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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 OSTI2016

Magnetotelluric Data Collected in 2016 over the San Emidio Geothermal Field in Nevada

This data set includes the magnetotelluric (MT) data collected from October 21 to November 9, 2016 over the San Emidio geothermal field in Nevada by Quantec Geoscience USA Inc. on behalf of US Geothermal Inc. as part of a project entitled "A Novel Approach to Map Permeability Using Passive Seismic Emission Tomography". This data set includes descriptions of the instrumentation, data acquisition and processing procedures, as well as the final processed data and digital archive formats. A total of 81 MT locations were surveyed (52 profile sites, and 29 MT sites). Data were processed and inspected for quality assurance on site, and reviewed daily by the geophysicist in charge of the project.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

NSLS-II biomedical beamlines for micro-crystallography, FMX, and for highly automated crystallography, AMX: New opportunities for advanced data collection

We present the final design of the x-ray optics and experimental stations of two macromolecular crystallography (MX) beamlines at the National Synchrotron Light Source-II. The microfocusing FMX beamline will deliver a flux of ∼5×10{sup 12} ph/s at 1 Å into a 1 – 20 µm spot, its flux density surpassing current MX beamlines by up to two orders of magnitude. It covers an energy range from 5 – 30 keV. The highly automated AMX beamline is optimized for high throughput, with beam sizes from 4 – 100 µm, an energy range of 5 – 18 keV and a flux at 1 Å of ∼10{sup 13} ph/s. A focus in designing the beamlines lay on achieving high beam stability, for example by implementing a horizontal bounce double crystal monochromator at FMX. A combination of compound refractive lenses and bimorph mirror optics at FMX supports rapid beam size changes. Central components of the in-house developed experimental stations are horizontal axis goniometers with a target sphere of confusion of 100 nm, piezo-slits for dynamic beam size changes during diffraction experiments, dedicated secondary goniometers for data collection from specimen in crystallization plates, and next generation pixel array detectors. FMX and AMX will support a broad range of biomedical structure determination methods from serial crystallography on micron-sized crystals, to structure determination of complexes in large unit cells, to rapid sample screening and room temperature data collection of crystals in trays.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Participant Assisted Data Collection Methods in the California Healthy Homes Indoor Air Quality Study of 2011-13

From November 2011 to March 2013, air quality was measured over 6-day periods in 324 residences across California using a mail-out strategy. All interactions with study participants, from recruitment, to data collection, to communication of results, were conducted with remote communication methods including conventional mail, electronic mail, telephone and text messaging. Potential participants were reached primarily by sharing study information with community groups and organizations that directed interested individuals to complete an online screening survey. Pollutant concentrations were measured with sampling equipment that was mailed to participants’ homes with deployment instructions. Residence and household characteristics and activity data were collected via two phone surveys and an activity log. A comparison of responses to survey questions completed online versus over the phone indicated that a substantial fraction of participants (roughly 20%) required a researcher’s assistance to respond to basic questions about appliance characteristics. Using the printed instructions and telephone assistance from researchers, roughly 90% of participants successfully deployed and returned sampling materials accurately and on schedule. The mail-out strategy employed in this study was found to be a cost-effective means for collecting residential air quality data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Participant Assisted Data Collection Methods in the California Healthy Homes Indoor Air Quality Study of 2011-13

From November 2011 to March 2013, air quality was measured over 6-day periods in 324 residences across California using a mail-out strategy. All interactions with study participants, from recruitment, to data collection, to communication of results, were conducted with remote communication methods including conventional mail, electronic mail, telephone and text messaging. Potential participants were reached primarily by sharing study information with community groups and organizations that directed interested individuals to complete an online screening survey. Pollutant concentrations were measured with sampling equipment that was mailed to participants' homes with deployment instructions. Residence and household characteristics and activity data were collected via two phone surveys and an activity log. A comparison of responses to survey questions completed online versus over the phone indicated that a substantial fraction of participants (roughly 20%) required a researcher's assistance to respond to basic questions about appliance characteristics. Using the printed instructions and telephone assistance from researchers, roughly 90% of participants successfully deployed and returned sampling materials accurately and on schedule. The mail-out strategy employed in this study was found to be a cost-effective means for collecting residential air quality data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Quantification of Data Needs, Data Collection and

Further to the development of a model analysis framework suitable for calibration and validation of complex multivariate multiphysics models, this report presents an approach to data collection and characterization which can work in parallel with the above-mentioned model analysis framework and support the calibration and validation of the case-study subcooled flow boiling model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

PNWSGD Data Collection: Ellensburg, WA

5-minute energy data from January 1, 2008 - December 31, 2014 for the City of Ellensburg, WA, U.S.A. This data was collected under the Pacific Northwest Smart Grid Demonstration Project under the American Recovery and Reinvestment Act (ARRA).

Kuchar, Olga Anna↗
DOE OSTI2017

Comparing Methods for Assessing Reliability Uncertainty Based on Pass/Fail Data Collected Over Time

In this paper, we compare statistical methods for analyzing pass/fail data collected over time; some methods are traditional and one (the RADAR or Rationale for Assessing Degradation Arriving at Random) was recently developed. These methods are used to provide uncertainty bounds on reliability. We make observations about the methods' assumptions and properties. Finally, we illustrate the differences between two traditional methods, logistic regression and Weibull failure time analysis, and the RADAR method using a numerical example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Next-Level Energy Management in Manufacturing: Facility-Level Energy Digital Twin Framework Based on Machine Learning and Automated Data Collection

This research introduces an energy prediction framework at the facility level supported by automated data collection and machine learning models. It investigates whether reducing the prediction time scale allows for applying more complex machine learning techniques and if those techniques improve the prediction accuracy. The primary advantages of this framework lie in its automation of the energy prediction process and its provision of real-time energy data suitable for use in energy dashboards or digital twins. A sitewide dataset was created by combining 15 min energy and daily production data of five shops—assembly, battery, body (electric), body (gas), and paint—from a globally recognized electric vehicle manufacturer. Various machine learning models were evaluated on daily, weekly, and monthly datasets, including, in increasingly complex order: naïve, simple linear regression, net regularized generalized linear regression, principal component regression, k-nearest neighbor, random forest, and Bayesian regularized neural network. Compared to the current state-of-the-art energy consumption prediction for the industrial facility level, this research investigates more complex models and smaller time intervals for higher accuracy. The findings revealed that the more complex monthly models require a minimum of a year and a half of data to operate, while weekly models demand a year of data to achieve improved accuracy. Daily models can operate with only six months of data but exhibit poor performance due to reduced prediction accuracy of production. Key challenges identified include access to reliable, high-quality energy and production data and the initial demand for human labor.

digital twin↗
DOE OSTI2021

An analysis of gamma-ray data collected at traffic intersections in Northern Virginia

Gamma-ray spectral data were collected from sensors mounted to traffic signals around Northern Virginia. The data were collected over a span of approximately fifteen months. A subset of the data were analyzed manually and subsequently used to train machine-learning models to facilitate the evaluation of the remaining 50k anomalous events identified in the dataset. We describe the analysis approach used here and discuss the results in terms of radioisotope classes and frequency patterns over day-of-week and time-of-day spans. Data from this work has been archived and is available for future and ongoing research applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

DOE COVID-19 Data Curation Effort: Overview of Initial Data Collection Coverage (March - June 2020)

During the COVID-19 pandemic of 2020, major case reporting outlets quickly coalesced around two or three primary vendors. Johns Hopkins University and The New York Times were among the more prominent, and all were of great value to the nation, particularly during the uncertain early stages of the pandemic. They primarily focused on three major attributes: number of new cases, deaths, and recovery, but only at the state level. Recognizing that many states were reporting very detailed data sets (e.g., hospital beds) at a count level or finer, the ORNL Pandemic Modeling team embarked on a major data curation effort from March to June 2020 for the purpose of capturing this wealth of detailed data. The challenge of curating this data was daunting. The number of attributes reported by the states grew on almost on a weekly basis. States were routinely shifting their web tool strategies away from easily parsable HTML-based formatting to new Tableau and ArcGIS content. This growth in the sheer number of attributes combined with the unpredictable shifts in data format meant an aggressive and agile combination of automated scripting and manual scraping was required to capture new daily streams. To keep up, the team had to scale up staff and widen its approach for capture and storage. The DOE COVID-19 data collection effort resulted in over 11 million data points being collected, covering over 13,000 unique geographies and over 2,000 unique attributes that spanned predominantly from early March through the end of June 2020.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Modified Data Collection And Analysis Codes Of Using Tcm (thermal Conductivity Microscope) To Measure Thermal Conductivity And Diffusivity

The "data collection" basically involves setting up the thermal wave frequency, laser scan distance, and other parameters related to the experimental setup. The modification of this code is minor and the details of this code can be found in the earlier patent ("thermal conductivity microscope"). The "data analysis" instead, replaces the simplified analytical model by a more complete analytical model, and used a "thermoquadruple" method to solve the analytical model. The efficiency is orders of magnitude improved and the accuracy is also better. Meanwhile, the previous model can only handle a two-layer sample structure. The new, complete model can handle materials with multiple layers (any given number), which is necessary to handle post ion irradiated materials.

Hua, Zilong [Idaho National Laboratory (INL), Idah↗
DOE OSTI2015

Neutron and high-resolution room-temperature X-ray data collection from crystallized lytic polysaccharide monooxygenase

Bacteria and fungi express lytic polysaccharide monooxgyenase (LPMO) enzymes that act in conjunction with canonical hydrolytic sugar-processing enzymes to rapidly convert polysaccharides such as chitin, cellulose and starch to single monosaccharide products. In order to gain a better understanding of the structure and oxidative mechanism of these enzymes, large crystals (1–3 mm 3 ) of a chitin-processing LPMO from the Gram-positive soil bacterium Jonesia denitrificans were grown and screened for their ability to diffract neutrons. In addition to the collection of neutron diffraction data, which were processed to 2.1 Å resolution, a high-resolution room-temperature X-ray diffraction data set was collected and processed to 1.1 Å resolution in space group P 2 1 2 1 2 1 . To our knowledge, this work marks the first successful neutron crystallographic experiment on an LPMO. As a result, joint X-ray/neutron refinement of the resulting data will reveal new details of the structure and mechanism of this recently discovered class of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Gamma-ray raster imaging with robotic data collection. FY18 report

This project has developed an alternative imaging capability for measuring radioactive materials in situ. This approach uses a robotic-mounted gamma-ray detector which can move around an area of interest, sampling the space at a high frequency. By rastering across the area, an image can be created with no collimation and a high efficiency. A regression model was developed to map out material distribution as the robot moves through the environment. An informative path planning algorithm was also developed to maximize the information collected throughout the movement path. The use of a robotic mount allows data collection for long periods of time unattended, and it will also eliminate uncertainties in positioning typically introduced by personnel. This approach will be particularly relevant for gloveboxes, shielded cells, or process piping which may have complex, non-uniform distributions of material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Increasing Reliability and Safety of Hydrogen Components - Reliability Data Collection

Come learn about the new Hydrogen Component Reliability Database (HyCReD) and participate in discussions on hydrogen component reliability data collection, collaboration, and analysis. Funded by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy under the Hydrogen and Fuel Cell Technologies Office, HyCReD is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety reliability for hydrogen facilities by integrating risk reduction methodologies and component reliability data taxonomies that support hydrogen infrastructure failure rate analysis.

component↗
DOE OSTI2019

Discharge data collected within the East River for the Lawrence Berkeley National Laboratory Watershed Function Science Focus Area (water years 2015-present)

Discharge data collected at the East River in the Upper Colorado River Basin for the Lawrence Berkeley National Laboratory's Watershed Function Scientific Focus Area. Files contain instantaneous observed discharge data, corrected 10 min and mean daily discharge. Several sites also contain temperature and transducer depth. Please contact Rosemary Carroll if you have any questions or wish to access the raw data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Time domain-induced polarization geophysical data collected in the Rifle Floodplain, Colorado, USA

The IP data set was collected using a time domain-induced polarization (TDIP) method along 65 profiles of various lengths over the floodplain. Surface time domain?induced polarization (TDIP) data was collected to create the 3?D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. The TDIP data was then used to estimate the spatial distribution of naturally reduced zones, which are known to be biogeochemical hotspots in floodplains having increased uranium and other redox-sensitive metal concentrations as well as high carbon contents. In the TDIP method, the transient decay of voltage is measured after current shut-off, typically in the form of an integral of decay curves over a predefined time window (so-called integral chargeability). TDIP measurements at the site were collected using the Syscal Iris Pro Switch equipment with a square-wave current injection, 50% duty cycle, and a pulse length of 2 s. The integral chargeability measurements were carried out using 20 windows during voltage decay between 240 and 1840 ms after current shut-off. Tomographic measurements were collected by deploying stainless steel electrodes with an electrode separation of 1.8 m and using a dipole-dipole ‘‘skip-2’’ and ‘‘skip-3’’ measuring protocol (i.e., for a dipoles length of 5.4 and 7.2 m, respectively). The sequence of dipole-dipole measurements was carefully arranged to (1) minimize unwanted electromagnetic coupling effects in the data, avoiding potential measurements with electrodes located inside the current dipole, (2) prevent voltage measurements using electrodes, which might be polarized due to previous current injection, and (3) increase the signal-to-noise ratio for an intended exploration depth of 8 m, i.e., the bottom of the aquifer. All measurements were collected as normal and reciprocal pairs for estimation of the data error. The IP measurements were collected with symmetric arrays (i.e., the measuring equipment placed at the center of the electrode array) with a maximum of 36 electrodes, considering that longer profiles revealed a significant increase in the normal-reciprocal misfit for the measurements of the decay curve, probably due to greater impact of electromagnetic coupling on the data. The TDIP data sets were inverted in a twodimensional domain along each transect using CRTomo, which is a smoothness-constraint inversion code based on a finite element algorithm. The resistivity and phase shift values at each pixel were then assigned at the corresponding point within the 3-D floodplain domain (the black rectangle Figure 1b) and used in the 3-D estimation. The TDIP inversion results provided the distribution of the complex resistivity, expressed in terms of its magnitude and phase-shift. The analysis of the normal-reciprocal misfit was used to estimate the relative error. We removed the measurement with smallest voltage difference (<2 mV), representing about 2% variations in the data. For the inversion of TDIP measurements, chargeability values were linearly converted to frequency domain phase values (at the fundamental frequency of 0.125 Hz), by assuming a constant-phase response. This approach has been demonstrated to provide consistent results in previous studies

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

MicroED data collection and processing

The collection and processing of MicroED data are presented. MicroED, a method at the intersection of X-ray crystallography and electron cryo-microscopy, has rapidly progressed by exploiting advances in both fields and has already been successfully employed to determine the atomic structures of several proteins from sub-micron-sized, three-dimensional crystals. A major limiting factor in X-ray crystallography is the requirement for large and well ordered crystals. By permitting electron diffraction patterns to be collected from much smaller crystals, or even single well ordered domains of large crystals composed of several small mosaic blocks, MicroED has the potential to overcome the limiting size requirement and enable structural studies on difficult-to-crystallize samples. This communication details the steps for sample preparation, data collection and reduction necessary to obtain refined, high-resolution, three-dimensional models by MicroED, and presents some of its unique challenges.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗