-like H 1 and a singlino-like neutralino of small transverse momentum. Upper limits are set on the product of the squark or gluino pair production cross section and the square of the branching fraction of the $\text{b}\bar{\text{b}}$ in a benchmark model containing almost mass-degenerate gluinos and light-flavour squarks. Under the assumption of an SM-like H 1 → $\text{b}\bar{\text{b}}$ branching fraction, H 1 bosons with masses in the range 40–120 GeV arising from the decays of squarks or gluinos with a mass of 1200–2500 GeV are excluded at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗
DOE OSTI2020

Validation of Recent Changes in Actinide Evaluations U-235, U-233, Pu-239 [Slides]

This presentation discusses U-235 updates, including fluctuations in the fission cross section in the URR range that were refined to represent measured data following the Paradela et al. evaluation. There were small changes to the low-energy resonances to improve the fit to measured capture data from RPI (capture reduced by 5% from 0.06-7.8 eV, by 7.7% from 7.8-11 eV) and there was a very small change to the thermal nu-bar within uncertainties. Discrete level data are stored in MF=6 (format requirement, no impact on calculations) and issues leading to negative eigenvalues in cross-covariances in the RR have been sorted out. In conclusion, many improvements were made to evaluated nuclear data of actinides in the resonance region and above, such as minor changes to U-235 including assessment of changes that depend on the finalization of the O-16 evaluation. U-233 improvements show significant progress in performance and some further improvement might be needed at intermediate energies. Pu-239 ORNL/IAEA evaluation is promising; however, more work is needed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Corrections to official ENDF/B Evaluation Releases for SCALE Nuclear Data

The official ENDF/B nuclear data evaluation releases in the past two decades have incrementally incorporated more detailed information, new nuclide evaluations, and very often have improved the accuracy of radiation transport codes when modeling shielding, fission reactors, criticality benchmarks, and fusion systems. However, like any large collaborative data compilation, these releases have all included small errors. This report documents the small corrections to ENDF/B releases ENDF/B-VII.1, ENDF/B-VIII.0, and ENDF/B-VIII.1 that have been applied during nuclear data processing to produce data libraries for the SCALE code system.

Brown, Jesse M. [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

Testing and validating SMDS algorithms implemented in the cloud

Pacific Northwest National Laboratory (PNNL) provided technical assistance to NorthWrite Inc. under the Small Business Vouchers (SBV) Pilot. NorthWrite delivered services to owners of small commercial buildings, using a cloud-based service to monitor, control, and optimize building operations, saving energy and reducing operating costs for the owners while ensuring that occupant comfort needs were consistently met. NorthWrite had a longstanding desire to add a new suite of diagnostic capabilities to their service offering and had been trying, without success, to incorporate several diagnostic algorithms published by PNNL. These algorithms arise from research previously supported by BTO. Through the SBV awarded to NorthWrite, PNNL made available technical knowledge regarding the derivation and application of the following sets of algorithms for use in the NorthWrite Cloud-based service delivery system: • algorithms for monitoring rooftop packaged air conditioners and heat pumps (often referred to as rooftop units or RTUs) and diagnosing faults in these units, • advanced algorithms for automated fault detection and diagnosis of other equipment found in small buildings, and • algorithms for identifying, prioritizing, and assessing the economic effectiveness of implementing energy saving measures in small commercial buildings based on sensed data. The PNNL researchers involved were the original developers of these algorithms, had a unique understanding of the derivation of the algorithms, and had the source data used for this derivation. Further, the PNNL researchers had extensive experience using these algorithms in the laboratory, unique experience applying these algorithms in real-world small commercial buildings and could solve a number of key problems that NorthWrite and other users faced in using these algorithms at scale. In addition, PNNL had recently installed a pair of RTUs in a laboratory setting that were instrumented and connected with data acquisition systems that provided a unique test rig for validating the algorithms before NorthWrite began to deploy their new services in the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the growth rate of structure from the small-scale clustering of the luminous red galaxy sample

ABSTRACT We measure the small-scale clustering of the Data Release 16 extended Baryon Oscillation Spectroscopic Survey Luminous Red Galaxy sample, corrected for fibre-collisions using Pairwise Inverse Probability weights, which give unbiased clustering measurements on all scales. We fit to the monopole and quadrupole moments and to the projected correlation function over the separation range $7-60\, h^{-1}{\rm Mpc}$ with a model based on the aemulus cosmological emulator to measure the growth rate of cosmic structure, parametrized by fσ8. We obtain a measurement of fσ8(z = 0.737) = 0.408 ± 0.038, which is 1.4σ lower than the value expected from 2018 Planck data for a flat ΛCDM model, and is more consistent with recent weak-lensing measurements. The level of precision achieved is 1.7 times better than more standard measurements made using only the large-scale modes of the same sample. We also fit to the data using the full range of scales $0.1\text{--}60\, h^{-1}{\rm Mpc}$ modelled by the aemulus cosmological emulator and find a 4.5σ tension in the amplitude of the halo velocity field with the Planck + ΛCDM model, driven by a mismatch on the non-linear scales. This may not be cosmological in origin, and could be due to a breakdown in the Halo Occupation Distribution model used in the emulator. Finally, we perform a robust analysis of possible sources of systematics, including the effects of redshift uncertainty and incompleteness due to target selection that were not included in previous analyses fitting to clustering measurements on small scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Ten simple rules for getting and giving credit for data

This article attempts to summarize current best practices that support the movement towards enabling researchers to cite and receive credit for their data. The authors are a small representation of the people and organizations trying to make this happen, and we acknowledge that it is not possible to capture all efforts behind this endeavor in 10 Simple Rules. We encourage interested readers to dive deeper by providing related resources along the way.

59 BASIC BIOLOGICAL SCIENCES↗