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At least 1,765 records · Page 98

Temporal and Spatial Evolution of Non-Elastic Strain Accumulation in Stanstead Granite During Brittle Creep

Understanding the long-term behavior of brittle rocks requires fundamental consideration of time-dependent strain evolution and brittle creep processes. Previous studies have evaluated sub-critical crack growth during time-dependent deformation and damage evolution in brittle rocks; however, there is an incomplete knowledge of how damage evolves spatially and temporally within the body of intact rocks, where distributed regions of damage interact and coalesce during creep. This paper presents laboratory research focusing on evaluating brittle creep damage processes in Stanstead granite (SG) using 2-dimensional digital image correlation (2D-DIC). In the laboratory, the prismatic SG specimens were loaded beyond an estimated Crack Damage stress threshold (CD) level and then maintained a constant stress to initiate the creep process. DIC was used to characterize full-field spatiotemporal strain evolution, which was then interpreted in the context of local regions of “damage”, determined according to a strain-based criterion. Here, a method was proposed for identifying “existing” and “new” damage regions over specified intervals during the test, followed by spatial clustering of these regions to assess their spatiotemporal evolution. The clustering analysis results demonstrated the extension of existing damage regions was the main damage process during brittle creep, which is consistent with existing models of sub-critical crack growth. In addition, temporal analysis of tensile and shear strains on a point-by-point basis revealed both new damage formation and the strain concentration within existing damaged regions significantly contribute to overall specimen strain during primary creep. In contrast, during secondary creep, increases in specimen deformation are influenced by the accumulation of strains within already damaged regions.

58 GEOSCIENCES↗

“It’s Raining Bits”: Patterns in Directional Precipitation Persistence Across the United States

The spatial and temporal ordering of precipitation occurrence impacts ecosystems, streamflow, and water availability. For example, both large-scale climate patterns and local landscapes drive weather events, and the typical speeds and directions of these events moving across a basin dictate the timing of flows at its outlet. We address the predictability of precipitation occurrence at a given location, based on the knowledge of past precipitation at surrounding locations. We identify ‘‘dominant directions of precipitation influence’’ across the continental United States based on a gridded daily dataset. Specifically, we apply information theory–based measures that characterize dominant directions and strengths of spatial and temporal precipitation dependencies. On a national average, this dominant direction agrees with the prevalent direction of weather movement from west to east across the country, but regional differences reflect topographic divides, precipitation gradients, and different climatic drivers of precipitation. Trends in these information relationships and their correlations with climate indices over the past 70 years also show seasonal and spatial divides. This study expands upon a framework of information-based predictability to answer questions about spatial connectivity in addition to temporal persistence. The methods presented here are generally useful to understand many aspects of weather and climate variability.

North America↗

Remote sensing of near surface humidity over north Pacific

Humidity soundings at 12 midocean stations of small islands and weather ships in the north Pacific from 7 deg N to 57 deg N during a 9-year period from 1972 to 1980 were used to study the variation of columnar water vapor W (as measured by spaceborne sensors) in relation to the variation of surface level specific humidity Q (as required in the determination of air-sea moisture and latent heat exchanges). It was found that a simple regression can be used to specify monthly mean Q from W to an accuracy of about 0.0008, corresponding to about 20 W/sq m in latent heat flux. The regression accounts for both temporal and spatial variations of Q and W. Better accuracy can be achieved by using regional regressions. The study affirms the potential of spaceborne sensors in providing global monitoring of air-sea moisture and heat exchanges.

Liu, W. T.↗

Spatial and temporal trends in contaminant concentrations in Hexagenia nymphs following a coal ash spill at the Tennessee Valley Authority's Kingston Fossil Plant

A dike failure at the Tennessee Valley Authority Kingston Fossil Plant in East Tennessee, United States, in December 2008, released approximately 4.1 million m(3) of coal ash into the Emory River. From 2009 through 2012, samples of mayfly nymphs (Hexagenia bilineata) were collected each spring from sites in the Emory, Clinch, and Tennessee Rivers upstream and downstream of the spill. Samples were analyzed for 17 metals. Concentrations of metals were generally highest the first 2 miles downstream of the spill, and then decreased with increasing distance from the spill. Arsenic, B, Ba, Be, Mo, Sb, Se, Sr, and V appeared to have strong ash signatures, whereas Co, Cr, Cu, Ni, and Pb appeared to be associated with ash and other sources. However, the concentrations for most of these contaminants were modest and are unlikely to cause widespread negative ecological effects. Trends in Hg, Cd, and Zn suggested little (Hg) or no (Cd, Zn) association with ash. Temporal trends suggested that concentrations of ash-related contaminants began to subside after 2010, but because of the limited time period of that analysis (4 yr), further monitoring is needed to verify this trend. The present study provides important information on the magnitude of contaminant exposure to aquatic receptors from a major coal ash spill, as well as spatial and temporal trends for transport of the associated contaminants in a large open watershed.

01 COAL, LIGNITE, AND PEAT↗

High temporal resolution generation expansion planning for the clean energy transition

As power systems integrate increasing quantities of wind, solar and energy storage resources, it is important to revisit power system capacity expansion modeling methods and assumptions that have been utilized in thermal- dominated systems. We conduct a series of case study analyses using a simplified representation of the Electric Reliability Council of Texas (ERCOT) system to demonstrate how least-cost capacity expansion outcomes are impacted by changes in model resolution across two temporal dimensions: 1) the number of considered representative periods, and 2) the system dispatch interval. First, we find that the least-cost generation portfolio can differ significantly for small changes in the number of representative days, but largely converges to the 365-day result once 104 representative days are considered. Furthermore, systems with wind, solar and storage resources were more sensitive to changes in the number of representative days than a thermal-dominated system. Second, we find that considering five-minute dispatch resolution consistently results in least-cost generation portfolios with less solar capacity and more energy storage capacity than corresponding scenarios with hourly dispatch intervals. This suggests that hourly dispatch representation fails to capture the intra-hour volatility of solar generation, and therefore also overlooks opportunities for storage resources to provide system value by balancing this volatility. Collectively these results indicate that capacity expansion modelers should revisit conventional approaches to temporal representation when conducting analyses of deeply decarbonized power systems to ensure that such analyses are robust and actionable. To our knowledge, this is the first study to analyze capacity expansion outcomes with five-minute dispatch resolution in this manner.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. Here, in this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

59 BASIC BIOLOGICAL SCIENCES↗

Detection of Chlorophyll and Leaf Area Index Dynamics from Sub-weekly Hyperspectral Imagery

Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense time series of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

Houborg, Rasmus↗

OPCPA front end and contrast optimization for the OMEGA EP kilojoule, picosecond laser

OMEGA EP is a large-scale laser system that combines optical parametric amplification and solid-state laser amplification on two beamlines to deliver high-intensity, high-energy optical pulses. The temporal contrast of the output pulse is limited by the front-end parametric fluorescence and other features that are specific to parametric amplification. The impact of the two-crystal parametric preamplifier, pump-intensity noise, and pump-signal timing is experimentally studied. The implementation of a parametric amplifier pumped by a short pump pulse before stretching, further amplification, and recompression to enhance the temporal contrast of the high-energy short pulse is described.

47 OTHER INSTRUMENTATION↗

Gamma-ray, neutron, and hard X-ray studies and requirements for a high-energy solar physics facility

The requirements for future high-resolution spatial, spectral, and temporal observation of hard X-rays, gamma rays and neutrons from solar flares are discussed in the context of current high-energy flare observations. There is much promise from these observations for achieving a deep understanding of processes of energy release, particle acceleration and particle transport in a complicated environment such as the turbulent and highly magnetized atmosphere of the active sun.

Ramaty, R.↗

Response of convective-diffusive transport to spatial and temporal variations in effective gravity

The response of heat, mass, and momentum transport to conditions characteristic of the microgravity environment is studied. It is found that the orientation of the experiment with respect to the steady component of the residual gravity is a crucial factor in determining the suitability of the spacecraft as a means of suppressing or eliminating unwanted effects caused by buoyant fluid motion. The process is highly sensitive to transient disturbances.

Alexander, J. Iwan D.↗

Application of digital image processing techniques to faint solar flare phenomena

Digital image processing of eight solar flare events was performed using the Video Information Communication and Retrieval language in order to study moving emission fronts, flare halos, and Moreton waves. The techniques used include contrast enhancement, isointensity contouring, the differencing of images, spatial filtering, and geometrical registration. The spatial extent and temporal behavior of the faint phenomena is examined along with the relation of the three types of phenomena to one another. The image processing techniques make possible the detailed study of the history of the phenomena and provide clues to their physical nature.

Glackin, D. L.↗

Quantifying Uncertainties in Modeling Wind Resource Data from Different PBL Schemes in the WRF Model: A Case Study Over the Puerto Rico Region

This study examines the modeling uncertainty of wind resource data stemming from the use of various planetary boundary layer (PBL) parameterizations available in the Weather Research and Forecasting (WRF) model. WRF-based wind simulations spanning 20 years at 3-km resolution using 11 different PBL schemes are used to objectively investigate the uncertainty in modeling wind speed for land-based wind (LBW) and offshore wind (OSW) locations in Puerto Rico. The uncertainty in the wind modeling for the 20-year dataset is quantified using the spread index (SI) and standard deviation (SD). For virtual LBW and OSW sites, the SI and SD values are analyzed as calculated across various spatial and temporal scales. Because the PBL's atmospheric stability conditions can be characterized into two dominant categories, the study focuses on analyzing the SI and SD for daytime (mainly unstable PBL conditions) and nighttime (mainly stable PBL conditions). For wind shear (10 m-200 m) at the OSW and LBW sites, WRF-based numerical experiments indicate the following SI (or SD) ranges: 39%-94% (0.74 m/s-1.44 m/s) during the daytime for OSW, 50%-75% (0.68 m/s-1.19 m/s) during the daytime for LBW, 37%-60% (0.73 m/s-1.12 m/s) during the nighttime for OSW, and 57%-143 % (0.65 m/s-1.43 m/s) during the nighttime for LBW. While a high SI is observed when modeling LBW during the nighttime, there are notable modeling uncertainties during the daytime on the leeward side of the orographic barriers for Puerto Rico.

17 WIND ENERGY↗

Seeing is Believing: Monitoring Future Time Temporal Logic

Runtime monitors for future-time unbounded temporal logics like RVLTL, LTL 3 and FLTL, have double-exponential (2^2^n) worst-case space complexity bounds in size of the input formula. The semantics of these logics require monitors to perform general satisfiability solving for LTL expressions, a well-studied problem whose computational complexity is NP-hard and PSPACE-complete. This paper introduces an unbounded future-time linear temporal logic defined over a lattice. We call our logic an incremental temporal logic as it can be viewed as incrementally constructing proofs about the trace. On this account, we view online runtime monitoring as a decision procedure for proofs systems about incrementally growing traces. We demonstrate that our incremental temporal logic allows monitor construction to void satisfiability solving while still soundly detecting when the property is violated in an online fashion. This enables asymptotic improvements in space complexity. As proof, we provide a procedure to construct monitors that utilize linear space and time in the size of the input formula, while remaining constant in the size of the input stream and suitable for online monitoring. We further demonstrate, through several examples, that our incremental temporal logic is straightforward to adopt and practical for runtime verification.

temporal logic↗

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for CN values specific to various land and crop cover types and account for various farming best practices but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and it captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geologic Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

Ella Griffith↗

Protein adsorption onto nanoparticles induces conformational changes: Particle size dependency, kinetics, and mechanisms

The use of nanomaterials in bioapplications demands a detailed understanding of protein–nanoparticle interactions. Proteins can undergo conformational changes while adsorbing onto nanoparticles, but studies on the impact of particle size on conformational changes are scarce. We have shown that conformational changes happening upon adsorption of myoglobin and BSA are dependent on the size of the nanoparticle they are adsorbing to. Out of eight initially investigated model proteins, two (BSA and myoglobin) showed conformational changes, and in both cases this conformational change was dependent on the size of the nanoparticle. Nanoparticle sizes ranged from 30 to 1000 nm and, in contrast to previous studies, we attempted to use a continuous progression of sizes in the range found in live viruses, which is an interesting size of nanoparticles for the potential use as drug delivery vehicles. Conformational changes were only visible for particles of 200 nm and bigger. Using an optimized circular dichroism protocol allowed us to follow this conformational change with regard to the nanoparticle size and, thanks to the excellent temporal resolution also in time. We uncovered significant differences between the unfolding kinetics of myoglobin and BSA. In this study, we also evaluated the plausibility of commonly used explanations for the phenomenon of nanoparticle size-dependent conformational change. Currently proposed mechanisms are mostly based on studies done with relatively small particles, and fall short in explaining the behavior seen in our studies.

Biotechnology & Applied Microbiology↗

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Houborg, Rasmus↗