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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

TRACER Lightning Mapping Array Field Campaign Report

Our observational contribution to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Tracking Aerosol Convection Interactions Experiment (TRACER) was the deployment of additional Lightning Mapping Array sensors to provide enhanced capability to the Houston Lightning Mapping Array (HLMA) during the TRACER intensive operational period. To that end, the Texas Tech University personnel (Professor Bruning and Dr. Brunner, and graduate students Jessica Souza, David Singewald, Stephanie Weiss, and Matthew Miller) deployed two portable LMA antennae at locations G and B shown in the map below. The map also shows the predicted lightning flash detection efficiency in black contours, as well as color-shaded very-high-frequency (VHF) source detection efficiency, which roughly corresponds to the sensitivity to lightning channel detail. Feeds from these sensors were integrated in the HLMA processing in real-time and in post-processing, partially leveraging National Science Foundation support through the TRACER campaign that supported the core HLMA, operated by Timothy Logan.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Offshore Wind Energy and Communities: Perspectives on Local Impacts [Slides]

In this webinar hosted by the U.S. Department of Energy's WINDExchange initiative, an expert panel discusses the myriad ways that offshore wind may impact communities. Impacted communities can take a variety of forms, from coastal communities hosting ports and cable landings to ocean users such as commercial fishermen, and can experience a range of environmental, economic, cultural, and other impacts related to offshore wind energy. This webinar explores these topics from diverse perspectives and provides an introduction to the local footprints of this emerging industry.

17 WIND ENERGY↗
DOE OSTI2023

TRACER Carbonaceous Aerosols Thrust – University of California, Davis Field Campaign Report

The broader U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign aims to increase our understanding of convective cloud life cycles and aerosol-convection interactions. Our TRACER Carbonaceous Aerosols Thrust-University of California, Davis (TRACER-CAT-UCDavis) study complemented these broader aims by characterizing and quantifying the optical properties and composition of carbonaceous aerosols during part of the TRACER intensive sampling period (July 1- July 31, 2022) at the first ARM Mobile Facility (AMF1) main site (M1) in La Porte, Texas. Our measurements complemented the suite of instrumentation already provided by the AMF1, expanding the capabilities through deployment of unique, state-of-the-science instrumentation. The instrumentation included: (i) two cavity-attenuated phase shift spectroscopy single-scatter albedo (CAPS-SSA) instruments operating at 530 nm and 630 nm, and that were modified to characterize particle light absorption, extinction, and scattering at elevated humidities; (ii) the UC Davis dual-wavelength cavity ringdown-photoacoustic spectrometer (CRD-PAS), which characterizes dry particle extinction and absorption at 405 nm and 532 nm; (iii) a soot particle aerosol mass spectrometer (SP-AMS) that operated in “laser only” mode that characterized the size-dependent compositions of black carbon (BC)-containing particles; (v) a thermal denuder, to remove coatings on particles; and (vi) a scanning electrical mobility sizer (SEMS), to characterize particle mobility diameters from 10-1300 nm. Our measurements occurred alongside complementary observations made by Los Alamos National Laboratory (LANL) during the TRACER-CAT-LANL study, including a humidified CAPS-SSA instrument operating at 450 nm. Our primary scientific interest is in understanding the relationship between particle composition and light absorption, with a particular focus on the influence of water uptake. While it is known that coatings on BC can enhance absorption, the extent to which this occurs in the atmosphere and the specific role that water plays as a coating remain unclear. The TRACER-CAT-UCDavis measurements were made with near-complete coverage for the CRD-PAS, SP-AMS, and SEMS throughout the intensive period. The UC Davis humidified CAPS-SSA instruments had significant challenges with operation owing to the demanding conditions (large temperature fluctuations, high humidity), exacerbated by supply chain issues that delayed resolution of these challenges. However, the humidified CAPS-SSA instrument operated by LANL operated throughout the intensive period with near-complete coverage. The dry light extinction measurements from the CRD-PAS measurements and the LANL CAPS-SSA exhibited a good correlation, although the CAPS-SSA systematically measured greater extinction values than expected. While all instruments, with the exception of an aerodynamic particle sizer (APS), measured behind a common particulate matter (PM)2.5 μm cyclone, the greater extinction measured by the LANL CAPS-SSA compared to the CRD-PAS may have resulted from different losses of larger particles in the sampling lines from the cyclone to the instruments; the tubing length was shorter from the cyclone to the LANL CAPS-SSA, consistent with this idea. A summary of the TRACER-CAT-UCDavis measurements, along with some of the TRACER-CAT-LANL measurements, are shown in the figure below. Notably, there were periods when the contributions of presumed dust were substantial and even dominated the observed light extinction and absorption. Also, there was a clear shift in the behavior of submicron particles from before July 16, 2022 to after, with the prior period exhibiting regular episodes of new particle formation and the latter period exhibiting rapid variations in the concentrations of small particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modularization of EDGE Workflows Using Nextflow: Improving the Efficiency and Maintainability of Bioinformatics Software

EDGE is a bioinformatics platform developed in 2016 by researchers at Los Alamos National Laboratory (LANL) to facilitate the analysis of next-generation sequencing data by researchers with varying levels of experience in bioinformatics (Li et al., 2017). Users with single-end, paired-end or long-read sequencing data can provide their reads as input to EDGE and select the combination of workflows to run that are most useful for their research (e.g., quality control of reads, genome assembly, or the taxonomic classification of input reads). Table 1 summarizes the modules available in EDGE. EDGE is available as a web platform at https://edgebioinformatics.org, as installable source code maintained on GitHub under a GPLv3 license, and as a publicly hosted Docker image.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

OpenCSP Step-by-Step: Getting Started Guide for Windows (V.1.0)

This document provides a step-by-step tutorial on how to set up OpenCSP for both users and developers. It is meant to support novice users and does not require software engineering experience. It is a detailed extension of the OpenCSP getting started on-line documentation, found here: https://opencsp.readthedocs.io/en/main/contributing.html#getting-started. For an overview of OpenCSP overall, see the OpenCSP website: https://opencsp.sandia.gov. For details on OpenCSP components and algorithm, see the references.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Working Safely at KEK

This booklet has been prepared for KEK users, primarily working on the Belle II experiment, with useful information for maintaining a safe working environment. In it, topics from initiating and fulfilling a work plan to radiological and electrical safety to fall prevention are introduced with instructions and hints for keeping your workplace safe.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

TRACER-iso Field Campaign Report

The TRACER-iso project took place from June 1 to September 30, 2022, as part of the intensive operational period (IOP) of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s TRacking Aerosol Convection interactions ExpeRiment (TRACER) at the main project site at the La Porte, Texas, municipal airport. The project sought to use measurements of the stable isotopic composition of water vapor to better understand cloud-aerosol interactions in deep convection in a polluted urban setting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey

Artificial intelligence (AI) approaches have been introduced in various disciplines but remain rather unused in head and neck (H&N) cancers. This survey aimed to infer the current applications of and attitudes toward AI in the multidisciplinary care of H&N cancers. From November 2020 to June 2022, a web-based questionnaire examining the relationship between AI usage and professionals’ demographics and attitudes was delivered to different professionals involved in H&N cancers through social media and mailing lists. A total of 139 professionals completed the questionnaire. Only 49.7% of the respondents reported having experience with AI. The most frequent AI users were radiologists (66.2%). Significant predictors of AI use were primary specialty (V = 0.455; p < 0.001), academic qualification and age. AI’s potential was seen in the improvement of diagnostic accuracy (72%), surgical planning (64.7%), treatment selection (57.6%), risk assessment (50.4%) and the prediction of complications (45.3%). Among participants, 42.7% had significant concerns over AI use, with the most frequent being the ‘loss of control’ (27.6%) and ‘diagnostic errors’ (57.0%). This survey reveals limited engagement with AI in multidisciplinary H&N cancer care, highlighting the need for broader implementation and further studies to explore its acceptance and benefits.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Microtopographic and Depth Controls on Active Layer Chemistry in Arctic Polygonal Ground: Supporting Data

Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. This data package includes one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Scikit HEP Project -- overview and prospects

Scikit-HEP is a community-driven and community-oriented project with the goal of providing an ecosystem for particle physics data analysis in Python. Scikit-HEP is a toolset of approximately twenty packages and a few "affiliated" packages. It expands the typical Python data analysis tools for particle physicists. Each package focuses on a particular topic, and interacts with other packages in the toolset, where appropriate. Most of the packages are easy to install in many environments; much work has been done this year to provide binary "wheels" on PyPI and conda-forge packages. The Scikit-HEP project has been gaining interest and momentum, by building a user and developer community engaging collaboration across experiments. Some of the packages are being used by other communities, including the astroparticle physics community. An overview of the overall project and toolset will be presented, as well as a vision for development and sustainability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

sourcePy

Pollutant source identification techniques (of which there are many variations) are either locked behind researchers writing their own code for each use case or GUI platforms that are easy to use but inflexible and opaque. The Python package sourcePy brings together many of the pollutant source identification algorithms, giving the user full control out of the box. It aims to create a platform for source identification experiments where the full analysis from beginning to end can be done in Python, with a level of specificity in design that isn't available in the GUI options. sourcePy provides users with a few key features: -A Python interface with HYSPLIT, which can be used to generate trajectories and concentration plumes -Several Python classes which standardize the preparation and processing of data related to source identification experiments -Example scripts and notebooks that allow even new python users to get started with their own experiments quickly -Visualization methods

Arseneau, Isaac [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

A frugal CRISPR kit for equitable and accessible education in gene editing and synthetic biology

Equitable and accessible education in life sciences, bioengineering, and synthetic biology is crucial for training the next generation of scientists, fostering transparency in public decision-making, and ensuring biotechnology can benefit a wide-ranging population. As a groundbreaking technology for genome engineering, CRISPR has transformed research and therapeutics. However, hands-on exposure to this technology in educational settings remains limited due to the extensive resources required for CRISPR experiments. Here, we develop CRISPRkit, an affordable kit designed for gene editing and regulation in high school education. CRISPRkit eliminates the need for specialized equipment, prioritizes biosafety, and utilizes cost-effective reagents. By integrating CRISPRi gene regulation, colorful chromoproteins, cell-free transcription-translation systems, smartphone-based quantification, and an in-house automated algorithm (CRISPectra), our kit offers an inexpensive (~$2) and user-friendly approach to performing and analyzing CRISPR experiments, without the need for a traditional laboratory setup. Experiments conducted by high school students in classroom settings highlight the kit’s utility for reliable CRISPRkit experiments. Furthermore, CRISPRkit provides a modular and expandable platform for genome engineering, and we demonstrate its applications for controlling fluorescent proteins and metabolic pathways such as melanin production. We envision CRISPRkit will facilitate biotechnology education for communities of diverse socioeconomic and geographic backgrounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Measurement Uncertainty in One-Of-A-Kind Event Data Analysis

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable, have unavoidable built-in differences resulting in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates over the measurement uncertainty. Range of true values depends on built-in differences in physics of the experiment. Stochastic physical processes result typically in a broader range of true values than non-stochastic processes do. Measurement uncertainty depends on a measurement method (properties of the detector not of the experiment). Modern measurement methods, including digital ones, frequently make the measurement uncertainty very small. When data from one–of –a kind experiment are analyzed, only the measurement uncertainty is reported. It provides no information about the range of true experimental values, neither about reliability of a reported data point. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable. Methods for data analysis from an experiment repeated statistically significant number of times are very well developed. They do not require a detailed expertise in physics of an experiment, nor in the properties of the measurement system used, and meaning of the reported uncertainty is well understood in any scientific community. It all changes when data from one-of-a-kind experiment is analyzed. Analyst’s expertise is required both in the physics of the experiment and in all aspects of the measurement system, all possible malfunctions. Data users must remember that only measurement uncertainty is reported from any one-of-a-kind experiment. Theory with simulations may provide estimation of expected built-in differences in the experiment, and by this of expected range of true values for a given experiment; yet measurement uncertainty can never be used in place of the range of true experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Enabling power measurement and control on Astra: The first petascale Arm supercomputer

Astra, deployed in 2018, was the first petascale supercomputer to utilize processors based on the ARM instruction set. The system was also the first under Sandia's Vanguard program which seeks to provide an evaluation vehicle for novel technologies that with refinement could be utilized in demanding, large-scale HPC environments. In addition to ARM, several other important first-of-a-kind developments were used in the machine, including new approaches to cooling the datacenter and machine. Here we document our experiences building a power measurement and control infrastructure for Astra. While this is often beyond the control of users today, the accurate measurement, cataloging, and evaluation of power, as our experiences show, is critical to the successful deployment of a large-scale platform. While such systems exist in part for other architectures, Astra required new development to support the novel Marvell ThunderX2 processor used in compute nodes. In addition to documenting the measurement of power during system bring up and for subsequent on-going routine use, we present results associated with controlling the power usage of the processor, an area which is becoming of progressively greater interest as data centers and supercomputing sites look to improve compute/energy efficiency and find additional sources for full system optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Design and evaluation of alphabetic and numeric input methods for virtual reality

In today’s virtual reality (VR), users have various ways to influence their VR experience, including alphanumeric input. While typing characters and numbers is straightforward on desktop computers, it presents challenges and opportunities in head-mounted display VR due to specific interaction methods and a lack of real-world visual stimuli. Addressing these open questions, our work implements and evaluates ten approaches to alphabetic and numeric inputs in VR. Here, we describe the design motivation behind these input methods and evaluate them in a user study with 40 participants divided into groups for alphabetic and numeric keyboards. This comparison investigates each method’s performance and user interactions. Our findings suggest that different input methods significantly impact words per minute and error rates, and that certain keyboard designs may receive better subjective evaluations despite poorer objective performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An Error Analysis Toolkit for Binned Counting Experiments

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

The U.S. Nuclear Test History

This paper describes a desktop application designed to introduce users to unclassified information for the series of nuclear experiments conducted by the United States, colloquially referred to within the nuclear weapons design community as simply, the “Test History.” The application facilitates simple browsing (by name, by date, and MMDD date code), and more complex analyses based on user-defiend relational database queries.

99 GENERAL AND MISCELLANEOUS↗