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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Determination of the Disperse Composition of a PbO Suspension Containing Aggregates of Particles of Lamellar Shape by the Laser-Polarimetry Method

The results of measurements of the scattering matrix at a wavelength of 0.63 μm in the range of scattering angles of 10°–155° are presented for an aqueous suspension of lead oxide containing particles of plate form and their aggregates of monomers with dimensions of ~5 nm. The results of the measurements are compared with the results of calculations for axially symmetric scatterers (ellipsoids of rotation, cylinders). It is shown that the presence of aggregates affects the scattering properties of such a medium. The results of reconstructing the distribution of particles of a disperse medium in sizes from the measurements data of the scattering matrix are presented. The reconstruction of the distributions was carried out by solving the problem of optimizing the sum of the squared deviations of the experimental and calculated values of matrix elements in the framework of the model of axially symmetric scatterers. It is shown that the distribution of particles by sizes is more accurately reconstructed by minimizing the sum of the squares of the deviations for the sum of the diagonal elements. The obtained distribution is compared with the distribution measured by the method of dynamic light scattering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

McrEngine: A Scalable Checkpointing System Using Data-Aware Aggregation and Compression

High performance computing (HPC) systems use checkpoint-restart to tolerate failures. Typically, applications store their states in checkpoints on a parallel file system (PFS). As applications scale up, checkpoint-restart incurs high overheads due to contention for PFS resources. The high overheads force large-scale applications to reduce checkpoint frequency, which means more compute time is lost in the event of failure. We alleviate this problem through a scalable checkpoint-restart system, mcrEngine. McrEngine aggregates checkpoints from multiple application processes with knowledge of the data semantics available through widely-used I/O libraries, e.g., HDF5 and netCDF, and compresses them. Our novel scheme improves compressibility of checkpoints up to 115% over simple concatenation and compression. Our evaluation with large-scale application checkpoints show that mcrEngine reduces checkpointing overhead by up to 87% and restart overhead by up to 62% over a baseline with no aggregation or compression.

Islam, Tanzima Zerin↗
DOE OSTI2025

BAMCensus (The Behavior and Advanced Mobility Census Dataset Aggregator) [SWR-25-120]

This software is a high-performance tool developed in Rust for downloading and processing large-scale geospatial datasets, specifically focusing on US Census data. It is designed to address scaling limitations found in existing tools, such as R's [tidycensus](https://walker-data.com/tidycensus/), by providing performant streaming dataset JOIN operations between various US Census datasets (like ACS and LEHD) and their corresponding geometries stored on the TIGER/Lines web server. The tool automates the process of joining these data sources, returning aggregated data to the user based on a specified census GEOID type. The tool automates the process of joining these data sources, returning aggregated data to the user based on a specified census GEOID type. Its primary motivation stems from the need for a high-performance solution to combine spatial datasets with graph traversals within the context of mobility analysis tooling being developed at NREL's Behavior and Advanced Mobility (BAM) group.

Fitzgerald, Robert [National Renewable Energy Labo↗
DOE OSTI2019

The Fall Speed Variability of Similarly Sized Ice Particle Aggregates

The terminal velocity ( V t ) of ice hydrometeors is of high importance to atmospheric modeling. V t is governed by the physical characteristics of a hydrometeor, including mass and projected area, as well as environmental conditions. When liquid hydrometeors coalesce to form larger hydrometeors, the resulting hydrometeor can readily be characterized by its spherical or near-spherical shape. For ice hydrometeors, it is more complicated because of the variability of ice shapes possible in the atmosphere as well as the inherent randomness in the aggregation process, which leads to highly variable characteristics. The abundance of atmospheric processes affecting ice particle dimensional characteristics creates potential for highly variable V t for ice particles that are predicted or measured to be of the “same size.” In this article we explore the variability of ice hydrometeor V t both theoretically and through the use of experimental observations. Theoretically, the variability in V t is investigated by analyzing the microphysical characteristics of randomly aggregated hexagonal shapes. The modeled dimensional characteristics are then compared to aircraft probe measurements to constrain the variability in atmospheric ice hydrometeor V t . Results show that the spread in V t can be represented with Gaussian distributions relative to a mean. Variability expressed as the full width at half maximum of the normalized Gaussian probability distribution function is around 20%, with somewhat higher values associated with larger particle sizes and warmer temperatures. Field campaigns where mostly convective clouds were sampled displayed low variability, while Arctic and midlatitude winter campaigns showed broader V t spectra.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Secondary Ion Mass Spectrometry Imaging of Dictyostelium discoideum Aggregation Streams

High resolution imaging mass spectrometry could become a valuable tool for cell and developmental biology, but both, high spatial and mass spectral resolution are needed to enable this. In this report, we employed Bi3 bombardment time-of-flight (Bi3 ToF-SIMS) and C60 bombardment Fourier transform ion cyclotron resonance secondary ion mass spectrometry (C60 FTICR-SIMS) to image Dictyostelium discoideum aggregation streams. Nearly 300 lipid species were identified from the aggregation streams. High resolution mass spectrometry imaging (FTICR-SIMS) enabled the generation of multiple molecular ion maps at the nominal mass level and provided good coverage for fatty acyls, prenol lipids, and sterol lipids. The comparison of Bi3 ToF-SIMS and C60 FTICR-SIMS suggested that while the first provides fast, high spatial resolution molecular ion images, the chemical complexity of biological samples warrants the use of high resolution analyzers for accurate ion identification.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

Quantification of massive seasonal aggregations of blacktip sharks ( Carcharhinus limbatus ) in Southeast Florida

Southeast Florida witnesses an enormous seasonal influx of upper trophic level marine predators each year as massive aggregations of migrating blacktip sharks ( Carcharhinus limbatus ) overwinter in nearshore waters. The narrow shelf and close proximity of the Gulf Stream current to the Palm Beach County shoreline drive tens of thousands of sharks to the shallow, coastal environment. This natural bottleneck provides a unique opportunity to estimate relative abundance. Over a four year period from 2011–2014, an aerial survey was flown approximately biweekly along the length of Palm Beach County. A high definition video camera and digital still camera mounted out of the airplane window provided a continuous record of the belt transect which extended 200 m seaward from the shoreline between Boca Raton Inlet and Jupiter Inlet. The number of sharks within the survey transect was directly counted from the video. Shark abundance peaked in the winter (January-March) with a maximum in 2011 of 12,128 individuals counted within the 75.6 km -2 belt transect. This resulted in a maximum density of 803.2 sharks km -2 . By the late spring (April-May), shark abundance had sharply declined to 1.1% of its peak, where it remained until spiking again in January of the following year. Shark abundance was inversely correlated with water temperature and large numbers of sharks were found only when water temperatures were less than 25°C. Shark abundance was also correlated with day of the year but not with barometric pressure. Although shark abundance was not correlated with photoperiod, the departure of the sharks from southeast Florida occurred around the vernal equinox. The shark migration along the United States eastern seaboard corresponds spatially and temporally with the spawning aggregations of various baitfish species. As a result, these baseline abundance data can be compared to future studies to determine if shark population size is changing and if sharks are restricting their southward migration as global water temperatures increase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Building Advanced Materials via Particle Aggregation and Molecular Self-Assembly

Hierarchical and other advanced materials have attracted increasing attention due to their unique physical and chemical properties, which strongly depend on morphology and size.1-2 These materials have been applied in important technological fields such as energy, catalysis, optical devices, water purification, pollutant removal, CO2 sequestration, and biomedicine.3-7 Particle-based crystallization and self-assembly of molecules are important pathways to synthesize advanced materials of complex structures.8-11 Unlike monomer-by-monomer addition or Ostwald ripening, particle-based crystallization occurs via particle-by-particle addition, to form larger crystals or clusters.8, 12 To date, numerous advanced materials have been synthesized in the lab using particle-based crystallization. Examples include metals such as Pt, Pd, Au, Ag, and Cu;13 alloys such as Pt-Ni, Pt-Cu, Pt-Fe, and Au-Ag;14 metal oxides such as ZnO, TiO2, CuO, and a-Fe2O3, Fe3O4;15-19 and metal sulfides such as PbS, PbSe, ZnS, and CdS.20-21 In addition, particle aggregation-based crystallization has been observed in nature, such as in various geological and biological minerals including calcite, collagen, and others.22-24 Different from the particle-based crystallization, self-assembly of molecules has also been used to build advanced materials such as molecular clusters and nanoparticles. For instance, advanced luminescent materials have been prepared by aggregation-induced emission (AIE) of intrinsically non-emissive molecules.25-26 One of the challenges facing this fast-growing field of advanced materials is to develop a fundamental understanding of the interactions between particles or molecules in a growth medium and the resulting response dynamics.

Zhang, Xin↗
DOE OSTI2011

Limitations in Determining Multifractal Spectra from Pore-Solid Soil Aggregate Images

Multifractal methods have the potential to be useful tools for characterizing spatial distributions of soil pores from microtomographic images of undisturbed soil cores and soil aggregates. The objective of this study was to examine the limitations of multifractal analyses in binary (void and solid) soil images and to explore conditions under which multifractal spectra can be obtained. Multifractal characteristics of binary soil images are bounded within certain limiting values corresponding to nonfractal scaling. In this study, we first addressed the theoretical limitations of multifractal analysis of binary images and examined the nonfractal scaling boundaries in multifractal calculations by the method of moments. Then we developed boundary conditions for multifractal calculations by the direct method. Results revealed that fractal scaling is potentially possible only across a relatively narrow range of cell sizes restricted by the nonfractal scaling boundaries. Moreover, the range of cell sizes where fractal scaling is potentially possible varies with pore size. That is, in multifractal calculations it changes continuously with changes in the q value. For the soil aggregates examined in this study, this range varied from two to eight pixels for low q values to 128 pixels for high q values. The varying range makes calculations of true multifractal spectra for binary soil image data impossible. These results are consistent with a general theoretical notion that binary soil images are not multifractal in a strict mathematical sense. We suggest, however, that application of multifractal formalism can generate 'pseudo-multifractal spectra' that might still be useful for summarizing pore distribution information and for comparing pore data among different agricultural management regimes and soil type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Small File Aggregation with PLFS [Slides]

Today’s computational science demands have resulted in ever larger parallel computers, and storage systems have grown to match these demands. Parallel file systems used in this environment are increasingly specialized to extract the highest possible performance for large I/O operations, at the expense of other potential workloads. While some applications have adapted to I/O best practices and can obtain good performance on these systems, the natural I/O patterns of many applications result in the generation of a huge number of small files, the creation of which is poorly served by current parallel file systems at very large scale. This paper describes a new technique for optimizing small file access in parallel file systems for these very large scale systems. The idea is to use a virtual parallel log-structure file system on the compute nodes in order to aggregate large numbers of small files in compute node memory and then stream their data sequentially to a much smaller number of physical files on an underlying parallel file system. The technique is implemented and evaluated using PLFS as the aggregating middleware. We evaluate our system with micro-benchmarks on a local OSX filesystem and with an MPI extension of the standard Postmark to provide results at scale on both Lustre and PanFS parallel filesystems. We observe as much as a 33x improvement in small file create rates on a single host, and 30x improvement in small file write rates, compared to a baseline Lustre configuration on a leadership computing platform using 16,384 cores and achieve an unprecedented create rate of 200 million files per second.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Superionic conduction using ion aggregates

Project objective: Engineer solid polymeric electrolytes with an optimized, self-assembled, ion network that conducts independently of polymer segmental dynamics. The goal of this project is to engineer an optimized, self-assembled ion aggregate network, by which we can incorporate an aggregate assisted, collective, superionic conduction paradigm into polymeric electrolytes. We do not seek to improve conductivity, although this is a likely result of our approach, but to propose systems in which collective motion is the main conduction mechanism. We believe that once such materials are identified, they will quickly become a subject of research in the solid polymer electrolyte community. With this in mind, we pursue three design strategies: increase ion content in PEG single ion conductors, use mixed anions (including divalent ions as crosslinkers), and introduce swelled polyanion/polycation complexes as a potential ion conducting material.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Cyber Security Primer for DER Vendors Aggregators and Grid Operators

This report provides an introduction to cyber security for distributed energy resources (DER) - such as photovoltaic (PV) inverters and energy storage systems (ESS). This material is motivated by the need to assist DER vendors, aggregators, grid operators, and broader PV industry with cyber security resilience and describe the state-of-the-art for securing DER communications. The report outlines basic principles of cyber security, encryption, communication protocols, DER cyber security recommendations and requirements, and device-, aggregator-, and utility-level security best practices to ensure data confidentiality, integrity, and availability. Example cyber security attacks, including eavesdropping, masquerading, man-in-the-middle, replay attacks, and denial-of-service are also described. A survey of communication protocols and cyber security recommendations used by the DER and power system industry are included to elucidate the cyber security standards landscape. Lastly, a roadmap is presented to harden end-to-end communications for DER with research and industry engagement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 14: Model Verification/Validation Test Plan (Deliverable D10))

This report summarizes the technical progress and validation plan for each of AGGREGATE project modules, and integrated modules. The overall validation plan can be divided into two major parts. Firstly, it provides offline validation results of each module using the IEEE-123 node distribution system with certain modifications to support individual module results verification. The offline validation plan tentatively validated the usability and practicability of developed AGGREGATE tools. Secondly, the realworld test system - Seattle City Light (SCL) test feeder for verifying each module and the integrated modules using GE advanced distribution management system (ADMS) software.

42 ENGINEERING↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Subsurface Aggregation of Cationic Friction Reducers: Cause and Prevention

The purpose of this work was to identify the cause of a gelatinous aggregation of friction reducers that was found post-fracturing by RWS operators. RWS sent us samples which we analyzed by scanning electron microscope (SEM). Laboratory experiments were performed to identify the cause of the aggregations and propose a method of preventing them from forming. We concluded that cationic friction reducers were crosslinking with clays, and that this could be prevented by using higher-salinity injection fluid. The results of this study help promote recycling of produced water.

geochemistry↗
DOE OSTI2025

Community Choice Aggregation(CCA) Data Collection Webinar for Status and Trends in the Voluntary Market Report (2024 Data) [Slides]

We have subcontracted LEAN Energy US, to help us improve our CCA data collection effort for the Annual Voluntary Energy Markets Data Report. LEAN Energy US (Local Energy Aggregation Network) is a national 501(c)3 non-profit organization dedicated to accelerating the country's transition to clean and renewable power, supporting competition and customer choice in the energy sector, and maintaining affordable electricity rates. We work in partnership with a range of organizations to actively support the formation and operational success of Community Choice Aggregation (CCA) programs around the country. This webinar, hosted in partnership with LEAN Energy US, is intended to introduce their members to our data collection effort and encourage CCAs in their network to participate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗