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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

ShopperWorkerRatio

These data characterize spatial and temporal variation in the ratio between shoppers and workers in public places - points of interest - in the United States between 2019 and 2020. The underlying data on foot traffic to public places is collected by SafeGraph, a commercial data aggregator. We estimate the ratio of shoppers to workers based on recorded visit duration.These data may be useful for understanding how use of public spaces have changed during the Coronavirus pandemic, and more generally for understanding activity patterns in public.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

MCPC Friction Stir Welding (FSW) Process Data

Processing parameters and machine log data for the MCPC LDRD Agile investment is collected material samples processed. This dataset captures the selected processing parameters, machine logs captured during material processing, and descriptions of how characterization samples were extracted from processed plates of material. The collect characterization data is captured in other datasets.

316 Stainless Steel↗
DOE OSTI2025

Development and preliminary results of 270 GHz microwave forward scattering diagnostic system on the experimental advanced superconducting tokamak (EAST)

To measure localized (intermediate, high) poloidal wavenumber electron density fluctuations, a tangential millimeter-wave collective scattering system has been designed and successfully developed on the experimental advanced superconducting tokamak (EAST). This innovative system employs a 270 GHz mm-wave probe beam, emitted from the mid-plane of Port K and directed towards Port P after passing through a combination of two in-vessel mirrors. Here these two ports are located on the EAST device’s midplane and are 110° apart. The downward scattered signals pass through two in-vessel mirrors, and exit through the P window. The received multi-channel separated scattering signals are arranged along the poloidal direction. This optical arrangement makes the monitored turbulent wave number is poloidal dominant and up to 40 cm −1 . The tangential microwave scattering scheme enables this diagnostic to monitor local density fluctuations, with typically a radial spatial resolution △ R = 5 cm, and a wavenumber resolution of △ k = 0.4 cm −1 . The scattering system underwent comprehensive laboratory testing in 2023, with installation finalized in 2024. The system features steerable launch and receiver optics, allowing remote control to position the scattering volume from normalized radius ρ –0 to the pedestal region on a shot-by-shot basis. Effective experimental data, characterized by distinct off-center spectral peaks, have been successfully obtained in neutral beam-heated plasmas on EAST. The beam tracing forward modeling has been employed for experimental data interpretation. The advanced millimeter-wave scattering system provides fluctuation measurement capability from ion temperature gradient to electron temperature gradient scale on low field side. Preliminary experimental density fluctuation data have been successfully obtained in neutral beam-heated plasmas on EAST. The localized measurement will be used for kinetic turbulence transport numerical simulation validation.

high-k collective scattering↗
DOE OSTI2020

SNL will be able to provide well-calibrated models to weapons systems analysts by integrating an engine for constitutive model calibration with the GRANTA materials database

Researchers at Sandia National Laboratories have integrated the GRANTA materials database with the MatCal calibration engine to calibrate material models from characterization data. GRANTA is gaining acceptance across the NNSA Tri-lab complex and is being populated with weapons-specific test data by Sandia experimentalists. To use that data to create material models for use by weapons systems analysts, MatCal has been enabled import calibration data and test conditions from GRANTA to quickly and reproducibly produce a calibrated set of parameters for a given constitutive model. The team is currently working to store the parameters characterizing material behavior in GRANTA to make them accessible by all weapons analysts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Catalytic Upgrading of Pyrolysis Products for the Production of Sustainable Aviation Fuel

The objective of this project is advance the state-of-technology for a catalytic fast pyrolysis (CFP) + hydrotreating (HT) process to produce sustainable aviation fuel and other biogenic products. Our approach focuses on performing integrated experiments using realistic biomass feedstocks and non-noble metal technical catalyst formulations. CFP is performed in an ex-situ configuration using a fluidized bed reactor without co-fed hydrogen. Research advancements over the past two years include establishing benchmark yield structures and compositional data for each step of the biomass-to-SAF process, demonstrating the ability to produce a cycloalkane-rich SAF product that meets key ASTM 4054 guidelines, generating benchmark characterization data for technical catalyst formulations with an emphasis on determining the unique composition and combustion properties of biogenic coke, and establishing bio-oil critical material attributes to mitigate the risk of plugging during down-stream hydroprocessing. Other impacts from this project include generation of broadly enabling scientific knowledge (12 publications/12 presentations since 2021), engagement with industry partners (Johnson Matthey, ExxonMobil, Phillips 66), and identification of a promising pathway to market that addresses emerging demands for biogenic refinery feedstocks.

biomass↗
DOE OSTI2023

Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows

This report details recent progress for the ASCR funded project “Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows”. We refer to the project as IPPD/2, reflecting the 2017 renewal under expanded scope and partners In IPPD/2, we increased our research scope to include data motion. We are focusing on three major aspects: a) observe how data is generated, distributed, and used; b) analyze how data is (repeatedly) consumed with a focus both on repeated patterns and anomalies; and c) explore how to optimize data motion. This new work on data motion will augment and complement IPPD/2’s research that focused on the computational aspects of tasks. We leverage and extend our existing tools and demonstrate our work on the Belle II workflow suite as well as on workflows from NSLS-II. The highlights of our work are as follows: Provenance for Workflows: Provenance is used to provide information enabling quality control, re-run computational workflows, and reproduce results. IPPD/2 has been building a scalable provenance management system that enables the capture of provenance from the high-level workflow through all relevant system levels in one integrated environment. Leveraging this work, our recent efforts have included using provenance as an enabling technique. Workload characterization: Leveraging provenance and analysis, we characterize data movement within network, storage, and memory over a variety of workloads. This characterization enables an understanding by performance analysts and application developers of the range of behaviors that could be expected. Performance Prediction for Workflows: The goal of modeling distributed workflows is to understand performance bottlenecks and enable more intelligent task scheduling to optimize selected metrics of interest (e.g., task throughput or output data rate). IPPD/2 has utilized both analytical and AI/ML modeling methodologies for performance modeling. Advanced Scheduling and Fault Modeling for Workflows: Scheduling of large-scale scientific workflows on geographically distributed resources is a challenging problem. To improve workflow throughput, we combined novel scheduling algorithms with task predictions from performance modeling and fault modeling. Dynamically Alleviating Bottlenecks in Workflows: Exploiting our provenance, analysis, and modeling efforts, we have explored and developed several techniques for dynamically detecting and alleviating bottlenecks in data movement. In particular, we have spent considerable effort demonstrating our techniques on production-like workflow configurations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Gasification Studies: Task 4 Topical Report, Utah Clean Coal Program

A key objective of the Task 4 activities has been to develop simulation tools to support development, troubleshooting and optimization of pressurized entrained-flow coal gasifiers. The overall gasifier models (Subtask 4.1) combine submodels for fluid flow (Subtask 4.2) and heat transfer (Subtask 4.3) with fundamental understanding of the chemical processes (Subtask 4.4) processes that take place as coal particles are converted to synthesis gas and slag. However, it is important to be able to compare predictions from the models against data obtained from actual operating coal gasifiers, and Subtask 4.6 aims to provide an accessible, non-proprietary system, which can be operated over a wide range of conditions to provide well-characterized data for model validation. Highlights of this work include: (1) Verification and validation activities performed with the Arches coal gasification simulation tool on experimental data from the CANMET gasifier (Subtask 4.1). (2) The simulation of multiphase reacting flows with coal particles including detailed gas-phase chemistry calculations using an extension of the one-dimensional turbulence model’s capability (Subtask 4.2). (3) The demonstration and implementation of the Reverse Monte Carlo ray tracing (RMCRT) radiation algorithm in the ARCHES code (Subtask 4.3). (4) Determination of steam and CO 2 gasification kinetics of bituminous coal chars at high temperature and elevated pressure under entrained-flow conditions (Subtask 4.4). In addition, attempts were made to gain insight into the chemical structure differences between young and mature coal soot, but both NMR and TEM characterization efforts were hampered by the highly reacted nature of the soot. (5) The development, operation, and demonstration of in-situ gas phase measurements from the University of Utah’s pilot-scale entrained-flow coal gasifier (EFG) (Subtask 4.6). This subtask aimed at acquiring predictable, consistent performance and characterizing the environment within the gasifier.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Characterization of a dimer preparation method for nanoscale organic aerosol

Nanoscale dimers have application in studies of aerosol physicochemical properties such as aerosol viscosity. These particle dimers can be synthesized using the dual tandem differential mobility analyzer (DTDMA) technique, wherein oppositely charged particle streams coagulate to form dimers that can be isolated using electrostatic filtration. Although some characterization of the technique has been published, a detailed thesis on the modes and theory of operation has remained outside the scope of prior work. In this paper we present new experimental data characterizing the output DTDMA size distribution and the physical processes underlying its apparent modes. Key experimental limitations for both general applications and for viscosity measurements are identified and quantified in six distinct types of DTDMA experiments. The primary consideration is the production of an adequate number of dimers, which typically requires high mobility-selected number concentration in the range 25,000-100,000 cm -3 . The requisite concentration threshold depends upon the rate of spontaneous monomer decharging, which arises predominately from interactions of the aerosol with ionizing radiation within the coagulation chamber and is instrument location dependent. Lead shielding of the coagulation chamber reduced the first-order decharging constant from ~2.0 x 10 -5 s -1 to ~0.8 x 10 -5 s -1 in our laboratory. Dimer production at monomer diameters less than 40 nm is hindered by low bipolar charging efficiency. Results from the characterization experiments shed light on design considerations for general applications and for characterization of viscous aerosol phase transitions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

TAP Report - Southwest Idaho Juniper Working Group

There is explicit need for characterization of the materials for possible commercialization as little characterization data exists. Pinyon-juniper woodlands are a major ecosystem type found in the Southwest and the Intermountain West regions of the United States including Nevada, Idaho and Oregon. These widespread ecosystems are characterized by the presence of several different species of pinyon and juniper as the dominant plant cover. Since the 1800s, pinyon-juniper woodlands have rapidly expanded their range at the expense of existing ecosystems. Additionally, existing woodlands have become denser, progressively creating potential fire hazards as seen in the Soda Fire, which burned more than 400 sq. miles. Land managers responsible for these areas often desire to reduce pinyon-juniper coverage on their lands for a variety of reasons, as stated in the Working Group objectives. However, the cost of clearing thinning pinyon-juniper stands can be prohibitive. One reason for this is the lack of utilization options for the resulting biomass that could help recover some of the cost of pinyon-juniper stand management. The goal of this TAP effort was to assess the feedstock characteristics of biomass from a juniper harvested from Owyhee County to evaluate possible fuel and conversion utilization options.

09 BIOMASS FUELS↗
DOE OSTI2016

Observation and characterization of a cosmic muon neutrino flux from the northern hemisphere using six years of IceCube data

The IceCube Collaboration has previously discovered a high-energy astrophysical neutrino flux using neutrino events with interaction vertices contained within the instrumented volume of the IceCube detector. We present a complementary measurement using charged current muon neutrino events where the interaction vertex can be outside this volume. As a consequence of the large muon range the effective area is significantly larger but the field of view is restricted to the Northern Hemisphere. IceCube data from 2009 through 2015 have been analyzed using a likelihood approach based on the reconstructed muon energy and zenith angle. At the highest neutrino energies between 194 TeV and 7.8 PeV a significant astrophysical contribution is observed, excluding a purely atmospheric origin of these events at 5.6σ significance. The data are well described by an isotropic, unbroken power-law flux with a normalization at 100 TeV neutrino energy of (0.90{sub −0.27}{sup +0.30})×10{sup −18} GeV{sup −1} cm{sup −2} s{sup −1} sr{sup −1} and a hard spectral index of γ=2.13±0.13. The observed spectrum is harder in comparison to previous IceCube analyses with lower energy thresholds which may indicate a break in the astrophysical neutrino spectrum of unknown origin. The highest-energy event observed has a reconstructed muon energy of (4.5±1.2) PeV which implies a probability of less than 0.005% for this event to be of atmospheric origin. Analyzing the arrival directions of all events with reconstructed muon energies above 200 TeV no correlation with known γ-ray sources was found. Using the high statistics of atmospheric neutrinos we report the current best constraints on a prompt atmospheric muon neutrino flux originating from charmed meson decays which is below 1.06 in units of the flux normalization of the model in Enberg et al.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site

Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.

58 GEOSCIENCES↗
DOE OSTI2022

WHONDRS Surface Water and Sediment Non-Purgeable Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2021 (v3)

This dataset supports a broader study examining land-atmosphere gas exchange associated with permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water and sediment. Samples were collected from 8 spatially diverse sites across central Svalbard and also from a more comprehensive temporal and spatial study within one glacial catchment area throughout one summer melt season. Related data were collected and will be published separately in collaboration with Yde and Kleber.This data package was originally published in September 2022. It was updated in March 2023 (v2; new and modified files), and July 2025 (v3; modified files). See the change history section in the readme for details.For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measure as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) sediment extraction protocol; (7) readme; (8) methods codes; (9) international generic sample number (IGSN) mapping file; and (10) folder of high resolution characterization of organic matter via 7 and 12 Tesla (7T and 12T) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders containing the 7T and 12T .xml data files and another subfolder containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

WHONDRS Surface Water Dissolved Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2022

This dataset supports a broader study examining climatic forcing of terrestrial greenhouse gas emission through permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from 11 sites across central Svalbard. Data were also collected in 2021 and can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1888571. Additional related data were collected and will be published separately in collaboration with Yde and Kleber.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; (9) a folder of field photos; and (10) folder of high resolution characterization of organic matter via 7 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Physical and Hydraulic Properties of RCRA Borehole Samples from the Hanford Site : Final Report, Fiscal Years 2023-2024

Sediment from 44 core samples collected from Resource Conservation and Recovery Act (RCRA) boreholes drilled in the 200 East and 200 West areas of the Hanford Site were characterized for physical and hydraulic properties (Table S.1). Characterization data included gravimetric water contents and matric potentials, grain-size distributions, saturated hydraulic conductivity, water retention characteristics, and unsaturated hydraulic conductivity. These properties provide site-specific data and parameters that can be used in subsurface flow and contaminant transport models to assess the transport and fate of contaminants in the vadose zone and underlying aquifer systems. The analyzed core samples come from specific areas and depth intervals at the Hanford Site that were targeted for sampling to address data gaps identified by site contractors (Khaleel 2020). X-ray computed tomography (XCT) was used to evaluate the general textural characteristics of the samples and to determine which samples to use for further physical and hydraulic property characterization. Subsequent sample selection was determined by consensus after review of the XCT images by Pacific Northwest National Laboratory, Central Plateau Cleanup Company, and INTERA staff.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Evaluation of Converter Performance Considering Static and Dynamic Device Part-to-Part Variability

This paper presents a methodology to incorporate and analyze the impact of semiconductor device part-to-part variation on power converter performance. By integrating extensive static and dynamic device characterization data with an automated compact model generation process that reflects manufacturing variability, device models with inherent variability features are utilized in converter simulations for a comprehensive assessment of performance impacts. The traditional converter performance evaluation process typically yields fixed efficiency values, often dismissing the inherent part-to-part variability caused by the manufacturing process of semiconductor devices. To address this limitation, a large population of devices was characterized to capture variations in static parameters-such as transfer, output, and capacitance characteristics-as well as dynamic behaviors, including switching losses. This data-driven approach enables the development of individual compact models, which were then integrated into converter simulations to evaluate efficiency ranges rather than single point estimated values. The converter simulation results show that part-to-part component variation can lead to significant efficiency deviations, exceeding several percentage points in high-power conversion applications. By offering a more accurate representation of converter behavior under real-world manufacturing conditions, this methodology enables designers to anticipate performance variability, improving the robustness of power converter designs.

device characterization↗
DOE OSTI2024

MatCal Users Guide: Release 1.3.0

Any continuum mechanics model will require three components: (1) a discretized geometry of the boundary value problem being studied, (2) the partial differential equations to be solved, and (3) the initial conditions and boundary conditions for the problem. To describe material behavior in these computational models, material models contribute to (2) the underlying equations and, occasionally, to (3) the initial conditions for the simulation. These material models can exhibit a mathematical form that is empirically based, based on first principles, or developed from both empirical observations and known physics. In general, these models are meant to represent a class of materials with well understood behavior. As a result, material models have parameters that must be tuned or calibrated so that the model response matches characterization data available for the specific material it is intended to represent when used to simulate a specific system. For simple models, such as isotropic, linear elastic materials in solid mechanics, this calibration process can be a simple analytical calculation directly extracting the parameters from experimental measurements. For complex models that have many inputs and require many characterization datasets to adequately identify the material behavior, the model calibration process can require an inverse problem approach where an optimization is performed to tune the model parameters to the available data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗