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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 109 records · Page 6

Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease

We previously found temporoparietal-predominant atrophy patterns in the behavioral variant of Alzheimer’s disease (bvAD), with relative sparing of frontal regions. Here, we aimed to understand the clinico-anatomical dissociation in bvAD based on alternative neuroimaging markers. We retrospectively included 150 participants, including 29 bvAD, 28 “typical” amnestic-predominant AD (tAD), 28 behavioral variant of frontotemporal dementia (bvFTD), and 65 cognitively normal participants. Patients with bvAD were compared with other diagnostic groups on glucose metabolism and metabolic connectivity measured by [ 18 F]FDG-PET, and on subcortical gray matter and white matter hyperintensity (WMH) volumes measured by MRI. A receiver-operating-characteristic-analysis was performed to determine the neuroimaging measures with highest diagnostic accuracy. bvAD and tAD showed predominant temporoparietal hypometabolism compared to controls, and did not differ in direct contrasts. However, overlaying statistical maps from contrasts between patients and controls revealed broader frontoinsular hypometabolism in bvAD than tAD, partially overlapping with bvFTD. bvAD showed greater anterior default mode network (DMN) involvement than tAD, mimicking bvFTD, and reduced connectivity of the posterior cingulate cortex with prefrontal regions. Analyses of WMH and subcortical volume showed closer resemblance of bvAD to tAD than to bvFTD, and larger amygdalar volumes in bvAD than tAD respectively. The top-3 discriminators for bvAD vs. bvFTD were FDG posterior-DMN-ratios (bvAD bvFTD, area under the curve [AUC] range 0.85–0.91, all p < 0.001). The top-3 for bvAD vs. tAD were amygdalar volume (bvAD>tAD), MRI anterior-DMN-ratios (bvAD<tAD), FDG anterior-DMN-ratios (bvAD<tAD, AUC range 0.71–0.84, all p < 0.05). Subtle frontoinsular hypometabolism and anterior DMN involvement may underlie the prominent behavioral phenotype in bvAD.

59 BASIC BIOLOGICAL SCIENCES↗

Baselining PMU Data to Find Patterns and Anomalies

This paper looks at the application of situational awareness methodologies with respect to power grid data. These methodologies establish baselines that look for typical patterns and atypical behavior in the data. The objectives of the baselining analyses are to provide: real-time analytics, the capability to look at historical trends and events, and reliable predictions of the near future state of the grid. Multivariate algorithms were created to establish normal baseline behavior and then score each moment in time according to its variance from the baseline. Detailed multivariate analytical techniques are described in this paper that produced ways to identify typical patterns and atypical behavior. In this case, atypical behavior is behavior that is unenvisioned. Visualizations were also produced to help explain the behavior that was identified mathematically. Examples are shown to help describe how to read and interpret the analyses and visualizations. Preliminary work has been performed on PMU data sets from BPA (Bonneville Power Administration) and EI (Eastern Interconnect). Actual results are not fully shown here because of confidentiality issues. Comparisons between atypical events found mathematically and actual events showed that many of the actual events are also atypical events; however there are many atypical events that do not correlate to any actual events. Additional work needs to be done to help classify the atypical events into actual events, so that the importance of the events can be better understood.

Baselining analyses↗

Size Effects of Micro-Pattern on Lithium Metal Surface on the Electrochemical Performance of Lithium Metal Secondary Batteries.

Two micro-patterns of different sizes (50 and 80 gm) are designed to have equivalent capacities of 1.06 and 2.44 mAh cm(-2) by building a computational battery model. After preparing two stamps each possessing a micro pattern design, the corresponding pattern is properly imprinted on the surface of 100 mu m lithium metal, which is confirmed by scanning electron microscopy. When both micro-patterned lithium metals are electrochemically reduced and oxidized up to 1 mAh cm(-2) in Li/Li symmetric cells at 1 or 2 mA cm(-2), the 80 mu m-patterned lithium shows a more stabilized lower overpotential during long-term cycling than the 50 mu m-patterned and bare lithium, probably due to the lithium anchoring effect and a larger empty volume in the patterns. Additionally, an overflow of lithium deposits is easily observed in the 50 mu m-patterned lithium metal, while the 80 mu m-patterned lithium metal holds most of the lithium deposits within the patterns. When both micro-patterned lithium metals are assembled to full cells with a LiNi0.6Co0.2Mn0.2O2 cathode of 2 mAh cm(-2), the 80 mu m-patterned lithium metal shows much better electrochemical performances with stable plating/stripping behavior within the patterns.

lithium metal↗

Thermal shock resistance of additively manufactured alumina

The mechanical behavior and cracking patterns of thermally-shocked additively manufactured alumina were investigated. The flexural strength of test specimens that had been heated to temperatures ranging from 200°C to 1000°C and then rapidly quenched in water was determined at ambient temperature by four-point bending. Results indicated that the surface cracking patterns had a multifractal structure and that an increase in the thermal shock temperature led to an increase in the density and uniformity of the crack network. Further, the flexural strength results were analyzed with Weibull statistics, where the Weibull moduli for most of the thermal shock conditions tested were found to be statistically indistinguishable. It was also found that a significant decrease (~50%) in flexural strength occurred for heating temperatures ≥300°C. The effect of the manufacturing method on cracking patterns is discussed, as well as the implication of the material behavior for practical applications of these materials.

36 MATERIALS SCIENCE↗

Directing the phase behavior of polyelectrolyte complexes using chiral patterned peptides

Polyelectrolyte complexes (PECs) have a broad range of promising applications as soft materials due to their self-assembly and diversity of structure and chemical composition. Peptide polymer PECs are highly biocompatible and biodegradable, making them particularly useful for encapsulation of food additives and flavors, micellar drug delivery, medical and underwater adhesives, fetal membrane patches, and scaffolds for cell growth in tissue engineering. While parameters affecting PEC formation and stability in regards to charge effects are well researched, little is known about the effects of van der Waals interactions, hydrogen bonding, and secondary structure in these materials. Peptide chirality provides a unique opportunity to manipulate PEC phase to modulate the amount of solid-like (precipitate) or liquid-like (coacervate) character by influencing hydrogen bonding interactions among peptide chains. In previous work, we showed that chiral peptides form solid complexes, while complexes with even one racemic peptide were fluid. This raised the interesting question of how long a homochiral sequence must be to result in solid phase formation. In this work, we designed chiral patterned peptides of polyglutamic acid and polylysine ranging from 50 to 90% L-chiral residues with increasing numbers of sequential L-chiral residues before a chirality change. These polymers were mixed together to form PECs. We observed that 8 or more sequential L-chiral residues are necessary to achieve both the appearance of a precipitate phase and sustained beta-sheets in the complex, as determined by optical imaging and FTIR Spectroscopy. Less homochiral content results in formation of a coacervate phase. Thus, we show that chiral sequence can be used to control the phase transition of PECs. Understanding how to manipulate PEC phase using chiral sequence as presented here may enable tuning of the material properties to achieve the desired mechanical strength for coatings and polymer brushes, or the most effective molecular release kinetics for drug delivery applications, for example.

Pacalin, Naomi M.↗

Modeling spatial patterns of longleaf pine needle dispersal using long-term data

Abstract Background Predicting patterns of fire behavior and effects in frequent fire forests relies on an understanding of fine-scale spatial patterns of available fuels. Leaf litter is a significant canopy-derived fine fuel in fire-maintained forests. Litter dispersal is dependent on foliage production, stand structure, and wind direction, but the relative importance of these factors is unknown. Results Using a 10-year litterfall dataset collected within eighteen 4-ha longleaf pine ( Pinus palustris Mill.) plots varying in canopy spatial pattern, we compared four spatially explicit models of annual needle litter dispersal: a model based only on basal area, an overstory abundance index (OAI) model, both isotropic and anisotropic litter kernel models, and a null model that assumed no spatial relationship. The best model was the anisotropic model (R 2 = 0.656) that incorporated tree size, location, and prevailing wind direction, followed by the isotropic model (R 2 = 0.612), basal area model (R 2 = 0.488), OAI model (R 2 = 0.416), and the null model (R 2 = 0.08). Conclusions As with previous studies, the predictive capability of the litter models was robust when internally validated with a subset of the original dataset (R 2 = 0.196–0.549); however, the models were less robust when challenged with an independent dataset (R 2 = 0.122–0.319) from novel forest stands. Our model validation underscores the need for rigorous tests with independent, external datasets to confirm the validity of litter dispersal models. These models can be used in the application of prescribed fire to estimate fuel distribution and loading, as well as aid in the fine tuning of fire behavior models to better understand fire outcomes across a range of forest canopy structures.

54 ENVIRONMENTAL SCIENCES↗

Experimental and 3D Micromechanical Analysis of Stress–Strain Behavior and Damage Initiation in Dual-Phase Steels

In the recent decade, dual-phase steel has been used extensively in the industry due to its high strength and formability. In this paper, deformation pattern and mechanical behavior of DP steel are predicted using the 2D and 3D representative volume element (RVE) and finite elements method. Also, the obtained results were compared with the experimental SEM images. The experiments are performed in three stages to obtain the stress–strain curve and failure pattern in the specimens with the different state of stress distribution at the test sections. In the 3D state of stress, the state of applied stress to the RVE is obtained from macro-modeling of the test specimens and this model was analyzed using the finite element method. Furthermore, the effects of volume fraction and mesh size in 3D simulation on the stress–strain behavior are investigated. Metallography and SEM images are also used to access the failure mechanism at the microscale. It is shown that the martensite particles remain almost in their original form and their deformations are very small for the specimens with the thickness-to-width ratio of 0.8 (3D state of stress). This phenomenon is completely different from those obtained for smaller thickness-to-width ratio that the martensite particles were pulled and its length was increased. On the other hand, SEM images show that voids are located in the phase boundaries. According to the experimental and numerical results, although the main factor in the formation and growth of 2D voids is shear stress, in the 3D state of stress, the voids grow in spherical form due to the existence of large hydrostatic stresses.

36 MATERIALS SCIENCE↗

The variation in self-organized anode plasma pattern structure with solution electrolyte type in 1 atm DC glow discharge

Abstract Plasma self-organization on anode surfaces in 1 atm DC glow discharges remains poorly understood. This effort aims to elucidate the nature of self-organization through the experimental study of resulting patterns on liquid anode surfaces with 13 different electrolytes and thus improves our understanding of the underlying physical processes that give rise to self-organization by investigating electrolyte sensitivity. Self-organization pattern formation and behavior were studied as a function of discharge current, solution ionic strength, and their chemical property evaluation. The response of the patterns to variation in these parameters was measured using an imaging camera and optical emission spectroscopy. Observed pattern characteristic length scales for all of the electrolytes were ranged from 2 to 13 mm and typically increased with current over the investigated range of 20–80 mA. Complex self-organized pattern structures not reported to date were also observed. The parameters associated with pattern formation and morphology complexity are discussed and summarized.

Physics↗

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↗

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↗

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↗

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↗

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)↗

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↗

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↗

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↗