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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Dereplication, Aggregation and Scoring Tool (DAS Tool) v1.0

Communities of uncultivated microbes are critical to ecosystem function and microorganism health, and a key objective of metagenomic studies is to analyze organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of genes to genomes, yet existing binning methods often fail to predict a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotypes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tools applied to a constructed community generated more accurate bins than any automated method. Further, when applied to samples of different complexity, including soil, natural oil seeps, and the human gut, DAS Tool recovered substantially more near-complete genomes than any single binning method alone. Included were three genomes from a novel lineage . The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.

SIEBER, CHRISTIAN↗
DOE OSTI2025

TimeStitch-Memento-Aggregator

Memento Aggregator is a Java service that federates web archives worldwide: given an Original-URL and optional datetime, it discovers mementos and exposes standards-compliant Memento TimeGate and TimeMap APIs.

Balakireva, Lyudmila↗
DOE OSTI2021

Ascending Columns, WTG, and Convective Aggregation

Analytic solutions are derived for a convecting atmosphere with mean ascent using a zero-buoyancy bulk-plume approximation for moist convection. It has been suggested that such solutions should serve as a model for the relationship between humidity, instability, and precipitation in the tropics, but it is shown here that this interpretation is incompatible with the observed weak temperature gradient (WTG). Instead, the solutions can be used to understand the atmospheric state averaged over all tropical convecting regions. Further, using the analytic solutions in this way, they predict the changes in humidity, instability, and precipitation as a function of the size of the moist patch in a convectively aggregated state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Natural Language Processing-Enhanced Nuclear Industry Operating Experience Data Analysis: Aggregation and Interpretation of Multi-Report Analysis Results

Industry-wide operating experience is a critical source of raw data for reliability and risk model parameter estimations for nuclear power plants. A large portion of operating experience data are failure events stored as reports that contain unstructured data, such as narratives. In current practice, a failure report is usually reviewed and manually coded by analysts. The coding is based on extracting several event characteristics such as system name, component type, sub-part type, failure mode, and failure cause. Event narratives are mostly used to help understand events and extract their characteristics. In this line of research, we aim to maximize the usage of event narratives by leveraging natural language processing (NLP) methods to automatically convert an event narrative to a causal graph. This research has promise to improve physical understanding of failure initiation and propagation and to facilitate use of non-failure data (e.g., near-misses and degradations) to complement the limited data pool of failures. In our previous work, we developed an NLP tool and applied it to analyze a number of licensee event reports submitted by U.S. nuclear power plants to the Nuclear Regulatory Commission. In this paper, we will report our recent research progress in aggregating the results of multiple reports, developing network model(s), and drawing statistical insights.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Effects of soil particles and convective transport on dispersion and aggregation of nanoplastics via small-angle neutron scattering (SANS) and ultra SANS (USANS)

Terrestrial nanoplastics (NPs) pose a serious threat to agricultural food production systems due to the potential harm of soil-born micro- and macroorganisms that promote soil fertility and ability of NPs to adsorb onto and penetrate into vegetables and other crops. Very little is known about the dispersion, fate and transport of NPs in soils. This is because of the challenges of analyzing terrestrial NPs by conventional microscopic techniques due to the low concentrations of NPs and absence of optical transparency in these systems. Herein, we investigate the potential utility of small-angle neutron scattering (SANS) and Ultra SANS (USANS) to probe the agglomeration behavior of NPs prepared from polybutyrate adipate terephthalate, a prominent biodegradable plastic used in agricultural mulching, in the presence of vermiculite, an artificial soil. SANS with the contrast matching technique was used to study the aggregation of NPs co-dispersed with vermiculite in aqueous media. We determined the contrast match point for vermiculite was 66% D 2 O / 33% H 2 O. At this condition, the signal for vermiculite was ~50–100%-fold lower that obtained using neat H 2 O or D 2 O as solvent. According to SANS and USANS, smaller-sized NPs (50 nm) remained dispersed in water and did not undergo size reduction or self-agglomeration, nor formed agglomerates with vermiculite. Larger-sized NPs (300–1000 nm) formed self-agglomerates and agglomerates with vermiculite, demonstrating their significant adhesion with soil. However, employment of convective transport (simulated by ex situ stirring of the slurries prior to SANS and USANS analyses) reduced the self-agglomeration, demonstrating weak NP-NP interactions. Convective transport also led to size reduction of the larger-sized NPs. Therefore, this study demonstrates the potential utility of SANS and USANS with contrast matching technique for investigating behavior of terrestrial NPs in complex soil systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Aggregated carbon dioxide flux and hydrometeorology data from an Amazonian palm swamp peatland in Peru: 2018, 2019, and 2022

This dataset contains eddy covariance carbon dioxide flux and hydrometeorological measurements made in an Amazonian palm swamp peatland near Iquitos, Peru. These data have been aggregated from half-hourly observations that are available from AmeriFlux (https://ameriflux.lbl.gov/; site PE-QFR). These data files are CSV (comma separated values) format and can be imported using Matlab, R, or Excel. Three full years of data are reported (2018, 2019 and 2022) during which time there were large differences in annual net ecosystem carbon dioxide exchange. The gap was caused by instrument malfunction and extended delays in repairs because of the Covid-19 pandemic. This research was conducted to better understand the carbon cycle of tropical peatlands, and was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science Program, under Award Number DE-SC0020167.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Aggregating QECB Allocations & Using QECBs to Support the Private Sector: A Case Study on Massachusetts

Qualified Energy Conservation Bonds (QECBs) are federally-subsidized bonds that enable state, tribal, and local government issuers to borrow money to fund a range of energy conservation projects at very attractive interest rates and long terms. While small allocation sizes have deterred some local governments from pursuing issuances, state agencies in Massachusetts have partnered with local governments to aggregate QECBs to support a range of public and private projects. In most states, QECBs have been utilized primarily to fund energy conservation projects for public entities, but Massachusetts has facilitated over $10 million of private activity QECB issuances to support three privately-owned renewable energy projects—with more projects in the pipeline.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Experimental deformation in sandstone, carbonates and quartz aggregate

The first part of my thesis is mainly focused on the effect of grain size distribution on compaction localization in porous sandstone. To identify the microstructural parameters that influence compaction band formation, I conducted a systematic study of mechanical deformation, failure mode and microstructural evolution in Bleurswiller and Boise sandstones, of similar porosity (~25%) and mineralogy but different sorting. Discrete compaction bands were observed to develop over a wide range of pressure in the Bleurswiller sandstone that has a relatively uniform grain size distribution. In contrast, compaction localization was not observed in the poorly sorted Boise sandstone. My results demonstrate that grain size distribution exerts important influence on compaction band development, in agreement with recently published data from Valley of Fire and Buckskin Gulch, as well as numerical studies. The second part aimed to improve current knowledge on inelastic behavior, failure mode and brittle-ductile transition in another sedimentary rock, porous carbonates. A micritic Tavel (porosity of ~13%) and an allochemical Indiana (~18%) limestones were deformed under compaction in wet and dry conditions. At lower confining pressures, shear localization occurred in brittle faulting regime. Through transitional regime, the deformation switched to cataclastic flow regime at higher confining pressure. Specifically in the cataclastic regime, the (dry and wet) Tavel and dry Indiana failed by distributed cataclastic flow, while in contrast, wet Indiana failed as compaction localization. My results demonstrate that different failure modes and mechanical behaviors under different deformation regimes and water saturation are fundamental prior to any geophysical application in porous carbonates. The third part aimed to focus on investigating compaction on quartz aggregate starting at low (MPa) using X-ray diffraction. We report the diffraction peak evolution of quartz with increasing pressures. Through evaluating the unit cell lattice parameters and the volume of the quartz sample, macroscopic stress and strain were resolved. Moreover, we observed quartz peak broadened asymmetrically at low pressure, such extent is more prominent in axial than in radial direction. Our evaluation on peak [101] (highest intensity among peaks) demonstrated that full width at half maximum can be a good proxy for microscopic stress distribution. We observed deviations in the pressurevolume curves at P = ~0.4 GPa and speculated that it was the point of which onset of grain crushing and pore collapse occur in quartz. This is on the same order of which onset of grain crushing (commonly known as P*) is observed in sandstones in the rock mechanics literature. This demonstrated that there is potential in estimating grain crushing and pore collapse pressure with our technique.

58 GEOSCIENCES↗
DOE OSTI2019

Microbial drivers of global change at the aggregate scale: linking genomic function to carbon metabolism and warming

Understanding and accurately predicting the microbial cycling of carbon in soil environments has been challenged by our ability to associate microbial community dynamics into ecosystem-scale biogeochemical models. Soil fractionation techniques provide an opportunity to examine intact microbial communities in a context that is relevant to both microbial community metabolism and ecosystem processes. We developed approaches that targeted metabolically active microorganisms and functions that drive carbon cycling in soils from bioenergy cropping systems. We used metatranscriptomics, genome sequencing, cell sorting, and cell isolation methods to access the key organisms involved in soil carbon cycling (e.g. cellulose decomposition) in soil aggregate fractions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The goal of this project is to develop statistical methods and tools that can be used to rigorously calculate achieved DPs on individual material strata and then aggregate these to the facility and state levels. In particular, this project is evaluating the utility of stochastic ("Monte Carlo") methods as a potentially more powerful and flexible option to the analytical solutions traditionally employed by IAEA statisticians.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Open-Source High-Fidelity Aggregate Composite Load Models of Emerging Load Behaviors for Large-Sale Analysis

The goal of this project is to accurately model the dynamic loads for power system planning and operation and to address the challenges inherent in such modeling. Existing load models are inadequate to handle the increasing proliferation of residential air conditioner loads and distributed energy resources, the emerging trends of price-responsive demand, and the growing importance of protective devices in equipment and buildings. A need has emerged to develop a fundamentally new class of load models and next-generation data tools. This work proposes to develop a set of regional–level, scalable open source load models and tools, including large-scale aggregate load protection, concept of price responsive demand, advanced load composition data, next-generation load model data tools, and advanced composite load model calibration and validation frameworks to address new challenges in the representation of next-generation load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 11 & 12: Components and Capabilities of the Resiliency Driven Outage Management and Feeder Restoration System (Deliverable D8))

This report provides progress update for the development of a outage management, feeder restoration, and restoration action feasibility check modules as part of the AGGREGATE project. Details for integration with controllability module, data driven situational awareness of network and distributed energy resources as well cyber security plan for these modules integrated with GE ADMS are also presented in the report. These three modules for outage management, feeder restoration, and restoration action feasibility check modules are developed in MATLAB and validated with a modified IEEE 123-node feeder. Results demonstrate ability of these new modules to improve the restoration process post-disaster to enhance the system resilience.

42 ENGINEERING↗
DOE OSTI2021

Report for Task 15: Developed Tool Verification/Validation Report (Deliverable D11): AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency

This report summarizes the verification report for the developed modules. The team conducted verification in two phases. In phase 1, the modules were validated using offline validation methods and in phase 2 the modules were subjected to real-time validation. This report outlines the approach and the results for the modules under offline and real-time settings. The rest of the report details the functional workflow of AGGREGATE modules, we then transition to offline validation followed by real-time validation of modules. We conclude the report by discussing some of the key points of this report.

14 SOLAR ENERGY↗
DOE OSTI2019

Data Integration Aggregated Model and Ontology for Nuclear Deployment (DIAMOND): Preliminary Model and Ontology

The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often performed manually and on an as-needed basis to achieve a targeted cost saving. A holistic approach to the integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data warehouse results in direct and indirect cost saving because it automates the manual search for data, enables sharing and comparison of data from various tools of a single or multiple plants, enable digital transformation of data, increase frequencies of needed data that are sparse in nature (such as failures signatures), reduces the need for training on various tools for plant staff, enables a holistic staff perception of plant activities, reveals cost-saving opportunities, and improves the visual perception of all parts a plant necessary for operations and maintenance. One of the main challenges to deploy a data warehouse is associated with the integration of data sources into a consistent data model using a standard ontology that is developed by and for the nuclear power industry. This model is non-existent and is a necessity to enable the nuclear data warehouse role. A data model contains objects that make up a given domain along with their attributes and relationships. It provides domain standardization and maintainability, setting forth the objects, attributes, and relationships within that domain and acting as the guide by which the various applications within that domain will structure their data and interchange. An ontology is defined as “a set of concepts and categories in a subject area or domain that shows their properties and the relations between them”. Ontologies consist of a taxonomy or directed rooted tree. A survey of the models and ontologies available to support a data integration aggregated model and ontology for nuclear deployment (DIAMOND) was performed and different standards that address specific aspects of the needed model and ontology were leveraged and integrated in this effort. In specific, the Basic Formal Ontology (BFO) and Lifecycle Modeling Language (LML) were leveraged for the base ontology. The ISO 4224 and 15926 were leveraged in the development of the overlapping nuclear and fossil data aspects. The electric power research institute (EPRI) power distribution common information model (CIM) was also reviewed and the experience gained was leveraged in the power generation scope of DIAMOND. The initial aim targeted by this effort was to develop the ontology definitions and model structure. This report documents the resulting model and ontology to develop DIAMOND. The report describes the various elements of the model development based on a growing tree development approach, i.e. DIAMOND’s tree structure is established with the core data aspects and is populated with a preliminary level of details. Fifteen sources of data in a nuclear power plant were considered and incorporated into DIAMOND at this stage of development, representing the majority of operations data sources in nuclear power plants. Additional data sources, scope, and a higher level of fidelity will be incorporated into DIAMOND next in collaboration with the nuclear industry and relevant stakeholders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

In situ Characterization of Soot Aggregates Produced by Burning Contaminated Liquid Fuels with Nuclear Waste Surrogate

The motivation of this work was to complement other studies intended to enhance and update DOE-HDBK-3010-94 for hazard scenarios like nuclear waste fires. In this work, a uniquely designed combustion chamber was successfully integrated with a light scattering technique to characterize soot aggregates. The chamber design allowed for soot investigation within the flame as well as after soot left the incandescent flame region.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

State Regulatory Opportunities to Advance Distributed Energy Resource Aggregations in Wholesale Markets

The report discusses how state regulators can promote the participation of DERs in wholesale markets, including complementary actions that they can take to support Federal Energy Regulatory Commission Order 2222 implementation. It also summarizes wholesale market operators’ Order 2222 compliance and associated compliance challenges along with potential state regulator roles. The report identifies actions that state regulators can take to accelerate DER aggregations providing grid services.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗