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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Parallel I/O Evaluation Techniques and Emerging HPC Workloads: A Perspective

Emerging workloads such as artificial intelligence, big data analytics and complex multi-step workflows alongside future exascale applications are anticipated future HPC workloads, which will result in a more diverse I/O system workload and even less predictable I/O behavior and access patterns. Along with the ever increasing gap between the compute and storage performance capabilities, the in-depth understanding of extreme-scale I/O behavior and the I/O performance modeling and prediction are essential tools of the large-scale I/O evaluation process for addressing the needs of extreme-scale hybrid workloads. In this survey article, we focus on the state-of-the-art of the I/O behavior and performance analysis process for HPC systems in a 5-year time window and identify future research challenges.

Neuwirth, Sarah↗
DOE OSTI2016

Characteristics and Travel Patterns of New York Residents: Subpopulations of Persons with a Disability in 2009

In this study, Oak Ridge National Laboratory (ORNL) was tasked by the NYS Department of Transportation (DOT) to conduct a detailed examination of travel behaviors, and identify patterns and trends, on several NYS subpopulations, including disabled persons. Unlike other studies that concentrated on national level statistics, this research is focused on examining issues associated with travelers among NYS residents only. For each special subpopulation group, ORNL will identify differences, if any, in travel patterns that are attributable to demographic characteristics, household characteristics, modal characteristics, geographic location, and other concepts. Focus will be given to trip frequency, trip chaining, as well as travel by time of day, trip purpose, and mode choice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Complex collective dynamics of active torque-driven colloids at interfaces

Modern self-assembly techniques aiming to produce complex structural order or functional diversity often rely on non-equilibrium conditions in the system. Light, electric, or magnetic fields are predominantly used to modify interaction profiles of colloidal particles during self-assembly or induce complex out-of-equilibrium dynamic ordering. The energy injection rate, properties of the environment are important control parameters that influence the outcome of active (dynamic) self-assembly. The current review is focused on a case of collective dynamics and self-assembly of particles with externally driven torques coupled to a liquid or solid interface. The complexity of interactions in such systems is further enriched by strong hydrodynamic coupling between particles. Unconventionally ordered dynamic self-assembled patterns, spontaneous symmetry breaking phenomena, self-propulsion, and collective transport have been reported in torque-driven colloids. Some of the features of the complex collective behavior and dynamic pattern formation in those active systems have been successfully captured in simulations.

Snezhko, Alexey↗
DOE OSTI2019

Combining Tensor Decompositions and Graph Analytics to Provide Cyber Situational Awareness at HPC Scale

This paper describes MADHAT (Multidimensional Anomaly Detection fusing HPC, Analytics, and Tensors), an integrated workflow that demonstrates the applicability of HPC resources to the problem of maintaining cyber situational awareness. MADHAT combines two high-performance packages: ENSIGN for large-scale sparse tensor decompositions and HAGGLE for graph analytics. Tensor decompositions isolate coherent patterns of network behavior in ways that common clustering methods based on distance metrics cannot. Parallelized graph analysis then uses directed queries on a representation that combines the elements of identified patterns with other available information (such as additional log fields, domain knowledge, network topology, whitelists and blacklists, prior feedback, and published alerts) to confirm or reject a threat hypothesis, collect context, and raise alerts. MADHAT was developed using the collaborative HPC Architecture for Cyber Situational Awareness (HACSAW) research environment and evaluated on structured network sensor logs collected from Defense Research and Engineering Network (DREN) sites using HPC resources at the U.S. Army Engineer Research and Development Center DoD Supercomputing Resource Center (ERDC DSRC). To date, MADHAT has analyzed logs with over 650 million entries.

Cyber security, Tensor decomposition, graph analyt↗
DOE OSTI2013

Validation of a Hot Water Distribution Model Using Laboratory and Field Data

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the Building America research team ARBI validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. This project also looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. The team concluded that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws, which has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Validation of a Hot Water Distribution Model Using Laboratory and Field Data

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the ARBI team validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. In addition to completing validation activities, this project looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. Based on these datasets, we conclude that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws. This has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Exploring the Utility-Privacy Trade-Off: Impacts of Semantic and Visit Types Ambiguities on Human Mobility Simulation

Humans are in perpetual movement, constantly traversing buildings, cities, waters, oceans, and countries. Mobility stands out as a major driving force shaping our modern societies. Capturing and explaining human behavior in a world of eight billion distinct mobility agendas is a complex challenge. With the rise of interconnected devices and platforms, such as smartphones, wearables, and point-of-interest data, largescale behavioral data has become more accessible, enabling rich insights into mobility patterns. However, the widespread availability of such data introduces significant ethical challenges. Detailed mobility data can inadvertently reveal sensitive personal information, including individuals' locations, habits, social interactions, and even political or religious affiliations. Beyond privacy breaches, the ethical implications of uncovering and potentially manipulating underlying behavioral patterns demand attention. Striking a balance between the utility of mobility models and the protection of individual privacy is therefore paramount. This paper explores the utility-privacy trade-offs in human mobility modeling, focusing on the impacts of introducing semantic and visit type ambiguities. By systematically examining how these ambiguities affect the fidelity of simulated trajectories and privacy risks, we provide a framework for evaluating ethical and privacy-conscious modeling practices. Our findings emphasize the need for methods that safeguard privacy without undermining the usefulness of mobility models, contributing to the responsible advancement of mobility science in alignment with ethical standards and societal expectations.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
DOE OSTI2014

Tunable exchange bias-like effect in patterned hard-soft two-dimensional lateral composites with perpendicular magnetic anisotropy

Patterned hard-soft 2D magnetic lateral composites have been fabricated by e-beam lithography plus dry etching techniques on sputter-deposited NdCo{sub 5} thin films with perpendicular magnetic anisotropy. Their magnetic behavior is strongly thickness dependent due to the interplay between out-of-plane anisotropy and magnetostatic energy. Thus, the spatial modulation of thicknesses leads to an exchange coupled system with hard/soft magnetic regions in which rotatable anisotropy of the thicker elements provides an extra tool to design the global magnetic behavior of the patterned lateral composite. Kerr microscopy studies (domain imaging and magneto-optical Kerr effect magnetometry) reveal that the resulting hysteresis loops exhibit a tunable exchange bias-like shift that can be switched on/off by the applied magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Coherent X-ray diffraction imaging and characterization of strain in silicon-on-insulator nanostructures

Coherent X-ray diffraction imaging (CDI) has emerged in the last decade as a promising high resolution lens-less imaging approach for the characterization of various samples. It has made significant technical progress through developments in source, algorithm and imaging methodologies thus enabling important scientific breakthroughs in a broad range of disciplines. In this report, we will introduce the principles of forward scattering CDI and Bragg geometry CDI (BCDI), with an emphasis on the latter. BCDI exploits the ultra-high sensitivity of the diffraction pattern to the distortions of crystalline lattice. Its ability of imaging strain on the nanometer scale in three dimensions is highly novel. We will present the latest progress on the application of BCDI in investigating the strain relaxation behavior in nanoscale patterned strained silicon-on-insulator (sSOI) materials, aiming to understand and engineer strain for the design and implementation of new generation semiconductor devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Travel Patterns and Characteristics of Elderly Subpopulation in New York State

With the increasing demographic shift towards a larger population of elderly (individuals 65 years and older), it is essential for policy makers and planners to have an understanding of transportation issues that affect the elderly. These issues include livability of the community, factors impacting travel behavior and mobility, transportation safety, etc. In this study, Oak Ridge National Laboratory was tasked by the New York State (NYS) Department of Transportation to conduct a detailed examination of travel behaviors, and identify patterns and trends of the elderly within NYS. The National Household Travel Survey (NHTS) was used as the primary data source to analyze subjects and address questions such as: Are there differences in traveler demographics between the elderly population and those of younger age groups who live in various NYS regions; e.g., New York City, other urban areas of NYS, or other parts of the country? How do they compare with the population at large? Are there any regional differences (e.g., urban versus rural)? Gender differences? Do any unique travel characteristics or patterns exist within the elderly group? In addition to analysis of NHTS data, roadway travel safety concerns associated with elderly travelers were also investigated in this study. Specifically, data on accidents involving the elderly (including drivers, passengers, and others) as captured in the Fatal Analysis Reporting System (FARS) database was analyzed to examine elderly driver and elderly pedestrian travel safety issues in NYS. The analyses of these data sets provide a greater understanding of the elderly within NYS and their associated transportation issues. Through this study, various key findings on elderly population size, household characteristics, and travel patterns were produced and are report herein this report.

elderly travel patterns↗
DOE OSTI2024

Hydrogen, Methane, Brine Flow Behavior, and Saturation in Sandstone Cores During H 2 and CH 4 Injection and Displacement

Large-scale underground hydrogen storage (UHS) is a critical component in the emerging hydrogen economy. Knowledge of multiphase flow behavior involving hydrogen in storage reservoir formations is crucial to characterizing hydrogen transport properties and essential for the deliverability and storage operations of UHS. There are still many gaps in fully understanding hydrogen–methane–brine multiphase phase flow that require further investigation. In this work, H 2 and CH 4 were injected through brine-saturated sandstone cores using a tri-axial core holder system fitted with flow rate meters and pressure transducers, while the effluent gas concentrations were analyzed using an online micro gas chromatograph. Brine displacement, permeability, and gas breakthrough curves were measured. We studied the flow behavior of hydrogen and methane in sandstone cores through testing brine displacement by gas injection and comparing the hydrogen displacement of methane with the methane displacement of hydrogen. We also tested the differences between horizontal and vertical flow in brine displacement. The results showed that brine displacement was more efficient in a core with higher permeability and porosity, resulting in a higher initial gas saturation. A higher gas injection rate brought about faster gas breakthrough measured by pore volume and sharper concentration curves. Hydrogen did not exhibit abnormal flow in the sandstone when the flow was horizontal and downward vertical. Gas overriding was observed in brine displacements when the flow was horizontal, with hydrogen showing this behavior more profoundly compared to methane. Downward vertical gas injection induced higher efficiency brine displacement compared to horizontal displacement and resulted in a higher initial gas saturation in the sandstone cores. These findings address critical knowledge gaps regarding gas flow patterns and displacement behaviors during hydrogen injection and recovery phases in UHS facilities using methane as the cushion gas. The insights from this research offer valuable guidance for optimizing UHS systems, ensuring operational efficiency, and advancing sustainable energy solutions in alignment with decarbonization goals.

08 HYDROGEN↗
DOE OSTI2014

Irradiation performance of U-Mo monolithic fuel

High-performance research reactors require fuel that operates at high specific power to high fission density, but at relatively low temperatures. Research reactor fuels are designed for efficient heat rejection, and are composed of assemblies of thin-plates clad in aluminum alloy. The development of low-enriched fuels to replace high-enriched fuels for these reactors requires a substantially increased uranium density in the fuel to offset the decrease in enrichment. Very few fuel phases have been identified that have the required combination of very-high uranium density and stable fuel behavior at high burnup. U-Mo alloys represent the best known tradeoff in these properties. Testing of aluminum matrix U-Mo aluminum matrix dispersion fuel revealed a pattern of breakaway swelling behavior at intermediate burnup, related to the formation of a molybdenum stabilized high aluminum intermetallic phase that forms during irradiation. In the case of monolithic fuel, this issue was addressed by eliminating, as much as possible, the interfacial area between U-Mo and aluminum. Based on scoping irradiation test data, a fuel plate system composed of solid U-10Mo fuel meat, a zirconium diffusion barrier, and Al6061 cladding was selected for development. Developmental testing of this fuel system indicates that it meets core criteria for fuel qualification, including stable and predictable swelling behavior, mechanical integrity to high burnup, and geometric stability. In addition, the fuel exhibits robust behavior during power-cooling mismatch events under irradiation at high power.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Leaching characteristics of toxic constituents from coal fly ash mixed soils under the influence of pH

Highlights: • The impact of pH on the leaching of elements and metals from fly ash mixed soils. • Generally Ca, Cd, Mg, and Sr follows a cationic leaching pattern. • The leaching of As and Se shows an oxyanionic leaching pattern. • The leaching behavior of elements does not change based on material type. • Different fly ash types show different abilities in immobilizing trace elements. - Abstract: Leaching behaviors of Arsenic (As), Barium (Ba), Calcium (Ca), Cadmium (Cd), Magnesium (Mg), Selenium (Se), and Strontium (Sr) from soil alone, coal fly ash alone, and soil-coal fly ash mixtures, were studied at a pH range of 2–14 via pH-dependent leaching tests. Seven different types of soils and coal fly ashes were tested. Results of this study indicated that Ca, Cd, Mg, and Sr showed cationic leaching pattern while As and Se generally follows an oxyanionic leaching pattern. On the other hand, leaching of Ba presented amphoteric-like leaching pattern but less pH-dependent. In spite of different types and composition of soil and coal fly ash investigated, the study reveals the similarity in leaching behavior as a function of pH for a given element from soil, coal fly ash, and soil-coal fly ash mixtures. The similarity is most likely due to similar controlling mechanisms (e.g., solubility, sorption, and solid-solution formation) and similar controlling factors (e.g., leachate pH and redox conditions). This offers the opportunity to transfer knowledge of coal fly ash that has been extensively characterized and studied to soil stabilized with coal fly ash. It is speculated that unburned carbon in off-specification coal fly ashes may provide sorption sites for Cd resulting in a reduction in concentration of these elements in leachate from soil-coal fly ash mixture. Class C fly ash provides sufficient CaO to initiate the pozzolanic reaction yielding hydrated cement products that oxyanions, including As and Se, can be incorporated into.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Analysis of WRF extreme daily precipitation over Alaska using self‐organizing maps

Abstract We analyze daily precipitation extremes from simulations of a polar‐optimized version of the Weather Research and Forecasting (WRF) model. Simulations cover 19 years and use the Regional Arctic System Model (RASM) domain. We focus on Alaska because of its proximity to the Pacific and Arctic oceans; both provide large moisture fetch inland. Alaska's topography also has important impacts on orographically forced precipitation. We use self‐organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events. The SOM algorithm employs an artificial neural network that uses an unsupervised training process, which results in finding general patterns of circulation behavior. The SOM is trained with mean sea level pressure (MSLP) anomalies. Widespread extreme events, defined as at least 25 grid points experiencing 99th percentile precipitation, are examined using SOMs. Widespread extreme days are mapped onto the SOM of MSLP anomalies, indicating circulation patterns. SOMs aid in determining high‐frequency nodes, and hence, circulations are conducive to extremes. Multiple circulation patterns are responsible for extreme days, which are differentiated by where extreme events occur in Alaska. Additionally, several meteorological fields are composited for nodes accessed by extreme and nonextreme events to determine specific conditions necessary for a widespread extreme event. Individual and adjacent node composites produce more physically reasonable circulations as opposed to composites of all extremes, which include multiple synoptic regimes. Temporal evolution of extreme events is also traced through SOM space. Thus, this analysis lays the groundwork for diagnosing differences in atmospheric circulations and their associated widespread, extreme precipitation events.

Glisan, Justin M.↗
DOE OSTI2022

Travel Patterns and Characteristics of Elderly Population in New York State: 2017 Update

According to US Census Bureau, the elderly population (individuals 65 years and older) has grown by over a third during the past decade (2010 to 2019), and by 3.2% from 2018 to 2019. It is essential for policymakers and planners to understand transportation issues associated with the elderly to meet their increasing travel demands. These issues include transportation and mobility of the elderly population, factors impacting their travel behavior, and transportation safety. In this study, Oak Ridge National Laboratory was tasked by the New York State Department of Transportation (NYSDOT) to conduct a detailed examination of travel behaviors and identify patterns and trends of its elderly residents. The National Household Travel Survey (NHTS) was used as the primary data source to analyze subjects and address questions such as: Are there differences in traveler demographics between the elderly population and those of younger age groups who live in various New York State (NYS) regions, e.g., New York City (NYC), other urban areas of NYS, or other parts of the country? How do they compare with the population at large? Are there any regional differences (e.g., urban versus rural)? Do any unique travel characteristics or patterns exist within the elderly group? How did these patterns change over time? In addition to the analysis of NHTS data, roadway travel safety concerns associated with elderly travelers were also investigated. Specifically, data on crashes involving the elderly (including drivers, passengers, and pedestrians) as captured in the Fatal Analysis Reporting System database was analyzed to examine elderly drivers and elderly pedestrian travel safety issues in NYS. This study report provides a summary of travel behavior and social-demographic characteristics of NYS elderly residents. These statistics could be used to examine equity issue concerning elderly New Yorkers, as well as to evaluate how well their mobility needs are being met. With a deeper understanding of issues and needs that this special population group is facing, policymakers and transportation planners would be able to make informed decisions on transportation investments and design services that could better address them.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Modeling the transmission of community-associated methicillin-resistant Staphylococcus aureus: a dynamic agent-based simulation

Background: Methicillin-resistant Staphylococcus aureus (MRSA) has been a deadly pathogen in healthcare settings since the 1960s, but MRSA epidemiology changed since 1990 with new genetically distinct strain types circulating among previously healthy people outside healthcare settings. Community-associated (CA) MRSA strains primarily cause skin and soft tissue infections, but may also cause life-threatening invasive infections. First seen in Australia and the U.S., it is a growing problem around the world. The U.S. has had the most widespread CA-MRSA epidemic, with strain type USA300 causing the great majority of infections. Individuals with either asymptomatic colonization or infection may transmit CA-MRSA to others, largely by skin-to-skin contact. Control measures have focused on hospital transmission. Limited public health education has focused on care for skin infections. Methods: We developed a fine-grained agent-based model for Chicago to identify where to target interventions to reduce CA-MRSA transmission. An agent-based model allows us to represent heterogeneity in population behavior, locations and contact patterns that are highly relevant for CA-MRSA transmission and control. Drawing on nationally representative survey data, the model represents variation in sociodemographics, locations, behaviors, and physical contact patterns. Transmission probabilities are based on a comprehensive literature review. Results: Over multiple 10-year runs with one-hour ticks, our model generates temporal and geographic trends in CA-MRSA incidence similar to Chicago from 2001 to 2010. On average, a majority of transmission events occurred in households, and colonized rather than infected agents were the source of the great majority (over 95%) of transmission events. The key findings are that infected people are not the primary source of spread. Rather, the far greater number of colonized individuals must be targeted to reduce transmission. Conclusions: Our findings suggest that current paradigms in MRSA control in the United States cannot be very effective in reducing the incidence of CA-MRSA infections. Furthermore, the control measures that have focused on hospitals are unlikely to have much population-wide impact on CA-MRSA rates. New strategies need to be developed, as the incidence of CA-MRSA is likely to continue to grow around the world.

59 BASIC BIOLOGICAL SCIENCES↗