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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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DOE OSTI2022

Experimental Unevaluated Nuclear Data List (XUNDL)

Contains nuclear structure and decay data from published articles. Data include nuclear level properties, such as energy, half-life, decay modes, spin and parity, as well as energy and intensity for radiation types such as gammas, alphas, betas and neutrons. For articles published in Physical Review C and the European Physical Journal, compilation takes place during the article submission process. Data from approximately 250 articles are added per year. All the compilation effort is supported by the US Nuclear Data Program and coordinated by the National Nuclear Data Center at Brookhaven National Laboratory, which is also responsible for its web dissemination.

Basic Nuclear Research, nuclear structure and deca↗
DOE OSTI2019

Multiyear Analysis of the Fate and Transport of Contaminated Soils at Plutonium Valley and the Smoky Site, Nevada National Security Site

Desert Research Institute (DRI) has collected approximately 10 years of atmospheric and hydrologic data at Plutonium Valley and the Smoky Site on the Nevada National Security Site to identify the potential for radionuclide-contaminated soils to be transported via wind and water. Plutonium preferentially binds to finer soil particles (Shinn et al., 1993; Miller et al., 2015), which can be transported through erosion processes. Data collected by DRI are used to determine the mechanisms and thresholds that result in the transport of radionuclide-contaminated soils, and climate model projections are used to understand how these mechanisms may change in the future. This work will help identify the parameters and threshold conditions that should be incorporated into post-closure monitoring plans for these and other Soils Corrective Action Unit (CAU) sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Automatic Processing Framework for In Situ Determination of Ecohydrological Root Water Content by Ground-Penetrating Radar

This report concerns Root water content (RWC) as a vital component in water flux in soil-plant-atmosphere continuum. Knowledge of RWC helps to better understand the root function and the soil-root interaction and improves water cycle modeling. However, due to the lack of appropriate methods, field monitoring of RWC is seriously constrained. In this study, we used ground-penetrating radar (GPR), a common geophysical technique, to characterize RWC of coarse roots noninvasively. An automatic GPR data processing framework was proposed to (1) identify hyperbolic root reflections and locate roots in GPR images and (2) extract waveform parameters from the reflected wave of identified roots. These waveform parameters were then used to establish an empirical model and a semiempirical model to determine RWC. We validated the developed models using GPR root data at three antenna center frequencies (500 MHz, 900 MHz, and 2 GHz) that were produced from simulation experiments (with RWC ranging from 70% to 150%) and field experiments in sandy soils (with RWC ranging from 66% to 144%). Our results show that both the empirical and the semiempirical models achieved a good performance in estimating RWC with similar accuracy, i.e., the prediction error [root-mean-square error (RMSE)] was less than 8% for the simulation data and 12% for the field data. For both models, the accuracy of RWC estimation was the highest when applied to 2-GHz data. This study renders a new opportunity to determine RWC under field conditions that enhances the application of GPR for root study and the understanding and modeling of ecohydrology in the rhizosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Robust inference of ecosystem soil water stress from eddy covariance data

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. Here, we develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site’s soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

WE-D-BRF-04: Experimental Investigations On Ion Radiography with Beam Scanning Using a Range Telescope

Purpose: Ion beams exhibit a finite range and an inverted depth-dose profile, the Bragg peak. These favorable properties allow superior tumordose conformality, but introduce sensitivity to range uncertainties. Hence, imaging techniques play an increasingly important role to support the treatment planning and the in-vivo monitoring of the actual ion beam treatment. Methods: This work presents the experimental investigations carried out to address the feasibility of ion transmission imaging at the Heidelberg Ion Therapy center using an active raster scanning beam delivery system and a prototype range telescope set-up based on a stack of 61 parallel-plate ionization chambers (PPIC) interleaved with 3 mm absorber plates of PMMA. Results: An extensive characterization of the set-up in terms of beam parameters and settings of the read-out electronics was performed and results will be presented. A data processing method to increase the range resolution (MIRR) of the PPIC stack was developed. In this approach, the position of the maximum of the Bragg curve is deduced from the ratio of measured signals in adjacent PPIC channels. MIRR evaluation is based on Bragg curves obtained from Monte Carlo simulations and validated with experimental data acquired with the PPIC stack using ion beams. MIRR was applied to the carbon ion radiography of an anthropomorphic Alderson head phantom yielding a resolution of 0.8 mm water equivalent thickness (WET) compared to the nominal value of 3.495 mm WET given by the thickness of the absorber slabs in the PPIC stack. An absolute comparison of the Alderson phantom carbon ion transmitted image with an X-ray digitally reconstructed radiography, both converted into WET, will also be shown. Conclusion: The obtained results are very promising and motivate further developments of the system towards an eventual clinical use.This work is supported by the German Research Foundation and the German Academic Exchange Service. This work is supported by the German Research Foundation (DFG) and the German Academic Exchange Service (DAAD)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Using OpenMP for HEP Framework Algorithm Scheduling [Slides]

The OpenMP standard is the primary mechanism used at high performance computing facilities to allow intra-process parallelization. In contrast, many HEP specific software (such as CMSSW, GaudiHive, and ROOT) make use of Intel's Threading Building Blocks (TBB) library to accomplish the same goal. In this talk we will discuss our work to compare TBB and OpenMP when used for scheduling algorithms to be run by a HEP style data processing framework (i.e. running hundreds of interdependent algorithms at most once for each event read from the detector). This includes both scheduling of different algorithms to be run concurrently as well as scheduling concurrent work within one algorithm. As part of the discussion we present an overview of the OpenMP threading model. We also explain how we used OpenMP when creating a simplified HEP-like processing framework. Using that simplified framework, and a similar one written using TBB, we will present performance comparisons between TBB and different compiler versions of OpenMP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

LArSoft and Future Framework Directions at Fermilab

The diversity of the scientific goals across HEP experiments necessitates unique bodies of software tailored for achieving particular physics results. The challenge, however, is to identify the software that must be unique, and the code that is unnecessarily duplicated, which results in wasted eort and inhibits code maintainability. Fermilab has a history of supporting and developing software projects that are shared among HEP experiments. Fermilab’s scientific computing division currently expends eort in maintaining and developing the LArSoft toolkit, used by liquid argon TPC experiments, as well as the event-processing framework technologies used by LArSoft, CMS, DUNE, and the majority of Fermilab-hosted experiments. As computing needs for DUNE and the HL-LHC become clearer, the computing models are being rethought. Presented here are Fermilab’s plans for addressing the evolving software landscape as it relates to LArSoft and the data-processing frameworks, specifically as it relates to the DUNE experiment.

Knoepfel, Kyle↗
DOE OSTI2020

Using OpenMP for HEP framework algorithm scheduling

The OpenMP standard is the primary mechanism used at high performance computing facilities to allow intra-process parallelization. In contrast, many HEP specific software packages (such as CMSSW, GaudiHive, and ROOT) make use of Intel’s Threading Building Blocks (TBB) library to accomplish the same goal. In these proceedings we will discuss our work to compare TBB and OpenMP when used for scheduling algorithms to be run by a HEP style data processing framework. This includes both scheduling of different interdependent algorithms to be run concurrently as well as scheduling concurrent work within one algorithm. As part of the discussion we present an overview of the OpenMP threading model. We also explain how we used OpenMP when creating a simplified HEP-like processing framework. Using that simplified framework, and a similar one written using TBB, we will present performance comparisons between TBB and different compiler versions of OpenMP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Beowulf v2.5.3 User Guide: Revision 5

This document is a user guide for the Beowulf (rebranding of Watchmen) tool. It describes how operators can access and utilize the application's functionality. Beowulf is a research software application developed by Pacific Northwest National Laboratory (PNNL) that incorporates the scientific and operational expertise for reviewing data from treaty monitoring radionuclide stations. These stations are part of a worldwide network to monitor for nuclear explosions, and the data they produce are critical to make the determination of whether a sample is from a nuclear explosion or some other source (i.e., nuclear reactor or medical isotope production facility). Stations deliver their measurements and system status to the International Monitoring System (IMS), which forwards it via email to all subscribers. Beowulf is capable of processing data from several radioxenon station types and development is in progress on a solution for particulate stations. Screening of data in Beowulf may be done by a number of different users such as radionuclide analysts, evaluators, and data quality experts. This guide is provided to assist those users in navigating the application. The term Beowulf is used generically throughout this document to refer to any of the various components in the software application. The user interface that is viewed with a web browser is the primary focus of this user guide. Other components include a database to store measurements and state of health (SOH) data; and the data loader that monitors incoming emails, parses the data, populates the database, does the initial analysis, and routes data for review.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment

Abstract. Hydrological modeling is a crucial component in hydrology research, particularly for projecting future scenarios. However, achieving reproducibility and automation in distributed hydrological modeling research for modeling, simulation, and analysis is challenging. This paper introduces rSHUD v2.0, an innovative, open-source toolkit developed in the R environment to enhance the deployment and analysis of the Simulator for Hydrologic Unstructured Domains (SHUD). The SHUD is an integrated surface–subsurface hydrological model that employs a finite-volume method to simulate hydrological processes at various scales. The rSHUD toolkit includes pre- and post-processing tools, facilitating reproducibility and automation in hydrological modeling. The utility of rSHUD is demonstrated through case studies of the Shale Hills Critical Zone Observatory in the USA and the Waerma watershed in China. The rSHUD toolkit's ability to quickly and automatically deploy models while ensuring reproducibility has facilitated the implementation of the Global Hydrological Data Cloud (https://ghdc.ac.cn, last access: 1 September 2023), a platform for automatic data processing and model deployment. This work represents a significant advancement in hydrological modeling, with implications for future scenario projections and spatial analysis.

Shu, Lele (ORCID:0000000269034466)↗
DOE OSTI2020

Data for “Lightning Interferometry Uncertainty, “Focused Interferometry”, and Evidence of Lightning being Ignited by a Cosmic-ray Shower” by Shao et al.

This summarizes the data from our broadband RF interferometric mapping and polarization (BIMAP) system used to produce the figures in the revised manuscript “Lightning Interferometry Uncertainty, “Focused Interferometry”, and Evidence of Lightning being Ignited by a Cosmic-ray Shower” that was originally submitted to Journal of Geophysical Research (JGR) for publication. Note that the original manuscript was titled ““Focused Interferometry” and Fine Structure of Lightning-Initiating Fast Positive Streamers” and was released with LA-UR-19-32549. In accordance with JGR’s data policy (https://www.agu.org/Publish-withAGU/Publish/Author-Resources/Policies/Data-policy), it is the intention to make this data publicly available at the time of article submission. The data set includes raw BIMAP RF data and processed results for two lightning flashes. The data is available in two files (“FPS_data_20170606_361.sav” and “Small_IC_20180520_205644_408.sav”) located at “/home/xshao/HEPL/Analysis” which were packaged with IDL save commend. The raw data includes 3 channels of RF data, 2 channels of RF polarization data, and 1 channel of electric field change data. The processed data includes the RF source positions, source position uncertainties, and the polarization analysis.

58 GEOSCIENCES↗
DOE OSTI2019

Real-Time Simultaneous 3D Volumetric Imaging and Mapping of Gamma-ray and Neutron Sources

The invention combines radiation detection instrumentation, data processing algorithms, and visualization software to enable, for the first time ever, simultaneous, real-time imaging of both gamma ray and neutron sources (fast and slow). Radiation detectors sensitive to gamma rays and neutrons are integrated with readout electronics that allow discriminated particles to be incorporated into real-time 3D volumetric reconstructions as two separate data streams. Using the Scene Data Fusion (SDF) conceptual framework and contextual sensors from the Localization and Mapping Platform (LAMP) developed at LBNL, gamma-ray and neutron data are fused onto contextual information from the environment around the detection system. The invention is compatible with radiation detection media capable of detecting and discriminating between gamma rays and neutrons or the pairing of multiple detectors separately capable of detecting gamma rays and/or neutrons. It can be integrated into a compact, lightweight imaging platform for operation as a hand-carry device, on unmanned aerial systems, and with unmanned vehicles. The ability to measure neutron enables the detection and 3D localization of shielded nuclear materials such as Pu-239 which is not possible with means of gamma-ray detection and spectroscopy overcoming of major limitation in the detection of such materials to-date.

Cates, Joshua↗
DOE OSTI2018

Data-Driven Mathematical Modeling of the Effect of Particle Size Distribution on the Transitory Reaction Kinetics of Hot Metal Desulfurization

The aim of this work was to develop a prediction model for hot metal desulfurization. More specifically, the study aimed at finding a set of explanatory variables that are mandatory in prediction of the kinetics of the lime-based transitory desulfurization reaction and evolution of the sulfur content in the hot metal. The prediction models were built through multivariable analysis of process data and phenomena-based simulations. The model parameters for the suggested model types are identified by solving multivariable least-squares cost functions with suitable solution strategies. One conclusion we arrived at was that in order to accurately predict the rate of desulfurization, it is necessary to know the particle size distribution of the desulfurization reagent. It was also observed that a genetic algorithm can be successfully applied in numerical parameter identification of the proposed model type. It was found that even a very simplistic parameterized expression for the first-order rate constant provides more accurate prediction for the end content of sulfur compared to more complex models, if the data set applied for the modeling contains the adequate information.

36 MATERIALS SCIENCE↗
DOE OSTI2026

STM/S Grid LDOS Data and Analysis Code for Deciphering Majorana Zero Modes in Topological Superconductor

This dataset provides raw millikelvin scanning tunneling microscopy/spectroscopy (STM/S) grid spectroscopy data and Python analysis scripts supporting the manuscript “Deciphering Majorana Zero Modes in Topological Superconductor FeTe0.55Se0.45 with Machine-Learning-Assisted Spectral Deconvolution.” The dataset includes a raw grid spectroscopy file acquired on FeTe0.55Se0.45 at 40 mK under magnetic field, together with Python/Jupytext analysis scripts used for STM/S data processing, visualization, spectral deconvolution, Lorentzian peak fitting, feature extraction, machine-learning-assisted clustering, and figure generation. These files support the analysis of vortex-core local density of states and the identification of zero-bias-peak-related spectral components from complex in-gap states. The dataset is intended to provide a citable archival record of the data and analysis code associated with the published manuscript and to support transparency and reproducibility of the reported STM/S and machine-learning workflow.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Software Development for Data Visualization and Analysis of PN-Diodes & MOSFET Devices

The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development of an end state vision to implement digital monitoring in nuclear plants

Transitioning from an onsite Maintenance & Diagnostics Center to cloud-based services offers many new opportunities with computing power and storage, but also new challenges in terms of networking and security. This report will cover everything required for that transition including data processing and uploading to cloud services, feature selection, model creation, and result visualization for decision making. Although there are several other cloud-based services (e.g. Amazon Web Services and Google Cloud), this report explores Microsoft Azure to simplify nomenclature and maintain a consistent focus. Many of the services offered by Microsoft Azure are also available in the other cloud-based services, and their differences have been recorded in other literature. The Azure services most important to a nuclear power plant including networking & security, storage & databases, and Artificial Intelligence (AI) are reviewed here. Networking covers all aspects related to communication to Azure resources including security, privacy, and redundancy. Storage & databases includes data storage, upgrading, patching, backups, and monitoring. The AI services allows the user access to the machine learning (ML) techniques developed with Azure including automated ML, anomaly detection, computer vision, and natural language processing. This report summaries the features, capabilities, and challenges when using cloud-based services in a user-friendly manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

New generation of data acquisition and data storage systems of the IBR-2 reactor spectrometers complex

The paper presents an overview of works on the creation of data acquisition and data storage systems, which have been carried out in the Department of the IBR-2 spectrometers complex (DCS) of the Frank Laboratory of Neutron Physics (FLNP) over the past 15 years (before, during, and after the modernization of the IBR-2 reactor). These systems represent a unified set of identical (from the viewpoint of hardware) modules limited in type but functionally complete, wherein distinctions in parameters, functional capabilities, encoding, correction and preliminary data processing procedures specific to each spectrometer are realized on the level of microprograms, electronic tables, and integrated software control system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor

Neuromorphic processors have garnered considerable interest in recent years for their potential in enabling energy-efficient and high-speed computing. The Locally Competative Algorithm (LCA) has been utilized for power efficient sparse coding on neuromophic processors, including the first Loihi processor \cite{appletospikes, loihi1}. With the Loihi 2 processor enabling custom neuron models and graded spike communication, more complex implementations of LCA are possible \cite{loihi2}. We present a new implementation of LCA designed for the Loihi 2 processor and perform an initial set of benchmarks comparing it to LCA on CPU and GPU devices. In these experiments LCA on Loihi 2 is faster and orders of magnitude more efficient, while maintaining similar reconstruction quality. We find this performance improvement increases as the LCA parameters are tuned towards greater representation sparsity. Our study highlights the potential of neuromorphic processors, particularly Loihi 2, in enabling intelligent,autonomous, real-time processing on small robots, satellite where there are strict SWaP (small, lightweighr, and low-power) requirement. By demonstrating the superior performance of LCA on Loihi 2 compared to conventional computing device, our study suggests that Loihi 2 could be a valuable tool in advancing these types of applications. Overall, our study highlights the potential of neuromorphic processors for efficient and accurate data processing on resource-constrained devices.

Parpart, Gavin G.↗