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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Measurement of the Antineutrino Double-Differential Charged-Current Quasi-Elastic Scattering Cross Section at MINERvA

Next-generation neutrino oscillation experiments, such as DUNE and Hyper-Kamiokande, hope to measure charge-parity (CP) violation in the lepton sector. In order to do this, they must dramatically reduce their current levels of uncertainty, particularly those due to neutrino-nucleus interaction models. As CP violation is a measure of the difference between the oscillation properties of neutrinos and antineutrinos, data about how the less-studied antineutrinos interact is especially valuable. We present the MINERvA experiment's first double-differential scattering cross sections for antineutrinos on scintillator, in the few-GeV range relevant to experiments such as DUNE and NOvA. We also present total antineutrino-scintillator quasi-elastic cross sections as a function of energy, which we compare to measurements from previous experiments. As well as being useful to help reduce oscillation experiments' uncertainty, our data can also be used to study the prevalence of various cor relation and final-state interaction effects within the nucleus. We compare to models produced by different model generators, and are able to draw first conclusions about the predictions of these models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Final Technical Report - DOE Grant No. DE-FG02-07ER46424

We present a final report on the activities undertaken under DOE Grant No. DE-FG02-07ER46424, titled "Interaction effects in quasi one-dimensional electronic systems," originally under the direction of Prof. Julia Meyer. The report includes an overview of the grant and the personnel involved, a list of publications acknowledging the grant, and a summary of the results and conclusions drawn from research supported by the grant.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Open-source FCPEM-Performance & Durability Model Consideration of Membrane Properties on Cathode Degradation

The durability of PEM fuel cells is a primary requirement for large scale commercialization of these power systems in transportation and stationary market applications which target operational lifetimes of 5,000 hours and 60,000 hours by 2020, respectively. Key degradation modes contributing to fuel cell lifetime limitations have been largely associated with the platinum-based cathode catalyst layer. Furthermore, as fuel cells are driven to low cost materials and lower catalyst loadings in order to meet the cost targets for commercialization, the catalyst durability has become even more important. While over the past few years significant progress has been made in identifying the underlying causes of fuel cell degradation and key parameters that greatly influence the degradation rates, many gaps with respect to knowledge of the driving mechanisms still exist; in particular, the acceleration of the mechanisms due to different membrane compositions remains an area not well understood. The focus of this project extension was to enhance the predictive capability of the PEM Fuel Cell Performance & Durability Model called FC-APOLLO (Application Package for Open-source Long Life Operation) by including interaction effects of membrane transport properties such as water transport, changes in proton conductivity, and overall water uptake/adsorption and the state of the catalyst layer local conditions to further understand the driving forces for platinum dissolution.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2016

Inter-Disciplinary Collaboration in Support of the Post-Standby TREAT Mission

Although analysis methods have advanced significantly in the last two decades, high fidelity multi- physics methods for reactors systems have been under development for only a few years and are not presently mature nor deployed. Furthermore, very few methods provide the ability to simulate rapid transients in three dimensions. Data for validation of advanced time-dependent multi- physics is sparse; at TREAT, historical data were not collected for the purpose of validating three-dimensional methods, let alone multi-physics simulations. Existing data continues to be collected to attempt to simulate the behavior of experiments and calibration transients, but it will be insufficient for the complete validation of analysis methods used for TREAT transient simulations. Hence, a 2018 restart will most likely occur without the direct application of advanced modeling and simulation methods. At present, the current INL modeling and simulation team plans to work with TREAT operations staff in performing reactor simulations with MAMMOTH, in parallel with the software packages currently being used in preparation for core restart (e.g., MCNP5, RELAP5, ABAQUS). The TREAT team has also requested specific measurements to be performed during startup testing, currently scheduled to run from February to August of 2018. These startup measurements will be crucial in validating the new analysis methods in preparation for ultimate application for TREAT operations and experiment design. This document describes the collaboration between modeling and simulation staff and restart, operations, instrumentation and experiment development teams to be able to effectively interact and achieve successful validation work during restart testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Demand-Side Grid (dsgrid) Model

This presentation gives a high-level overview of the recently published demand-side grid (dsgrid) model documentation. The general modeling philosophy and technical approach of dsgrid is described, as is an initial data set covering 2012 contiguous United States (CONUS) electricity demand. The initial data set describes about 80% of electrical load at an hourly level by county, subsector and end use. Coarser models and data sets are used to describe the remainder. Model residuals are calculated at different levels of aggregation by leveraging historical electricity sector data and a model of 2012 distributed generation. Overall, the dsgrid model has been developed to support analysis of future load scenarios, including interactive effects between energy efficiency, electrification, demand response, renewable energy, battery energy (or other forms of) storage, and future grid conditions broadly construed. Planned future work includes the development of future load scenarios and physically realistic estimates of the flexible load resource.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

ECP ALCC Quarterly Report (Oct-Dec 2017)

The scientific goal of ExaWind Exascale Computing Project (ECP) is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. Current methods for modeling wind plant performance fall short due to insufficient model fidelity and inadequate treatment of key phenomena, combined with a lack of computational power necessary to address the wide range of relevant length scales associated with wind plants. Thus, our ten-year exascale challenge is the predictive simulation of a wind plant composed of O(100) multi-MW wind turbines sited within a 100 km2 area with complex terrain, involving simulations with O(100) billion grid points. The project plan builds progressively from predictive petascale simulations of a single turbine, where the detailed blade geometry is resolved, meshes rotate and deform with blade motions, and atmospheric turbulence is realistically modeled, to a multi turbine array in complex terrain. The ALCC allocation will be used continually throughout the allocation period. In the first half of the allocation period, small (e.g., for testing Kokkos algorithms) and medium (e.g., 10K cores for highly resolved ABL simulations) sized jobs will be typical. In the second half of the allocation period, we will also have a number of large submittals for our resolved-turbine simulations. A challenge in the latter period is that small time step sizes will require long wall-clock times for statistically meaningful solutions. As such, we expect our allocation-hour burn rate to increase as we move through the allocation period.

17 WIND ENERGY↗
DOE OSTI2019

Accelerator Integration in CMS [Slides]

CMS data processing framework uses a mechanism to interact effectively with non-cpu resources. Non-CPU algorithms are divided into 3 phases: (1) CPU stage which acquires data and transfers to non-CPU resource, (2) Non-CPU algorithm is then run, and (3) When finished, a publish step is run on the CPU to move data back to CPU memory. While non-CPU algorithm runs, the CPU is available for other algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Bringing heterogeneity to the CMS software framework [Slides]

Co-processors or accelerators like GPUs and FPGAs are becoming more and more popular. CMS' data processing framework (CMSSW) implements multi-threading using Intel TBB utilizing tasks as concurrent units of work. We have developed generic mechanisms within the CMSSW framework to interact effectively with non-CPU resources and configure CPU and non-CPU algorithms in a unified way. As a first step to gain experience, we have explored mechanisms for how algorithms could offload work to NVIDIA GPUs with CUDA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Bringing heterogeneity to the CMS software framework [Slides]

Co-processors or accelerators like GPUs and FPGAs are becoming more and more popular. CMS’ data processing framework (CMSSW) implements multi-threading using Intel TBB utilizing tasks as concurrent units of work. We have developed generic mechanisms within the CMSSW framework to interact effectively with non-CPU resources and configure CPU and non-CPU algorithms in a unified way. As a first step to gain experience, we have explored mechanisms for how algorithms could offload work to NVIDIA GPUs with CUDA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Spot Size Optimization of the Scorpius Accelerator

The Scorpius Linear Induction Accelerator (LIA) is being developed by the Advanced Sources and Diagnostics (ASD) Project and will complement other U1a capabilities by providing a multi-pulse, DARHT-class, flash-radiography capability. Commissioning activities are expected to end in Spring of 2026. All of the diagnostics discussed in this chapter are relevant to LIAs that generate high-current relativistic electron beams, and some diagnostics will also be relevant to other accelerators. The Scorpius Accelerator will be the world’s most advance LIA. Although significant technological advancements have been incorporated throughout the machine, many performance aspects of Scorpius will be similar to those of FXR and DARHT Axis-I and -II. These LIAs offer the same challenges, whether it is suppressing beam instabilities, improving diagnostic accuracy, validating computer simulations and beam tunes, or reducing beam-target interaction effects. However, the ultimate figure of merit is consistent between these LIAs, which is spot size and dose.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Ellipsoidal Fitting Methodology for Defect Clusters in Gallium Arsenide

In assessing the initial spatial distribution of defects from neutron or heavy ion irradiation, it is useful to have a reliable, automated, and fast-running tool to evaluate characteristic metrics such as the number of sub-clusters or the overall cluster volume. The latter metric, for instance, can be utilized to estimate a reference neutron fluence level at which inter-cluster interaction effects begin to become significant. This paper details a methodology to fit an arbitrarily complex defect map with a set of ellipsoids (one per identified sub-cluster) in which the constituent defects of a sub-cluster are determined using fuzzy degree-of-membership analysis. Specifically, a parameterized model is developed for point defects in gallium arsenide. Cluster volume calculations based on the model are compared against convex hull and single- ellipsoid representations. Results show that the parameterized sub-cluster model begins to deviate from the two reference models at a recoil energy of about 100 keV in GaAs, with the convex hull and single-ellipsoid representations increasingly overestimating the volume thereafter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Simulation Studies on the Interactions of Electron Beam with Wastewater

The manufactured chemical pollutants, like 1,4 dioxane and PFAS (per- and polyfluroralkyl substances), found in the underground water and/or drinking water are challenging to be removed or biodegraded. Energetic electrons are capable of mediating and removing them. This paper utilizes FLUKA code to evaluate the beam-wastewater interaction effects with different energy, space and divergence distributions of the electron beam. With 8 MeV average energy, the electron beam exits from a 0.0127 cm thick titanium window, travels through a 4.3 cm distance air and a second 0.0127 cm thick stainless water container window with 2.43 cm radius, and finally is injected into the water area, where the volume of water is around 75 cubic cm. The distribution parameters of the electron beam are from the GPT (General Particle Tracer) simulations for UITF (Upgraded Injector Test Facility) in Jefferson lab. By varying the distributions, several measurements including the dose (or energy deposition) distribution, electron fluence, photon fluence are scored and compared. Taking the comparisons into consideration, this paper is aiming to find better electron beams for the wastewater irradiation.

Li, X.↗
DOE OSTI2024

Predictive Indicators of the Performance of Large Language Models

In several mission contexts, it is desirable to estimate the performance of large language models (LLMs) on tasks that we cannot run directly. In light of published “scaling laws” our hypothesis is that some tasks should be consistently more challenging than others based on characteristics of the task. The goal of this project was to begin quantifying how much information about LLM performance can be gained from the features of a model and a task. Two of our statistical models struggled to converge. Pass/fail test results may provide limited information for inference beyond model quality and task difficulty, but we see no evidence at this time for significant feature interaction effect sizes, arguing for simple models. Future work extending the models to capitalize on perplexity of ground truth answers is suggested. This project also introduces “Depth of Knowledge Variant Testing” as a strategy for more finely assessing language models on open domain question and answer tasks. We developed sets of questions that ask a language model to produce similar information while demonstrating increasing depth of knowledge, and also relabeled existing Q&A test questions with their depth of knowledge. Our results suggest further consideration of Bloom’s taxonomy and further refinement of prompts to properly elicit information at varying depths. In the course of this work, we set up a basic infrastructure for standardizing tasks and testing many language models on these tasks. In addition to testing the predictive quality of model features and performance across test suites, with this project we have introduced two new task features to contextualize each test question: the Dewey Classification main category of information covered, and the Bloom’s taxonomy level that corresponds to the depth of knowledge probed by the question. Splits across these and other features produced over five hundred task subtypes with distinct feature vectors, which we tested on half a dozen models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

From viruses to protists: temperature response of the neglected components of microbial controls on peatland nutrient cycling

The response of plant-associated microbial communities to rising temperatures likely plays a key role in global Carbon (C) and Nitrogen (N) biogeochemical cycles. Mosses of the genus Sphagnum, in particular, sequester 25% of all terrestrial C as recalcitrant peat. However, their ability to sequester C is mediated by interactions with microbes that fix N and pass it to the moss to grow in otherwise oligotrophic systems. Two important biotic controls on this processes are likely to respond to rising temperatures –predation by protists and infections by viruses– but whether and how this might occur is not well understood. This proposal addressed these questions using a combination of genomics and mathematical modeling with both field data from whole-ecosystem warming experiments, and laboratory-based microcosm experiments. We have discovered 1) mechanistic links between cell traits and thermal performance in protists, which 2) enabled predictions from populations to ecosystems, 3) we have identified eco-phenotypic feedbacks that determine protist–bacterial predator–prey dynamics, 4) have documented concomitant compositional and trait shifts in protist communities with warming in the field, 5) revealed consistent interactive effects of temperature and nutrients on bacterial and protist communities; 6) characterized the Sphagnum virome, and 7) made modeling predictions on its implications for thermal responses of microbial communities in peatlands globally. This award also substantially strengthened U.S. scientific capacity and workforce development.

Gibert, Jean Philippe [Duke University]↗
DOE OSTI2025

Interaction of HOMs in periodic accelerating structures

The paper discusses the HOM interaction effect in a 5-cell 650 MHz HB cavity prototype for the PIP-II project. This effect may lead to flat HOM passbands. In the presence of misalignments, this passband disintegrates into individual cell resonances that are not coupled to the beam pipes and, therefore, have a high-quality factor and R/Q ratio. These resonances can lead to excessive cryogenic loading, increased emittance, and beam instabilities. An analytical theory has been developed to explain this effect, as well as special methods for eliminating it.

Yakovlev, V. [Fermilab]↗
DOE OSTI2024

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System: Supporting Data

This data contains data from 90-day long incubation study which aimed to look at the soil moisture-texture relationship on soil organic carbon (SOC) cycling. Soils were collected from three distinct soil textures from mixed forests in 2017: sandy (Georgia, 2017-05-01), loamy (Missouri, 2017-06-14) and clayey (Texas, December 2017) were incubated at different soil moisture levels (air-dried, 25% water holding capacity (WHC), 50% WHC, 100% WHC and 175% WHC) at room temperature for a period of 90 days. Files contain microbial respiration, active and slow SOC pools, and their respective mineralization rates, extractable organic carbon (C), and C-acquiring extracellular enzymes. Findings from these data were used in Singh et al. (2021). This study aimed to examine the interactive effect of soil moisture and texture on SOC mineralization. Soil samples of three distinct textures (sandy, loamy, and clayey) were collected from mixed forests of Georgia, Missouri, and Texas, respectively. Soil cores of 5 cm diameter were collected from numerous random locations at each site from 0-15 cm depth after scraping the litter layer and mixed thoroughly to obtain a composite sample per site. Three additional soil cores were collected to determine the WHC using pressure plate extractors. Soil samples were composited, and triplicate soil samples were incubated in mason jars for a period of 90 days at room temperature under different moisture regimes: air dried, 25% WHC, 50% WHC, at WHC and 100% saturation. Soil respiration was measured weekly, and destructive sampling was conducted at 1, 15, 60, and 90 days to determine extractable organic C, C acquiring enzyme activity, and active and slow SOC pools with their respective mineralization rates. The C acquiring enzyme activity was the total activity of α-glucosidase, β-glucosidase, cellobiohydrolase, and β-xylosidase enzymes. Gas samples for microbial respiration measurements were collected from headspace of incubation jars through the sampling ports on the lids and then analyzed using a Shimadzu Gas Chromatograph (GC-2014). Prior to sampling, the vials were evacuated. Blank correction was also done by collecting gas samples from empty incubation jars. Double pool exponential decay model was used in SigmaPlot to determine the active and slow SOC pools and their mineralization rates (Farrar et al., 2012; Jagadamma et al., 2014). The C-acquiring extracellular enzymes were measured using the microplate method by German et al., (2011). Microbial community structure was determined using the phospholipid fatty acid (PLFA) and neutral lipid fatty acid (NLFA) analyses (Buyer and Sasser, 2012). This dataset has seven data files provided in comma-separate (*.csv) format. Additional metadata are provided: seven data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

Carbon acquiring enzyme activity↗
DOE OSTI2016

Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO 2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the 'High CO 2 +Nitrogen+Precipitation' treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗