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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A low-luminosity core-collapse supernova very similar to SN 2005cs

ABSTRACT We present observations and analysis of PSN J17292918+7542390, a low-luminosity Type II-P supernova (LL SN IIP). The observed sample of such events is still low, and their nature is still under debate. Such SNe are similar to SN 2005cs, a well-observed LL Type II-P event, having low expansion velocities, and small ejected 56Ni mass. We have developed a robust and relatively fast Monte Carlo code that fits semi-analytic models to light curves of core-collapse SNe. This allows the estimation of the most important physical parameters, like the radius of the progenitor star, the mass of the ejected envelope, the mass of the radioactive nickel synthesized during the explosion, among others. PSN J17292918+7542390 has $R_0 = 91_{-70}^{+119} \times 10^{11} \, \text{cm}$, $M_\text{ej} = 9.89_{-1.00}^{+2.10} \, \mathrm{ M}_{\odot }$, $E_{\mbox{kin}} = 0.65_{-0.18}^{+0.19} \, \text{foe}$, and $v_{\mbox{exp}} = 3332_{-347}^{+216}$ km s−1, for its progenitor radius, ejecta mass, kinetic energy, and expansion velocity, respectively. The initial nickel mass of the PSN J17292918+7542390 turned out to be $1.55_{-0.70}^{+0.75} \times 10^{-3} \, \mathrm{M}_{\odot }$. The measured photospheric velocity at the earliest observed phase is 7000 km s−1. As far as we can tell based on the small population of observed LL SNe IIP, the determined values are typical for these events.

Jäger, Jr, Zoltán↗
DOE OSTI2016

Analyzing diffuse scattering with supercomputers. Corrigendum

The study by Michels-Clark et al. (2013 [Michels-Clark, T. M., Lynch, V. E., Hoffmann, C. M., Hauser, J., Weber, T., Harrison, R. & Bürgi, H. B. (2013). J. Appl. Cryst. 46, 1616-1625.]) contains misleading errors which are corrected here. The numerical results reported in that paper and the conclusions given there are not affected and remain unchanged. The transition probabilities in Table 1 (rows 4, 5, 7, 8) and Fig. 2 (rows 1 and 2) of the original paper were different from those used in the numerical calculations. Corrected transition probabilities as used in the computations are given in Table 1 and Fig. 1 of this article. The Δ parameter in the stacking model expresses the preference for the fifth layer in a five-layer stack to be eclipsed with respect to the first layer. This statement corrects the original text on p. 1622, lines 4–7. In the original Fig. 2 the helicity of the layer stacks b L and b R in rows 3 and 4 had been given as opposite to those in rows 1, 2 and 5. Fig. 1 of this article shows rows 3 and 4 corrected to correspond to rows 1, 2 and 5.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Prospective memory in dynamic environments: effects of load, delay, and phonological rehearsal

A new paradigm was developed to examine prospective memory performance in a visual-spatial task that resembles some aspects of the work of air traffic controllers. Two experiments examined the role of workload (number of aeroplanes that participants directed), delay (between receipt of prospective instructions and execution), and phonological rehearsal. High workload increased prospective memory errors but increasing delay from 1-3 or 5 minutes had no effect. Shadowing aurally presented text reduced prospective memory performance, presumably because it prevented verbal rehearsal of the prospective instructions. However, performance on the foreground task of directing aeroplanes to routine destinations was affected only by workload and not by opportunity for rehearsal. Our results suggest that ability to maintain performance on a routine foreground task while performing a secondary task--perhaps analogous to conversation--does not predict ability to retrieve a prospective intention to deviate from the routine.

Aerospace Medicine↗
NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗
NASA NTRS1997

The flat fielding and achievable signal-to-noise of the MAMA detectors

The Space Telescope Imaging Spectrograph (STIS) was designed to achieve a signal-to-noise (S/N) of at least 100:1 per resolution element. Multi-Anode Microchannel Arrays (MAMA) observations during Servicing Mission Orbital Verification (SMOV) confirm that this specification can be met. From analysis of a single spectrum of GD153, with counting statistics of approximately 165 a S/N of approximately 125 is achieved per spectral resolution element in the far ultraviolet (FUV) over the spectral range of 1280A to 1455A. Co-adding spectra of GRW+7OD5824 to increase the counting statistics to approximately 300 yields a S/N of approximately 190 per spectral resolution element over the region extending from 1347A to 1480A in the FUV. In the near ultraviolet (NUV), a single spectrum of GRW+7OD5824 with counting statistics of approximately 200 yields a S/N of approximately 150 per spectral resolution element over the spectral region extending from 2167 to 2520A. Details of the flat field construction, the spectral extraction, and the definition of a spectral resolution element will be described in the text.

Kaiser, Mary Elizabeth↗
NASA NTRS2008

Geologic Mapping of the Martian Impact Crater Tooting

Tooting crater is approximately 29 km in diameters, is located at 23.4 deg N, 207.5 deg E and is classified as a multi-layered ejecta crater. Tooting crater is a very young crater, with an estimated age of 700,000 to 2M years. The crater formed on virtually flat lava flows within Amazonis Planitia where there appears to have been no major topographic features prior to the impact, so that we can measure ejecta thickness and cavity volume. In the past 12 months, the authors have: published their first detailed analysis of the geometry of the crater cavity and the distribution of the ejecta layers; refined the geologic map of the interior of Tooting crater through mapping of the cavity at a scale of 1:1100K; and continued the analysis of an increasing number of high resolution images obtained by the CTX and HiRISE instruments. Currently the authors seek to resolve several science issues that have been identified during this mapping, including: what is the origin of the lobate flows on the NW and SW rims of the crater?; how did the ejecta curtain break apart during the formation of the crater, and how uniform was the emplacement process for the ejecta layers; and, can we infer physical characteristics about the ejecta? Future study plans include the completion of a draft geologic map of Tooting crater and submission of it to the U.S. Geological survey for a preliminary review, publishing a second research paper on the detailed geology of the crater cavity and the distribution of the flows on the crater rim, and completing the map text for the 1:100K geologic map description of units at Tooting crater.

Mouginis-Mark, Peter↗
NASA NTRS2009

Worldwide Spacecraft Crew Hatch History

The JSC Flight Safety Office has developed this compilation of historical information on spacecraft crew hatches to assist the Safety Tech Authority in the evaluation and analysis of worldwide spacecraft crew hatch design and performance. The document is prepared by SAIC s Gary Johnson, former NASA JSC S&MA Associate Director for Technical. Mr. Johnson s previous experience brings expert knowledge to assess the relevancy of data presented. He has experience with six (6) of the NASA spacecraft programs that are covered in this document: Apollo; Skylab; Apollo Soyuz Test Project (ASTP), Space Shuttle, ISS and the Shuttle/Mir Program. Mr. Johnson is also intimately familiar with the JSC Design and Procedures Standard, JPR 8080.5, having been one of its original developers. The observations and findings are presented first by country and organized within each country section by program in chronological order of emergence. A host of reference sources used to augment the personal observations and comments of the author are named within the text and/or listed in the reference section of this document. Careful attention to the selection and inclusion of photos, drawings and diagrams is used to give visual association and clarity to the topic areas examined.

Johnson, Gary↗
DOE OSTI2024

Automating the Analysis of Large Language Models Responses through Zero-Shot Question Answering

Recent advancements in Large Language Models (LLMs) have shown significant potential in various applications, yet their evaluation, particularly in zero-shot question answering scenarios, remains a challenging task. In this study, our objective was to explore precision metrics for Large Language Models (LLM) and design and implement a software pipeline to automatically evaluate LLMs' outputs under zero-shot question answering. Zero-shot question answering involves a model providing answers to questions about topics it hasn't seen during training. It leverages the principles of zero-shot learning by relying on semantic understanding and generalization from related knowledge. The data used was metadata from medical databases on congenital heart disease. We explored eleven LLM metrics and selected three for our evaluation: BLEU, BERTScore, and MoverScore. BLEU calculates a score based on the overlap of n-grams (contiguous sequences of n items, typically words) between the machine-generated translation and the reference translations. Higher BLEU scores indicate better correspondence between the machine-generated and human-generated translations. BERTScore is a metric used to evaluate the quality of machine-generated text by measuring the similarity of token embeddings produced by BERT (Bidirectional Encoder Representations from Transformers) between the generated text and reference text. MoverScore is a metric that quantifies the dissimilarity between the distributions of word embeddings from machine-generated text and reference text, emphasizing semantic similarity over exact token overlap. We also introduced HBKI, a composite metric summarizing these approaches. We tested five models —GPT-3, Llama-2, Gemini 1.5 Pro, Solar 10.7B, and Mixtral-8x7b. Our software pipeline, designed and implemented using Object-Oriented Programming principles, allows users to customize the selection and extraction of features for topics of interest in their own research. Our results show that MoverScore delivered the most precise evaluation of the LLM's outputs, while Mixtral-8x7b achieved the best overall performance in extracting metadata from the databases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Production Operations Management System (POMS) for Fermilab Experiments

The Production Operations Management System (POMS) software allows production teams and analysis groups across multiple Fermilab experiments to launch, modify and monitor large scale campaigns of related Monte Carlo or data processing jobs, and currently manages the majority of production computing of experiments at Fermilab.POMS provides a web service interface that enables automated job submission on distributed resources according to customers’ requests, as well as subsequent monitoring of those submissions as well as recovery of failed submissions, debugging and record keeping.POMS interfaces with existing HEP data access, processing, movement and monitoring tools at Fermilab, including Jobsub (for job submission), SAM (for data management), and Landscape (for monitoring), and in combination with them handles the creation of intermediate datasets of files for multistage campaigns.POMS visualizes these campaigns with an interactive GUI interface. An important feature of POMS is a one-to-one connection between the GUI campaign visualizer and a text based representation of the complete campaign configuration. An extensible library of template campaign configurations is available. The templates are user modifiable and map cleanly to and from the GUI description of the campaign.This paper will discuss the current usage, history, and some technical details of POMS, as well as planned future extensions, particularly interfacing with Rucio as well as SAM for file movement.

Mengel, Marc↗
DOE OSTI2023

Measurements of neutrino oscillation parameters from the T2K experiment using $$3.6\times 10^{21}$$ protons on target

Abstract The T2K experiment presents new measurements of neutrino oscillation parameters using $$19.7(16.3)\times 10^{20}$$ 19.7 ( 16.3 ) × 10 20 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional $$4.7\times 10^{20}$$ 4.7 × 10 20 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on $$\sin ^2\theta _{13}$$ sin 2 θ 13 and the impact of priors on the $$\delta _{\textrm{CP}}$$ δ CP measurement. Both analyses prefer the normal mass ordering and upper octant of $$\sin ^2\theta _{23}$$ sin 2 θ 23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 from reactors, $$\sin ^2\theta _{23}=0.561^{+0.021}_{-0.032}$$ sin 2 θ 23 = 0 . 561 - 0.032 + 0.021 using Feldman–Cousins corrected intervals, and $$\varDelta {}m^2_{32}=2.494_{-0.058}^{+0.041}\times 10^{-3}~\text {eV}^2$$ Δ m 32 2 = 2 . 494 - 0.058 + 0.041 × 10 - 3 eV 2 using constant $$\varDelta \chi ^{2}$$ Δ χ 2 intervals. The CP-violating phase is constrained to $$\delta _{\textrm{CP}}=-1.97_{-0.70}^{+0.97}$$ δ CP = - 1 . 97 - 0.70 + 0.97 using Feldman–Cousins corrected intervals, and $$\delta _{\textrm{CP}}=0,\pi $$ δ CP = 0 , π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than $$2\sigma $$ 2 σ credible level using a flat prior in $$\delta _{\textrm{CP}},$$ δ CP , and just below $$2\sigma $$ 2 σ using a flat prior in $$\sin \delta _{\textrm{CP}}.$$ sin δ CP . When the external constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 is removed, $$\sin ^2\theta _{13}=28.0^{+2.8}_{-6.5}\times 10^{-3},$$ sin 2 θ 13 = 28 . 0 - 6.5 + 2.8 × 10 - 3 , in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

A Comparison of Maps and Power Spectra Determined from South Pole Telescope and Planck Data

We study the consistency of 150 GHz data from the South Pole Telescope (SPT) and 143 GHz data from the \textit{Planck} satellite over the 2540 $\text{deg}^2$ patch of sky covered by the SPT-SZ survey. We first visually compare the maps and find that the map residuals appear consistent with noise after we account for differences in angular resolution and filtering. To make a more quantitative comparison, we calculate (1) the cross-spectrum between two independent halves of SPT 150 GHz data, (2) the cross-spectrum between two independent halves of \textit{Planck} 143 GHz data, and (3) the cross-spectrum between SPT 150 GHz and \textit{Planck} 143 GHz data. We find the three cross-spectra are well-fit (PTE = 0.30) by the null hypothesis in which both experiments have measured the same sky map up to a single free parameter characterizing the relative calibration between the two. As a by-product of this analysis, we improve the calibration of SPT data by nearly an order of magnitude, from 2.6\% to 0.3\% in power; the best-fit power calibration factor relative to the most recent published SPT calibration is $1.0174 \pm 0.0033$. Finally, we compare all three cross-spectra to the full-sky \textit{Planck} $143 \times 143$ power spectrum and find a hint ($\sim$1.5$\sigma$) for differences in the power spectrum of the SPT-SZ footprint and the full-sky power spectrum, which we model and fit as a power law in the spectrum. The best-fit value of this tilt is consistent between the three cross-spectra in the SPT-SZ footprint, implying that the source of this tilt---assuming it is real---is a sample variance fluctuation in the SPT-SZ region relative to the full sky. Despite the precision of our tests, we find no evidence for systematic errors in either data set. The consistency of cosmological parameters derived from these datasets is discussed in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Data-driven linear time advance operators for the acceleration of plasma physics simulation

In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2021

JPSS-1 ATMS Post-launch Active Geolocation Analysis

A NOAA-20 (N20) ATMS active geolocation test was performed around Jan. 2018 with 24 pre-selected coastline crossing scenes. After comprehensive analysis of ATMS stare data and the corresponding VIIRS data, the ATMS pitch, roll and yaw pointing angle errors are found from the nadir perpendicular, the nadir oblique shallow angle, and the off-nadir perpendicular coastline crossing data, respectively. In this study, we first determine the ATMS radiometric coastline crossing time by using the ATMS radiometric count data. Since the coastline can be located anywhere within one ATMS FOV from the passive (regular scanning) geolocation data, depending on the scan starting time, it is not a valid assumption for the inflection point being the same as the coastline location. Consequently, using the passive geolocation data to validate the sensor’s on-orbit pointing angle performance is limited. After finding the ATMS radiometric coastline crossing time from the ATMS data, we compare it with the VIIRS effective time stamp (see main text). Specifically the VIIRS M3, M4 & M5 (true color) & M15 and M16 bands (thermal) data have a much smaller footprint size. Using the differences of the ATMS and VIIRS (effective) coastlines crossing times, the N20 ATMS pitch, roll and yaw pointing angle errors are found to be -0.09o, -0.24o and 0.28o, respectively. To determine ATMS geolocation properly, these on-orbit pointing errors need to be corrected, adding to the ATMS SDR Processing Coefficient Table, and passed on to the operational geolocation processing code.

Active Geolocation↗
NASA NTRS2008

Displaying Composite and Archived Soundings in the Advanced Weather Interactive Processing System

In a previous task, the Applied Meteorology Unit (AMU) developed spatial and temporal climatologies of lightning occurrence based on eight atmospheric flow regimes. The AMU created climatological, or composite, soundings of wind speed and direction, temperature, and dew point temperature at four rawinsonde observation stations at Jacksonville, Tampa, Miami, and Cape Canaveral Air Force Station, for each of the eight flow regimes. The composite soundings were delivered to the National Weather Service (NWS) Melbourne (MLB) office for display using the National version of the Skew-T Hodograph analysis and Research Program (NSHARP) software program. The NWS MLB requested the AMU make the composite soundings available for display in the Advanced Weather Interactive Processing System (AWIPS), so they could be overlaid on current observed soundings. This will allow the forecasters to compare the current state of the atmosphere with climatology. This presentation describes how the AMU converted the composite soundings from NSHARP Archive format to Network Common Data Form (NetCDF) format, so that the soundings could be displayed in AWl PS. The NetCDF is a set of data formats, programming interfaces, and software libraries used to read and write scientific data files. In AWIPS, each meteorological data type, such as soundings or surface observations, has a unique NetCDF format. Each format is described by a NetCDF template file. Although NetCDF files are in binary format, they can be converted to a text format called network Common data form Description Language (CDL). A software utility called ncgen is used to create a NetCDF file from a CDL file, while the ncdump utility is used to create a CDL file from a NetCDF file. An AWIPS receives soundings in Binary Universal Form for the Representation of Meteorological data (BUFR) format (http://dss.ucar.edu/docs/formats/bufr/), and then decodes them into NetCDF format. Only two sounding files are generated in AWIPS per day. One file contains all of the soundings received worldwide between 0000 UTC and 1200 UTC, and the other includes all soundings between 1200 UTC and 0000 UTC. In order to add the composite soundings into AWIPS, a procedure was created to configure, or localize, AWIPS. This involved modifying and creating several configuration text files. A unique fourcharacter site identifier was created for each of the 32 soundings so each could be viewed separately. The first three characters were based on the site identifier of the observed sounding, while the last character was based on the flow regime. While researching the localization process for soundings, the AMU discovered a method of archiving soundings so old soundings would not get purged automatically by AWl PS. This method could provide an alternative way of localizing AWl PS for composite soundings. In addition, this would allow forecasters to use archived soundings in AWIPS for case studies. A test sounding file in NetCDF format was written in order to verify the correct format for soundings in AWIPS. After the file was viewed successfully in AWIPS, the AMU wrote a software program in the Tool Command Language/Tool Kit (Tcl/Tk) language to convert the 32 composite soundings from NSHARP Archive to CDL format. The ncgen utility was then used to convert the CDL file to a NetCDF file. The NetCDF file could then be read and displayed in AWIPS.

Barrett, Joe H., III↗
DOE OSTI2019

Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports

Automated text information extraction from cancer pathology reports is an active area of research to support national cancer surveillance. A well-known challenge is how to develop information extraction tools with robust performance across cancer registries. In this study we investigated whether transfer learning (TL) with a convolutional neural network (CNN) can facilitate cross-registry knowledge sharing. Specifically, we performed a series of experiments to determine whether a CNN trained with single-registry data is capable of transferring knowledge to another registry or whether developing a cross-registry knowledge database produces a more effective and generalizable model. Using data from two cancer registries and primary tumor site and topography as the information extraction task of interest, our study showed that TL results in 6.90% and 17.22% improvement of classification m acro F -score o ver the baseline single-registry models. Detailed analysis illustrated that the observed improvement is evident in the low prevalence classes.

Alawad, Mohammed↗
DOE OSTI2026

PFLOTRAN modeling data and scripts associated with “Refining the Hydrogeologic Framework of a Large River Corridor Model Using Waterborne Transient Electromagnetics”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Refining the Hydrogeologic Framework of a Large River Corridor Model Using Waterborne Transient Electromagnetics” submitted to Water Resources Research (Terry et al. 2025). The data package contains the groundwater modeling dataset from PFLOTRAN software. It includes the python script for mesh generation, boundary condition setting, PFLOTRAN input deck formation and postprocessing. It couples groundwater flow and species transport for Hanford Reach river corridor and pipelines the model generation and processing. This model can be used to easily generate the model and analysis for Hanford site. It can also be adjusted to other hydrologic area with ease. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. The data package consists of 6 folders: (1) “data” contains all necessary data as input and intermediate data for processing; (2) “mesh” contains all mesh related files to generate mesh in Hanford Reach river corridor; (3) “model_run” contains the generated script for PFLOTRAN modeling; (4) “notebooks” contains all the Python script to generate the model; (5) “output” contains all the output from the computation; (6) “postprocessing” contains the Python script to generate scientific figure for manuscript. All files are .csv (comma-separated values), .h5 (HDF5 format), .in (input files), .ipynb (Jupyter notebooks), .p (Python pickle), .png (images), .PNG (images), .py (Python scripts), .pyc (Python bytecode), .r (R scripts), .sh (shell scripts), .txt (text files), .vtu (3D mesh/visualization format), .xz (compressed archive), or .zip (compressed archive).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Computer-Aided System Engineering and Analysis (CASE/A) Programmer's Manual, Version 5.0

The Computer Aided System Engineering and Analysis (CASE/A) Version 5.0 Programmer's Manual provides the programmer and user with information regarding the internal structure of the CASE/A 5.0 software system. CASE/A 5.0 is a trade study tool that provides modeling/simulation capabilities for analyzing environmental control and life support systems and active thermal control systems. CASE/A has been successfully used in studies such as the evaluation of carbon dioxide removal in the space station. CASE/A modeling provides a graphical and command-driven interface for the user. This interface allows the user to construct a model by placing equipment components in a graphical layout of the system hardware, then connect the components via flow streams and define their operating parameters. Once the equipment is placed, the simulation time and other control parameters can be set to run the simulation based on the model constructed. After completion of the simulation, graphical plots or text files can be obtained for evaluation of the simulation results over time. Additionally, users have the capability to control the simulation and extract information at various times in the simulation (e.g., control equipment operating parameters over the simulation time or extract plot data) by using "User Operations (OPS) Code." This OPS code is written in FORTRAN with a canned set of utility subroutines for performing common tasks. CASE/A version 5.0 software runs under the VAX VMS(Trademark) environment. It utilizes the Tektronics 4014(Trademark) graphics display system and the VTIOO(Trademark) text manipulation/display system.

Knox, J. C.↗
DOE OSTI2018

Maximum Concentration Values Review for Use in NUCON Vapor Abatement Unit Testing

Exponent has recommended that “high inlet spike” concentrations be verified for accuracy regarding their representation of the maximum measured headspace concentrations for tanks at Hanford. Exponent further recommended that “high inlet spike” concentrations of chemicals of potential concern (COPCs) be inclusive of surrogate COPCs. In the initial analysis (Rev. A Test Plan), only analytical results from the Site-Wide Industrial Hygiene Database (SWIHD) were used. The reason for this initial decision was a concern about Washington River Protection Solutions (WRPS) taking responsibility for results that were not produced during their contract tenure. As a result of Exponent’s comments, WRPS verified the “high inlet spike” values for accuracy against the data for single-shell tanks in all the historical databases, not only SWIHD. Measurements made prior to interim waste stabilization or waste retrieval were not considered in the verification of maximum measured concentrations as they are not representative of current tank farm conditions. Data for surrogate COPCs were also considered in determining the “high inlet spike” concentrations. Table S.1 shows the newly evaluated concentrations (COPC and surrogate). The original and revised test conditions are also shown with changes indicated by red text.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗