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DOE OSTI2017

Development of CFD Flow Analysis for Nuclear Facility Ventilation Systems

Understanding and modeling of particulate transport has importance related to safety in ventilated environments that contain hot cells, gloveboxes, and fume hoods. In particular, good modeling of the airflow in these spaces is required to understand areas of stagnation where particles drop out of the free stream and accumulate. This accumulation of particulate can cause either contamination and/or higher than acceptable local dose levels. It is known that multiple sites across the DOE complex take credit for hot cells, gloveboxes, and/or hoods in their safety basis for providing a defense-in-depth benefit for both onsite and offsite releases. By providing confinement of radioactive materials, such features serve to reduce direct doses to facility workers and mitigate the consequences to the environment due to an uncontrolled release. Each of these features has access points that interface with the personnel space. Understanding how air flow behaves at these access points is of great interest to those performing hazard analysis. Computational Fluid Dynamics (CFD) can be used to analyze and model the flows in hot cells and glove boxes as a way to confirm operation. While CFD capability continues to advance, there are still important modeling assumptions that are left to the analyst's discretion. These are most notably the choice of the turbulence models, mesh structure, and wall boundary condition assumptions used in the model. In this work, we apply CFD in modeling airflow through an occupiable work area of the Alpha Gamma Hot Cell Facility (AGHCF) at Argonne National Laboratory (ANL). This modeling is then compared to field test data to both inform and verify the modeling assumptions. Based on the results of field tests, modeling assumptions and boundary conditions are refined and the process is repeated until the results are found to be reliable with a high level of confidence.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2000

Software IV and V Research Priorities and Applied Program Accomplishments Within NASA

The mission of this research is to be world-class creators and facilitators of innovative, intelligent, high performance, reliable information technologies that enable NASA missions to (1) increase software safety and quality through error avoidance, early detection and resolution of errors, by utilizing and applying empirically based software engineering best practices; (2) ensure customer software risks are identified and/or that requirements are met and/or exceeded; (3) research, develop, apply, verify, and publish software technologies for competitive advantage and the advancement of science; and (4) facilitate the transfer of science and engineering data, methods, and practices to NASA, educational institutions, state agencies, and commercial organizations. The goals are to become a national Center Of Excellence (COE) in software and system independent verification and validation, and to become an international leading force in the field of software engineering for improving the safety, quality, reliability, and cost performance of software systems. This project addresses the following problems: Ensure safety of NASA missions, ensure requirements are met, minimize programmatic and technological risks of software development and operations, improve software quality, reduce costs and time to delivery, and improve the science of software engineering

Blazy, Louis J.↗

NASA NTRS2023

PACE Technical Report Series, Volume 11: The PACE Postlaunch Airborne eXperiment (PACE-PAX)

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; https://pace.gsfc.nasa.gov) mission is NASA's latest and greatest effort to study the ocean-atmosphere system and build upon the legacy of previous satellite missions that have revolutionized our understanding of our home planet. By using advanced radiometric and polarimetric instruments to measure ocean color and key atmospheric variables, PACE aims to provide new insights into the complex interactions between the ocean, atmosphere, and biosphere. This information will be critical for improving our ability to model and predict changes in the Earth's climate, as well as to manage and conserve our planet's valuable natural resources. Performance assessments and science data product validation is a critical process for any Earth Science space-borne mission, as it involves assessing and verifying the quality of the data products generated by the mission while it is in orbit, as well as assigning uncertainties to these retrievals. More specifically, validation efforts are essential for assessing the accuracy of instrument data and the derived science products across varied spatial and temporal scales and ensuring their reliability and consistency with the mission's scientific goals and objectives. The overall plan for validation of PACE data is described in “PACE Science Data Product Validation Plan” (see, e.g., https://pace.gsfc.nasa.gov), and among range of post-launch activities, it describes the need and requirements for a post-launch airborne field campaign in support of PACE validation. This volume outlines the plans and requirements of the PACE Postlaunch Airborne eXperiment (PACE-PAX). The main goal of PACE-PAX is to gather validation and assessment data for the PACE mission, using a variety of airborne and ground-based assets. These assets will be coordinated to obtain complementary measurements of key ocean and atmospheric variables, such as ocean color, aerosols, and clouds. By collecting data from multiple sources, PACE-PAX will help to validate and refine the data products generated by the PACE mission, as well as to identify any potential errors or biases in the measurements. This will be essential for ensuring the accuracy and reliability of the PACE data products, and for maximizing the scientific value of the mission.

Kirk D Knobelspiesse↗

DOE OSTI2018

Simulation tools for atom probe tomography: A path for diagnosis and treatment of image degradation

The ideal picture of a near-perfect 3D microscope often presented regarding Atom Probe Tomography faces several issues. These issues degrade the metrological performance of the instrument and find their roots in the phenomena acting at the atomic to the mesoscopic level in the vicinity of the surface of a field emitter. From the field evaporation process at the atomic scale, to the macroscopic scale of the instrument, the path to model the imaging process and to develop more accurate and reliable reconstruction algorithms is not a single lane road. This paper focused on the numerical methods used to understand, treat, and potentially heal imaging issues commonly affecting the data in atom probe experiments. A lot of room for improvement exists in solving accuracy problems observed in complex materials by means of purely electrostatic models describing the image formation in a classical approach. Looking at the sample at the atomic scale, the phenomena perturbing the imaging process are subtle. An examination of atomic scale modifications of the sample surface in the presence of a high surface electric field is therefore mandatory. Atomic scale molecular dynamic models integrating the influence of the high surface electric are being developed with this aim. It is also demonstrated that the complex behavior of atoms and molecules in high fields, and consequences on collected data, can be understood through the use of accurate ab-initio models modified to include the impact of the extreme surface electric field.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2026

“One Table to Rule Them All”: How a Single Table can Enable Extensive Insights, Analytics and Assessment on Human Mobility Data

While much research has been conducted in Human Mobility Science, most studies on the analytics/insights part generally focus on one of the following: processing and analytics on human stop-trip behavior, design of individual mobility metrics (often in silos), calculation and characterization of only a handful (typically 5-6) of human mobility metrics on geospatial-temporal human mobility data of interest. Although human mobility research offers a vast and diverse array of available metrics, most individual studies typically compute only a small subset of five or six metrics at a time when analyzing trajectory datasets of human mobility across different areas of interest. This paper is motivated by the critical need to repeatedly compute an extensive array of human mobility metrics across several trajectory datasets and perform individual metric-level benchmarking to establish a new, standardized Test and Evaluation (T&E) suite for the field of Human Mobility Science. We first present our findings on the minimal yet sufficient pre-processing required to reliably and efficiently compute a wide range of human mobility metrics. The key findings are specifically related to the proposed Composite Stop Locations table, which serves as a core pre-processing data layer. Subsequently, we present a case study demonstrating how the Composite Stop Locations table facilitates computation of at least 14 distinct human mobility metrics (unlike 5-6 different set of metrics used for studies in the literature) using the popular and open-source OpenPFLOW dataset. Finally, we have also presented an example of our benchmarking methodology to evaluate the quality and performance of the trajectory dataset of interest, assessed across multiple human mobility metrics.

De, Debraj [ORNL] (ORCID:0000000233630020)↗

DOE OSTI2013

A PHOTOMETRIC STUDY OF THE ALGOL-TYPE BINARY FG Gem

High-quality three-color light curves of the binary FG Gem were measured and analyzed. A new method based on extensive searching of isochrones was used to investigate possible parameters for the binary. FG Gem is found to be an Algol-type semi-detached binary system with a primary star temperature of 8200 K and a mass ratio of 0.41(1). The correctness and reliability of our result requires the verification of precision spectroscopy or standard star observations. We investigate a new possible cause for the orbital period variations based on times of minimum light data. It is suggested from the quantitative analysis that variations in the orbital period can be explained by intermittent mass transfer and angular momentum loss from stellar winds leaving the system on rotating magnetic fields.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Improve earthquake hypocenter using adaptive simulated annealing inversion in regional tectonic, volcano tectonic, and geothermal observation

Observation of earthquakes is routinely used widely in tectonic activity observation, and also in local scale such as volcano tectonic and geothermal activity observation. It is necessary for determining the location of precise hypocenter which the process involves finding a hypocenter location that has minimum error between the observed and the calculated travel times. When solving this nonlinear inverse problem, simulated annealing inversion method can be applied to such global optimization problems, which the convergence of its solution is independent of the initial model. In this study, we developed own program codeby applying adaptive simulated annealing inversion in Matlab environment. We applied this method to determine earthquake hypocenter using several data cases which are regional tectonic, volcano tectonic, and geothermal field. The travel times were calculated using ray tracing shooting method. We then compared its results with the results using Geiger’s method to analyze its reliability. Our results show hypocenter location has smaller RMS error compared to the Geiger’s result that can be statistically associated with better solution. The hypocenter of earthquakes also well correlated with geological structure in the study area. Werecommend using adaptive simulated annealing inversion to relocate hypocenter location in purpose to get precise and accurate earthquake location.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra.

Szołdra, Tomasz (ORCID:0000000228970506)↗

DOE OSTI2025

Field expedient stool collection methods for gut microbiome analysis in deployed military environments

ABSTRACT Field expedient devices and protocols for the collection, storage, and shipment of stool samples in deployed settings are needed for the advancement of microbiome research in military health. Relevant assessments include the evaluation of microbiome signatures associated with susceptibility to travelers’ diarrhea and recovery of gut function following infection. However, inherent biases in microbial measurements due to preservatives and sampling methods are unclear and should be assessed for an accurate evaluation of the microbiome. We performed shotgun metagenomic sequencing and compared the microbiome composition in paired fecal samples collected using Flinters Technology Associates (FTA) cards and OMNIgene (OG) Gut tubes, prior to and during international travel, from 49 adult participants, 39 of whom remained asymptomatic and 10 experienced travelers’ diarrhea. Higher concentrations of nucleic acid and sequencing libraries were observed in OG samples. A majority of genera (82.9%) were detected with both methods, and detections of genera limited to one collection method were not highly prevalent across samples and were present in extremely low relative abundances (<0.01%). Differences in beta diversity were largely explained by inter-individuality of microbiome composition, followed by the effect of collection method and timepoint-disease states. Differential abundance analysis indicated that Corynebacterium and Blautia were consistently higher in abundance across all groups with FTA and OG collection, respectively. The observed differences in microbiome composition between methods suggest the need for consistent and standardized protocols within a study. Overall, the data presented here could help guide the future design of fecal microbiome study protocols in field and military deployment settings. IMPORTANCE The assessment of field-deployable methods for fecal sample collection and storage is required to reliably capture samples collected in remote and austere locations. This study describes a comparative metagenomics analysis between samples collected by two different commercially available methods in a military-deployed setting. The results presented here are foundational for the future design of fecal microbiome study protocols in an operational context.

field study↗

DOE OSTI2011

Wide Area Wind Field Monitoring Status & Results

Volume-scanning elastic has been investigated as a means to derive 3D dynamic wind fields for characterization and monitoring of wind energy sites. An eye-safe volume-scanning lidar system was adapted for volume imaging of aerosol concentrations out to a range of 300m. Reformatting of the lidar data as dynamic volume images was successfully demonstrated. A practical method for deriving 3D wind fields from dynamic volume imagery was identified and demonstrated. However, the natural phenomenology was found to provide insufficient aerosol features for reliable wind sensing. The results of this study may be applicable to wind field measurement using injected aerosol tracers.

17 WIND ENERGY↗

DOE OSTI2020

Plateau de Bure High-z Blue Sequence Survey 2 (PHIBSS2): Search for Secondary Sources, CO Luminosity Functions in the Field, and the Evolution of Molecular Gas Density through Cosmic Time

We report on the results of a search for serendipitous sources in CO emission in 110 cubes targeting CO(2 − 1), CO(3 − 2), and CO(6 − 5) at z ∼ 1–2 from the second Plateau de Bure High-z Blue Sequence Survey (PHIBSS2). The PHIBSS2 observations were part of a 4 yr legacy program at the IRAM Plateau de Bure Interferometer aimed at studying early galaxy evolution from the perspective of molecular gas reservoirs. We present a catalog of 67 candidate secondary sources from this search, with 45 of the 110 data cubes showing sources in addition to the primary target that appear to be field detections, unrelated to the central sources. This catalog includes redshifts, line widths, and fluxes, as well as an estimation of their reliability based on their false-positive probability. We perform a search in the 3D Hubble Space Telescope/CANDELS catalogs for the secondary CO detections and tentatively find that ∼64% of these have optical counterparts, which we use to constrain their redshifts. Finally, we use our catalog of candidate CO detections to derive the CO(2 − 1), CO(3 − 2), CO(4 − 3), CO(5 − 4), and CO(6 − 5) luminosity functions over a range of redshifts, as well as the molecular gas mass density evolution. Despite the different methodology, these results are in very good agreement with previous observational constraints derived from blind searches in deep fields. They provide an example of the type of “deep-field” science that can be carried out with targeted observations.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2001

Transport of Energetic Ions in the Ring Current During Geomagnetic Storms

In the final year (plus no-cost extentions) of this grant, we have: Used the particle tracing code to perform a systematic study of the expected energy spectra over the full range of local times in the ring current using a variety of electric and magnetic field models. Shown that the Weimer electric field is superior to the Volland-Stern electric field in reproducing the observed energy spectra on the AMPTE CCE spacecraft. Redone our analysis of the pitch angle spectra of energetic ions during storms in the magnetosphere, using a larger data set, and a more reliable classification technique.

Kistler, Lynn M.↗

NASA NTRS2004

Vibrational Spectroscopy of Ions and Radicals Present in the Interstellar Medium and in Planetary Atmospheres: A Theoretical Study

Anharmonic vibrational frequencies and intensities are calculated for OH(H2O)n and H(H2O)n radicals (that form on icy particles of the interstellar medium), HCO radical (the main intermediate in the synthesis of organic molecules in space), NH2(-) and C2H(-) anions, H5(+) cation, and other systems relevant to interstellar chemistry. In addition to pure ions and radicals, their complexes with water are studied to assess the effects of water environment on infrared spectra. The calculations are performed using the correlation-corrected vibrational self-consistent field (CC-VSCF) method with ab initio potential surfaces at the MP2 and CCSD(T) levels. Fundamental, overtone, and combination excitations are computed. The results are in good agreement with available experimental data and provide reliable predictions for vibrational excitations not yet measured in laboratory experiments. The data should be useful for interpretation of astronomically observed spectra and identification of ions and radicals present in the interstellar medium and in planetary atmospheres.

Chaban, Galina M.↗

NASA NTRS2018

Connecting Satellite-Based Precipitation Estimates to Users

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

Huffman, George J.↗

DOE OSTI2020

Feature Engineering and Process Mining to Enable Hazard Detection in Health Information Technology

Motivation for this work originates from a recognized need for developing data-driven approaches through analysis of complex electronic health records. Specifically, we aim to enhance the reliability of health information technology (HIT) systems by detection of plausible HIT hazards in clinical order transactions. In the absence of well-defined event logs in corporate data warehouses, our proposed approach identifies relevant timestamped data fields that could indicate transactions in the clinical order life cycle generating raw event sequences. Subsequently, we adopt state transitions of the OASIS Human Task standard to map the raw event sequences and simplify the complex process that clinical radiology orders go through. We describe how the current approach provides the potential to investigate areas of improvement and potential hazards in HIT systems. The discussion concludes with a use case and opportunities for future applications.

Ozmen, Ozgur↗

DOE OSTI2016

Correlation of Thermally Induced Pores with Microstructural Features Using High Energy X-rays

Combined application of a near-field High Energy Diffraction Microscopy measurement of crystal lattice orientation fields and a tomographic measurement of pore distributions in a sintered nickel-based superalloy sample allows pore locations to be correlated with microstructural features. Furthermore, measurements were carried out at the Advanced Photon Source beamline 1-ID using an X-ray energy of 65 keV for each of the measurement modes. The nickel superalloy sample was prepared in such a way as to generate significant thermally induced porosity. A three-dimensionally resolved orientation map is directly overlaid with the tomographically determined pore map through a careful registration procedure. The data are shown to reliably reproduce the expected correlations between specific microstructural features (triple lines and quadruple nodes) and pore positions. With the statistics afforded by the 3D data set, we conclude that within statistical limits, pore formation does not depend on the relative orientations of the grains. The experimental procedures and analysis tools illustrated are being applied to a variety of materials problems in which local heterogeneities can affect materials properties.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Joint inversion of marine seismic AVA and CSEM data using statistical rock-physics models and Markov random fields: Stochastic inversion of AVA and CSEM data

Joint inversion of seismic AVA and CSEM data requires rock-physics relationships to link seismic attributes to electrical properties. Ideally, we can connect them through reservoir parameters (e.g., porosity and water saturation) by developing physical-based models, such as Gassmann’s equations and Archie’s law, using nearby borehole logs. This could be difficult in the exploration stage because information available is typically insufficient for choosing suitable rock-physics models and for subsequently obtaining reliable estimates of the associated parameters. The use of improper rock-physics models and the inaccuracy of the estimates of model parameters may cause misleading inversion results. Conversely, it is easy to derive statistical relationships among seismic and electrical attributes and reservoir parameters from distant borehole logs. In this study, we develop a Bayesian model to jointly invert seismic AVA and CSEM data for reservoir parameter estimation using statistical rock-physics models; the spatial dependence of geophysical and reservoir parameters are carried out by lithotypes through Markov random fields. We apply the developed model to a synthetic case, which simulates a CO{sub 2} monitoring application. We derive statistical rock-physics relations from borehole logs at one location and estimate seismic P- and S-wave velocity ratio, acoustic impedance, density, electrical resistivity, lithotypes, porosity, and water saturation at three different locations by conditioning to seismic AVA and CSEM data. Comparison of the inversion results with their corresponding true values shows that the correlation-based statistical rock-physics models provide significant information for improving the joint inversion results.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Development of Mission Profiles for Humidity Models in the Reliability Testing of PV Inverters: Preprint

To understand the impacts of humidity on PV inverters, mission profiles were developed to accurately describe the different processes and rates based on the environmental factors of temperature, relative humidity, and irradiance. The operating environment of the device introduces stress factors dependent on component temperature, relative humidity, and component voltage. The development of profiles started from looking at historical climate conditions at Cocoa, Florida, a hot and humid location. The profile developed from field location was compared with existing humidity test profiles in industrial and military standards to determine acceleration factors. Prior to the evaluation of the mission profiles, critical components in the PV inverter were identified based on vendor discussions along with failure modes of interest. The profiles considered in this study was demonstrated using a 4-kVA string inverter. The measurements from the devices were substituted in device manufacturer specified equation to determine the severity of each test. The severity of each test was compared against the severity of the 24-hour result to determine the acceleration factor of each test. The acceleration factors were determined to be over a range of 1.2-6 for the existing humidity tests from standards, when compared against the mission profile developed from field data. This optimal humidity/thermal profile will be passed to the IEC standards development for inverter qualification testing.

humidity models↗