Beryllium Reflector Experiment Effects on High Flux Isotope Reactor Performance Metrics
Explore the source record for details and available documents.
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
This dataset provides the tabular summary of analysis of an alluvial floodplain reach of the East River, downstream of Gothic, CO near Crested Butte. The measurements include bank erosion and accretion rates, channel width, bank curvature, and the aspect/orientation of the river banks. The measurements were derived from binary masks of the location of the river channel from aerial and satellite imagery collected on seven dates over a sixty-year timespan: 1955, 1973, 1983, 1990, 2001, 2011, and 2015. The masks were analyzed using the Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM) software detailed in Rowland et al. 2016. The masks used in this analysis can be found an accompanying dataset (DOI: ). Rates of change along the East River were measured over a total of 8-time intervals: 1955-1973; 1955-2015; 1973-1983; 1983-1990; 1990-2001; 2001-2011; 2001-2015; and 2011-2015.In files with “summary” in the name, the data is provided at a pixel level, where each mapped bank pixel has an associated erosion or accretion value, a channel width, a curvature value, and an aspect each river and time period will have an individual file. Files with “Segments” in name provide data that is averaged along segments of the rivers. These segments are approximately 10 channel widths in length. In addition to erosion and accretion rates, the segment-based results include area measurements of erosion and accretion, islands, and channels. The number of islands is also included.
This dataset contains daily metabolism estimates of gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP), in addition to organic carbon spiraling length (SOC) and mineralization velocity (VfOC) estimates at the West Fork of Walker Branch, a small headwater stream, in the Walker Branch Watershed, Tennessee, USA. Observations were made from 2004-2010 (2004-01-01 to 2010-12-31). These data were generated to assess seasonal and interannual variability in metabolism and organic carbon spiraling and to explore potential driver variables, as analyses of intra- and interannual variability in metabolism and organic carbon spiraling are currently limited, leaving knowledge gaps in the driving mechanisms of and future changes to stream metabolism and carbon processing under climate change. Additionally, measurements of discharge (Q), stream width, stream- and canopy-level photosynthetically active radiation (PAR), water temperature, and precipitation from this time frame are included. This dataset contains one data file in comma separated (*.csv) format.
Major activities for this project consisted of three related elements: Comparing results using statistical downscaling to the dynamical downscaling performed by the UCLA (Dr. Alex Hall) team in the proposal Developing statistical downscaling methods for wind and near-surface humidity Evaluating differences in extremes across downscaling methods.
The LLNL “Microbes Persist” Soil Microbiome Scientific Focus Area (SFA) seeks to determine how microbial soil ecophysiology, population dynamics, and microbe-mineral-organic matter interactions regulate the persistence of microbial residues and the formation of soil carbon. Our SFA research program is now four years old; it evolved and benefited from previously-funded BSSD projects in the Firestone (UCB), Banfield (UCB), Sullivan (OSU) and Hungate (NAU) labs. We use stable isotope probing in combination with ‘omics to measure how changing water regimes shape activity of individual microbial populations and ecophysiological traits that affect the fate of microbial and plant C. Using measures of population dynamics and microbiome-mineral interactions, we are working to synthesize both genomescale and ecosystem-scale models of soil organic matter (SOM) turnover, to predict the long-aspired connection between soil microbiomes and fate of soil C.
The LLNL “Microbes Persist” Soil Microbiome Scientific Focus Area (SFA) seeks to determine how microbial soil ecophysiology, population dynamics, and microbe-mineral-organic matter interactions regulate the persistence of microbial residues and formation of soil carbon (C). In much of our research, we use imaging, mass spectrometry, and related methods to study plantmicrobe-mineral interactions, viral and microbial particles from soil, and the signatures plant and microbial necromass contribute as part of soil organic matter (SOM). Our project’s signature techniques include NanoSIMS-enabled approaches (to understand cell-cell and OM-mineral interactions at the single cell and even viral particle scale), radiocarbon (14C) analyses (to determine both the age and turnover time of soil organic matter), and a suite of soil chemical characterization techniques we describe below, and collectively refer to as ‘Multi- dimensional SOM-mineral characterization’ (SEM, TEM, STXM, NEXAFS, NMR, FTICR-MS, LC-MS). In this report, we focus on how imaging, NMR, beamline and mass spectrometry approaches can deepen our understanding of soil microbiomes and their engagement with the soil matrix.
Abstract not provided.
Abstract not provided.
This report summarizes a rigorous valuation analysis methodology used by the Distribution System Operator with Transactive (DSO+T) study to estimate the financial benefits and costs of adopting Transactive Energy coordination of distributed energy resources for key stakeholders (for example distribution system operators and customers). This was achieved by modeling the value exchanges between stakeholders and determining the annualized costs and revenues experienced by stakeholders, enabling the evaluation of overall impact on stakeholder’s annualized cash flow. Extensive work was conducted developing methods to estimate the operating costs of distribution system operators at a level of granularity that would allow the financial impact of implementing a transactive energy approach to be estimated. This work included developing parametric models for labor and software costs, distribution system capital and maintenance costs, growth rates, and factors to determine annualized costs of capital investments. Simulation results were used to calculate wholesale energy costs and revenues from retail sales. Valuation analysis methods were also developed for other stakeholders including customers, the transmission system operator, independent system operator, and generators. The resulting capability allows a complete mapping of the flow of financial value between stakeholders that can be directly integrated with the results of demand flexibility simulations. Example results are provided for a business-as-usual case and compared to a transactive energy case as well as to actual cost data.
Abstract not provided.
The Integrated Nuclear Detonation Detection (iNDD) project seeks to develop two statistical constructs. The first will fuse operational data from Nuclear Detonation Detection (NDD) systems in order to determine whether a nuclear event has likely occurred; this is referred to as the “fused detector.” The assorted detection domains of NDD systems span independent regimes with uncorrelated backgrounds; for example, lightning is a background for satellite-based systems, while earthquakes are a background for seismic systems.
Abstract not provided.
Abstract not provided.
LBNL and APPA (the team) jointly examined the extent to which differences in distribution feeder characteristics are correlated with differences in their reliability performance when exposed to three different types of natural hazards (wildlife, weather, and vegetation). The team employed data-driven approaches to quantify the relationships between various measures of feeder reliability and a suite of feeder characteristics individually and jointly via a statistically-based clustering method.
LBNL and APPA (the team) jointly examined the extent to which differences in distribution feeder characteristics are correlated with differences in their reliability performance when exposed to three different types of natural hazards (wildlife, weather, and vegetation). The team employed data-driven approaches to quantify the relationships between various measures of feeder reliability and a suite of feeder characteristics individually and jointly via a statistically-based clustering method. The team developed suggestions on how comparisons across groupings of feeders and review of the relative contributions of the constituents of SAIFI and SAIDI could be used to help prioritize utility actions to improve reliability. However, they also caution that their suggestions require further evaluation because they are based on only one year of information from a modest number of small utilities.
Classification is an assignment of an image to a certain category. Localization is identified by the box surrounding the object in the image. Object detection detects instances of semantic objects of a certain class. Semantic segmentation categorizes all the pixels of an image into classes of objects. Instance segmentation identifies each instance of each object in the image. Panoptic (i.e., showing or seeing everything at once) segmentation is a combination of semantic and instance segmentation and classifies all the pixels in the image.
The tendency of climate models to overstate warming in the tropical troposphere has long been noted. Here we examine individual runs from 38 newly released Coupled Model Intercomparison Project Version 6 (CMIP6) models and show that the warm bias is now observable globally as well. We compare CMIP6 runs against observational series drawn from satellites, weather balloons, and reanalysis products. We focus on the 1979–2014 interval, the maximum span for which all observational products are available and for which models were run using historically observed forcings. For lower-troposphere and midtroposphere layers both globally and in the tropics, all 38 models overpredict warming in every target observational analog, in most cases significantly so, and the average differences between models and observations are statistically significant. We present evidence that consistency with observed warming would require lower model Equilibrium Climate Sensitivity (ECS) values.
Nuclear criticality safety standards provide guidance on the requirements and recommendations to establish confidence in computerized model results used to support operation with fissionable materials. By design, the guidance is not prescriptive, leaving the analysts free to determine how various sources of uncertainties are to be statistically aggregated. This report compares the analyses and key assumptions behind four notable methodologies documented in the nuclear criticality safety literature: the parametric, nonparametric, Whisper, and TSURFER methodologies. Because of the involved use of statistics entangled with heuristic recipes, the results of these methodologies are often difficult to interpret. Also, they are augmented by additional large administrative margins, eliminating the incentive to understand their differences. With the new resurgent wave of advanced nuclear systems focused on economizing operation—including advanced reactors, fuel cycles, and fuel concepts—there is a strong need to develop a clear understanding of uncertainties and their fusion methodologies to reduce uncertainties in a scientifically defensible manner. This report offers a deep dive into the various assumptions of the four noted methodologies, their adequacy, and their limitations, to provide guidance on developing confidence for the emergent nuclear systems. These systems are expected to be challenged by the scarcity of experimental data.