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At least 1,783 records · Page 99

Measurements of the Vertical Structure of Aerosols and Clouds Over the Ocean Using Micro-Pulse LIDAR Systems

The determination of the vertical distribution of aerosols and clouds over the ocean is needed for accurate retrievals of ocean color from satellites observations. The presence of absorbing aerosol layers, especially at altitudes above the boundary layer, has been shown to influence the calculation of ocean color. Also, satellite data must be correctly screened for the presence of clouds, particularly cirrus, in order to measure ocean color. One instrument capable of providing this information is a lidar, which uses pulses of laser light to profile the vertical distribution of aerosol and cloud layers in the atmosphere. However, lidar systems prior to the 1990s were large, expensive, and not eye-safe which made them unsuitable for cruise deployments. During the 1990s the first small, autonomous, and eye-safe lidar system became available: the micro-pulse lidar, or MPL. The MPL is a compact and eye-safe lidar system capable of determining the range of aerosols and clouds by firing a short pulse of laser light (523 nm) and measuring the time-of-flight from pulse transmission to reception of a returned signal. The returned signal is a function of time, converted into range using the speed of light, and is proportional to the amount of light backscattered by atmospheric molecules (Rayleigh scattering), aerosols, and clouds. The MPL achieves ANSI eye-safe standards by sending laser pulses at low energy (micro-J) and expanding the beam to 20.32 cm in diameter. A fast pulse-repetition-frequency (2500 Hz) is used to achieve a good signal-to-noise, despite the low output energy. The MPL has a small field-of-view (< 100 micro-rad) and signals received with the instrument do not contain multiple scattering effects. The MPL has been used successfully at a number of long-term sites and also in several field experiments around the world.

Welton, Ellsworth J.↗

Toward a standardization of cryostructure and cryogenic soil structure terminology for the field description of permafrost‐affected soils

This paper establishes standardized terminology and field documentation protocols for cryostructures and cryogenic soil structures in permafrost‐affected soils and provides brief guidance on descriptions of ground ice morphology and ice volume estimates. We consolidate permafrost terminology from Russian and North American literature, clarify long‐standing ambiguities, and provide explicit guidelines that align with US Department of Agriculture‐Natural Resources Conservation Service soil description standards. Our scheme makes critical distinctions between cryostructure, the distribution of ice within soil, and cryogenic soil structure, the morphological structure of soil resulting from ice formation. The scheme organizes cryostructures into three main categories: non‐segregated ice, visible segregated ice, and ice matrices. We introduce standardized codes and parameters for field descriptions of ice and soil that enable machine‐readable data collection compatible with existing soil information systems. This standardization will significantly enhance the integration of field observations into landscape‐scale assessments of permafrost stability, infrastructure vulnerability, and ecosystem response to permafrost thaw, addressing an urgent need for quantitative data to inform modeling and decision‐making in rapidly changing Arctic and subarctic environments.

Andersen, Megan L. [University of Minnesota, Saint↗

Phoenix: A Scalable Streaming Hypergraph Analysis Framework

We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a distributed implementation of a streaming server architecture which acts as a gateway for various hypergraph generators/external sources to connect. Phoenix has the capability to utilize diverse hypergraph generators, including HyGen, a very large-scale hypergraph generator developed by ORNL. Phoenix incorporates specific algorithms for efficient data representation by exploiting hidden structures of the hypergraphs. Our experimental results demonstrate Phoenix’s scalable and stable performance on massively parallel computing platforms. Phoenix’s superior performance is due to the merging of high-performance computing with data analytic.

Kurte, Kuldeep↗

Multi-task Parallelism for Robust Pre-training of Graph Foundation Models on Multi-source, Multi-fidelity Atomistic Modeling Data

Graph foundation models using graph neural networks promise sustainable, efficient atomistic modeling. To tackle challenges of processing multi-source, multi-fidelity data during pre-training, recent studies employ multi-task learning, in which shared message passing layers initially process input atomistic structures regardless of source, then route them to multiple decoding heads that predict data-specific outputs. This approach stabilizes pre-training and enhances a model’s transferability to unexplored chemical regions. Preliminary results on approximately four million structures are encouraging, yet questions remain about generalizability to larger, more diverse datasets and scalability on supercomputers. We propose a multi-task parallelism method that distributes each head across computing resources with GPU acceleration. Implemented in the open-source HydraGNN architecture, our method was trained on over 24 million structures from five datasets and tested on the Perlmutter, Aurora, and Frontier supercomputers, demonstrating efficient scaling on all three highly heterogeneous super-computing architectures.

Lupo Pasini, Massimiliano [ORNL] (ORCID:0000000249↗

Fractal Dimension Calculation for Big Data Using Box Locality Index

The box-counting approach for fractal dimension calculation is scaled up for big data using a data structure named box locality index (BLI). The BLI is constructed as key-value pair style with the key (an integer array) indexing the location of a “box” (i.e., a gird cell on the multi-dimensional space embedding a given dataset) and the value counting the number of data points inside the box (called “box occupancy”). Compared with the traditionally used E-dim tree, the BLI avoids complex hierarchical structure and encodes only necessary information required by box-counting approach for fractal dimension calculation. Moreover, the key-value pair nature of BLI, together with the fact that the box occupancy is aggregatable, grants box-counting approach the needed scalability for fractal dimension calculation of big data using distributed computing techniques (e.g., MapReduce and Spark). Taking the advantage of the BLI, MapReduce and Spark methods for fractal dimension calculation of big data are developed, which conduct box-counting for each grid level as a cascade of MapReduce/Spark jobs in a bottom-up fashion. In an empirical validation, the MapReduce and Spark methods demonstrated good effectiveness and efficiency in fractal calculation of a big synthetic dataset. In summary, this work provides an efficient solution for the estimation of intrinsic dimension of big data that is essential for many machine learning methods and data analytics.

Fractal dimension, Intrinsic dimension, Box-counti↗

Multiscale Based Characterization and Classification of Urban Land-Use

Machine learning and deep learning provide a means for generating urban land-use maps with relatively little human effort compared to manually digitizing images. This is especially important for supporting global and regional initiatives focused on sustainability, planning, health, pro-poor policy, infrastructure, and population distribution estimates. Many of these initiatives work in areas where geospatial data is scarce, such as the global south, and often use land-use maps to help achieve their goals. In this study, we develop a typology for automated labeling of urban land-use data that captures the variation in structural patterns within cities. A comparison of classification accuracy between convolutional neural networks (CNNs) and support vector machines (SVMs) coupled with handcrafted features is conducted. Through experimental validation on two highly dense cities in Africa, we report on new insights and the potential benefits offered by both multiscale handcrafted features and multiscale-CNNs even with limited training data.

Arndt, Jacob↗

Resolved photons in S HERPA

We present the first complete simulation framework, in the SHERPA event generator, for resolved photon interactions at next-to leading order accuracy. It includes photon spectra obtained through the equivalent-photon approximation, parton distribution functions to parametrize the hadronic structure of quasi-real photons, the matching of the parton shower to next-to leading order QCD calculations for resolved photon cross sections, and the modelling of multiple-parton interactions. We validate our framework against a wide range of photo-production data from LEP and HERPA experiments, observing good overall agreement. We identify important future steps relevant for high-quality simulations at the planned Electron–Ion Collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Interdiffusion in the Ni/TD-NiCr and Cr/TD-NiCr systems

The diffusion of Ni and Cr into TD-NiCr has been studied over the 900 to 1100 C temperature range. The diffusion couples were prepared by electroplating Cr and Ni on polished TD-NiCr wafers. Concentration profiles produced as a result of isothermal diffusion at 905, 1000, and 1100 C were determined by electron microprobe analysis. The Boltzmann-Matano analysis was used to determine concentration-dependent diffusion coefficients which were found to compare favorably with previously reported values. These data suggest that 2 vol % ThO2 distribution has no appreciable effect on the rates of diffusion in TD-NiCr with a large grain size. This supports the view that an inert dispersoid in an alloy matrix will not in itself lead to enhanced diffusion unless a short-circuit diffusion structure is stabilized.

Pawar, A. V.↗

Maps of Jovian radio emission

Observations were made of Jupiter with the Westerbork telescope at all three frequencies available: 610 MHz, 1415 MHz, and 4995 MHz. The raw measurements were corrected for position errors, atmospheric extinction, Faraday rotation, clock, frequency, and baseline errors, and errors due to a shadowing effect. The data was then converted into brightness distribution of the sky by Fourier transformation. Maps of both thermal and nonthermal radiation were developed. Results indicate that the thermal disk of Jupiter measured at a wavelength of 6 cm has a temperature of 236 + or - 15 K. The radiation belts have an overall structure governed by the trapping of electrons in the dipolar field of the planet with significant beaming of the synchrotron radiation into the plane of the magnetic equator.

Depater, I.↗

Space shuttle solid rocket booster water entry cavity collapse loads

Solid rocket booster cavity collapse flight measurements included external pressures on the motor case and aft skirt, internal motor case pressures, accelerometers located in the forward skirt, mid-body area, and aft skirt, as well as strain gages located on the skin of the motor case. This flight data yielded applied pressure longitudinal and circumferential distributions which compare well with model test predictions. The internal motor case ullage pressure, which is below atmospheric due to the rapid cooling of the hot internal gas, was more severe (lower) than anticipated due to the ullage gas being hotter than predicted. The structural dynamic response characteristics were as expected. Structural ring and wall damage are detailed and are considered to be attributable to the direct application of cavity collapse pressure combined with the structurally destabilizing, low internal motor case pressure.

Keefe, R. T.↗

Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies

Efforts to develop a three dimensional model to predict canopy, bidirectional reflectance for heterogenous plant stands using incident radiation and canopy structural descriptions as inputs are described. Utility programs were developed to cope with the complex output from the 3 dimensional model. In addition an attempt was made to define leaf and soil properties, which are appropriate to the mode, by measuring leaf and soil bidirectional reflectance distribution functions; since almost no data exist on these distributions. In the process it was realized that most models probably are using the wrong leaf spectral properties, and that off-nadir reflectance measurements are difficult to make because of non-Lambertian properties of reference surfaces. Also, in the visible wavebands, rough soil may not be distinguishable from canopies when viewed from above.

Norman, J. M.↗

Thunderstorm currents and lightning charges at the NASA Kennedy Space Center

The NASA Kennedy Space Center, (KSC) and the U.S. Air Force are currently operating an extensive network of ground-based electric-field mills in order to detect atmospheric electrical hazards to ground operations, launches, and landings of spacecraft. Over the past 10 years, the University of Arizona has utilized data provided by this network, and other instrumentation, to investigate the electrical structure of thunderstorms and lightning in Florida. Recent analyses have included estimates of the Maxwell current density that thunderstorms produce at the ground and computations of the locations and magnitudes of lightning-caused changes in the cloud charge distribution. This work is reviewed, and an example of how thunderstorm current patterns and lightning charges develop in both space and time is presented.

Krider, E. P.↗

Rare earth element transport in the western North Atlantic inferred from Nd isotopic observations

The relationship between the Nd isotopic composition in the Atlantic waters and the origin and circulation of the water masses was investigated. Samples were collected in the western North Atlantic between 7 and 54 deg N. The isotopic composition (Nd-143/Nd-144 ratios) showed extensive vertical structure at all locations. In regions where a thermocline was well-developed, large isotopic shifts were observed across the base of the thermocline, while regions without a thermocline were characterized by much more gradual shifts in isotopic composition with depth. The data reveal an excellent correlation between the Nd isotopic distribution in the western North Atlantic water column and the distribution of water masses identified from temperature and salinity measurements.

Piepgras, D. J.↗

Lidar cloud studies for FIRE and ECLIPS

Optical remote sensing measurements of cirrus cloud properties were collected by one airborne and four ground-based lidar systems over a 32 h period during this case study from the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE) Intensive Field Observation (IFO) program. The lidar systems were variously equipped to collect linear depolarization, intrinsically calibrated backscatter, and Doppler velocity information. Data presented describe the temporal evolution and spatial distribution of cirrus clouds over an area encompassing southern and central Wisconsin. The cirrus cloud types include: dissipating subvisual and thin fibrous cirrus cloud bands, an isolated mesoscale uncinus complex (MUC), a large-scale deep cloud that developed into an organized cirrus structure within the lidar array, and a series of intensifying mesoscale cirrus cloud masses. Although the cirrus frequently developed in the vertical from particle fall-streaks emanating from generating regions at or near cloud tops, glaciating supercooled (-30 to -35 C) altocumulus clouds contributed to the production of ice mass at the base of the deep cirrus cloud, apparently even through riming, and other mechanisms involving evaporation, wave motions, and radiative effects are indicated. The generating regions ranged in scale from approximately 1.0 km cirrus uncinus cells, to organized MUC structures up to approximately 120 km across.

Sassen, Kenneth↗

The Clouds distributed operating system - Functional description, implementation details and related work

Clouds is an operating system in a novel class of distributed operating systems providing the integration, reliability, and structure that makes a distributed system usable. Clouds is designed to run on a set of general purpose computers that are connected via a medium-of-high speed local area network. The system structuring paradigm chosen for the Clouds operating system, after substantial research, is an object/thread model. All instances of services, programs and data in Clouds are encapsulated in objects. The concept of persistent objects does away with the need for file systems, and replaces it with a more powerful concept, namely the object system. The facilities in Clouds include integration of resources through location transparency; support for various types of atomic operations, including conventional transactions; advanced support for achieving fault tolerance; and provisions for dynamic reconfiguration.

Dasgupta, Partha↗

Providing structural modules with self-integrity monitoring software user's manual

National Aeronautics and Space Administration (NASA) Contract NAS7-961 (A Small Business Innovation and Research (SBIR) contract from NASA) involved research dealing with remote structural damage detection using the concept of substructures. Several approaches were developed. The main two were: (1) the module (substructure) transfer function matrix (MTFM) approach; and (2) modal strain energy distribution method (MSEDM). Either method can be used with a global structure; however, the focus was on substructures. As part of the research contract, computer software was to be developed which would implement the developed methods. This was done and it was used to process all the finite element generated numerical data for the research. The software was written for the IBM AT personal computer. Copies of it were placed on floppy disks. This report serves as a user's manual for the two sets of damage detection software. Sections 2.0 and 3.0 discuss the use of the MTFM and MSEDM software, respectively.

Source record↗

Efficient development and processing of thermal math models of very large space truss structures

As the spacecraft moves along the orbit, the truss members are subjected to direct and reflected solar, albedo and planetary infra-red (IR) heating rates, as well as IR heating and shadowing from other spacecraft components. This is a transient process with continuously changing heating loads and the shadowing effects. The resulting nonuniform temperature distribution may cause nonuniform thermal expansion, deflection and stress in the truss elements, truss warping and thermal distortions. There are three challenges in the thermal-structural analysis of the large truss structures. The first is the development of the thermal and structural math models, the second - model processing, and the third - the data transfer between the models. All three tasks require considerable time and computer resources to be done because of a very large number of components involved. To address these challenges a series of techniques of automated thermal math modeling and efficient processing of very large space truss structures were developed. In the process the finite element and finite difference methods are interfaced. A very substantial reduction of the quantity of computations was achieved while assuring a desired accuracy of the results. The techniques are illustrated on the thermal analysis of a segment of the Space Station main truss.

Warren, Andrew H.↗

Estimating Forest Vertical Structure from Multialtitude, Fixed-Baseline Radar Interferometric and Polarimetric Data

Parameters describing the vertical structure of forests, for example tree height, height-to-base-of-live-crown, underlying topography, and leaf area density, bear on land-surface, biogeochemical, and climate modeling efforts. Single, fixed-baseline interferometric synthetic aperture radar (INSAR) normalized cross-correlations constitute two observations from which to estimate forest vertical structure parameters: Cross-correlation amplitude and phase. Multialtitude INSAR observations increase the effective number of baselines potentially enabling the estimation of a larger set of vertical-structure parameters. Polarimetry and polarimetric interferometry can further extend the observation set. This paper describes the first acquisition of multialtitude INSAR for the purpose of estimating the parameters describing a vegetated land surface. These data were collected over ponderosa pine in central Oregon near longitude and latitude -121 37 25 and 44 29 56. The JPL interferometric TOPSAR system was flown at the standard 8-km altitude, and also at 4-km and 2-km altitudes, in a race track. A reference line including the above coordinates was maintained at 35 deg for both the north-east heading and the return southwest heading, at all altitudes. In addition to the three altitudes for interferometry, one line was flown with full zero-baseline polarimetry at the 8-km altitude. A preliminary analysis of part of the data collected suggests that they are consistent with one of two physical models describing the vegetation: 1) a single-layer, randomly oriented forest volume with a very strong ground return or 2) a multilayered randomly oriented volume; a homogeneous, single-layer model with no ground return cannot account for the multialtitude correlation amplitudes. Below the inconsistency of the data with a single-layer model is followed by analysis scenarios which include either the ground or a layered structure. The ground returns suggested by this preliminary analysis seem too strong to be plausible, but parameters describing a two-layer compare reasonably well to a field-measured probability distribution of tree heights in the area.

Treuhaft, Robert N.↗