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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Highly Dynamic Gamma-Ray Emissions Are Common in Tropical Thunderclouds

Thunderstorms emit fluxes of gamma rays known as gamma-ray glows, sporadically observed by aircraft, balloons and from ground. Glows are observed as increased gamma-ray emissions by tens of percent up to two orders of magnitude above the background, sometimes abruptly terminated by lightning discharges. Glows are produced by the acceleration of energetic electrons in high electric field regions within thunderclouds, and contribute to charge dissipation. Glows are considered as quasi-stationary phenomena, with durations up to a few tens of seconds and spatial scales up to 10-20 kilometers. No measurement of the full extension in space and time of a gamma ray glow region and their occurring frequency has been reported so far. Here we show that tropical thunderclouds over ocean and coastal regions commonly emit gamma rays for hours over areas up to a few thousands of square kilometers. Emission is associated with deep convective cores; it is not uniform and continuous but shows characteristic timescales of 1-10 seconds and even sub-second for individual glows. The dynamics of gamma-glowing thunderclouds starkly contradicts the quasi-stationary picture of glows, but rather resembles that of a huge gamma-glowing «boiling pot» both in pattern and behavior.

M Marisaldi↗
DOE OSTI2018

Network protection system using linkographs

A method and apparatus for managing an attack on a computer system. A computer identifies actions taken by an adversary in the computer system and links connecting the actions over time using an ontology defining linking rules for linking the actions over time. The computer creates a graph of the actions with the links connecting the actions over time. The graph shows a number of patterns of behavior for the adversary. The computer then identifies a protective action to take with respect to the computer system using the graph of the actions taken by the adversary.

Zage, David John↗
DOE OSTI2020

Phase I Closeout Report: Invoking Artificial Neural Networks to Measure Insider Threat Mitigation

Researchers from Sandia National Laboratories (Sandia) and the University of Texas at Austin (UT) conducted this study to explore the effectiveness of commercial artificial neural network (ANN) software to improve insider threat detection and mitigation (ITDM). This study hypothesized that ANNs could be "trainee to learn patterns of organizational behaviors, detect off-normal (or anomalous) deviations from these patterns, and alert when certain types, frequencies, or quantities of deviations emerge. The ReconaSense ANN system was installed at UT's Nuclear Engineering Teaching Laboratory (NETL) and collected 13,653 access control data points and 694 intrusion sensor data points over a three-month period. Preliminary analysis of this baseline data demonstrated regularized patterns of life in the facility, and that off-normal behaviors are detectable under certain situations -- even for a facility with anticipated highly non-routine, operational behaviors. Completion of this pilot study demonstrated how the ReconaSense ANN could be used to identify expected operational patterns and detect unexpected anomalous behaviors in support of a data-analytic approach to ITDM. While additional studies are needed to fully understand and characterize this system, the results of this initial study are overall very promising for demonstrating a new framework for ITDM utilizing ANNs and data analysis techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Texture and precipitation behavior of friction stir welded Inconel 825 alloy

The microstructure, texture pattern, and precipitation behavior of friction stir butt welded Inconel 825 alloy are highlighted here. The microstructure of bright regions and black-banded regions in the stir zone (SZ) is characterized by SEM, EBSD, and TEM with EDS. EBSD analysis justifies that the SZ exhibits a dynamic recrystallized structure. Grain boundary mapping corroborates the insignificant difference in the low- and high-angle grain boundaries fraction between the SZ, the thermo-mechanically affected zone, and the base metal. TEM analysis confirms the formation of nano twins and dispersion of nano-size precipitations in the grains, and at the grain boundaries as well. Grain refinement and nano-size precipitation formation in the SZ significantly enhanced both microhardness and tensile strength.

Das, Hrishikesh↗
NASA NTRS1997

Solar Cycle Predictions Near Sunspot Minimum

Observations of solar magnetic activity and the dynamics of the solar convection zone have produced severe constraints on models of the Sun's magnetic dynamo. These constraints are so severe that, at present, we do not have numerical models that can accept the current conditions and then march forward in time to predict future activity. Given this state of solar dynamo theory we are forced to examine previous behavior to discover patterns and trends that afford us some measure of predictability. Here we examine the behavior of several indicators of solar activity near solar minimum that are well correlated with the amplitude of the following solar maximum to predict the level of solar activity over cycle 23. Sunspot numbers, areas, and positions are useful for characterizing solar cycle behavior due to the extent of the data (12 cycles or more). These data exhibit several patterns that relate future activity to past behavior. With the Odd-Even effect the odd numbered cycles have been larger than their even numbered predecessors for each of the last six cycle pairs. With the Amplitude-Period effect short period cycles have been followed by large amplitude cycles and long period cycles have been followed by small amplitude cycles for 10 of the last 13 cycles. With the Maximum-Minimum effect the sunspot number at minimum is directly correlated with the sunspot number at maximum for a given cycle. The geomagnetic indices aa and Ap are also related to solar activity by the connections between disturbances in the solar wind and variations in the Earth's magnetic field. Like the Maximum-Minimum effect for sunspots, the size of the aa and Ap indices at minimum are directly related to the amplitude of the following maximum. The number of geomagnetically disturbed days (days with Ap >= 25) over the course of a cycle is another indicator for the size of the next cycle. The aa and Ap indices can each be separated into a component in phase with the current sunspot cycle and an "extended cycle" component that is directly related to the following cycle. Individually each of these indicators provides some measure of predictive ability for the amplitudes of previous cycles. Taken in combination we find that the predictions are much more accurate. Our multi-variate analysis indicates that a maximum sunspot number of 160 +/- 20 should occur near the end of 1999 for cycle 23.

Hathaway, David H.↗
DOE OSTI2022

Shifting temporal dynamics of human mobility in the United States

In this paper we analyze the average hourly temporal dynamics of human mobility in the United States from 2019 to 2020. We discuss how large decreases in human mobility nonuniformly effect the daily temporal dynamics of aggregate human behavior. The data used are weekly activity patterns for POIs from 2019 to 2020 in the United States, provided by SafeGraph and made openly available to academic and research institutions. We use clustering methods to create metrics describing how human activity changes throughout the day/week at the county and national levels. In response to significant mobility reductions starting March 2020, daily temporal patterns of human activity changed nonuniformly. Morning activity started later, and evening activity started earlier in 2020 compared to 2019, and temporal behavioral patterns on weekdays began to look more similar to weekends. The changes in daily temporal behavior persisted throughout the year even as total mobility levels recovered. The results provide insights on the changes in human behavior in response covid-19 policies and illustrate influences on social systems, health, and transportation networks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

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↗
DOE OSTI2016

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↗
NASA NTRS1985

Post-IOC space station: Models of operation and their implications for organizational behavior, performance and effectiveness

Issues of crew productivity during design work on space station are discussed. The crew productivity is defined almost exclusively in terms of human factors engineering and habitability design concerns. While such spatial environmental conditions are necessary to support crew performance and productivity, they are not sufficient to ensure high levels of crew performance and productivity on the post-Initial Operational Configurations (IOC) space station. The role of the organizational environment as a complement to the spatial environment for influencing crew performance in such isolated and confined work settings is examined. Three possible models of operation for post-IOC space station's organizational environment are identified and it is explained how they and space station's spatial environment will combine and interact to occasion patterns of crew behavior is suggested. A three phase program of research design: (1) identify patterns of crew behavior likely to be occasioned on post-IOC space station for each of the three models of operation; and (2) to determine proactive/preventative management strategies which could be adopted to maximize the emergence of preferred outcomes in crew behavior under each of the several spatial and organizational environment combinations.

Danford, S.↗
DOE OSTI2018

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↗
DOE OSTI2024

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↗
NASA NTRS1992

Physiological asymmetry in etiolated pea epicotyls: relation to patterns of auxin distribution and phototropic behavior

Etiolated pea seedlings require transformation of Pr phytochrome to Pfr before they display optimal phototropic response to unilateral blue light. This study investigates the possible role of auxin transport in explaining these phenomena. Labeled [2-14C]IAA applied to the intact terminal buds of dark-grown and red light-treated pea seedlings was measured 210 min later on the shaded and illuminated sides of the epicotyl as a function of direction and duration of irradiation with blue light. Totally darkened epicotyls show an asymmetry in distribution of radioactivity in the upper growth zone of the epicotyl, in favor of the side under the concave part of the apical hook. Red light, which greatly potentiates curvature toward subsequent unilateral blue light, lowers this asymmetry. Blue light directed to the epicotyl of red-pretreated plants in a plane parallel to the hook and from the side bearing the convex portion of the hook induces positive phototropic curvature as well as a surplus of radioactivity on the illuminated side of the upper epicotyl and on the shaded side of the lower growth zone of the epicotyl. Light directed to the side bearing the concave part of the hook also causes an accumulation of counts in the upper part of the lighted side but produces neither curvature of the epicotyl nor accumulation of counts in the lower shaded side. Because of this built-in physiological asymmetry in the growth zone just below the apical hook, it is difficult to explain the effects of red and blue light on curvature in terms of patterns of auxin distribution alone.

NASA Program Space Biology↗
NASA NTRS2010

Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

Rohloff, Kurt↗
NASA NTRS2004

Immunity-Based Aircraft Fault Detection System

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

Dasgupta, D.↗
DOE OSTI2016

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.↗
DOE OSTI2023

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↗