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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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NASA NTRS2008

Implementing a Digital Phasemeter in an FPGA

Firmware for implementing a digital phasemeter within a field-programmable gate array (FPGA) has been devised. In the original application of this firmware, the phase that one seeks to measure is the difference between the phases of two nominally-equal-frequency heterodyne signals generated by two interferometers. In that application, zero-crossing detectors convert the heterodyne signals to trains of rectangular pulses, the two pulse trains are fed to a fringe counter (the major part of the phasemeter) controlled by a clock signal having a frequency greater than the heterodyne frequency, and the fringe counter computes a time-averaged estimate of the difference between the phases of the two pulse trains. The firmware also does the following: Causes the FPGA to compute the frequencies of the input signals; Causes the FPGA to implement an Ethernet (or equivalent) transmitter for readout of phase and frequency values; and Provides data for use in diagnosis of communication failures. The readout rate can be set, by programming, to a value between 250 Hz and 1 kHz. Network addresses can be programmed by the user.

Rao, Shanti R.↗

DOE OSTI2020

Specifying Calibration of Environmental Sensors

The emergence of the Internet of Things is resulting in an increased ability of devices and systems to share data and is generating increasing interest in integrating sensors into a variety of devices deployed in the built environment. The value of such data is a function of how the data can be used. Data-producing devices and systems that enable valuable use-cases in turn can be seen as more valuable. Lighting systems are particularly interesting platforms for integrated sensors. Both indoor and outdoor lighting devices are becoming more connected, and their location is often ideally suited for hosting environmental sensors that can characterize the properties of indoor or outdoor spaces in ways that support a wide variety of use cases, from improving air quality to supporting fault diagnostics and prediction. The value of environmental-sensor-driven use-cases and the lighting systems that house them is dependent to some degree on sensor accuracy. Environmental sensors utilize a wide variety of sensing techniques or technologies and have varying accuracy. More-accurate, laboratory-grade products or reference standards are often used to characterize, refine, calibrate, adjust, and monitor devices that are deployed, or are intended to be deployed, in physical spaces of interest. Sensors or reference standards need to be calibrated periodically to ensure that their use yields accurate measurements. Calibration needs, however, vary in sophistication, based on user and use-case requirements. This paper provides guidance for evaluating the performance of environmental sensors so as to ensure that they meet user or use-case needs. It describes best practices that have been developed for a) calibrating sensors to ensure some known level of accuracy, and b) determining whether calibration-laboratory accreditation meets user or use-case needs. Excerpts from laboratory scopes of accreditation are shared to reveal the diversity of terminology and format among them. In an effort to aid those who currently have sensors calibrated or who have new or changing needs for sensor calibration, rationale is provided for why a specification might be used to request calibration services that meet specific needs. Commercially available calibration-service providers that are accredited for environmental-sensor calibration are compared and contrasted, and a specification template that might be used for requesting this calibration is presented. The specification template should be tailored to meet each user’s needs. To illustrate, an example set of environmental-sensor test conditions (reflecting the planned usage of the device to be calibrated) is used to develop a customized calibration specification, and commercially available service providers are assessed in terms of their qualifications for calibration to that particular implementation of the specification template.

42 ENGINEERING↗

DOE OSTI2025

Laboratory time series moisture manipulative experiment from sediment across San Antonio, Texas: time series aerobic respiration and geochemistry

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration. The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS Allison Veach collaboration (AV1). The data package associated with the AV1 study is available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2529428. AV1 sampling occurred across 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). This study uses subsamples from a subset of AV1 samples. The original field samples were labeled as AV1_###. Subsequent subsamples for this study were labeled as EV_###. The labels from the field samples and the EV subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EV_001 is a subsample from AV1_001). See the critical details section below for more details on sample naming. 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) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) effect size; (2) iron (II); (3) gravimetric moisture; (4) respiration rates; (5) raw dissolved oxygen values and plots; (6) specific conductance; (7) pH; (8) temperature; (9) a summary containing mean, median, and standard deviation values of each data type for each treatment (wet and dry); and (10) methods codes. All files are .csv or.pdf.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

Electrochemical impedance spectroscopy of metal alloys in the space transportation system launch environment

AC impedance measurements were performed to investigate the corrosion resistance of 18 alloys under conditions similar to the Space Transportation System (STS) launch environment. The alloys were: (1) zirconium 702; (2) Hastelloy C-22, C-276, C-4, and B-2; (3) Inconel 600 and 825; (4) Ferralium 255; (5) Inco Alloy G-3; (6) 20Cb-3; (7) SS 904L, 304LN, 316L, 317L, and 304L; (8) ES 2205; and (9) Monel 400. AC impedance data were gathered for each alloy at various immersion times in 3.55 percent NaCl-0.1N HCl. Polarization resistance values were obtained for the Nyguist plots at each immersion time using the EQUIVALENT CIRCUIT software package available with the 388 electrochemical impedance software. Hastelloy C-22 showed the highest overall values for polarization resistance while Monel 400 and Inconel 600 had the lowest overall values. There was good general correlation between the corrosion performance of the alloys at the beach corrosion testing site, and the expected rate of corrosion as predicted based on the polarization resistance values obtained. The data indicate that electrochemical impedance spectroscopy can be used to predict the corrosion performance of metal alloys.

Calle, Luz↗

DOE OSTI2013

'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elements of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.

Big Data↗

NASA NTRS1980

Potential impacts of Brayton and Stirling cycle engines

Two engine technologies (Brayton cycle and Stirling cycle) are examined for their potential economic impact and fuel utilization. An economic analysis of the expected response of buyers to the attributes of the alternative engines was performed. Hedonic coefficients for vehicle fuel efficiency, performance and size were estimated for domestic cars based upon historical data. The marketplace value of the fuel efficiency enhancement provided by Brayton or Stirling engines was estimated. Under the assumptions of 10 years for plant conversions and 1990 and 1995 as the introduction data for turbine and Stirling engines respectively, the comparative fuel savings and present value of the future savings in fuel costs were estimated.

Heft, R. C.↗

NASA NTRS2014

Forecasting Sensorimotor Adaptability from Baseline Inter-Trial Correlations

One of the greatest challenges surrounding adaptation to the spaceflight environment is the large variability in symptoms, and corresponding functional impairments, from one crewmember to the next. This renders preflight training and countermeasure development difficult, as a "one-size-fits-all" approach is inappropriate. Therefore, it would be highly advantageous to know ahead of time which crewmembers might have more difficulty adjusting to the novel g-levels inherent to spaceflight. Such knowledge could guide individually customized countermeasures, which would enable more efficient use of crew time, both preflight and inflight, and provide better outcomes. The primary goal of this project is to look for a baseline performance metric that can forecast sensorimotor adaptability without exposure to an adaptive stimulus. We propose a novel hypothesis that considers baseline inter-trial correlations, the trial-to-trial fluctuations in motor performance, as a predictor of individual sensorimotor adaptive capabilities. To-date, a strong relationship has been found between baseline inter-trial correlations and adaptability in two oculomotor systems. For this project, we will explore an analogous predictive mechanism in the locomotion system. METHODS: Baseline Inter-trial Correlations: Inter-trial correlations specify the relationships among repeated trials of a given task that transpire as a consequence of correcting for previous performance errors over multiple timescales. We can quantify the strength of inter-trial correlations by measuring the decay of the autocorrelation function (ACF), which describes how rapidly information from past trials is "forgotten." Processes whose ACFs decay more slowly exhibit longer-term inter-trial correlations (longer memory processes), while processes whose ACFs decay more rapidly exhibit shorterterm inter-trial correlations (shorter memory processes). Longer-term correlations reflect low-frequency activity, which is more easily measured in the frequency domain. Therefore, we use the power spectrum (PS), which is the Fourier transform of the ACF, to describe our inter-trial correlations. The decay of the PS yields a straight line on a log-log frequency plot, which we quantify by Beta = - (slope of PS on log-log axes). Hence, Beta is a measure of the strength of inter- trial correlations in the baseline data. Larger Beta values are indicative of longer inter-trial correlations. Experimental Approach: We will begin by performing a retrospective analysis of treadmill-gait adaptation data previously collected by Dr. Bloomberg and colleagues. Specifically, we will quantify the strength of inter-trial correlations in the baseline step cadence and heart rate data and compare it to the locomotor adaptability performance results already described by these investigators. Incorporating these datasets will also allow us to explore the applicability of (and potential limitations surrounding) the use of Beta in forecasting physiological performance. We will also perform a new experiment, in which Beta will be derived from baseline data collected during over-ground (non-treadmill) walking, which will enable us to consider locomotor performance, through the parameter Beta, under the most functionallyrelevant, natural gait condition. This experiment will incorporate two baseline and five post-training over-ground locomotion tests to explore the consistency and potential adaptability of the Beta values themselves. HYPOTHESES: We hypothesize that the strength of baseline inter-trial correlations of step cadence and heart rate will relate to locomotor adaptability. Specifically, we anticipate that individuals who show weaker longer-term inter-trial correlations in baseline step cadence data will be the better adaptors, as step cadence can be modified in real-time (i.e., online corrections are an inherent property of the locomotor system; analogous to results observed in the VOR). Conversely, because heart rate is not altered mid-beat, we expect that individuals who demonstrate stronger longer-term correlations in heart rate will be the better adaptors (analogous to results observed in the saccadic system). CONCLUSIONS: At the conclusion of this project we hope to uncover a baseline predictor of locomotor adaptability. If our hypotheses hold true, our results will demonstrate that the temporal structure of baseline behavioral data contains important information that may aid in forecasting adaptive capacities. The ability to predict such adaptability in the sensorimotor system has significant implications for spaceflight, where astronauts must adjust their motor programs following a change in g-level to retain movement accuracy.

Beaton, K. H.↗

NASA NTRS2018

NASA Earth Science Data Rescue Efforts

Historically, at the end of a NASA mission, earth and space science data were stored at NASA's National Space Science Data Center (NSSDC). The original data archive consisted of both magnetic tapes and film media. As data storage technology improved, data from later missions were stored on disks and platters and higher capacity magnetic media for online accessibility. To conserve physical space at NASA archive sites and to meet disaster recovery guidelines, historical data originally stored on magnetic tapes and film were moved to the Federal Archives and Record Center (FRC) as a temporary holding area until its long-term value was determined by NASA. All records at the FRC are controlled by the NASA Records Retention Schedule (NRRS) which determines the disposal date for each record. On that date, responsible NASA parties are notified that all scheduled records should be reviewed and assessed to determine if they continue to hold significant historical, scientific or administrative value. For Earth Science data records being held at FRC, the Earth Science Data and Information System (ESDIS) Project office is the party responsible for making the value assessment that determines which records warrant preservation and which are ready for proper disposal according to NASA guidelines. Once the data's long-term value is determined, ESDIS takes definitive steps to preserve this data for future discovery and access. Deteriorating media containing historic data of value are recalled from FRC and brought back to ESDIS. Through a tedious, laborious process, digital data are recovered and restored to modern formats with improved metadata and documentation to aid discovery. The restored digital products are then incorporated into our modern online archive, and made immediately accessible to the public. In this paper, we will discuss how we identify data-at-risk, ways to minimize data loss, how we plan for recovery, how we delegate recovery activities to our archive facilities, and how we make recovered data more accessible.

Data Systems; Social and Information sciences↗

NASA NTRSDate not supplied

MEDLI2: MISP Inferred Aerothermal Environment and Flow Transition Assessment

The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite on the Mars2020 mission contained multiple sensors on the aeroshell to measure the aerothermal environment during entry into the Martian atmosphere. These sensors performed superbly and successfully returned forebody and aftbody heating measurements. Analysis of MEDLI2 data indicated flow transitioning from a laminar to turbulent state on the heatshield. No evidence of flow transition was observed on the backshell. Two methods were used to estimate flow transition times on the heatshield: (1) temperature gradient of near-surface thermocouple data and (2) heat flux gradient from an inverse reconstruction approach using thermocouple data and material response modeling. Both methods produced similar transition times with an estimated accuracy of ±1 s. To assess various transition criteria, transition parameters were evaluated at each sensor location using flow field solutions from computational fluid dynamics (CFD) simulations. The idea was to use conservative values inferred from MEDLI2 data as transition criteria for other Mars missions. To test this hypothesis, MEDLI data from the Mars Science Laboratory (MSL) mission was used to compare predicted vs. actual flow transition times. The comparisons suggest smooth wall transition criteria are not well-suited in modeling the rapid progression of a turbulent transition front. Transition criteria containing a roughness element parameter agreed better with the flight data. In summary, critical transition values derived from MEDLI2 data may be used as a starting point in constructing a flow transition model for future Mars missions.

Chun Y Tang↗

DOE OSTI2011

Numerical modeling of the elution peak profiles of retained solutes in supercritical fluid chromatography

In supercritical fluid chromatography (SFC), the significant expansion of the mobile phase along the column causes the formation of axial and radial gradients of temperature. Due to these gradients, the mobile phase density, its viscosity, its velocity, its diffusion coefficients, etc. are not constant throughout the column. This results in a nonuniform flow velocity distribution, itself causing a loss of column efficiency in certain cases, even at low flow rates, as they do in HPLC. At high flow rates, an important deformation of the elution profiles of the sample components may occur. The model previously used to account satisfactorily for the retention of an unsorbed solute in SFC is applied to the modeling of the elution peak profiles of retained compounds. The numerical solution of the combined heat and mass balance equations provides the temperature and the pressure profiles inside the column and values of the retention time and the band profiles of retained compounds that are in excellent agreement with independent experimental data for large value of mobile phase reduced density. At low reduced densities, the band profiles can strongly depend on the column axial distribution of porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Data Mining Scientific Literature Demonstrates Use of Biological and Medical Data Across Scientific Disciplines

The Protein Data Bank (PDB) was established as the 1st open access digital data resource in biology and medicine. Today, the PDB archive contains over 140,000 atomic‐level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. About 20 new structures are deposited daily. PDB data is used in basic and applied research, patent applications, discovery of lifesaving drugs, product innovation, and education. About 80% of all PDB structures deposited have a “primary citation,” which is the first paper to describe the molecule and its structure and function. In turn, these primary citations have contributed to more than 1 million publications. An initial study by Clarivate Analytics on the Nucleic Acids Research publication demonstrated that PDB data drive high‐impact research in diverse scientific fields. To build on this study, we used Python programming to perform several data mining studies to understand the impact of these structures in fundamental biology, biomedicine, and energy in the scientific literature. The scientific literature database, Web of Science, tracks scientific article metrics such as the number of times cited, subject category, year published, funding source, and keywords. Web of Science data for PDB primary citations was compiled as used as the data set. Two main investigations were performed. In the first, we examined the number of citations per article (data overall and by individual subject categories) to develop “top 10 cited structures” lists and analyzed for trends. In the second investigation, we extended our data mining analysis to consider for each main subject category, the papers with the most citations and the structures they cite, and the most frequently occuring keywords. We have observed different aspects of biological data utility in various subject areas, at times in ways unanticipated from the structures' primary citation. This research demonstrates the value of biological data from the PDB by showing the diverse ways in which the data are being used. Support or Funding Information RCSB PDB is funded by a grant (DBI‐1338415) from the National Science Foundation, the National Institutes of Health, and the US Department of Energy. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Verdiguel, Natalie↗

DOE OSTI2014

SU-E-T-471: Small Field Jaw/MLC Reference Data

Purpose: In recent years the need for small field data of MLCs has increased due to the use of intensity-modulated radiation (IMRT), but moreover the use of stereotactic body radiation (SBRT) has increased, which uses not simply small field sizes, but small jaw and field sizes together. Having reference data for these small fields that is reliable would be invaluable to the physics community. Our study has gathered these values and the data distributions from the Radiological Physics Center's (RPC) site visits between 1990 and the present. Methods: For all measurements, the RPC used a 25 × 25 × 25cm water phantom placed at 100cm SSD. All measurements were made with an Exradin A16 cylindrical ion chamber at an effective depth of 10 cm. A total of 42 Varian machine measurements were used to compose the data for a 6 MV beam and 5 TrueBeam 6 MV flattening filter free (FFF) beams were used for FFF data. Results: Jaw/MLC fields were measured for both 6 MV and 6 MF FFF beams with the jaws and MLCs both at the following field sizes: 6×6, 4×4, 3×3, and 2×2cm. Measurements were normalized to the 10×10 field readings (defined by the jaws and MLC). Spread in the data was minimal and demonstrates a high level of accuracy of acquired data. Conclusion: Small field Jaw/MLC reference data for Varian 6MV and 6 MV FFF beams has been analyzed and presented here, composed of the aggregation of numerous RPC site visits. Obtaining reliable small field data remains difficult, however the RPC has collected high fidelity small field Jaw/MLC data. The data are presented as a reference along with their distributions, in such a way that the physicist can act based upon their own desired agreement with the reference data.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1991

An improved three-dimensional aerodynamics model for helicopter airloads prediction

The importance of unsteady aerodynamic effects due to rotor blade motion is demonstrated for a helicopter in high-speed forward flight. These unsteady effects are modeled as surface boundary conditions to a three-dimensional, unsteady Computational Fluid Dynamics (CFD) code called the Full-Potential Rotor Code (FPR). These boundary conditions cause significant changes in the computed lift and pitching moment at the front and rear of the rotor disk. Airloads from the modified FPR code are then iteratively coupled with the helicopter comprehensive code, CAMRAD/JA. Computed airloads show good agreement with flight-test data when lift values from the FPR code are used in the coupled calculation. However, the computed airloads from CAMRAD/JA along also show good agreement with the experimental data. Thus for this case one cannot demonstrate a significant improvement in computed airloads with the hybrid coupled scheme. The addition of the pitching moment values from the FPR code into the CAMRAD/JA calculation slows down the overall iterative convergence and does not yield any improvement in the final results.

Strawn, Roger C.↗

NASA NTRS2012

The NASA Tournament Laboratory (NTL): Improving Data Access at PDS while Spreading Joy and Engaging Students through 16 Micro-Contests

NASA PDS hosts terabytes of valuable data from hundreds of data sources and spans decades of research. Data is stored on flat-file systems regulated through careful meta dictionaries. PDS's data is available to the public through its website which supports data searches through drill-down navigation. While the system returns data quickly, result sets in response to identical input differ depending on the drill-down path a user follows. To correct this Issue, to allow custom searching, and to improve general accessibility, PDS sought to create a new data structure and API, and to use them to build applications that are a joy to use and showcase the value of the data to students, teachers and citizens. PDS engaged TopCoder and Harvard Business School through the NTL to pursue these objectives in a pilot effort. Scope was limited to Small Bodies Node data. NTL analyzed data, proposed a solution, and implemented it through a series of micro-contests. Contest focused on different segments of the problem; conceptualization, architectural design, implementation, testing, etc. To demonstrate the utility of the completed solution, NTL developed web-based and mobile applications that can compare targets, regardless of mission. To further explore the potential of the solution NTL hosted "Mash-up" challenges that integrated the API with other publically available assets, to produce consumer and teaching applications, including an Augmented Reality iPad tool. Two contests were also posted to middle and high school students via the NoNameSite.com platform, and as a result of these contests, PDS/SBN has initiated a Facebook program. These contests defined and implemented a data warehouse with the necessary migration tools to transform legacy data, produced a public web interface for the new search, developed a public API, and produced four mobile applications that we expect to appeal to users both within and, without the academic community.

LaMora, Andy↗

NASA NTRS2023

Development of Level of Detail System and First-Person Camera for the GCAS Visualization Suite

The use of data-driven simulations has become standard practice as part of planning for future space missions. These simulations allow visualizing the data interactively to show what the data represents, as well as the importance of the data in the context of the mission. Using this visualized data can enhance users’ understanding of it and accelerate analysis efforts related to missions planned around it. Three-dimensional (3D) visualization software was developed to allow creating 3D representations of various communication systems, as well as the physical terrain of the Moon, for upcoming missions. The goal of this software development effort was to create interactive visualization capabilities in the Glenn Research Center Communication Analysis Suite (GCAS) using data exported from MATLAB® (MathWorks, Inc.) scripts. This software had the functionality to visualize the line of sight and dynamic link margins of the communication satellites orbiting the Earth and the Moon. One important addition to this was the visualization of the terrain data located within the GeoTIFF files, which were produced in an effort to understand the Moon’s terrain. Proper displacement values of this data have to be visualized to showcase where craters are located and how the shadow casting works with said craters at different points of the day, as well as analysis of possible landing sites for future lunar expeditions. The graphics library coded in JavaScript, three.js, had been previously selected for developing this visualization software. The software was revised to conform to modern standards, then further developed to convert the MATLAB® data into JavaScript 3D objects and Blender GL Transmission Format Binary file (GLB) objects, which were to be imported into the scene. In the process, a variety of other testing projects were created to be combined with this project at a later point; these included the first-person camera movements around spherical objects to portray human movement around the Moon, GeoTIFF loading methods, data transfer methods for incorporating the elevation data into the scene, and level of detail (LOD) capabilities to decrease memory usage and rendering time.

Visualization↗

DOE OSTI2019

Nuclear Data Sheets for A=73☆

Experimental nuclear structure data for the known A=73 isobaric nuclides (Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, As, Se, Br, Kr, Rb and Sr) have been evaluated, and presented together with Adopted properties of level energies, and associated γ rays. The decay data for these nuclides have also been evaluated, providing Adopted values of γ and β radiations, and log ft values. For {sup 73}Mn, only the isotopic identification has been established, with no knowledge of its g.s. half-life. For {sup 73}Fe, {sup 73}Co and {sup 73}Sr, only the ground states and their half-lives are known with no information about the excited states. For {sup 73}Ni, {sup 73}Cu, {sup 73}Zn and {sup 73}Rb, little data are available for excited states. The half-life and decay modes of possibly proton-unbound {sup 73}Rb need firmly established. {sup 73}Ga structure presents a special challenge in that the 1/2{sup −} ground state and the first 3/2{sup −} state have recently been proposed, in a Coulomb excitation experiment by 2010Di14, to form an almost degenerate doublet with an estimated spacing of 229 Th with its first excited state at 7.8 eV, and {sup 235}U with its first excited state at 76 eV. Ultra-high resolution gamma-ray spectroscopic studies are warranted to search for the low-lying (73 Ga, and to determine its half-life. Level structures of {sup 73}Ga, {sup 73}Ge, {sup 73}As, {sup 73}Se, {sup 73}Br and {sup 73}Kr are quite well known, although decay schemes of radioactive ground states of {sup 73}Co, {sup 73}Cu and {sup 73}Br are considered incomplete. The reactions and decays for which no new experimental information has become available since the 2003 update have undergone revisions to incorporate conversion coefficients from BrIcc code, and evaluated Q values from 2017Wa10, but essential content of such datasets may have remained the same as in previous evaluations. In this respect the present work greatly benefited from all the previous NDS evaluations (2004Si08,1993Ki25,1987Ki13, 1980Ek01,1974Al33), but at the same time data presented herein supersede all the previous published evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Proxy-based Bayesian inversion of strain tensor data measured during well tests

Recent instrument developments have made it possible to measure the strain tensor caused by injecting or pumping fluid from aquifers or reservoirs, but the full value of these data is limited because the long runtimes of poroelastic forward models makes it impractical to use many inversion schemes. This limits the interpretation of strain data for managing the recovery of resources or storage of wastes in the subsurface. This paper describes a method of inverting deformation data using a poroelastic numerical simulator so the results can be used to manage reservoirs or aquifers. We developed a workflow designed to reduce the number of simulations sufficiently to make it feasible to use DREAMzs, an advanced Bayesian inversion method that translates the uncertainties from different sources into unbiased posterior parameter distributions and uncertainty envelopes around the field data. Using a KNN proxy model for the poroelastic simulator is key to reducing the overall computations, and the workflow includes a strategy for ensuring the proxy model results converge on the results from the simulator. The workflow is tested using an idealized example that verifies the ability to correctly identify parameters and characterize noise used to perturb the data. Field data from an injection test at an oil reservoir near Tulsa, Oklahoma, are also used to evaluate the efficacy of the workflow with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), where the results were used to characterize posterior parameter distribution and evaluate the prediction uncertainty. Furthermore, this workflow is significant because it enables strain tensor, or other geomechanical measurements to be interpreted to guide decision-making during energy and environmental processes in the subsurface.

42 ENGINEERING↗

DOE OSTI2025

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗