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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Clinical Outcomes of Transcatheter Arterial Embolisation for Chronic Knee Pain: Mild-to-Moderate Versus Severe Knee Osteoarthritis

Purpose: This retrospective study was conducted to compare the clinical outcomes of transcatheter arterial embolisation for chronic knee pain in patients with mild-to-moderate versus severe knee osteoarthritis. Materials and Methods: This study included patients (n = 41) who were refractory to conservative treatments and who underwent transcatheter arterial embolisation using imipenem/cilastatin sodium between June 2017 and July 2018. A total of 71 knees, including 30 bilateral cases, were treated and categorised into two groups according to the Kellgren–Lawrence grade: mild-to-moderate osteoarthritis (n = 59, Kellgren–Lawrence grade 1–3) and severe osteoarthritis (n = 12, Kellgren–Lawrence grade 4). The clinical outcomes were measured by the visual analogue scale score. Results: There were no significant differences in age, body mass index or baseline visual analogue scale scores between the two groups. The mean visual analogue scale scores in the mild-to-moderate osteoarthritis group were significantly decreased at 1 day, 1 week, 1 month, 3 months, and 6-months (5.5 at baseline vs. 3.2, 3.1, 2.9, 2.2, and 1.9, after treatment; all P = .00). These improvements were maintained at a mean of 10 ± 3 months (range 6–19 months) post-treatment. The visual analogue scale scores were significantly decreased in the severe osteoarthritis group for 1 month post-treatment (6.3 at baseline vs. 4.1, 4.1, and 4.4 at 1 day, 1 week, and 1 month; all P < .01). However, a decrease in pain was not statistically significant from 3 to 6 months (5.4 and 5.9 at 3 months and 6 months, respectively). Conclusion: Transcatheter arterial embolisation effectively relieved pain in patients with mild-to-moderate osteoarthritis. In patients with severe osteoarthritis, pain severity decreased for 1 month but gradually increased to the initial severity score within 3 months. Level of Evidence: 4, Case series.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Transient mixing behavior of a supercritical fluid injected into supercritical and subcritical environments

Transient, near-field mixing of a supercritical fluid injected into supercritical and subcritical environments is investigated experimentally. Fuel (propane) from a 100 μm diameter Bosch diesel injector is injected into a high-pressure test rig with a steady flow of heated, low-velocity nitrogen to control the ambient pressure and temperature. The fuel supply pressure is approximately 190 bar, allowing short injections lasting 3–4 ms to be performed in quick succession to acquire statistically significant datasets to represent the unsteady fuel–air mixing. Two test cases with the same ambient density and injector inlet pressure and temperature were chosen in an attempt to isolate effects of mixture phase behavior. Microscopic rainbow Schlieren deflectometry (RSD) is used for visualization and quantitative data acquisition. In the case of the supercritical ambient, the injector inlet and exit and ambient conditions are all supercritical. The RSD analysis reveals a mixing process similar to the single phase fluid mixing, though condensation is also observed locally, and can be explained by the adiabatic mixing theory presented in the paper. For the subcritical ambient case, the injector inlet is supercritical, but the injector exit and ambient conditions are both subcritical. The results show a rapid expansion in the near-field promoting mixing between propane and nitrogen. At downstream locations, significant condensation is also observed as predicted by the adiabatic mixing theory. As a result, the supercritical ambient case exhibited longer and narrower jet penetration compared to the subcritical ambient case.

02 PETROLEUM↗
DOE OSTI2014

Star formation rate and extinction in faint z ∼ 4 Lyman break galaxies

We present a statistical detection of 1.5 GHz radio continuum emission from a sample of faint z ∼ 4 Lyman break galaxies (LBGs). To constrain their extinction and intrinsic star formation rate (SFR), we combine the latest ultradeep Very Large Array 1.5 GHz radio image and the Hubble Space Telescope Advanced Camera for Surveys (ACS) optical images in the GOODS-N. We select a large sample of 1771 z ∼ 4 LBGs from the ACS catalog using B {sub F435W}-dropout color criteria. Our LBG samples have I {sub F775W} ∼ 25-28 (AB), ∼0-3 mag fainter than M{sub UV}{sup ⋆} at z ∼ 4. In our stacked radio images, we find the LBGs to be point-like under our 2'' angular resolution. We measure their mean 1.5 GHz flux by stacking the measurements on the individual objects. We achieve a statistical detection of S {sub 1.5} {sub GHz} = 0.210 ± 0.075 μJy at ∼3σ for the first time on such a faint LBG population at z ∼ 4. The measurement takes into account the effects of source size and blending of multiple objects. The detection is visually confirmed by stacking the radio images of the LBGs, and the uncertainty is quantified with Monte Carlo simulations on the radio image. The stacked radio flux corresponds to an obscured SFR of 16.0 ± 5.7 M {sub ☉} yr{sup –1}, and implies a rest-frame UV extinction correction factor of 3.8. This extinction correction is in excellent agreement with that derived from the observed UV continuum spectral slope, using the local calibration of Meurer et al. This result supports the use of the local calibration on high-redshift LBGs to derive the extinction correction and SFR, and also disfavors a steep reddening curve such as that of the Small Magellanic Cloud.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints

Abstract Dimension reduction techniques are an essential part of the climate analyst’s toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative , sparse , and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection.

Weylandt, Michael↗
DOE OSTI2021

SDSS-IV MaNGA: the physical origin of off-galaxy H α blobs in the local Universe

ABSTRACT H α blobs are off-galaxy emission-line regions with weak or no optical counterparts. They are mostly visible in H α line, appearing as concentrated blobs. Such unusual objects have been rarely observed and studied, and their physical origin is still unclear. We have identified 13 H α blobs in the public data of MaNGA survey, by visually inspecting both the optical images and the spatially resolved maps of H α line for ∼4600 galaxy systems. Among the 13 H α blobs, 2 were reported in previously MaNGA-based studies and 11 are newly discovered. This sample, though still small in size, is by far the largest sample with both deep imaging and integral field spectroscopy. Therefore, for the first time we are able to perform statistical studies to investigate the physical origin of H α blobs. We examine the physical properties of these H α blobs and their associated galaxies, including their morphology, environments, gas-phase metallicities, kinematics of ionized gas, and ionizing sources. We find that the H α blobs in our sample can be broadly divided into two groups. One is associated with interacting/merging galaxy systems, of which the ionization is dominated by shocks or diffuse ionized gas. It is likely that these H α blobs used to be part of their nearby galaxies, but were stripped away at some point due to tidal interactions. The other group is found in gas-rich systems, appearing as low-metallicity star-forming regions that are visually detached from the main galaxy. These H α blobs could be associated with faint discs, spiral arms, or dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Statistical analysis of support thickness and particle size effects in HRTEM imaging of metal nanoparticles

High-resolution transmission electron microscopy (HRTEM) examination of nanoparticles requires their placement on some manner of support – either TEM grid membranes or part of the material itself, as in many heterogeneous catalyst systems – but a systematic quantification of the practical imaging limits of this approach has been lacking. Here, in this paper, we address this issue through a statistical evaluation of how nanoparticle size and substrate thickness affects the ability to resolve structural features of interest in HRTEM images of metallic nanoparticles on common support membranes. The visibility of lattice fringes from crystalline Au nanoparticles on amorphous carbon and silicon supports of varying thickness was investigated with both conventional and aberration-corrected TEM. Over the 1–4 nm nanoparticle size range examined, the probability of successfully resolving lattice fringes differed significantly as a function both of nanoparticle size and support thickness. Statistical analysis was used to formulate guidelines for the selection of supports and to quantify the impact a given support would have on HRTEM imaging of crystalline structure. For nanoparticles ≥1 nm, aberration-correction was found to provide limited benefit for the purpose of visualizing lattice fringes; electron dose is more predictive of lattice fringe visibility than aberration correction. These results confirm that the ability to visualize lattice fringes is ultimately dependent on the signal-to-noise ratio of the HRTEM images, rather than the point-to-point resolving power of the microscope. Lastly, this study provides a benchmark for HRTEM imaging of crystalline supported metal nanoparticles and is extensible to a wide variety of supports and nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Database-wide hazard modelling of the onset of DIII-D tearing modes with field features

The rate of onset (hazard) of tearing modes is modelled probabilistically using statistical learning algorithms. Axisymmetric energy-density equilibrium fields are taken as raw high-dimensional input features which are reduced with principal component analysis. Signal processing of non-axisymmetric magnetics fluctuation array data provides the target information from which to learn. Model selection, visualization and calibration assessment procedures are detailed. Here, the analysis is deployed at large scale across the DIII-D tokamak database. Standard model selection criteria suggest that the energy-density post-processed feature is a better choice for modelling the onset rate compared to the non-processed equilibrium reconstruction solution. Two example applications of the learned rate function are demonstrated: (i) proximity-to-onset discharge monitoring and (ii) database analysis showing an (expected) observational global trend that the general hazard increases as a plasma performance metric increases. An important connection between the hazard function and its use as a conditional probability generator is reviewed in the Appendix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Hardware-Accelerated Ray Tracing of CAD-Based Geometry for Monte Carlo Radiation Transport

Monte Carlo radiation transport (MCRT) methods have been used to simulate radiation environments for many decades by tracking individual particles through a model to accumulate statistical information. MCRT geometry is historically formed using the constructive solid geometry (CSG). Recently, significant work has been performed to support simulations using computer-aided design (CAD)-based tessellated surfaces to support highly complex geometries. Ray tracing acceleration data structures from the rendering and visualization community are applied to accelerate particle tracking in CAD-based models. Despite these efforts, CSG representations provide the superior performance in surface intersection operations during particle flight. Concurrently, pseudo Monte Carlo methods have become prevalent in rendering applications to support more realistic models for scattering media, motivating innovations that are advantageous for MCRT simulations. Finally, the authors’ work extends these innovations by employing Intel’s Embree ray tracing kernel within a geometry toolkit for Monte Carlo to improve the simulation performance using CAD-based models by factors of 1.5 to 2.

42 ENGINEERING↗
DOE OSTI2014

SU-F-19A-09: Propagation of Organ at Risk Contours for High Dose Rate Brachytherapy Planning for Cervical Cancer: A Deformable Image Registration Comparison

Purpose: To compare the performance of two deformable image registration (DIR) algorithms for contour propagation and to evaluate the accuracy of DIR for use with high dose rate (HDR) brachytherapy planning for cervical cancer. Methods: Five patients undergoing HDR ring and tandem brachytherapy were included in this retrospective study. All patients underwent CT simulation and replanning prior to each fraction (3–5 fractions total). CT-to-CT DIR was performed using two commercially available software platforms: SmartAdapt, Varian Medical Systems (Demons) and Velocity AI, Velocity Medical Solutions (B-spline). Fraction 1 contours were deformed and propagated to each subsequent image set and compared to contours manually drawn by an expert clinician. Dice similarity coefficients (DSC), defined as, DSC(A,B)=2(AandB)/(A+B) were calculated to quantify spatial overlap between manual (A) and deformed (B) contours. Additionally, clinician-assigned visual scores were used to describe and compare the performance of each DIR method and ultimately evaluate which was more clinically acceptable. Scoring was based on a 1–5 scale—with 1 meaning, “clinically acceptable with no contour changes” and 5 meaning, “clinically unacceptable”. Results: Statistically significant differences were not observed between the two DIR algorithms. The average DSC for the bladder, rectum and rectosigmoid were 0.82±0.08, 0.67±0.13 and 0.48±0.18, respectively. The poorest contour agreement was observed for the rectosigmoid due to limited soft tissue contrast and drastic anatomical changes, i.e., organ shape/filling. Two clinicians gave nearly equivalent average scores of 2.75±0.91 for SmartAdapt and 2.75±0.94 for Velocity AI—indicating that for a majority of the cases, more than one of the three contours evaluated required major modifications. Conclusion: Limitations of both DIR algorithms resulted in inaccuracies in contour propagation in the pelvic region, thus hampering the clinical utility of this technology. Further work is required to optimize these algorithms and take advantage of the potential of DIR for HDR brachytherapy planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

NMR_DIFFSIM v. 1.0

The software generates and analyzes nuclear magnetic resonance spin diffusion simulations for the purpose of measuring domain sizes or spin diffusion constants in a heterogenous sample. Its primary capabilities are: 1. It solves the spin magnetization diffusion equation to simulate the results of a spin diffusion experiment using any structural input geometry, including structure models generated by molecular dynamics or other computational or experimental methods. 2. It compares the results of simulations on an input structure to experimental data, providing a data fitting algorithm to extract physical information from the experimental data via the simulation. 3. It can provide statistical measures to compare correlations between structural models, to determine domain clustering and connectedness, and to provide goodness-of-fit measures including chord length distributions, chi-squared values, Pearson coefficients and pair correlation functions. 4. It provides output reports, data files, and movies to visualize simulation results.

Sorte, Eric↗
DOE OSTI2019

Evaluation of Geologic Carbon Storage Resource Estimates (SREs) of Cambrian Ordovician Units within the CarbonSAFE Prefeasibility Study Region Subtasks 4.2 and 4.3 – Topical Report

This report by the Indiana Geological & Water Survey (IGWS) assessed the storage resource estimate (SRE) of Cambrian-Ordovician stratigraphic units located within the CarbonSAFE prefeasibility area within the Illinois Basin. A comprehensive data set of wireline logs and petrophysical information was used. These data include core analysis for porosity and permeability, and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for four potential storage reservoirs (Upper Ordovician Trenton Limestone/Black River Group, Middle Ordovician St. Peter Sandstone, Lower Ordovician and Upper Cambrian Knox Supergroup, including a separate assessment for the lower Knox Potosi Dolomite. The resultant SREs volumes are displayed using georeferenced maps and boxplots. The latter allow for comparing data statistics (mean values and variability) between five methods employed for the SRE calculations. Differences observed in SRE results from the five methods are mainly attributable to differences in the data used for porosity in each method. 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 OSTI2017

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models: Preprint

We have developed a framework for the exploration, design, and planning of energy systems that combines interactive visualization with machine-learning based approximations of simulations through a general purpose dataflow API. Our system provides a visual inter- face allowing users to explore an ensemble of energy simulations representing a subset of the complex input parameter space, and spawn new simulations to 'fill in' input regions corresponding to new enegery system scenarios. Unfortunately, many energy simula- tions are far too slow to provide interactive responses. To support interactive feedback, we are developing reduced-form models via machine learning techniques, which provide statistically sound esti- mates of the full simulations at a fraction of the computational cost and which are used as proxies for the full-form models. Fast com- putation and an agile dataflow enhance the engagement with energy simulations, and allow researchers to better allocate computational resources to capture informative relationships within the system and provide a low-cost method for validating and quality-checking large-scale modeling efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Prevalence of Listeria monocytogenes , Salmonella spp., Shiga toxin-producing Escherichia coli , and Campylobacter spp. in raw milk in the United States between 2000 and 2019: A systematic review and meta-analysis

Raw (unpasteurized) milk is available for sale and direct human consumption within some states in the United States (US); it cannot be sold or distributed in interstate commerce. Raw milk may contain pathogenic microorganisms that, when consumed, may cause illness and sometimes may result in death. No comprehensive review for prevalence and levels of the major bacterial pathogens in raw milk in the US exists. The objective of the present research was to systematically review the scientific literature published from 2000 to 2019 to estimate the prevalence and levels of Listeria monocytogenes, Salmonella spp., Shiga toxin-producing Escherichia coli (STEC), and Campylobacter spp. in raw milk in the US. Peer-reviewed studies were retrieved systematically from PubMed®, Embase®, and Web of ScienceTM. The unique complete nonduplicate references were uploaded into the Health Assessment Work Collaborative (HAWC). Based on the selection criteria, twenty studies were included in the systematic review and meta-analysis. Comprehensive Meta-Analysis (CMA) was used for statistical analyses, specifically, random effects meta-analyses were used to synthesize raw bulk tank milk (BTM) and milk filters (MF) data. Data from studies using culture and non–culture-based detection methods were included. Forest plots generated in CMA (Biostat, Englewood, NJ) were used to visualize the results. The average prevalence (event rate) of L. monocytogenes, Salmonella spp., STEC, and Campylobacter spp. in raw BTM in the US was estimated at 4.3% (95% confidence intervals [CIs], 2.8–6.5%), 3.6% (95% CIs, 2.0–6.2%), 4.3% (95% CIs, 2.4–7.4%), and 6.0% (95% CIs, 3.2–10.9%), respectively. Estimated prevalence was generally larger in MF than in BTM. There was not enough data to perform a meta-analysis for the prevalence or levels of pathogens in raw milk from retail establishments or other milk categories.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Operando characterization and regulation of metal dissolution and redeposition dynamics near battery electrode surface

Mn dissolution has been a longstanding, ubiquitous issue that negatively impacts the performance of Mn-based battery materials. Mn dissolution involves complex chemical and structural transformations at the electrode-electrolyte interface. The continuously evolving electrodeelectrolyte interface has posed great challenges for characterizing the dynamic interfacial process and quantitatively establishing the correlation with battery performance. In this study, we visualize and quantify the temporally and spatially resolved Mn dissolution/redeposition (D/R) dynamics of electrochemically operating Mn-containing cathodes. The particle-level and electrode-level analyses reveal that the D/R dynamics is associated with distinct interfacial degradation mechanisms at different states of charge. Our results statistically differentiate the contributions of surface reconstruction and Jahn-Teller distortion to the Mn dissolution at different operating voltages. Introducing sulfonated polymers (Nafion) into composite electrodes can modulate the D/R dynamics through trapping the dissolved Mn species and rapidly establishing the local Mn D/R equilibrium. This work represents an inaugural effort to pinpoint the chemical and structural transformations responsible for Mn dissolution via an operando synchrotron study and develops an effective method to regulate Mn interfacial dynamics for improving battery performance.

25 ENERGY STORAGE↗
DOE OSTI2016

Proper orthogonal decomposition analysis of parallel twin jets measured using particle image velocimetry - 18685

The mixing of turbulent jets has been found in several locations of High Temperature Gas-cooled Reactors (HTGRs) including upper and lower plenums, where jets impinge into open space from coolant channels. In the present work, a parallel twin jets experimental facility was used to generate velocity field of mixing jets by means of Particle Image Velocimetry (PIV), which can be eventually used for validation of Computational Fluid Dynamics (CFD) simulations. The facility has two fixed parallel rectangular jet nozzles (5.8 mm in width, 87.8 mm in length) submerged in the middle of the water tank, which allows an assumption of free jet mixing. In order to compare the experimental data produced to existing data, Re = 4000 {approx} 5000 at the jet outlet was selected. In the past, several statistically meaningful data have been reported using Laser Doppler Velocimetry (LDV) and Hot Wire Anemometer (HWA), which can support Reynolds Averaged Navier-Stokes turbulent models. However, recent CFD simulations using Large Eddy Simulation (LES) require high resolution experimental data in time and space. Thus, in this study, in addition to statistically enough number of data sets for RANS models validation, high temporal and spatial resolution data were collected for the validation of LES calculations. In order to study the turbulent structure Reynolds decomposition and Proper Orthogonal Decomposition (POD) were applied to the data obtained. These decomposition analyses visualized multi-scale vortices and the transportation of eddies. In terms of twin jets structure, the present experimental data showed good agreement with other techniques for the important characteristic parameters including the length of the converging region and the location of the merging point. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Guide to Using the WIND Toolkit Validation Code

In response to the U.S. Department of Energy's goal of using 20% wind energy by 2030, the Wind Integration National Dataset (WIND) Toolkit was created to provide information on wind speed, wind direction, temperature, surface air pressure, and air density on more than 126,000 locations across the United States from 2007 to 2013. The numerical weather prediction model output, gridded at 2-km and at a 5-minute resolution, was further converted to detail the wind power production time series of existing and potential wind facility sites. For users of the dataset it is important that the information presented in the WIND Toolkit is accurate and that errors are known, as then corrective steps can be taken. Therefore, we provide validation code written in R that will be made public to provide users with tools to validate data of their own locations. Validation is based on statistical analyses of wind speed, using error metrics such as bias, root-mean-square error, centered root-mean-square error, mean absolute error, and percent error. Plots of diurnal cycles, annual cycles, wind roses, histograms of wind speed, and quantile-quantile plots are created to visualize how well observational data compares to model data. Ideally, validation will confirm beneficial locations to utilize wind energy and encourage regional wind integration studies using the WIND Toolkit.

17 WIND ENERGY↗
DOE OSTI2022

Triton Field Trials - Changes in Habitats, a Literature Review of Monitoring Technologies

Marine energy devices are installed in highly dynamic environments and have the potential to affect benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats. Selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years, as well as national and international guidelines for surveying habitats around offshore activities. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Sampling designs varied considerably among the reviewed studies but transect was the predominant design for surveying seafloor, epifauna, and pelagic habitats. The most common data analyses were univariate and multivariate statistical analyses aimed at calculating and comparing biodiversity indices, characterizing faunal assemblages or sediment classes, or modeling the distribution of animals related to abiotic parameters. Technologies and sampling methods adaptable and designed to work efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗