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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Flexible and Accessible 4D Subsurface Visualization Using a Web-Based Platform

4D subsurface visualization using a web platform can provide improved communication, education and outreach to non-experts and stakeholders. It allows for the improved understanding of complex relationships and interactions that occur in inaccessible locations of which many experimental testbeds exist in. The use of a web-based visualization tool lessens the cognitive impact further by reducing the need of specialized software. Users can define their own exploration of a 3D or 4D scene, adding and removing data as needed and are able to make informed decisions based on accurate model visualizations, while providing a collaborative tool that can be accessed on any platform using a browser window. The tool is also able to point to real time streams to display up-to-the-second data as an experiment is ongoing. This level of latency can also provide operators with essential information that can direct an experiment’s progress. Additionally, this tool can leverage augmented and virtual reality (AR, VR) capabilities of certain mobile devices and head-mounted displays, providing further engaging visualization possibilities.

Pratt, Martin J.↗
DOE OSTI2024

IC w22_phadiagractox Highlight: Composition-dependent melting temperature of a compound [Poster]

Figure 1 displays, ambient melting points of the Au-Cu system as a function of Cu atomic percent: present model vs. experimental data from four different sources. Figure 2 displays, ambient melting points of the U-O system as a function of O atomic percent: present model vs. both experiment and quantum molecular dynamics (QMD) simulations on the stoichiometric U-O compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Towards a Public Event Display for DUNE

The Deep Underground Neutrino Experiment (DUNE) is a next generation long baseline neutrino experiment based at Fermilab, with a near detector near the beam target and a Far Detector (FD) in South Dakota. As the experiment prepares for its first data runs, creating pathways for public engagement and data transparency is essential. We present the first-ever DUNE event display designed for public outreach and education. Developed using data from the ProtoDUNE detectors at the CERN Neutrino Platform, this tool provides an intuitive and interactive interface that allows non-experts to visualise and explore particle interactions in a Liquid Argon Time Projection Chamber (LArTPC). By translating raw experimental data into a browser-accessible format, we establish the essential infrastructure for DUNE’s pathway to open data. This talk will detail the technical development of the display, its current implementation with ProtoDUNE data, and the strategic roadmap for integrating it into DUNE’s long-term open-access framework.

Sabater, Eva [U. Sussex (main)] (ORCID:00090001748↗
DOE OSTI2025

A New Vehicle-to-Vehicle Communication System: Visual-Enhanced Cooperative Traffic Operations

The advent of Connected and Autonomous Vehicles (CAVs) has highlighted the necessity for robust communication systems between vehicles and their environment. This study introduces a novel vehicle-to-vehicle (V2V) communication system, termed the Visual-Enhanced Cooperative Traffic Operations (VECTOR) system. The VECTOR system addresses the need for robust communication by converting dynamic data (including velocity and yaw angle data) into binary code, which is displayed on an LED panel mounted on the top of the vehicle. Following vehicles detect this panel and decode the information using a camera, implementing a visual-based communication method. VECTOR system employs a comprehensive five-module process. Initially, polynomial fitting techniques are applied to velocity data over fixed time intervals using third-degree polynomials, with validation via R² and MSE metrics. The second module converts velocity and yaw angle data into binary form, thereby enhancing detection and processing efficiency. The third module focuses on improving detection stability across various environmental conditions to enhance traffic safety. The fourth module decodes the binary data back into trajectory information, ensuring the fidelity of velocity and yaw angles. The final module integrates eco-control through the VECTOR system, employing advanced control algorithms to minimize energy consumption in CAVs. Experimental evaluations conducted using a modified CAV test platform based on the Lincoln MKZ demonstrate the feasibility and efficiency of the VECTOR system, achieving a 75% R-squared accuracy rate in replicating original velocity data. This methodology not only highlights potential applications but also underscores significant implications for advancing CAV technology.

Ma, Ke↗
DOE OSTI2024

Prospective Seal Name Catalog for U.S. Sedimentary Basins V1.0

The Prospective Seal Name Catalog for U.S. Sedimentary Basins V1.0 is an aggregation of prospective seal units for prospective storage resources within the USA for geologic carbon storage in both onshore and offshore basins. The catalog is intended to guide users to available literature and data resources. Prospective seal names are displayed with respect to the associated prospective storage resource target, for which the specified prospective seal may act as a confining layer for CO2 storage. A prospective seal unit’s lithology, position with respect to the reservoir (Primary, Secondary, Intraformational, etc.), and age (Geologic Period) are included when stated in the original literature or data resource. The information source for each record in the catalog includes the published citation, year of publication, resource type (Journal Article, Event Proceedings, etc.) and additional record notes.

Basin↗
DOE OSTI2023

A Machine Learning–Based Approach to Time-series Wave Identification in the Solar Wind

The Wind spacecraft has yielded several decades of high-resolution magnetic field data, a large fraction of which displays small-scale structures. In particular, the solar wind is full of wavelike fluctuations that appear in both the field magnitude and its components. The nature of these fluctuations can be tied to the properties of other structures in the solar wind, such as shocks, that have implications for the time evolution of the solar wind. As such, having a large collection of wave events would facilitate further study of the effects that these fluctuations have on solar wind evolution. Given the large volume of magnetic field data available, machine learning is the most practical approach to classifying the myriad small-scale structures observed. To this end, a subset of Wind data is labeled and used as a training set for a multibranch 1D convolutional neural network aimed at classifying circularly polarized wave modes. Using this algorithm, a preliminary statistical study of 1 yr of data is performed, yielding about 300,000 wave intervals out of about 5,000,000 solar wind intervals. The wave intervals come about more often in the fast solar wind and at higher temperatures, and the number of waves per day is highly periodic. This machine learning–based approach to wave detection has the potential to be a powerful, inexpensive way to catalog waves throughout decades of spacecraft data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

SRNL High and Low Activity Residue Characterization System Phase II [Poster]

The characterization system contains data sampled from 1996 to 2024 and can display any desired combination of 45 different isotopes. This system is intended to be used to quickly access historical data, generate trends for accurate future projections, and evaluate relevant unit conversion calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

MAPPRAISER: A massively parallel map-making framework for multi-kilo pixel CMB experiments

Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however distributed over voluminous data sets which these experiments will collect. These data sets will need to be efficiently processed and unwanted contributions due to astrophysical, environmental, and instrumental effects characterized and efficiently mitigated in order to uncover the signatures. This poses a significant challenge to data analysis methods, techniques, and software tools which will not only have to be able to cope with huge volumes of data but to do so with unprecedented precision driven by the demanding science goals posed for the new experiments. A keystone of efficient CMB data analysis is solvers of very large linear systems of equations. Such systems appear in very diverse contexts throughout CMB data analysis pipelines, however they typically display similar algebraic structures and can therefore be solved using similar numerical techniques. Linear systems arising in the so-called map-making problem are one of the most prominent and common ones. In this work we present a massively parallel, flexible and extensible framework, comprised of a numerical library, MIDAPACK, and a high level code, MAPPRAISER, which provide tools for solving efficiently such systems. Here, the framework implements iterative solvers based on conjugate gradient techniques: enlarged and preconditioned using different preconditioners. We demonstrate the framework on simulated examples reflecting basic characteristics of the forthcoming data sets issued by ground-based and satellite-borne instruments, executing it on as many as 16,384 compute cores. The software is developed as an open source project freely available to the community at: https://github.com/B3Dcmb/midapack.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Outdoor performance of a tandem InGaP/Si photovoltaic luminescent solar concentrator

Here, we report the design, fabrication and outdoor characterization of a tandem luminescent solar concentrator/Si multi-junction photovoltaic module. Our tandem LSC/Si device consists of an InGaP LSC functioning as a top cell and a passivated contact Si bottom cell. The LSC comprises of an InGaP microcell array coupled to a polymer waveguide, loaded with CdSe/CdS core-shell quantum dot luminophores. The light trapping efficiency of the LSC waveguide is enhanced by encapsulation with photoluminescence trapping mirrors consisting of dielectric multilayer thin films. We demonstrate the performance of the LSC/Si device through a series of outdoor tests under various irradiance conditions conducted at the National Renewable Energy Laboratory. We report the first outdoor testing data of an LSC/Si tandem module, displaying maintained performance across varied diffusivity conditions for the LSC component. Finally, we model the tandem module performance using a ray optic simulation-based multiphysics model and forecast a pathway for high efficiency tandem LSC/Si module performance.

14 SOLAR ENERGY↗
DOE OSTI2022

Light sources with bias tunable spectrum based on van der Waals interface transistors

Light-emitting electronic devices are ubiquitous in key areas of current technology, such as data communications, solid-state lighting, displays, and optical interconnects. Controlling the spectrum of the emitted light electrically, by simply acting on the device bias conditions, is an important goal with potential technological repercussions. However, identifying a material platform enabling broad electrical tuning of the spectrum of electroluminescent devices remains challenging. Here, we propose light-emitting field-effect transistors based on van der Waals interfaces of atomically thin semiconductors as a promising class of devices to achieve this goal. We demonstrate that large spectral changes in room-temperature electroluminescence can be controlled both at the device assembly stage –by suitably selecting the material forming the interfaces– and on-chip, by changing the bias to modify the device operation point. Even though the precise relation between device bias and kinetics of the radiative transitions remains to be understood, our experiments show that the physical mechanism responsible for light emission is robust, making these devices compatible with simple large areas device production methods.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Planck 2018 results

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E -mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: f NL local = -0.9 ± 5.1; f NL equil = -26 ± 47; and f NL ortho = -38 ± 24 (68% CL, statistical). These results include low-multipole (4 ≤ ℓ < 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5 σ . Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial trispectrum shape is g NL local = (-5.8 ± 6.5) × 10 4 (68% CL, statistical), while constraints for other trispectrum shapes are also determined. Exploiting the tight limits on various bispectrum and trispectrum shapes, we constrain the parameter space of different early-Universe scenarios that generate primordial NG, including general single-field models of inflation, multi-field models (e.g. curvaton models), models of inflation with axion fields producing parity-violation bispectra in the tensor sector, and inflationary models involving vector-like fields with directionally-dependent bispectra. Our results provide a high-precision test for structure-formation scenarios, showing complete agreement with the basic picture of the ΛCDM cosmology regarding the statistics of the initial conditions, with cosmic structures arising from adiabatic, passive, Gaussian, and primordial seed perturbations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Featureless adaptive optimization accelerates functional electronic materials design

Electronic materials that exhibit phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features that impede model training. In this article, we demonstrate a discovery strategy based on multi-objective Bayesian optimization to directly circumvent these bottlenecks by utilizing latent variable Gaussian processes combined with high-fidelity electronic structure calculations for validation in the chalcogenide lacunar spinel family. We directly and simultaneously learn phase stability and bandgap tunability from chemical composition alone to efficiently discover all superior compositions on the design Pareto front. Previously unidentified electronic transitions also emerge from our featureless adaptive optimization engine. Our methodology readily generalizes to optimization of multiple properties, enabling co-design of complex multifunctional materials, especially where prior data is sparse.

36 MATERIALS SCIENCE↗
DOE OSTI2023

RadVolViz: An Information Display-Inspired Transfer Function Editor for Multivariate Volume Visualization

In volume visualization transfer functions are widely used for mapping voxel properties to color and opacity. Typically, volume density data are scalars which require simple 1D transfer functions to achieve this mapping. If the volume densities are vectors of three channels, one can straightforwardly map each channel to either red, green or blue, which requires a trivial extension of the 1D transfer function editor. Here, we devise a new method that applies to volume data with more than three channels. These types of data often arise in scientific scanning applications, where the data are separated into spectral bands or chemical elements. Our method expands on prior work in which a multivariate information display, RadViz, was fused with a radial color map, in order to visualize multi-band 2D images. In this work, we extend this joint interface to blended volume rendering. The information display allows users to recognize the presence and value distribution of the multivariate voxels and the joint volume rendering display visualizes their spatial distribution. We design a set of operators and lenses that allow users to interactively control the mapping of the multivariate voxels to opacity and color. This enables users to isolate or emphasize volumetric structures with desired multivariate properties. Furthermore, it turns out that our method also enables more insightful displays even for RGB data. We demonstrate our method with three datasets obtained from spectral electron microscopy, high energy X-ray scanning, and atmospheric science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

HydrogenAR: Interactive Data-Driven Presentation of Dispenser Reliability: Preprint

When delivering presentations to a co-located audience, we typically use slides with text and 2D graphics to complement the spoken narrative. Though presentations have largely been explored on 2D media, augmented reality (AR) allows presentation designers to add data and augmentations to existing physical infrastructure on display. This could provide a more engaging experience to the audience and support comprehension. With HydrogenAR, we present a novel application that leverages the benefits of data-driven storytelling with those of AR to explain the unique challenges of hydrogen dis- penser reliability. Utilizing physical props, situated data, and virtual augmentations and animations, HydrogenAR serves as a unique presentation tool, particularly critical for stakeholders, tour groups, and VIPs. HydrogenAR is a product of multiple collaborative de- sign iterations with a local Hydrogen Fuel research team and is evaluated through interviews with team members and a user study with end-users to evaluate the usability and quality of the interactive AR experience. Through this work, we provide design considera- tions for AR data-driven presentations and discuss how AR could be used for innovative content delivery beyond traditional slide-based presentations.

augmented reality↗
DOE OSTI2022

Limitations of reanalysis data for wind power applications

Wind energy resource estimates commonly depend on simulated wind speed profiles generated by reanalysis or weather models due to the lack of long time series measurements with sufficient coverage at relevant heights (roughly 90 m above ground). However, modeled data, including reanalyses, can be noisy and display a wide range of biases and errors, variously attributed to terrain effects, poor coverage of assimilated inputs, and model resolution. Wind generation records, if available at high temporal and geographical resolution, can provide a proxy for wind measurements and allow for evaluation of reanalyses and weather model wind time series. We use a 7-year-long data set of hourly, plant-level generation records from over 100 wind plants across Texas to evaluate two commonly used reanalysis data sets (MERRA2 and ERA5). Additionally, we use 1-year of records (2019) to evaluate an operational, high-resolution regional weather modeling product (HRRR v3). We find that across the region, and across all modeling products, the modeled representation of wind generation (i.e., wind speeds at hub heights passed through a power curve) has relatively small mean errors when aggregated daily, but that accuracy and hourly correlation have a strong diurnal sensitivity. Accuracy and correlation systematically decline through the evening and markedly improve after sunrise. These diurnal patterns persist even in the highest resolution model tested (HRRR v3). We hypothesize the nighttime decline in accuracy is mostly due to poorly represented boundary layer conditions, perhaps related to model representation of stability, while other uncertainties (such as wake effects) play a secondary role.

17 WIND ENERGY↗
DOE OSTI2024

System and method for transparent augmented reality

A system and method for displaying augmented reality information for a real object. A transparent display displays the information for the real object within a field of view, such that the information and the real object are simultaneously viewable by a user. Data-gathering peripheral devices gather data of the field of view, including a camera gathering visual data for tracking the real object. An articulating arm moveably supports and facilitates repositioning the display and redirecting the data-gathering peripheral devices in a particular direction. A security interlock disables the data-gathering peripherals when the articulating arm is moved beyond a pre-established threshold, thereby preventing the data-gathering peripherals from gathering data of a real environment outside of a limit of the field of view as determined by the pre-established threshold. The security interlock may include an adjustable contact switch which adjustably defines the pre-established threshold in at least one direction.

Runyan, Paul Ryan↗