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This page contains the data for the publication "Vanadium-Induced Lattice Compression and Electronic Modulation in Iridium-Ruthenium Electrocatalysts Boost Acidic Oxygen Evolution Reaction", 2026.
U 3 Si 2 is a candidate accident tolerant fuel (ATF) replacement for UO 2 . U 3 Si 2 ’s high uranium density and high thermal conductivity are favorable properties in steady-state and accident conditions. Low power performance of this U3Si2-SiC concept fuel is compared to that of UO 2 -Zr4 fuels by implementing models that describe the properties of U 3 Si 2 and SiC-SiC into Idaho National Laboratory's (INL) fuel performance code, BISON. Included in these material models is a thermal creep model for U 3 Si 2 based on compressive creep data. The simulated results are in keeping with community knowledge that the U 3 Si 2 -SiC concept fuel may serve as a replacement for UO 2 -Zr4 fuels during steady-state operation, provided the mSiC layer remains under compression. Through a moderate power history and three 24-month fuel cycles, the mSiC layer remains under compressive stress through a burnup of 80 MWd/kgU. During low power operation, failure of the mSiC layer generally occurs prior to significant thermal creep in U 3 Si 2 . Generally, U 3 Si 2 creep is temperature sensitive and of little importance at the temperatures and stresses simulated during steady operation and during fuel-to-cladding contact. A parameter variation study including 11,520 individual simulations with variations in nominal fuel thermal creep rate, cladding thermal conductivity, cladding irradiation creep and swelling, cladding gap size, and cladding thickness demonstrated that research priorities for this ATF should revolve around reducing cladding thickness as a means to minimize cladding failure. Generally, despite advances in SiC-SiC compliance, the brittle nature of mSiC excludes U 3 Si 2 -SiC for use where fuel cladding contact may occur.
STUDY DESIGN: Axial load-dependent changes in the lumbar spine of supine healthy volunteers were examined using a compression device compatible with magnetic resonance imaging. OBJECTIVE: To test two hypotheses: Axial loading of 50% body weight from shoulder to feet in supine posture 1) simulates the upright lumbar spine alignment and 2) decreases disc height significantly. SUMMARY OF BACKGROUND DATA: Axial compression on the lumbar spine has significantly narrowed the lumbar dural sac in patients with sciatica, neurogenic claudication or both. METHODS: Using a device compatible with magnetic resonance imaging, the lumbar spine of eight young volunteers, ages 22 to 36 years, was axially compressed with a force equivalent to 50% of body weight, approximating the normal load on the lumbar spine in upright posture. Sagittal lumbar magnetic resonance imaging was performed to measure intervertebral angle and disc height before and during compression. RESULTS: Each intervertebral angle before and during compression was as follows: T12-L1 (-0.8 degrees +/- 2.5 degrees and -1.5 degrees +/- 2.6 degrees ), L1-L2 (0.7 degrees +/- 1.4 degrees and 3.3 degrees +/- 2.9 degrees ), L2-L3 (4.7 degrees +/- 3.5 degrees and 7.3 degrees +/- 6 degrees ), L3-L4 (7.9 degrees +/- 2.4 degrees and 11.1 degrees +/- 4.6 degrees ), L4-L5 (14.3 degrees +/- 3.3 degrees and 14.9 degrees +/- 1.7 degrees ), L5-S1 (25.8 degrees +/- 5.2 degrees and 20.8 degrees +/- 6 degrees ), and L1-S1 (53.4 degrees +/- 11.9 degrees and 57.3 degrees +/- 16.7 degrees ). Negative values reflect kyphosis, and positive values reflect lordosis. A significant difference between values before and during compression was obtained at L3-L4 and L5-S1. There was a significant decrease in disc height only at L4-L5 during compression. CONCLUSIONS: The axial force of 50% body weight in supine posture simulates the upright lumbar spine morphologically. No change in intervertebral angle occurred at L4-L5. However, disc height at L4-L5 decreased significantly during compression.
Innovations in the identification or classification of features in a data set are described, such as a data set representing measurements taken by a scientific instrument. For example, a task-specific processing component, such as a video encoder, is used to generate task-specific metadata. When the data set includes video frames, metadata can include information regarding motion of image elements between frames, or other differences between frames. A feature of the data set, such as an event, can be identified or classified based on the metadata. For example, an event can be identified when metadata for one or more elements of the data set exceed one or more threshold values. When the feature is identified or classified, an output, such as a display or notification, can be generated. Although the metadata may be useable to generate a task-specific output, such as compressed video data, the identifying or classifying is not used solely in production of, or the creation of an association with, the task-specific output.
A low-complexity, adaptive predictive technique for lossless compression of hyperspectral data is presented. The technique relies on the sign algorithm from the repertoire of adaptive filtering. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity.
The concept we describe is an integrated instrument (a Pluto Integrated Camera-Spectrometer -- PICS) that will perform the functions of all three optical instruments required by the Pluto Fast Flyby Mission: the near-IR spectrometer, the camera, and the UV spectrometer. This integrated approach minimizes mass and power use. It also forced us early in the conceptual design to consider integrated observational sequences and integrated power management, thus ensuring compatible duty cycles (i.e., exposure times, readout rates) to meet the composite requirements for data collection, compression, and storage. Based on flight mission experience we believe that this integrated approach will result in substantial cost savings, both in reworking instrument designs during accommodation, as well as in sequence planning and integration. Finally, this integrated payload automatically yields a cohesive mission data set, optimized for correlative analysis. The presentation will provide details of the PICS instrument design and describe the fabrication and testing of the integrated SiC structure and optics at SSG Inc. Final integration and test plans for the prototype will also be described.
The goal of this study is to model the lifetime of different types of seal materials based on results obtained from accelerated experiments. A semi-mechanistic approach was taken. Thermal aging data were taken from the literature whereas experiments were conducted at Auburn under this contract for selected environments. The seal materials of interest are Silicone 383, Silicone 650, Viton 835, and Viton 747. The relevant conditions include thermal, oxygen, inert gas, vacuum, and gamma radiation. Compression set data available from NASA were used to examine the thermal effect. Experiments were conducted at Auburn University and at NASA to isolate the role of thermal, oxygen, inert gas, vacuum, gamma irradiation, and proton irradiation. A simple discrete stress relaxation method was developed to determine the relaxation response of the elastomers. Dynamic mechanical thermal analysis was also used to characterize the mechanical response of the specimens. These provide a more meaningful correlation between mechanisms and degradation.
In this work, we provide a compressive sensing architecture for implementing on a space based observatory for detecting transient photometric parallax caused by gravitational microlensing events. Compressive sensing (CS) is a simultaneous data acquisition and compression technique, which can greatly reduce on-board resources required for space flight data storage and ground transmission. We simulate microlensing parallax observations using a space observatory constellation, based on CS detectors. Our results show that average CS error is less than 0.5% using 25% Nyquist rate samples. The error at peak magnification time is significantly lower than the error for distinguishing any two microlensing parallax curves at their peak magnification. Thus, CS is an enabling technology for detecting microlensing parallax, without causing any loss in detection accuracy.
Variations in the levels of muscle hemoglobin and of myoglobin oxygen saturation can be detected non-invasively with near-infrared spectroscopy. This technique could be applied to the diagnosis of chronic compartment syndrome, in which invasive testing has shown increased intramuscular pressure associated with ischemia and pain during exercise. We simulated chronic compartment syndrome in ten healthy subjects (seven men and three women) by applying external compression, through a wide inflatable cuff, to increase the intramuscular pressure in the anterior compartment of the leg. The tissue oxygenation of the tibialis anterior muscle was measured with near-infrared spectroscopy during gradual inflation of the cuff to a pressure of forty millimeters of mercury (5.33 kilopascals) during fourteen minutes of cyclic isokinetic dorsiflexion and plantar flexion of the ankle. The subjects exercised with and without external compression. The data on tissue oxygenation for each subject then were normalized to a scale of 100 per cent (the baseline value, or the value at rest) to 0 per cent (the physiological minimum, or the level of oxygenation achieved by exercise to exhaustion during arterial occlusion of the lower extremity). With external compression, tissue oxygenation declined at a rate of 1.4 +/- 0.3 per cent per minute (mean and standard error) during exercise. After an initial decrease at the onset, tissue oxygenation did not decline during exercise without compression. The recovery of tissue oxygenation after exercise was twice as slow with compression (2.5 +/- 0.6 minutes) than it was without the use of compression (1.3 +/- 0.2 minutes).
The Galileo Near-Infrared Mapping Spectrometer (NIMS) is a sophisticated multi-spectral instrument that was developed to study the spatial/compositional aspects of the atmosphere of Jupiter and the surfaces of it's satellites. Since its original development, the communication capability of the Galileo spacecraft has been severly reduced as the result of a failure of ground controllers to open the main antenna. The data rate which will be available for all instruments at the first Jupiter encounter in 1995 has been reduced by several orders of magnitude (even after recent numerous improvements to data link efficiency.).
This mosaic of visible to shortwave infrared (VSWIR) data was derived from the assignable asset NEON AOP radiance data that was collected by LBNL’s Watershed Function SFA during the summer of 2018 (DOI: 10.15485/1617204). This atmospheric correction was completed to take into account site-specific terrain variability in the 334 km2 survey area centered around Crested Butte, CO. The atmospheric correction was completed using ACORN atmospheric correction software executed on 200 x 200 pixel kernels rather than line by line in order to capture local flight altitude conditions. Manual cloud delineation removed any small shaded areas that occurred within the data collection areas. Mosaics were developed based on preference for days that were in close timing proximity to the coincident ground campaign and with mosaicing criteria that minimized the angle between the sun and the sensor to retrieve the most consistent reflectance (min_phase_refl_tiled). Finally, we generated shade masks based on the geometry between the sun angle at time of flight, the ground surface, and the sensor. Here we provide the orthomosaiced estimated reflectance data (min_phase_refl_tiled.tif), canopy water content (wtrl), estimated atmospheric water vapor (wtrv), the observational data (obs) for this particular mosaic, the estimated visibility (vis), shade masks derived from the digital surface elevation model (shade) and the digital terrain model (shade_tch) added to the canopy height model (DOI: 10.15485/1617203), and a wavelength metadata file. Each image file is provided as a GeoTiff with internal tiling and LZW compression. These data can also be found on Google Earth Engine for extraction, download, and analysis of smaller extents (Google Earth Engine data is linked in external link table).
Compressive sensing is a novel mathematical technique for simultaneous data acquisition and compression. This technique is particularly apt for time-series photometric measurements. In this work we apply compressive sensing to time-series photometric measurements specifically obtained due to gravitational microlensing events. We show through simulation modelling the error sensitivity for detecting microlensing event parameters. Particularly, we show the relation of the amount of error and its impact on the microlensing parameters of interest. We derive statistical error bounds to apply those as a baseline for analyzing the effectiveness of compressive sensing application. Our results conclude that for single and binary microlensing events we can obtain error less than 1% over a 3-pixel radius of the center of the microlensing star by using 25% Nyquist rate measurements.
Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated over timesteps to accommodate storage and I/O limitations. In this paper, we propose a technique that addresses storage costs while improving post-analysis accuracy through spatiotemporal adaptive, error-controlled lossy compression. We investigate the trade-off between data precision and temporal output rates, revealing that reducing data precision and increasing timestep frequency lead to more accurate analysis outcomes. Additionally, we integrate spatiotemporal feature detection with data compression and demonstrate that performing adaptive error-bounded compression in higher dimensional space enables greater compression ratios, leveraging the error propagation theory of a transformation-based compressor. To evaluate our approach, we conduct experiments using the well-known E3SM climate simulation code and apply our method to compress variables used for cyclone tracking. Our results show a significant reduction in storage size while enhancing the quality of cyclone tracking analysis, both quantitatively and qualitatively, in comparison to the prevalent timestep decimation approach. Compared to three state-of-the-art lossy compressors lacking feature preservation capabilities, our adaptive compression framework improves perfectly matched cases in TC tracking by 26.4-51.3% at medium compression ratios and by 77.3-571.1% at large compression ratios, with a merely 5–11% computational overhead.
Research related to the International Satellite Cloud Climatology Project (ISCCP) began with a pilot study initiated in late 1981 to evaluate currently available cloud analysis algorithms. Other objectives of this study are related to a test of the effects of data volume compression schemes and the design of the operational algorithms for ISCCP. The present paper summarizes the pilot study by focusing on the most fundamental step of any cloud algorithm, that of cloud detection. An outline is provided of the objectives and limitations of the pilot study, and a description is given of the criteria used to design the operational analysis algorithm. Attention is given to the pilot study data set, a cloud detection intercomparison, a cloud analysis, and ISCCP cloud algorithm design.
Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.
Abstract Motivated by measurements of compressibility and STM spectra in twisted bilayer graphene, we analyze the pattern of symmetry breaking for itinerant fermions near a van Hove singularity. Making use of an approximate SU(4) symmetry of the Landau functional, we show that the structure of the spin/isospin order parameter changes with increasing filling via a cascade of transitions. We compute the feedback from different spin/isospin orders on fermions and argue that each order splits the initially 4-fold degenerate van Hove peak in a particular fashion, consistent with the STM data and compressibility measurements, providing a unified interpretation of the cascade of transitions in twisted bilayer graphene. Our results follow from a generic analysis of an SU(4)-symmetric Landau functional and are valid beyond a specific underlying fermionic model. We argue that an analogous van Hove scenario explains the cascade of phase transitions in non-twisted Bernal bilayer and rhombohedral trilayer graphene.
Lie group methods are used to find both exact and numerical similarity solutions for compressible perturbations to all incompressible, two-dimensional, axisymmetric vortex reference flow. The reference flow vorticity satisfies an eigenvalue problem for which the solutions are a set of two-dimensional, self-similar, incompressible vortices. These solutions are augmented by deriving a conserved quantity for each eigenvalue, and identifying a Lie group which leaves the reference flow equations invariant. The partial differential equations governing the compressible perturbations to these reference flows are also invariant under the action of the same group. The similarity variables found with this group are used to determine the decay rates of the velocities and thermodynamic variables in the self-similar flows, and to reduce the governing partial differential equations to a set of ordinary differential equations. The ODE's are solved analytically and numerically for a Taylor vortex reference flow, and numerically for an Oseen vortex reference flow. The solutions are used to examine the dependencies of the temperature, density, entropy, dissipation and radial velocity on the Prandtl number. Also, experimental data on compressible free vortex flow are compared to the analytical results, the evolution of vortices from initial states which are not self-similar is discussed, and the energy transfer in a slightly-compressible vortex is considered.
The Galileo mission operations concept is undergoing substantial redesign, necessitated by the deployment failure of the High Gain Antenna, while the spacecraft is on its way to Jupiter. The new design applies state-of-the-art technology and processes to increase the telemetry rate available through the Low Gain Antenna and to increase the information density of the telemetry. This paper describes the mission planning process being developed as part of this redesign. Principal topics include a brief description of the new mission concept and anticipated science return (these have been covered more extensively in earlier papers), identification of key drivers on the mission planning process, a description of the process and its implementation schedule, a discussion of the application of automated mission planning tool to the process, and a status report on mission planning work to date. Galileo enhancements include extensive reprogramming of on-board computers and substantial hard ware and software upgrades for the Deep Space Network (DSN). The principal mode of operation will be onboard recording of science data followed by extended playback periods. A variety of techniques will be used to compress and edit the data both before recording and during playback. A highly-compressed real-time science data stream will also be important. The telemetry rate will be increased using advanced coding techniques and advanced receivers. Galileo mission planning for orbital operations now involves partitioning of several scarce resources. Particularly difficult are division of the telemetry among the many users (eleven instruments, radio science, engineering monitoring, and navigation) and allocation of space on the tape recorder at each of the ten satellite encounters. The planning process is complicated by uncertainty in forecast performance of the DSN modifications and the non-deterministic nature of the new data compression schemes. Key mission planning steps include quantifying resource or capabilities to be allocated, prioritizing science observations and estimating resource needs for each, working inter-and intra-orbit trades of these resources among the Project elements, and planning real-time science activity. The first major mission planning activity, a high level, orbit-by-orbit allocation of resources among science objectives, has already been completed; and results are illustrated in the paper. To make efficient use of limited resources, Galileo mission planning will rely on automated mission planning tools capable of dealing with interactions among time-varying downlink capability, real-time science and engineering data transmission, and playback of recorded data. A new generic mission planning tool is being adapted for this purpose.