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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The First Neptunium Dioxide Neutron Diffraction Experiment at HFIR

Here we present the first neutron diffraction experiment of a 50 mg sample of neptunium(IV) dioxide (NpO 2 ) powder at the High Flux Isotope Reactor (HFIR) using the wide-angle neutron diffractometer (WAND 2 ) HB-2C. We also provide a brief literature survey to pinpoint gaps in the crystal, electronic, and magnetic structure of NpO 2 to determine the optimum experiment to be pursued in the next HFIR user proposal cycle. Characterizing actinide materials with neutron diffraction, inelastic scattering, neutron imaging, polarized neutron studies, and small-angle neutron scattering techniques will increase our understanding of 5f electron behavior and elucidate atomic and magnetic structural properties. This strategy will help fill gaps in the literature and provide theoretical physicists with the data needed to build physical and chemical models to guide and validate computational methods. These methods may be used for predicting structural and chemical features of actinide-based materials. This proof-of-principle effort begins to uncover how to advance actinide science and technology at Oak Ridge National Laboratory (ORNL) using neutron capabilities. This effort has already sparked collaborative discussions between researchers outside the Radioisotope Science and Technology Division, including theoretical physicists from the Nuclear Nonproliferation Division and beamline scientists in the Neutron Scattering Division. We intend to continue pursuing neutron experiments and develop a scientific strategy focused on studying transuranium elements (e.g., Np, Pu, Am, and Cm) using the advanced neutron capabilities at ORNL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Evaluation of the NSUF Reactor Activation and Damage (RAD) Calculator damage component

The Nuclear Science User Facilities (NSUF) provide researchers access to nuclear research facilities and expertise all over the United States and at the Belgian Center for Nuclear Research (SCK/CEN). One special capability of the NSUF is providing access to nuclear research and test reactors often used for conducting material testing experiments. These services are provided at no cost to the researcher through a competitive, peer-reviewed process. With so many proposals being submitted simultaneously, an NSUF information management resource called the Combined Materials Experiment Toolkit (CoMET) was implemented to speed up the review process and give users access to the information and tools necessary for designing meaningful experiments and writing the best proposals possible. One of CoMET’s tools is the Reactor Activation and Damage (RAD) Calculator. For those with little or no background in it, neutron irradiation in research and test reactors can be a challenging subject to include in a proposal. That is why the RAD Calculator was created to assist users with providing estimates of irradiation and post-irradiation conditions, enabling them to select the best neutron irradiation and post-irradiation examination facilities for reaching their experiment goals. The RAD Calculator is a general scoping tool that estimates radiation damage in terms of DPA, in addition to the resulting radioactivity of the material post-irradiation. This report evaluates the neutron damage component of the RAD Calculator. The evaluation of the activation component of the calculator is covered in report INL/EXT-20-58080.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Advancing uncertainty characterization for understanding projected water scarcity in multi-sector, multi-actor river basins across scales.

Invited Talk at AGU Fall Meeting 2023 Modeling how human institutions and infrastructure interact with the water cycle is essential to better understand the vulnerability, and resilience of water resources systems from the local to the global scale. This is especially true when investigating multi-sector, multi-actor responses to the effects of long-term changes and short-term shocks. It is also well recognized that uncertainty present throughout the modeling cycle (e.g., in data, functional relations, and model coupling approaches) limits our ability to trace the interactive dynamics of human-water systems, as well as to quantify their implications for management and planning. Systems with large numbers of diverse stakeholders further compound this challenge, as uncertain drivers and complex dynamics might have very disparate effects on water users. The work presented is conducted through the Integrated Multisector Multiscale Modeling (IM3) Science Focus Area, which explores how human and natural systems co-evolve in response to change. Through this multi-year effort, we have developed exploratory modeling methods to better characterize how the uncertain human and natural drivers of water scarcity yield consequential vulnerabilities in institutionally complex, multi-sectoral systems. This talk will specifically present on a series of uncertainty characterization experiments performed in the Upper Colorado River Basin, a sub-basin of the Colorado with thousands of water users. These complementary and systematic experiments are aimed at understanding: How are various uncertain stressors (e.g., climate change, demand growth) affecting the diverse water users of this basin in terms of water shortage? What are the key drivers of this shortage for each user? Methods and results from this work are used to address additional questions on the ability of adaptation to modulate the effects of these uncertain drivers, and on their compounding effects across spatial scales and through sectoral interactions.

Hadjimichael, Antonia↗
DOE OSTI2022

Mitigate: An Adaptive Network Data Anonymization Tool Using Condensation-Based Differential Privacy

Modern network devices collect a large amount of data that can be analyzed to identify bottlenecks, anomalies, cyber-attacks, etc. Therefore, there is often a need to analyze such collections of network data quite often by an external expert or by the research community. However, these collections of data contain sensitive, proprietary information. In order for the network data to be shared, it must first be anonymized. The overall objective of this project is to develop an innovative privacy management tool to anonymize network data and achieve sufficient privacy, acceptable data utility, and efficient data analysis at the same time. No existing anonymization methods can achieve all of these at the same time. The core of this technology is a differential private clustering algorithm that provides strong privacy protection, preserves data properties important for subsequent analysis, and allows the party receiving the anonymized data to conduct analysis directly on anonymized data without the need of decryption or any extra processing. The research carried out was to design, implement and verify a solution to this problem by completing the following tasks: 1) developing the core technology; 2) developing a context based method that automatically recommends fields that must be anonymized; 3) conducted experiments showing superior results using our approach compared to existing tools, and 4) developed an intuitive but basic user interface. The research that was conducted generated novel algorithmic techniques that utilize state-of-the-art methods such as condensation, differential privacy preservation, clustering, automated tuning based on contextual awareness, and recommendation techniques to specify columns to users for anonymization leading to optimal privacy that allows research analysis on the dataset. Experiments were conducted to evaluate the efficacy of these novel algorithmic techniques by performing analysis on original non-anonymized datasets, then conducting analysis on the same yet anonymized datasets and comparing the results of the analyses. Overall, the anonymized analysis results were within 1% of the original results, verifying that the generated technology not only guarantees a high level of privacy but also enables research analysis as if it were conducted on the original dataset. Potential applications of this technology include anonymization of any type of structured network datasets that contain sensitive identifiers, such as IP addresses, that can be used in multiple applications. For example, to create an AI or machine learning model for cyber security, e.g., to detect attacks, or for performance analysis, e.g., identify bottlenecks or predict performance. In addition, a market analysis that was conducted for potential applications of this technology identified a broader range of applications of our anonymization technology beyond the network sector that includes healthcare, banking, insurance, securities, finance (FISB), data brokering, cloud services, ad sales, and government.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Development of the Pooled Rideshare Acceptance Model (PRAM)

Due to the advancements in real-time information communication technologies and sharing economies, rideshare services have gained significant momentum by offering dynamic and/or on-demand services. Rideshare service companies evolved from personal rideshare, where riders traveled solo or with known individuals, into pooled rideshare (PR), where riders can travel with one to multiple unknown riders. Similar to other shared economy services, pooled rideshare is beneficial as it efficiently utilizes resources, resulting in reduced energy usage, as well as reduced costs for the riders. However, previous research has demonstrated that riders have concerns about using pooled rideshare, especially regarding personal safety. A U.S. national survey with 5385 participants was used to understand human factor-related barriers and user preferences to develop a novel Pooled Rideshare Acceptance Model (PRAM). This model used a covariance-based structural equation model (CB-SEM) to identify the relationships between willingness to consider PR factors (time/cost, privacy, safety, service experience, and traffic/environment) and optimizing one’s experience of PR factors (vehicle technology/accessibility, convenience, comfort/ease of use, and passenger safety), resulting in the higher-order factor trust service. We examined the factors’ relative contribution to one’s willingness/attitude towards PR and user acceptance of PR. Privacy, safety, trust service, and convenience were statistically significant factors in the model, as were the comfort/ease of use factor and the service experience, traffic/environment, and passenger safety factors. The only two non-significant factors in the model were time/cost and vehicle technology/accessibility; it is only when a rider feels safe that individuals then consider the additional non-significant variables of time, cost, technology, and accessibility. Privacy, safety, and service experience were factors that discouraged the use of PR, whereas the convenience factor greatly encouraged the acceptance of PR. Despite the time/cost factor’s lack of significance, individual items related to time and cost were crucial when viewed within the context of convenience. This highlights that while user perceptions of privacy and safety are paramount to their attitude towards PR, once safety concerns are addressed, and services are deemed convenient, time and cost elements significantly enhance their trust in pooled rideshare services. This study provides a comprehensive understanding of user acceptance of PR services and offers actionable insights for policymakers and rideshare companies to improve their services and increase user adoption.

dynamic rideshare system↗
DOE OSTI2021

SPEARS: A Database-Invariant Spectral modeling API

The Spectral Physics Environment for Advanced Remote Sensing (SPEARS) application programming interface (API) is a Python-based, line-by-line, local thermal equilibrium (LTE) spectral modeling code which is optimized for simultaneously synthesizing optical spectra from any combination of fundamental spectroscopic databases. In this article, we contribute two novel spectral modeling techniques to the scientific literature. First we describe how SPEARS integrates a physics-based collisional model for calculating pressure broadening in the absence of available broadening coefficients. With this collisional model implementation, a generalized approach to fundamental spectroscopic databases can be achieved across multiple databases. We also detail our adaptive grid mesh algorithm developed to make the code scalable for simulating large spectral bandwidths at high spectral fidelity using intuitive grid parameters. Here, we present comparisons to other modeling tools, experiments, and provide a discussion on the SPEARS user interface.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Sample Management Tools for the Irradiation Test Area (ITA)

The ITA offers onsite radiation testing, and will be available starting Fall 2020. It is projected to have testing slots about 40x/year and a capacity to reach fluences of 1016 protons/cm2 in four hours. A 400 MeV proton beam is directed to samples in a concrete shielding cave, with variations in place available to the user’s preferences. The ITA regulates all its experiment data through ITA’s Data Manager (IDM).

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

K-Modules

K-Modules are capacitive energy modules designed to be stacked together to form a capacitor bank (aka a Marx bank). Discharging the stack produces a single, high voltage, high current pulse that when coupled to an X-ray (or electron) tube, produces energetic X-rays (or an intense electron beam, E-beam). The energetic X-rays are used in Flash X-ray Radiography (FXR), a technique to image objects moving at extremely high speed to measure their speed, shape and internal density profiles. The images help validate computer models for materials behavior under extreme pressure and temperature. FXR is a technology critical to dynamic experiments for the national security mission, and most users are DOE and DOD labs. Febetrons, the X-ray generating devices, are used at these sites and rely on capacitive energy modules for their operation. A stack of the newly developed K-modules will significantly extend the capabilities of these Febetrons

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

TRACER NASA Goddard Space Flight Center TOLNet Field Campaign Report

In September 2021, the National Aeronautics and Space Administration (NASA) deployed assets to the Houston, Texas region to measure air-quality-relevant constituents at high spatial and temporal resolutions. This effort was conducted in partnership with the Texas Commission on Environmental Quality, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility-led Tracking Aerosol Convection interactions ExpeRiment (TRACER) field campaign, and several academic collaborators.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Addressing Regulatory Burdens to Accessing Solar Among Municipal, Commercial and Institutional Customers Through Collaborative Partnerships (Final Technical Report)

The project focused on providing education to large energy customers, with a focus on local governments, to help them better understand and overcome barriers to solar energy adoption that currently exist (or could exist) in utility planning processes and/or within wholesale energy markets. The project team created accessible educational materials — ranging from reports to case studies to webinars — that could connect with stakeholders who rarely engage in these venues, have limited bandwidth to do so, and possess little previous knowledge of these issues. The project team focused on sharing lessons learned and best practices based on the experiences of other local governments and large energy users that have engaged on these issues, including the PJM Cities and Communities Coalition (PJMCCC). The project sought to better connect these customers and other stakeholders to deepen and expand opportunities for them to engage together on these issues, as well as build peer networks to facilitate the exchange of information. The project team held convenings of key partners — such as local governments, developers, regulators, utilities and large solar buyers — to discuss best practices, develop research products to broaden stakeholders’ knowledge base, and to foster these peer networks.

14 SOLAR ENERGY↗
DOE OSTI2024

POEM

User manual for software POEM (Platform of Optimal Experiment Management).

42 ENGINEERING↗
DOE OSTI2024

EPCAPE – Ultrafine Particle Properties Field Campaign Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Eastern Pacific Cloud Aerosol Precipitation Experiment – Ultrafine Particle Properties (EPCAPE-UPP) campaign combined a unique suite of instruments to probe the chemical and physical properties of ultrafine (sub-100-nm) atmospheric particles from 15 April to 15 June 2023 at the Mt. Soledad campaign site near San Diego, California.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of the Self Retrieval Augmented Generation Technique on Common Security Advisory Framework Data

This small experimental report evaluates a variation of Retrieval Augmented Generation (RAG), called Self-RAG. This method uses a generative language model that incorporates retrieved facts into its generation and is explicitly trained to be able to determine whether retrieved information is enough to answer the input query, with a user-defined threshold for confidence. We performed an experiment using data from the publicly available CISA Common Security Advisory Framework (CSAF) repository (https://github.com/cisagov/CSAF) as the database of facts to be used in retrieval. Qualitative results from the experiment demonstrate that the Self-RAG method has some ability to provide reasonable answers to queries that are in the dataset and will often ignore irrelevant information when asked outside of domain questions (e.g., general facts). In settings with deliberately confusing questions (the question is within domain, but asks about a fabricated advisory), it was able to refuse 40% of the time without further adjustments to the original framework. While this performance is not sufficient for current practical use, further improvements to data formatting, disambiguating results, and leveraging threshold values could improve performance significantly. However, evaluating this will require more extensive evaluations on larger datasets and potentially better models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Total Column Infrared Trace Species in Baltimore Field Campaign Report

The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE), including the first ARM Mobile Facility (AMF1), occurred during 2025 at a site in Baltimore, Maryland owned by Morgan State University. Our goal was to supplement the measurements taken by locating a Bruker EM27/SUN spectrometer at the site to make total column measurements of trace gases in the near-infrared. This EM27 location was one of six locations in the Washington, D.C./Maryland region during the summer of 2025, and the network of observations was intended to help us better understand emissions in the region, as well as how emissions interact with meteorology to affect air quality and other atmospheric attributes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Developments in Performance and Portability for MadGraph5_aMC@NLO

Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the simulation worflow of collider experiments, represent approximately 5 to 20% of the annual WLCG usage for the ATLAS and CMS experiments. With computing architectures becoming more heterogeneous, it is important to ensure that these key software frameworks can be run on future systems, large and small. In this contribution, recent progress on porting and speeding up the Madgraph5_aMC@NLO event generator on hybrid architectures, i.e. CPU with GPU accelerators, is discussed. The main focus of this work has been in the calculation of scattering amplitudes and "matrix elements", which is the computational bottleneck of an event generation application. For physics processes limited to QCD leading order, the code generation toolkit has been expanded to produce matrix element calculations using C++ vector instructions on CPUs and using CUDA for NVidia GPUs, as well as using Alpaka, Kokkos and SYCL for multiple CPU and GPU architectures. Performance is reported in terms of matrix element calculations per time on NVidia, Intel, and AMD devices. The status and outlook for the integration of this work into a production release usable by the LHC experiments, with the same functionalities and very similar user interfaces as the current Fortran version, is also described.

Valassi, Andrea↗
DOE OSTI2020

NGEE Arctic Plant Traits: Plant Community Composition, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

This dataset reports the characteristics of the dominant vegetation communities at the NGEE Arctic Kougarok field site, Kougarok Road Mile Marker 64 on the Seward Peninsula. Selected plots were surveyed from 18-23 July 2016. Environmental data (e.g., elevation, slope, soil moisture regime, disturbance type and degree, mean canopy height, etc.) were also recorded for each plot. Elevation measurements were updated 2020-08-18. All plant species (vascular plants, bryophytes and lichens) were recorded along with their percent cover in the plots as determined visually by the lead author. Plots were chosen subjectively in areas of homogeneous and representative vegetation and varied in size from 1-25 m2 depending on canopy structure and height. The site is an east-facing hillslope with vegetation that varies from the summit to the toeslope. The 30 total plots were selected as five replicate plots sampled from each of the six identified habitat types: 1) non-acidic mountain complex at the hillcrest, 2) dwarf-shrub lichen tundra on the shoulder, 3) alder shrublands predominantly on an elevational band across the backslope, 4) willow-birch tundra on the upper backslope, 5) tussock tundra on the footslope in inter-water tracks, and 6) tussock tundra mixed with willow-birch tundra or alder savanna in poor developed water tracks on the footslope. This dataset is comprised of two comma-separated (*.csv) files containing species and environmental data for the plant community composition plots. It also contains seven zipped folders of plot photographs, one map showing plot locations (*.pdf), one blank datasheet with the key to codes used in the field (*.pdf), select photos organized in a (*.pdf), and one User file (*.pdf). 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 OSTI2021

End-of-Winter Snow Depth, Temperature, Density and SWE Measurements at Kougarok Road Site, Seward Peninsula, Alaska, 2018

Measurements of snow properties were taken in 2018 at the NGEE Arctic Kougarok field site. This dataset contains spatially distributed values of snow depth, integrated snow pack density, snow water equivalent (SWE), temperature at the snow surface and at the bottom of the snow pack, and snow density as a function of depth from top of snow pack. Data was collected toward the end of the winter season, in late March, when snow pack would be near its maximum. Data was collected toward the end of the winter season, in late March, when snow pack would be near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used for collection efficiency and enhanced spatial coverage. This package contains four *.csv data files and one *.pdf user guide file. 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↗