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At least 37 records · Page 2

Current plate velocities relative to the hotspots incorporating the NUVEL-1 global plate motion model

The NUVEL-1 model of current global relative plate velocities is presently incorporated into HS2-NUVEL1, a global model for plate velocities relative to hotspots; the results thus obtained are compared with those of the AM1-2 model of hotspot-relative plate velocities. While there are places in which plate velocities relative to the hotspots differ between HS2-NUVEL1 and AM1-2 by tens of degrees in direction and 15 mm/yr in speed, the hotspot Euler vectors differ with 95 percent confidence only for the Arabian and Indian plates. Plates attached to subducting slabs move faster relative to the hotspots than do plates without slabs.

Gripp, Alice E.↗

Discovery of hotspots on Io using disk-resolved infrared imaging

First results are presented using two new techniques for ground-based observation of Io's hotspots. An IR array camera was used to obtain direct IR images of Io with resolution better than 0.5 arcsec, so that more than one hotspot is seen on Io in Jupiter eclipse. The camera was also used to make the first observations of the Jupiter occultation of the hotspots. These new techniques have revealed and located at least three hotspots and will now permit routine ground-based monitoring of the locations, temperatures, and sizes of multiple hotspots on Io.

Spencer, J. R.↗

Antipodal hotspot pairs on the earth

The results of statistical analyses performed on three published hotspot distributions suggest that significantly more hotspots occur as nearly antipodal pairs than is anticipated from a random distribution, or from their association with geoid highs and divergent plate margins. The observed number of antipodal hotspot pairs depends on the maximum allowable deviation from exact antipodality. At a maximum deviation of not greater than 700 km, 26 to 37 percent of hotspots form antipodal pairs in the published lists examined here, significantly more than would be expected from the general hotspot distribution. Two possible mechanisms that might create such a distribution include: (1) symmetry in the generation of mantle plumes, and (2) melting related to antipodal focusing of seismic energy from large-body impacts.

Rampino, Michael R.↗

Importance of viewing angle: Hotspot effect improves the ability of satellites to track terrestrial photosynthesis

The product of near-infrared reflectance of vegetation and photosynthetic active radiation (NIRvP) is a new tool for monitoring gross primary productivity (GPP) dynamics in terrestrial ecosystems, due to the discovered linear correlation between NIRvP and GPP. While remote sensing-based NIRvP is considerably influenced by sensor geometry, such geometry impacts on the NIRvP-GPP relationship remain underexplored. In this study, we calculate NIRvP using observations from the Deep Space Climate Observatory (DSCOVR) that provide unique hotspot observation geometry in which the sensor viewing angle coincides with the sun direction. We evaluated the linear correlation between NIRvP and GPP in both the common nadir direction and the special hotspot direction. The results indicate that NIRvP in the hotspot direction significantly outperforms that in the nadir direction for tracking GPP variations across different ecosystems from diurnal to daily scales. This conclusion is further supported by data from the MODerate resolution Imaging Spectroradiometer (MODIS) and simulations using the Soil Canopy Observation Photosynthesis Energy (SCOPE) model. Finally, our research highlights the value of using the unconventional hotspot-based sun-tracking satellite observations for a more accurate characterization of GPP dynamics in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Geologic evidence of hotspot activity of Venus - Predictions for Magellan

A number of distinctive types of geologic features have been identified on Venus that are interpreted to be related to thermal plumes including domal rises, coronae, and major composite shield volcanoes. The basic characteristics of these features as well as their distribution are documented. The three types of features have related morphologies and are interpreted to represent a continuum of features formed by mantle plumes at scales from 100s to over 1000 km. The Artemis structure, located in Aphrodite Terra, is proposed to be a large corona. If crustal spreading processes are operating on Venus, hotspot features should form chains on the surface as seen in terrestrial ocean basins. On the basis of current data on hotspot-related feature distribution on Venus, no clear evidence exists for hotspot chains. The complete distribution of hotspot features in Magellan data will be used to understand better the relationship between interior processes and surface features, as well as to provide a test for the crustal spreading hypothesis.

Stofan, Ellen R.↗

Models for the hotspot distribution

Published hotspot catalogs all show a hemispheric concentration beyond what can be expected by chance. Cumulative distributions about the center of concentration are described by a power law with a fractal dimension closer to 1 than 2. Random sets of the corresponding sizes do not show this effect. A simple shift of the random sets away from a point would produce distributions similar to those of hotspot sets. The possible relation of the hotspots to the locations of ridges and subduction zones is tested using large sets of randomly-generated points to estimate areas within given distances of the plate boundaries. The probability of finding the observed number of hotspots within 10 deg of the ridges is about what is expected.

Jurdy, Donna M.↗

Relativistic and Slowing Down: The Flow in the Hotspots of Powerful Radio Galaxies and Quasars

The 'hotspots' of powerful radio galaxies (the compact, high brightness regions, where the jet flow collides with the intergalactic medium (IGM)) have been imaged in radio, optical and recently in X-ray frequencies. We propose a scheme that unifies their, at first sight, disparate broad band (radio to X-ray) spectral properties. This scheme involves a relativistic flow upstream of the hotspot that decelerates to the sub-relativistic speed of its inferred advance through the IGM and it is viewed at different angles to its direction of motion, as suggested by two independent orientation estimators (the presence or not of broad emission lines in their optical spectra and the core-to-extended radio luminosity). This scheme, besides providing an account of the hotspot spectral properties with jet orientation, it also suggests that the large-scale jets remain relativistic all the way to the hotspots.

Kazanas, D.↗

Spatial Distribution of Volcanic Hotspots and Paterae on Io: Implications for Tidal Heating Models and Magmatic Pathways

Io, the innermost of Jupiter's Galilean satellites, is the most volcanically active body in the Solar. System. Io's global mean heat flow is approximately 2 W/square m, which is approximately 20 times larger than on Earth. High surface temperatures concentrate within "hotspots" and, to date, 172 Ionian hotspots have been identified by spacecraft and Earth-based telescopes. The Laplace resonance between Io, Europa, and Ganymede maintains these satellites in noncircular orbits and causes displacement of their tidal bulges as the overhead position of Jupiter changes for each moon. Gravitational interactions between Jupiter and Io dominate the orbital evolution of the Laplacian system and generate enormous heat within to as tidal energy is dissipated. If this energy were transferred out of Io at the same rate as it is generated, then the associated surface heat flux would be 2.24 +/- 0.45 W/square m. This estimate is in good agreement with observed global heat flow, but to better constrain tidal dissipation mechanisms and infer how thermal energy is transferred to Io's surface, it is critical to closely examine the spatial distribution of volcanic features. End-member tidal dissipation models either consider that heating occurs completely in the mantle, or completely in the asthenosphere. Mixed models typically favor one-third mantle and two-thirds asthenosphere heating. Recent models also consider the effects of mantle-asthenosphere boundary permeability and asthenospheric instabilities. Deep-mantle heating models predict maximum surface heat flux near the poles, whereas asthenosphere heating models predict maxima near the equator-particularly in the Sub-Jovian and Anti-Jovian hemispheres, with smaller maxima occurring at orbit tangent longitudes. Previous studies have examined the global distribution of Ionian hotspots and patera (i.e., irregular or complex craters with scalloped edges that are generally interpreted to be volcanic calderas), but in this study, we combine a new geospatial analysis technique with an improved hotspot and paterae database .

Hamilton, C. W.↗

The Potential Energy Hotspot: Effects of Impact Velocity, Defect Geometry, and Crystallographic Orientation

In energetic materials, the localization of energy into “hotspots” is known to dictate the initiation of chemical reactions and detonation. Recent all-atom simulations have shown that more energy is localized as internal potential energy (PE) than can be inferred from the kinetic energy (KE) alone. The mechanisms associated with pore collapse and hotspot formation are known to depend on pore geometry and dynamic material response such as plasticity. Therefore, we use molecular dynamics (MD) simulations to characterize shock-induced pore collapse and the subsequent formation of hotspots in 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a highly anisotropic molecular crystal, for various defect shapes, shock strengths, and crystallographic orientations. We find that the localization of energy as PE is consistently larger than the KE in cases with significant plastic deformation. Additionally, an analysis of MD trajectories reveals the underlying molecular- and crystal-level processes that govern the effect of orientation and pore shape on PE localization. We find that the regions of highest PE relate to the areas of maximum plastic deformation, while KE is maximized at the point of impact. Comparisons against octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) reveal less energy localization in TATB, which could be a contributing factor to the latter’s insensitivity.

36 MATERIALS SCIENCE↗

A Hotspot’s Better Half: Non-Equilibrium Intra-Molecular Strain in Shock Physics

Shockwave interactions with a material’s microstructure localizes energy into hotspots, which act as nucleation sites for complex processes such as phase transformations and chemical reactions. To date, hotspots have been described via their temperature fields. Nonreactive, all-atom molecular dynamics simulations of shock-induced pore collapse in a molecular crystal show that more energy is localized as potential energy (PE) than can be inferred from the temperature field and that PE localization persists beyond thermal diffusion. Furthermore, the origin of the PE hotspot is traced to large intramolecular strains, storing energy in modes readily available for chemical decomposition.

36 MATERIALS SCIENCE↗

On-chip sensing of hotspots in superconducting terahertz emitters

Intrinsic Josephson junctions in high-temperature superconductor Bi 2 Sr 2 CaCu 2 O 8+δ (BSCCO) are known for their capability to emit high-power terahertz photons with widely tunable frequencies. Hotspots, as inhomogeneous temperature distributions across the junctions, are believed to play a critical role in synchronizing the gauge-invariant phase difference among the junctions, so as to achieve coherent strong emission. In this paper, we demonstrate an on-chip in situ sensing technique that can characterize hotspot distributions on BSCCO. This is achieved by fabricating a series of micro-nanosized "sensor" junctions on top of an "emitter" junction and measuring the critical current on the sensors versus the bias current applied to the emitter. Furthermore, this fully electronic on-chip design can enable efficient close-loop control of hotspots in BSCCO junctions and significantly enhance the functionality of superconducting terahertz emitters.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Optimal choice of multiple line-of-sight measurements determining plasma hotspot velocity at the National Ignition Facility

The measurement of plasma hotspot velocity provides an important diagnostic of implosion performance for inertial confinement fusion experiments at the National Ignition Facility. The shift of the fusion product neutron mean kinetic energy as measured along multiple line-of-sight time-of-flight spectrometers provides velocity vector components from which the hotspot velocity is inferred. Multiple measurements improve the hotspot velocity inference; however, practical considerations of available space, operational overhead, and instrumentation costs limit the number of possible line-of-sight measurements. Here, we propose a solution to this classical “experiment design” problem that optimizes the precision of the velocity inference for a limited number of measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Three-dimensional electron temperature measurement of inertial confinement fusion hotspots using x-ray emission tomography

Here we present a novel approach to reconstruct three-dimensional (3D) electron temperature distributions of inertially confined fusion plasma hotspots at the National Ignition Facility. Using very limited number of two-dimensional (2D) x-ray imaging lines of sight, we perform 3D reconstructions of x-ray emission distributions from different x-ray energy channels ranging from 20 to 30 keV. 2D time-integrated x-ray images are processed using the algebraic reconstruction technique to reconstruct a 3D hotspot x-ray emission distribution that is self-consistent with the input images. 3D electron temperatures are computed using the energy channel ratios. We demonstrate the high accuracy and applicability of this method with different complex hotspot geometries in both synthetic and experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

HAM: Hotspot-Aware Manager for Improving Communications with 3D-Stacked Memory

merging High-Performance Computing (HPC) workloads, such as graph analytics, machine learning, and big data science, are data-intensive. Data-intensive workloads usually present fine-grained memory accesses with limited or no data locality, and thus incur frequent cache misses and low utilization of memory bandwidth. 3D-stacked memory devices such as Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM) can provide significantly higher bandwidth than conventional memory modules. However, the traditional interfaces and optimization methods for JEDEC DDR devices do not allow to fully exploit the potential performance of 3D-stacked memory with the massive amount of irregular memory accesses of data-intensive applications. In this paper, we propose a novel Hotspot-Aware Manager (HAM) infrastructure for 3D-stacked memory devices capable of optimizing memory access streams via request aggregation, hotspot detection, and in-memory prefetching. %and an associated hotspot-aware page policy. We present the HAM design and implementation, and simulate it on a system using RISC-V embedded cores with attached HMC devices. We extensively evaluate HAM with over 12 benchmarks and applications representing diverse irregular memory access patterns. The results show that, on average, HAM reduces redundant requests by 37.51\% and increases the prefetch buffer hit rate by 4.2 times, compared to a baseline streaming prefetcher. On the selected benchmark set, HAM provides performance gains of 21.81\% in average (up to 34.28\%) and power savings of 35.07\% over a standard 3D-stacked memory.

Wang, Xi↗

Potential of hotspot solar‐induced chlorophyll fluorescence for better tracking terrestrial photosynthesis

Abstract Remote sensing of solar‐induced fluorescence (SIF) opens a new window for quantifying a key ecological variable, the terrestrial ecosystem gross primary production (GPP), because of the revealed strong SIF–GPP correlation. However, similar to many other remotely sensed metrics, SIF observations suffer from the sun‐sensor geometry effects, which may have important impacts on the SIF–GPP relationship but remain poorly understood. Here we used remotely sensed SIF, globally distributed tower GPP data, and a mechanistic model to provide a systematic analysis. Our results reveal that leaf physiology, canopy structure, and sun‐sensor geometries all affect the SIF–GPP relationship. In particular, we found that SIF observations in the sun‐tracking hotspot direction can be a better proxy of GPP due to the similar responses of light use efficiency and SIF escaping probability in the hotspot direction to the increasing incoming solar radiation. Such conclusions are supported by a variety of modeling simulations and satellite observations over various plant function types, at different time scales and with satellite observational modes. This study demonstrates the potential and advantage of normalizing SIF observations to the hotspot direction for better global GPP estimations. This study also demonstrates the great potentials of current and future spaceborne sun‐tracking satellite missions for a significant improvement in measuring and monitoring, at a wide range of spatial and temporal scales, the changes in terrestrial ecosystem GPP in response to anticipated changes in the Earth's environmental conditions.

Hao, Dalei↗

Thermoelastic stress in oceanic lithosphere due to hotspot reheating

The effect of hotspot reheating on the intraplate stress field is investigated by modeling the three-dimensional thermal stress field produced by nonuniform temperature changes in an elastic plate. Temperature perturbations are calculated assuming that the lithosphere is heated by a source in the lower part of the thermal lithosphere. A thermal stress model for the elastic lithosphere is calculated by superposing the stress fields resulting from temperature changes in small individual elements. The stress in an elastic plate resulting from a temperature change in each small element is expressed as an infinite series, wherein each term is a source or an image modified from a closed-from half-space solution. The thermal stress solution is applied to midplate swells in oceanic lithosphere with various thermal structures and plate velocities. The results predict a stress field with a maximum deviatoric stress on the order of 100 MPa covering a broad area around the hotspot plume. The predicted principal stress orientations show a complicated geographical pattern, with horizontal extension perpendicular to the hotspot track at shallow depths and compression along the track near the bottom of the elastic lithosphere.

Zhu, Anning↗

A hotspot model for leaf canopies

The hotspot effect, which provides important information about canopy structure, is modeled using general principles of environmental physics as driven by parameters of interest in remote sensing, such as leaf size, leaf shape, leaf area index, and leaf angle distribution. Specific examples are derived for canopies of horizontal leaves. The hotspot effect is implemented within the framework of the model developed by Suits (1972) for a canopy of leaves to illustrate what might occur in an agricultural crop. Because the hotspot effect arises from very basic geometrical principles and is scale-free, it occurs similarly in woodlands, forests, crops, rough soil surfaces, and clouds. The scaling principles advanced are also significant factors in the production of image spatial and angular variance and covariance which can be used to assess land cover structure through remote sensing.

Jupp, David L. B.↗

Improving Satellite-Based Hotspot Detection Through Deep Learning-Enabled Smoke Recognition

While geostationary satellites, such as the GOES-R series, provide wildland fire hotspot readings at a high temporal resolution, they are prone to false negative readings and decreased confidence. One cause of decreased hotspot confidence is cloud contamination. Smoke produced from wildfire is often misinterpreted as cloud contamination, resulting in inaccurate and unsure sensor readings. To this end, we built a deep learning image segmentation model to identify smoke and cloud in true color satellite images. The model is pre-trained using self-supervised learning on over 10,000 GOES-R images to learn the underlying structure of satellite imagery. Then, the model is fine-tuned on a set of 130 labeled documents using supervised learning. The resulting model performs multi-class image segmentation with 85% accuracy and runs in under a minute on a standard personal computer. When paired alongside hotspot data, the model’s outputs can help increase confidence in wildfire location by identifying cases of cloud contamination that are due to smoke. The resulting model can be deployed in a stand-alone application or bundled in an Open Data Integration for wildland fire management (ODIN) application.

Earth observation↗