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At least 523 records · Page 29

Correlation of an optical system degradation with contamination on a critical surface

The loss of sensitivity of a radiantly cooled radiometer during space operation was investigated. A quartz crystal microbalance (QCM), mounted in the proximity of the instrument filter lens and held at its temperature, measured the contaminant at the location during a vacuum test. The temperature cycling of the lens and the QCM verified the contamination of the lens as the cause of the deterioration. Data on the instrument performance in space and in the chamber allowed estimation of the rate of contaminant accretion on the lens in space service. That rate was used to estimate the contaminant partial pressure. The nature of material was inferred by comparison of the partial pressures and the saturated vapor pressures of materials at the temperature of the contaminated surface. These data, in conjunction with data on fields of view of the lens, are used to identify the sources of contamination.

Scialdone, J. J.↗

Growth and characterization of high-performance photorefractive BaTiO3 crystals

Barium titanate has been used for many nonlinear optical applications primarily because it has high grain and high self-pumped phase conjugate reflectivities. However, barium titanate has had a relatively slow response time, and thus low sensitivity. Therefore, it has not been suited to real-time operations. In this report we will describe the modifications in crystal growth, doping, reduction, and poling that have produced barium titanate crystals with the fastest photorefractive response time reported to date, approximately 21 microseconds with a beam-coupling gain coefficient of 38.7 cm(exp -1) and the highest sensitivity reported to date of 3.44 cm(exp 3)/kJ. The sensitivity of these barium titanate crystals is comparable to or greater than other photorefractive oxides. We will show, for the first time, beam-coupling in barium titanate at video frame rates. We infer from response time measurements that barium titanate has a phonon limited mobility. Also, photorefractive response time measurements as a function of the crystallographic orientation and grating wave vector for our cobalt-doped oxygen reduced crystals indicate that their faster response time arise because of an increase in the free carrier lifetime.

Warde, C.↗

Volatile Analyzer for Lunar Polar Missions

One of the major questions remaining for the future exploration of the Moon by humans concerns the presence of volatiles on our nearest neighbor in space. Observational studies, and investigations involving returned lunar samples and using robotic spacecraft infer the existence of volatile compounds particularly water [1]. It seems very likely that a volatile component will be concentrated at the poles in circumstances where low-temperatures exist to provide cryogenic traps. However, the full inventory of species, their concentration and their origin and sources are unknown. Of particular importance is whether abundances are sufficient to act as a resource of consumables for future lunar expeditions especially if a long-term base involving humans is to be established. To address some of these issues requires a lander designed specifically for operation at a high-lunar latitude. A vital part of the payload needs to be a volatile analyzer such as the Gas Analysis Package specifically designed for identification quantification of volatile substances and collecting information which will allow the origin of these volatiles to be identified [1]. The equipment included, particularly the gas analyzer, must be capable of operation in the extreme environmental conditions to be encountered. No accurate information yet exists regarding volatile concentration even for sites closer to the lunar equator (because of contamination). In this respect it will be important to understand (and thus limit) contamination of the lunar surface by extraneous material contributed from a variety of sources. The only data for the concentrations of volatiles at the poles comes from orbiting spacecraft and whilst the levels at high latitudes may be greater than at the equator, the volatile analyzer package under consideration will be designed to operate at the highest specifications possible and in a way that does not compromise the data.

Gibons, Everett K.↗

BMINN: Learning chemical potentials and parameters from voltage data for multi-phase battery modeling

Free-energy landscapes and chemical potentials govern the dynamics of phase transitions, transport, and stability in functional materials, yet they remain experimentally inaccessible under realistic operating conditions. Here we introduce a Bayesian model-integrated neural network (BMINN) that embeds physics-based formulations of non-autonomous partial differential-algebraic equations into probabilistic learning. This approach reconstructs hidden thermodynamics directly from macroscopic current-voltage data, providing quantitative access to metastable states, staging transitions, and energy barriers without synchrotron probes. Demonstrated on lithium-graphite electrodes, BMINN recovers full Gibbs free-energy landscapes with fidelity validated against operando X-ray diffraction. The framework generalizes across dynamical regimes, enabling accurate voltage prediction, internal state estimation, and inference of governing parameters. Beyond batteries, BMINN exemplifies a broadly applicable strategy for learning missing physics in multiphase, non-equilibrium systems, offering a new pathway to uncover hidden thermodynamic functions across condensed matter and materials physics.

25 ENERGY STORAGE↗

Oxygen and Magnesium Isotopic Compositions of Asteroidal Materials Returned from Itokawa by the Hayabusa Mission

The Hayabusa spacecraft made two touchdowns on the surface of Asteroid 25143 Itokawa on November 20th and 26th, 2005. The Asteroid 25143 Itokawa is classified as an S-type asteroid and inferred to consist of materials similar to ordinary chondrites or primitive achondrites [1]. Near-infrared spectroscopy by the Hayabusa spacecraft proposed that the surface of this body has an olivine-rich mineral assemblage potentially similar to that of LL5 or LL6 chondrites with different degrees of space weathering [2]. The spacecraft made the reentry into the Earth s atmosphere on June 12th, 2010 and the sample capsule was successfully recovered in Australia on June 13th, 2010. Although the sample collection processes on the Itokawa surface had not been made by the designed operations, more than 1,500 grains were identified as rocky particles in the sample curation facility of JAXA, and most of them were judged to be of extraterrestrial origin, and definitely from Asteroid Itokawa on November 17th, 2010 [3]. Although their sizes are mostly less than 10 microns, some larger grains of about 100 microns or larger were also included. The mineral assembly is olivine, pyroxene, plagioclase, iron sulfide and iron metal. The mean mineral compositions are consistent with the results of near-infrared spectroscopy from Hayabusa spacecraft [2], but the variations suggest that the petrologic type may be smaller than the spectroscopic results. Several tens of grains of relatively large sizes among the 1,500 grains will be selected by the Hayabusa sample curation team for preliminary examination [4]. Each grain will be subjected to one set of preliminary examinations, i.e., micro-tomography, XRD, XRF, TEM, SEM, EPMA and SIMS in this sequence. The preliminary examination will start from the last week of January 2011. Therefore, samples for isotope analyses in this study will start from the last week of February 2011. By the time of the LPSC meeting we will have measured the oxygen and magnesium isotopic composition of several grains. We will present the first results from the isotope analyses that will have been performed.

Yurimoto, H↗

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗

Overview of Results from the Cassini Magnetospheric Imaging Instrument (MIMI) During the First Year of Operations

The MIMI investigation comprises three sensors covering the indicated energy ranges: the Ion and Neutral Camera (INCA) -- 7 keV/nuc 3 Mev) and protons (1.6 < E < 160 Mev) from the back end of the dual field-of-view telescope. The Saturn observation sequences began in January, 2004 and culminated in Saturn Orbit Insertion on July 1, 2004. The MIMI sensors observed substantial activity in interplanetary space for several months prior to SOI, including several interplanetary shocks associated with corotating interaction regions, numerous increases most likely originating from particle streams in the vicinity of the Saturnian bow shock and energetic neutral atoms (ENA) emanating from Saturn s magnetosphere. Results following SOI revealed: a dynamical magnetosphere with a day-night asymmetry and an 11-hour periodicity; several water-product ions (O+, OH+, H2O+), but little N+; inferred quantities of neutral gas sufficient to cause major losses in the trapped ions and electrons in the middle and inner magnetosphere; a Titan exosphere that is a copious source of ENA; INCA imaging through ENA has also revealed a previously unknown radiation belt residing inward of the D-ring that is most likely the result of double charge-exchange between the main radiation belt and the upper layers of Saturn s exosphere. Finally, there is ample evidence for the presence of substorm-like injections of plasma that subsequently corotates for a number of days before dissipating on the night-side magnetotail. The observations will be presented and discussed in the context of current theoretical models.

Krimigis, S. M.↗

Conformal Hierarchical Simulation-Based Inference with Local Validity

Trustworthy and interpretable uncertainty quantification is a long-standing challenge in artificial intelligence. Simulation-based inference (SBI) comprises a broad swath of approaches for estimating latent parameters with uncertainties. Although flexible neural density estimators in SBI can be remark- ably expressive capturing highly structured, high-dimensional posteriors their credible regions can be badly mis-calibrated and are often only accompanied by heuristic coverage checks. We present the first SBI framework that delivers finite-sample local valid coverage guarantees that hold in the neighborhood of each observation. Our framework can couple any off-the-shelf hierarchical SBI engine with a confor- mal Bayesian post-processing step that operates on the posterior predictive density. A kernel-weighted conformity score adapts the conformal quantile to the local geometry of the data, yielding prediction sets that are simultaneously (i) marginally calibrated, (ii) locally valid, and (iii) hierarchical, handling global and observation-specific parameters in a single pass. Through experiments on synthetic data and benchmarks from neuroscience and physics, we show that our approach attains 1 − α coverage, where prior SBI methods under- or over-cover. Our approach also maintains a competitive, credible set size with minimal computational overhead. Finally, our approach can be used to make predictions on real data and give valid credible regions modulo weight-initialization-based model mis-specification.

Trivedi, Shubhendu [Fermilab]↗

MIND-MAC: Multi-Level In-memory Quasi Non-Destructive MAC Operation in Compact 2T-nC FeRAM for Efficient DNN Accelerator

We present MIND-MAC, a compact 2T-nC FeRAM architecture that performs multi-level, quasi-non-destructive in-memory multiply–accumulate (MAC) for deep neural networks. By exploiting voltage-controlled partial domain switching in MFM capacitors and read-transistor amplification, the cell stores multi-bit weights and gates bit-serial inputs to produce an accumulated current on shared lines. We combine TCAD-extracted parasitics with experimentally calibrated ferroelectric models in SPICE to validate device-/circuit-level behavior, and validate multi-level sensing and QNRO with measurements on a fabricated 2T-3C test vehicle. An analytical system model maps MIND-MAC to a 6-GB main-memory in-memory compute (IMC) architecture and benchmarks VGG13 inference in 61.08 ms at 964.99 mJ. Results indicate high density, reduced rewrite overhead, and energy efficiency, positioning 2T-nC FeRAM as a promising IMC candidate for next-generation AI hardware.

36 MATERIALS SCIENCE↗

Forward variable selection enables fast and accurate dynamic system identification with Karhunen-Loève decomposed Gaussian processes

A promising approach for scalable Gaussian processes (GPs) is the Karhunen-Loève (KL) decomposition, in which the GP kernel is represented by a set of basis functions which are the eigenfunctions of the kernel operator. Such decomposed kernels have the potential to be very fast, and do not depend on the selection of a reduced set of inducing points. However KL decompositions lead to high dimensionality, and variable selection thus becomes paramount. This paper reports a new method of forward variable selection, enabled by the ordered nature of the basis functions in the KL expansion of the Bayesian Smoothing Spline ANOVA kernel (BSS-ANOVA), coupled with fast Gibbs sampling in a fully Bayesian approach. It quickly and effectively limits the number of terms, yielding a method with competitive accuracies, training and inference times for tabular datasets of low feature set dimensionality. Theoretical computational complexities are O ( N P 2 ) in training and O ( P ) per point in inference, where N is the number of instances and P the number of expansion terms. The inference speed and accuracy makes the method especially useful for dynamic systems identification, by modeling the dynamics in the tangent space as a static problem, then integrating the learned dynamics using a high-order scheme. The methods are demonstrated on two dynamic datasets: a ‘Susceptible, Infected, Recovered’ (SIR) toy problem, along with the experimental ‘Cascaded Tanks’ benchmark dataset. Comparisons on the static prediction of time derivatives are made with a random forest (RF), a residual neural network (ResNet), and the Orthogonal Additive Kernel (OAK) inducing points scalable GP, while for the timeseries prediction comparisons are made with LSTM and GRU recurrent neural networks (RNNs) along with the SINDy package.

Hayes, Kyle↗

Flow characteristics in an expansion tunnel as inferred from velocity measurements

A photoionization technique was used to study flow characteristics in an expansion tunnel. Vertical surveys of the axial component of flow velocity just downstream from the nozzle exit were obtained, and estimates of freestream density were inferred from the velocity measurement technique. The pitot pressure was measured and compared to the average axial component of velocity as a function of time for the two cases when air and CO2 were used as test gases. Vertical velocity and static density profiles at the nozzle exit are presented for the case when CO2 was used as test gas. Experimental results were used to determine the diameter and uniformity of the test core at the nozzle exit and the duration of the quasi-steady flow period. These data are relevant to evaluation of the suitability of operating an expansion tube as an expansion tunnel. The expansion tunnel is an expansion tube with a conical nozzle positioned at the exit of the acceleration section, so that nozzle entrance flow conditions are hypersonic and characterized by hypervelocity.

Miller, C. G.↗

Apatites in Gale Crater

ChemCam is an active remote sensing instrument suite that has operated successfully on MSL since landing Aug. 6th, 2012. It uses laser pulses to remove dust and to analyze rocks up to 7 m away. Laser-induced breakdown spectroscopy (LIBS) obtains emission spectra of materials ablated from the samples in electronically excited states. The intensities of the emission lines scale with the abundances of the related element. ChemCam is sensitive to most major rock-forming elements as well as to a set of minor and trace elements such as F, Cl, Li, P, Sr, Ba, and Rb. The measured chemical composition can then be used to infer the mineralogical composition of the ablated material. Here, we report a summary of inferred apatite detections along the MSL traverse at Gale Crater. We present the geologic settings of these findings and derive some interpretations about the formation conditions of apatite in time and space.

Forni, O.↗

Chemical environments of submarine hydrothermal systems

Perhaps because black-smoker chimneys make tremendous subjects for magazine covers, the proposal that submarine hydrothermal systems were involved in the origin of life has caused many investigators to focus on the eye-catching hydrothermal vents. In much the same way that tourists rush to watch the spectacular eruptions of Old Faithful geyser with little regard for the hydrology of the Yellowstone basin, attention is focused on the spectacular, high-temperature hydrothermal vents to the near exclusion of the enormous underlying hydrothermal systems. Nevertheless, the magnitude and complexity of geologic structures, heat flow, and hydrologic parameters which characterize the geyser basins at Yellowstone also characterize submarine hydrothermal systems. However, in the submarine systems the scale can be considerably more vast. Like Old Faithful, submarine hydrothermal vents have a spectacular quality, but they are only one fascinating aspect of enormous geologic systems operating at seafloor spreading centers throughout all of the ocean basins. A critical study of the possible role of hydrothermal processes in the origin of life should include the full spectrum of probable environments. The goals of this chapter are to synthesize diverse information about the inorganic geochemistry of submarine hydrothermal systems, assemble a description of the fundamental physical and chemical attributes of these systems, and consider the implications of high-temperature, fluid-driven processes for organic synthesis. Information about submarine hydrothermal systems comes from many directions. Measurements made directly on venting fluids provide useful, but remarkably limited, clues about processes operating at depth. The oceanic crust has been drilled to approximately 2.0 km depth providing many other pieces of information, but drilling technology has not allowed the bore holes and core samples to reach the maximum depths to which aqueous fluids circulate in oceanic crust. Such determinations rely on studies of pieces of deep oceanic crust uplifted by tectonic forces such as along the Southwest Indian Ridge, or more complete sections of oceanic crust called ophiolite sequences which are presently exposed on continents owing to tectonic emplacement. Much of what is thought to happen in submarine hydrothermal systems is inferred from studies of ophiolite sequences, and especially from the better-exposed ophiolites in Oman, Cyprus and North America. The focus of much that follows is on a few general features: pressure, temperature, oxidation states, fluid composition and mineral alteration, because these features will control whether organic synthesis can occur in hydrothermal systems.

Shock, Everett L.↗

Emergent tetragonality in a fundamentally orthorhombic material

Symmetry plays a key role in determining the physical properties of materials. By Neumann’s principle, the properties of a material remain invariant under the symmetry operations of the space group to which the material belongs. Continuous phase transitions are associated with a spontaneous reduction in symmetry. Less common are examples where proximity to a continuous phase transition leads to an increase in symmetry. We find signatures of an emergent tetragonal symmetry close to a charge density wave (CDW) bicritical point in a fundamentally orthorhombic material, ErTe 3 , for which the two distinct CDW phase transitions are tuned via anisotropic strain. We first establish that tension along the a axis favors an abrupt rotation of the CDW wave vector from the c to a axis and infer the presence of a bicritical point where the two continuous phase transitions meet. We then observe a divergence of the nematic elastoresistivity approaching this putative bicritical point, indicating an emergent tetragonality in the critical behavior.

36 MATERIALS SCIENCE↗

Synergistic use of optical and microwave data in agrometeorological applications

Remotely sensed optical and microwave data can be synergistically used to infer land surface properties. Optical data can be used to estimate surface albedo, radiation absorption by vegetation canopies and their photosynthetic efficiencies. Vegetation canopy reflectance at red and near-infrared wavelengths can be used to correct for vegetation effect on microwave emissivities at low frequencies for estimating soil moisture. Optical data can also provide information about surface and air temperatures, precipitable water vapor, cloud top temperature and its water content. This information can be utilized to correct microwave data for atmospheric effects. These points are illustrated with theoretical analyses and by application to satellite data. The basic physical mechanisms operative at the various wavelengths are also discussed.

Myneni, R. B.↗

Plasma jet effects on the ionospheric plasma

Heavy ion beams were injected into the ionospheric plasma (experiments ARCS 1 and ARCS 2). In ARCS 1, operation of a 25eV argon ion source, mounted on a plasma diagnostic payload, produced an accelerated electron population; broadband electric field turbulence; large, spin synchronized electric field perturbations; and depletions of thermal ions. In ARCS 2, the ion source was deployed upward along the local magnetic field direction away from the diagnostic payload, and observed effects are contained within several meters of the ion source. However, enhanced wave levels near the LHR frequency are observed at distances up to 1 km, as are the injected ions themselves. A measurement of the dominant wavelength of the enhanced waves is consistent with an inference based upon the accelerated electron population seen in ARCS 1. This electron population is not evident during ARCS 2.

Moore, T. E.↗

Introduction to MODIS Cloud Products

The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (MODIS) imagers on the Terra and Aqua Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar reflectance and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), MODIS provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core MODIS operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the MODIS atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies derived from heritage instruments. This chapter provides an overview of the MODIS Level-2 and -3 operational cloud products.

Baum, Bryan A.↗

The Onset of Nucleate Boiling Prediction in a Mini Channel with the Eulerian Multiphase Flow

The prediction of boiling incipience is a critical issue for a reactor. Vapor lock causes operating instability and undesirable temperature rise, especially for small channels. This study uses the Eulerian multiphase flow boiling model to predict the onset of nucleate boiling in a millimeter scale rectangular channel. Two wall boiling models, namely the RPI (Rensselaer Polytechnic Institute) and the non-equilibrium sub cooled model are applied. Computational fluid dynamics is employed for this study to investigate the impact of operating conditions like liquid flow rate, operating pressure, heat flux, velocity profile, turbulence model, and inlet liquid temperature. Here, the effect of fundamental boiling parameters on the surface wall temperature and vapor volume fraction is also studied. The parameters under consideration are the bubble departure diameter, bubble departure frequency, nucleate site density, quenching time period, and interface heat transfer coefficients. A series of CFD calculations is conducted by varying the considered variables systematically in a wide range of flow conditions covering laminar, transition, and turbulent flows. The sub-component heat fluxes like the liquid convective, the vapor convective, the evaporative, and the quenching terms are monitored to infer the boiling dynamics in the transition region from the single-phase flow to the nucleate boiling zone. It is found that the CFD approach to detecting the boiling incipience point agrees reasonably with available experimental data. However, its limitations, like inaccuracy for lower flow rates and early transition to boiling flow, are also noticed due to the nature of the considered RPI model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗