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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scanning SQUID characterization of extremely overdoped La 2-x Sr x CuO 4

Recently, advances in film synthesis methods have enabled a study of extremely overdoped La 2 - x Sr x Cu O 4 . This has revealed a surprising behavior of the superfluid density as a function of doping and temperature, the explanation of which is vividly debated. One popular class of models posits electronic phase separation, where the superconducting phase fraction decreases with doping, while some competing phase (e.g., ferromagnetic) progressively takes over. A problem with this scenario is that all the way up to the dome edge the superconducting transition remains sharp, according to mutual inductance measurements. However, the physically relevant scale is the Pearl penetration depth Λ P , and this technique probes the sample on a length scale L that is much larger than Λ P . In the present paper, we use local scanning superconducting quantum interference device (SQUID) measurements that probe the susceptibility of the sample on the scale L << Λ P . Our SQUID maps show uniform landscapes of susceptibility and excellent overall agreement of the local penetration depth data with the bulk measurements. Overall, these results contribute an important piece to the puzzle of how high-temperature superconductivity vanishes on the overdoped side of the cuprate phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms

Occupancy estimation is an important primitive for a wide range of applications including building energy efficiency, safety, and security. In this paper, we explore the potential of using depth sensors to detect, estimate, identify, and track occupants in buildings. While depth sensors have been widely used for human detection and gesture recognition, computer vision algorithms are typically run on a powerful computer like XBOX or Intel R CoreTM i7 processor. In this work, we develop a prototype system called FORK using off-the-shelf components that performs the entire depth data processing on a cheaper and low power ARM processor in real-time. As ARM processors are extremely weak in running computer vision algorithms, FORK is designed to detect humans and track them in a very efficient way by leveraging a novel lightweight model based approach instead of traditional approaches based on histogram of oriented gradients (HOG) features. Unlike other camera based approaches, FORK is much less privacy invasive (even if the sensor is compromised). Based on a complete implementation, real-world deployment, and extensive evaluation at realistic scenarios, we observe that FORK achieves over 99% accuracy in real-time (4-9 FPS) in occupancy estimation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Continuous Snow Depth, Intensive Site 1, Utqiagvik (Barrow), Alaska, 2012-2014

Continuous Snow depth data were collected at several points within four intensive study areas in near Utqiagvik (Barrow), Alaska. All sites were located on polygonal permafrost and co-located with micromet surface measurements and subsurface measurements. These data assist in the calculation of the energy balance at the land surface and will also be useful as inputs into modeling activities. Included are 18 CSV data files and one file level metadata CSV file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Alteration in micro-mechanical characteristics of wellbore cement fracture surfaces due to fluid exposure

The stiffness of wellbore cement fracture surfaces was measured after exposing to the advective flow of nitrogen, silicone oil, and medium sweet dead crude oil for different exposure periods. The test specimens were extracted from fractured cement cylinders, where the cement fracture surfaces were exposed to the different fluids up to 15 weeks. A nanoindenter with a Berkovich indenter tip was used to measure load-indentation depth data, which was used to extract the elastic modulus (E) and nano-hardness (H) of the cement fracture surfaces. A reduction in the elastic modulus compared with an unexposed specimen were observed in all the specimens. Both elastic modulus and nano-hardness for the specimens exposed to silicone oil were lower than specimens exposed to nitrogen gas and varied with the period of exposure. The elastic modulus and nano-hardness of the specimens exposed to crude oil were the lowest with a significant decrement with the exposure period. The frequency distribution of the nanoindentation measurements shows that the volume-fraction ratio of the two types of cement hydrated nanocomposites for both the unexposed and test specimens is about 70:30%. Phase transformation beneath the indenter is observed for all of the specimens, with more obvious plastic deformation in specimens exposed to crude oil. Analytical measurements (SEM, EDS, FT-IR, and XRD) on exposed cement fracture surfaces reveal different levels of physical and chemical alteration that are consistent with the reduction in stiffness measured by nanoindentation. Furthermore, the study suggests that cement stiffness will decrease due to crude oil exposure, and the fracture will be sensitive to stress and pore pressure with time.

42 ENGINEERING↗
DOE OSTI2025

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting

Abstract Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experiments as underlying pathogenic mechanisms are broad and associated with multiple genomic pathways. The scientific community has exerted significant efforts to generate public drug screening datasets, giving a path to various machine learning models that attempt to reason over complex data space of small compounds and biological characteristics of tumors. However, the data depth is still lacking compared to application domains like computer vision or natural language processing domains, limiting current learning capabilities. To combat this issue and improves the generalizability of the DRP models, we are exploring strategies that explicitly address the imbalance in the DRP datasets. We reframe the problem as a multi-objective optimization across multiple drugs to maximize deep learning model performance. We implement this approach by constructing Multi-Objective Optimization Regularized by Loss Entropy loss function and plugging it into a Deep Learning model. We demonstrate the utility of proposed drug discovery methods and make suggestions for further potential application of the work to achieve desirable outcomes in the healthcare field.

Biochemistry & Molecular Biology↗
DOE OSTI2016

SU-C-209-06: Improving X-Ray Imaging with Computer Vision and Augmented Reality

Purpose: To determine the feasibility of using a computer vision algorithm and augmented reality interface to reduce repeat rates and improve consistency of image quality and patient exposure in general radiography. Methods: A prototype device, designed for use with commercially available hardware (Microsoft Kinect 2.0) capable of depth sensing and high resolution/frame rate video, was mounted to the x-ray tube housing as part of a Philips DigitalDiagnost digital radiography room. Depth data and video was streamed to a Windows 10 PC. Proprietary software created an augmented reality interface where overlays displayed selectable information projected over real-time video of the patient. The information displayed prior to and during x-ray acquisition included: recognition and position of ordered body part, position of image receptor, thickness of anatomy, location of AEC cells, collimated x-ray field, degree of patient motion and suggested x-ray technique. Pre-clinical data was collected in a volunteer study to validate patient thickness measurements and x-ray images were not acquired. Results: Proprietary software correctly identified ordered body part, measured patient motion, and calculated thickness of anatomy. Pre-clinical data demonstrated accuracy and precision of body part thickness measurement when compared with other methods (e.g. laser measurement tool). Thickness measurements provided the basis for developing a database of thickness-based technique charts that can be automatically displayed to the technologist. Conclusion: The utilization of computer vision and commercial hardware to create an augmented reality view of the patient and imaging equipment has the potential to drastically improve the quality and safety of x-ray imaging by reducing repeats and optimizing technique based on patient thickness. Society of Pediatric Radiology Pilot Grant; Washington University Bear Cub Fund.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Aerosol Properties Downwind of Biomass Burns Field Campaign Report

We determined the morphological, chemical, and thermal properties of aerosol particles generated by biomass burning during the Biomass Burning Observation Project (BBOP) campaign during the wildland fire season in the Pacific Northwest from July to mid-September, 2013, and in October, 2013 from prescribed agricultural burns in the lower Mississippi River Valley. BBOP was a field campaign of the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility. The morphological information was both two-dimensional, as is typical of most microscopy images and that have many of the characteristic of shadows in that they lack depth data, and three-dimensional (3D). The electron tomographic measurements will provided 3D data, including the presence and nature of pores and interstices, and whether the individual particles are coated by or embedded within other materials. These microphysical properties were determined for particles as a function of time and distance from the respective sources in order to obtain detailed information regarding the time evolution of changes during aging.

aerosol particles, wildland fires, aerosol microph↗
DOE OSTI2016

Determination of the mechanical properties of blisters by nanoindentation

In light-water reactors, a zirconium oxide layer will be formed at the outer surface of the fuel cladding as a consequence of the chemical reaction which takes place between zirconium and the cooling water. This zirconium oxide layer is a good thermal insulator, but at some point, it may spall-out. As a consequence, a cold spot will be formed at the outer surface of the cladding. In this situation, the hydrogen will quickly migrate to this spot to form a highly-enriched hydride zone, known as blister. In this work, an experimental procedure has been devised to produce blisters with a similar shape to the ones reported in the literature for irradiated cladding with severe hydriding. Nano-indentation tests were performed on blisters prepared in laboratory. A numerical simulation by the finite element method was developed to fit the load versus penetration depth data from the aforementioned nano-indentation tests. By means of an inverse process which combines experimental data and numerical simulations, the constitutive equation of the blister was determined. The process has been used to calculate the plastic stress-strain curve of the blister under study at room temperature. The results show an almost perfect numerical fitting of the experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Results of In-Depth Analysis of Data Obtained in the Experimental Search for 2K(2ν)-Capture in {sup 78}Kr

A brief description of the results of joint analysis of data obtained in long-term measurements of krypton samples differing in {sup 78}Kr content is presented. Low-background high-pressure proportional gas counters were used as detectors. The comparative analysis of experimental data on single and double K -capture provided the first estimate of the probability of production of a double K -shell vacancy in the process of K -shell electron capture in {sup 81}Kr: P{sub KK}=[5.7±0.8 (stat.)±0.4 (syst.)]×10{sup −5}. A new result for the half-life of {sup 78}Kr with respect to the 2K(2ν)-mode was also obtained: T{sub 1/2}=[1.9{sub −0.7}{sup +1.3} (stat.)±0.3 (syst.)]×10{sup 22} years (90% CL).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Depth-resolved soil data from DOE-LM Riverton Wyoming site, April-September 2017

Averaged (from 3 to 5 replicates) and QA/QC:d data for soil cores taken roughly every month in the period April 5 to September 13 in 2017 at a location close to DOE Legacy Management well 855 at the Riverton, Wyoming floodplain site. The groundwater at this site exhibits persistent U, Mo, and sulfate plumes and is one of the field sites in focus for the SLAC Groundwater Quality SFA program. Cores were separated into 5-20 cm segments based on soil horizonation and each segment was subsampled for microbial analyses (data available at the NCBI Single Read Archive (SRA) Database, https://www.ncbi.nlm.nih.gov/sra/, BioProject ID# PRJNA626616) in addition to the soil analyses included in this dataset. The soil analyses dataset includes aerobic and anaerobic respiration rate estimates (MicroResp method), water content estimates (on collected samples, not in situ), total C, N, S, Ca, K, Mg, Na, Fe, As, Mo, U, and organic-C concentrations, water extractable concentrations of the same elements, and HCl-extractable Fe(II) concentrations.There are four files included in this data package: metadataFile.csv, avgDataFile.csv, methodFile.csv, and RVT2017soilData.xlsx. The excel file contains the same information as the individual csv-files (in separate tabs).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the Geothermal Play Fairway Analysis of the Appalachian Basin (GPFA-AB) Thermal Quality Analysis (GDR repository 879: https://gdr.openei.org/submissions/879). This dataset improves upon the GPFA-AB dataset by considering several additional uncertainties in the temperature-at-depth calculations, including geologic properties and thermal properties. A Monte Carlo analysis of these uncertain properties and the GPFA-AB estimated surface heat flow was used to predict temperatures at depth using a 1-D heat conduction model. In this data submission, temperatures are provided for depths from 1-5 km in 0.5 km increments. The mean, standard deviation, and selected quantiles of temperatures at these depths are provided as shapefiles with attribute tables that contain the data. Rasters are provided for the mean and standard deviation data. Figures and maps that summarize the data are also provided. For the pixel corresponding to Cornell University, Ithaca, NY, a .csv file containing the 10,000 temperature-depth profiles estimated from the Monte Carlo analysis is provided. These data are summarized in a figure containing violin plots that illustrate the probability of obtaining certain temperatures at depths below Cornell.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

SU-E-T-554: Comparison of Electron Disequilibrium Factor in External Photon Beams for Different Models of Linear Accelerators

Purpose: The dose in the buildup region of a photon beam is usually determined by the transport of the primary secondary electrons and the contaminating electrons from accelerator head. This can be quantified by the electron disequilibrium factor, E, defined as the ratio between total dose and equilibrium dose (proportional to total kerma), E = 1 in regions beyond buildup region. Ecan be different among accelerators of different models and/or manufactures of the same machine. This study compares E in photon beams from different machine models/ Methods: Photon beam data such as fractional depth dose curve (FDD) and phantom scatter factors as a function of field size and phantom depth were measured for different Linac machines. E was extrapolated from these fractional depth dose data while taking into account inverse-square law. The ranges of secondary electron were chosen as 3 and 6 cm for 6 and 15 MV photon beams, respectively. The field sizes range from 2x2 to 40x40 cm{sup 2}. Results: The comparison indicates the standard deviations of electron contamination among different machines are about 2.4 - 3.3% at 5 mm depth for 6 MV and 1.2 - 3.9% at 1 cm depth for 15 MV for the same field size. The corresponding maximum deviations are 3.0 - 4.6% and 2 - 4% for 6 and 15 MV, respectively. Both standard and maximum deviations are independent of field sizes in the buildup region for 6 MV photons, and slightly decreasing with increasing field size at depths up to 1 cm for 15 MV photons. Conclusion: The deviations of electron disequilibrium factor for all studied Linacs are less than 3% beyond the depth of 0.5 cm for the photon beams for the full range of field sizes (2-40 cm) so long as they are from the same manufacturer.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

SU-E-T-238: Deriving Electron Contamination Spectra From Pure and Clinical Photon Beams

Purpose: To extract the electron contamination energy spectra for an Elekta Precise Linac, based on pure photon and measured clinical beam percentage depth dose data. And to include this as an additional source in isource 4 in DOSXYZnrc. Methods: A pure photon beam was simulated for the Linac using isource 4 in the DOSXYZnrc Monte Carlo (MC) code. Percentage depth dose (PDD) data were extracted afterwards for a range of field sizes (FS). These simulated dose data were compared to actual measured dose PDD data, with the data normalized at 10 cm depth. The resulting PDD data resembled the electron contamination depth dose. Since the dose fall-off is a strictly decreasing function, a method was adopted to derive the contamination electron spectrum. Afterwards this spectrum was used in a DOSXYZnrc MC simulation run to verify that the original electron depth dose could be replicated. Results: Various square aperture FS’s for 6, 8 and 15 megavolt (MV) photon beams were modeled, simulated and compared to their respective actual measured PDD data. As FS increased, simulated pure photon depth-dose profiles shifted deeper, thus requiring electron contamination to increase the surface dose. The percentage of electron weight increased with increase in FS. For a FS of 15×15 cm{sup 2}, the percentage electron weight is 0.1%, 0.2% and 0.4% for 6, 8 and 15 MV beams respectively. Conclusion: From the PDD results obtained, an additional electron contamination source was added to the photon source model so that simulation and measured PDD data could match within 2 % / 2 mm gamma-index criteria. The improved source model could assure more accurate simulations of surface doses. This research project was funded by the South African Medical Research Council (MRC) with funds from National Treasury under its Economic Competitiveness and Support package.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Estimating heterotrophic respiration at large scales: challenges, approaches, and next steps

Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of "Decomposition Functional Types" (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing models to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present and discuss an example clustering analysis to show how model-produced annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from already-existing PFTs. A similar analysis, incorporating observational data, could form a basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with high-performance computing; rigorous testing of analytical results; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR at large scales.

carbon cycle↗
DOE OSTI2021

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data for Influence of soil depth, irrigation, and plant genotype on the soil microbiome, metaphenome, and carbon chemistry: Summary Data

Climate change is causing an increase in drought in many soil ecosystems and a loss of soil organic carbon. Calcareous soils may partially mitigate these losses via carbon capture and storage. Here, we aimed to determine how irrigation-supplied soil moisture and perennial plants impact biotic and abiotic soil properties that underpin deep soil carbon chemistry in an unfertilized calcareous soil. Soil was sampled up to one meter in depth from irrigated and planted field treatments and analyzed using a suite of omics and chemical analyses. Carbon cycling processes in the surface soil were dominated by plant-microbe interactions that drive organic carbon cycling, whereas inorganic carbon chemistry dominated in deeper soil layers. Both irrigation and plant cover impacted organic and inorganic carbon pools in the soil profiles. This study reveals the complex interactions between water, plants, minerals, and microorganisms that govern organic and inorganic pools of soil carbon at different depths.

Naasko, Katherine I↗