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At least 883 records · Page 49

The Enigmatic Longevity of Granular Materials on Mars: The Case for Geologically Episodic Dune Formation

Martian sand dunes are concentrated in vast sand seas in the circumpolar belt of the planet's northern hemisphere, but they are also pervasive over the whole planet. Their occurrence is to be expected on a super-arid planetary surface subjected to boundary layer drag from a continually active atmosphere. Whilst their occurrence is to be expected, their survival is enigmatic. But the enigma only arises if the martian system is considered similar to Earth's --where sand is moved highly frequently, more or less on a seasonal basis. Experimentally it is readily demonstrated that active sand will soon wear down to small grains and eventually diminish to below the critical sand size required to sustain dune formation. According to conventional wisdom, sand moves at higher speeds on Mars than on Earth, and if it were to move as frequently as it does on Earth, then the dune-forming sand population should have long since disappeared, given the great longevity of the martian aeolian system (Sagan coined the term "kamikaze" grains to express this disappearance). No supply of sand could keep pace with this depletion, especially in light of the fact that Mars does not have very active weathering, nor significant crustal differentiation. On Earth, plate tectonics, magmatic activity, and general crustal differentiation over geological time have produced great concentrations of quartz crystals in the continental crustal masses. Not only are these quartz grains chemically and mechanically resilient, they are about the right size for being transported by either wind or water. Add to this, the geologically recent contribution of glacial grinding, and it is easy to see why there are dune field on Earth. So what are the martian dunes composed of, and how does the material survive the eons of attrition? In addition to experimental demonstrations of sand comminution in laboratory aeolian simulations, the problem can be approached from first principles. Sagan showed that by simple considerations of material strength versus mechanical work applied to the material, comminution to sub-sand size would be inevitable. Another semi-analytical approach might be taken by considering that the archetypal aeolian sand surface texture is an irregularly pitted ("frosted") surface composed of chipping hollows approximately 10 microns in diameter, 5 microns deep. Their volume = about 250 cubic microns, or about 1/25000 of the volume of a 100 micron diameter dune grain. Because a saltating grain always strikes another grain, then two surfaces are impacted. Thus each grain undergoes two impacts for every one saltation leap, when the impact statistics are considered for a closed dune system (it can be calculated that a grain can never undergo <1 impact, and never >2 per saltation leap). Hence, if we conservatively assume that there is damage to a grain each time it bounces, but with the minimum damage of only 2 microscopic craters per impact, then approximately 12,500 impacts are required to completely eliminate the grain. Of course, it would require only a fraction of this amount to reduce the grain to below sand size. A grain will make only several tens of saltation leaps on the stoss side of a dune before becoming buried on the lee slope. The dune then has to move its full length before the grain is exhumed again for abrasion. Even with this hiatus in transport, it is easy to see that terrestrial dunes need resupplying with sand in order to survive. In recent theoretical work it has been shown that martian aeolian transport may be initiated with high-speed grains, but this converts to a lower energy dynamic transport equilibrium in which a reptation population dominates grain transport (on Earth, at least half of the flux is by reptation and creep). On Mars, therefore, average grain speeds may be lower than those on Earth, or at least comparable. This would permit greater longevity for martian sands, but it would not go far enough to solve the survival problem. It may, however, explain why martian dunes are about the same size as terrestrial dunes. If martian saltation leaps were significantly longer than on Earth (as usually assumed), then a dune's lee slope would have to be correspondingly longer in order to trap the sand; this would scale up the whole dune structure. But with shorter trajectories in a reptation population, larger dunes would be unnecessary. Additional information is contained in the original.

Marshall, J.↗

UrbanScaping: Community Spatial Data Visualization & Analytics

Evaluating the electrification potential of buildings through retrofitting is crucial for reducing carbon emissions and the carbon footprint of built environments. This study leverages the Automatic Building Energy Modeling (AutoBEM) software, integrating the Model America database to create an urban context-based spatial analysis platform for community engagement and development. We selected Camp Hill Borough, PA, as a case study to analyze building-specific energy performance and evaluate the electrification potential of each building by switching to different Heating, Ventilation, and Air Conditioning (HVAC) systems and measurement components. The simulation results generated by the workflow provide retrofitting suggestions to help mitigate the carbon footprint as well as energy saving statistics of buildings. Additionally, the developed web-based interface serves as a community engagement platform, allowing residents to provide feedback and further develop interactive communication protocols. The outcomes of this project offer a baseline for community electrification planning and contribute to the design of low-carbon communities.

Chowdhury, Shovan [ORNL]↗

Stochastic modeling and statistical calibration with model error and scarce data

This paper introduces a procedure to assess the predictive accuracy of stochastic models subject to model error and sparse data. Model error is introduced as uncertainty on the coefficients of appropriate polynomial chaos expansions (PCE). The error associated with finite sample size allows us to conceive of these coefficients as statistics of the data that we describe as random variables whose influence on output quantities of interest is evaluated through the extended polynomial chaos expansion (EPCE). A Bayesian data assimilation scheme is introduced to update these expansions by considering the resulting nested chaos expansion as a hierarchical probabilistic model. Stochastic models of quantities of interest (QoI) are thus constructed and efficiently evaluated. Here, the Metropolis–Hastings Markov chain Monte Carlo procedure is used to sample the posterior. Two illustrative analytical and numerical problems are used to demonstrate the proposed approach.

Bayesian inference↗

Constraints on the Nature and Distribution of Iridium Host Phases at the Cretaceous-Tertiary Boundary: Implications for Projectile Identity and dispersal on impact

Among Cretaceous-Tertiary boundary sites worldwide, variations in the concentrations and ratios of elements commonly enriched in meteorites complicate traditional geochemical attempts at impactor identification. Yet they may provide constraints on the physical and chemical processes associated with large-body disruption and dispersal, as well as with diagenesis of projectile components. To this end, we continue our efforts to identify the mineral host-phases of projectile-derived elements, particularly for Ir, and to document their partitioning between crater deposits and ejecta resulting from the Chicxulub basin-forming impact. Building on earlier work, we used INAA to measure Ir concentrations in successively smaller splits of finely powdered impact melt breccia from the Chicxulub Crater in Mexico (sample Y6Nl9-R(b)), and K/T boundary fish clay from Stevns Klint, Denmark (sample FC-1, split from 40 kg of homogenized material intended as an analytical standard). Results for the Chicxulub sample show a heterogeneous Ir distribution and document that at least five discrete Ir-bearing host phases were isolated in subsequent splits, having Ir masses equivalent to pure Ir spheres from about 0.8 to about 3.5 mm in diameter. Three of these are within a sufficiently reduced mass of powder to warrant searching for them using backscattered electron microscopy. In contrast, successively smaller splits of the Stevns Klint fish clay show no statistically significant deviation from the reported value of 32 +/- 2 ng/g Ir, suggesting a uniform Ir host-phase distribution. For the smallest split obtained thus far (100 +/- 40 ng/g Ir), a pure Ir sphere of equivalent Ir mass would be <0.05 min in diameter. (n.b. Although homogenizing and sieving of FC-1 to <75 min obviously obscured variations in stratigraphic distribution, it is unlikely to have affected the size-frequency distribution of Ir host phases.) We previously identified micrometer-scale Ir host phases by electron microscopy in melt-rock samples from two widely separated drill holes at the Chicxulub Basin, including a replicate split of Y6-NI9-R. One is an aggregate of subhedral Ir metal grains enclosed in silicate, in which no other Pt group elements (PGE) were detected. A second particle with twice the mass as the first, concentrated predominantly in a single grain, is associated with minor concentrations of Os, Ru, and Pt, and with adhering particles of corundum and perovskite. A third Ir-rich particle, with a greater apparent Os concentration, was identified before being lost as a result of charging under the electron beam. In addition to demonstrating the preservation of projectile components within the Chicxulub Crater, analogous phase associations in Ca- and Al-rich inclusions (CAI) from C2 and C3 chondrites suggest to us that these melt-rock Ir host phases are relics from a carbonaceous chondrite K/T boundary impactor Although the obviously low Ru/Ir ratios of the Chicxulub Ir host phases are qualitatively consistent with suggested PGE fractionation with distance during condensation in an ejecta cloud, it seems difficult to explain the accumulation of the about 3 x 10(exp 11) Ir atoms required to form a about 10(exp -10) g nugget of pure Ir metal within a jet of vaporized projectile expanding at 1-4 km/s, or to effectively exclude or remove commonly alloyed PGE and siderophile elements by fractionation processes resulting from condensation, oxidation, sulfidization, exsolution, or autometamorphism during cooling of the melt. We do not dismiss the importance of these processes entirely; on the contrary, other geochemical and mineralogical aspects of the melt rocks require them, and condensation from the expanding ejecta cloud appears to best explain the primary Ir host-phase distribution in the fish clay, as well as the high Ir concentrations associated with spinel-bearing spheroids at the K/T boundary in the Pacific Ocean . If the "relict" hypothesis is correct, micronuggets of other PGEs and alloys, not detected by our INAA screening, should also occur in the melt rocks. Possibly, the discrete host phases with lesser Ir masses are such alloys with subordinate Ir, rather than simply smaller, predominantly Ir-bearing particles. A CAI source for the relics would be consistent with either a comet or an asteroid K/T impact at Chicxulub. (Additional information contained in the original.)

Schuraytz, B. C.↗

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Aires, Filipe↗

AI and ML Applications for PV Reliability and System Performance

This poster discusses AI and ML topics in PV reliability and system performance. In particular, automated metadata extraction and QA for fielded solar installations is covered for the PV Fleets Project. Additionally, statistical learning topics for the PVInsight Project are addressed, as well as development of the PV Validation Hub.

algorithm↗

Ex Machina Determination of Structural Correlation Functions

Determining the structural properties of condensed-phase systems is a fundamental problem in theoretical statistical mechanics. In this study, we present a machine learning method that is able to predict structural correlation functions with significantly improved accuracy in comparison with traditional approaches. The usefulness of this ex machina (from the machine) approach is illustrated by predicting the radial distribution functions of two paradigmatic condensed-phase systems, a Lennard-Jones fluid and a hard-sphere fluid, and then comparing those results to the results obtained using both integral equation methods and empirically motivated analytical functions. We find that application of the developed ex machina method typically decreases the predictive error by more than an order of magnitude in comparison with traditional theoretical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Raman spectrum and polarizability of liquid water from deep neural networks

We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a relatively small number of molecular configurations is sufficient to predict the polarizability of arbitrary liquid configurations in close agreement with ab initio density functional theory calculations. In combination with a neural network representation of the interatomic potential energy surface, the scheme allows us to calculate the Raman spectra along 2-nanosecond classical trajectories at different temperatures for H 2 O and D 2 O. The vast gains in efficiency provided by the machine learning approach enable longer trajectories and larger system sizes relative to ab initio methods, reducing the statistical error and improving the resolution of the low-frequency Raman spectra. Decomposing the spectra into intramolecular and intermolecular contributions elucidates the mechanisms behind the temperature dependence of the low-frequency and stretch modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active learning of chemical reaction networks via probabilistic graphical models and Boolean reaction circuits

Discerning networks of many reactions among multiple interconverting species is challenging. Here, we present a reaction network identification methodology. Our methodology enumerates all stoichiometrically and chemically feasible reactions and requires statistical evidence from effluent concentrations for the inclusion or exclusion of each from the reaction network, contrasting with the commonly seen incremental approach and other work of relying heavily upon chemical intuition and assuming the reactions occurring. Using graph theory alongside an active learning design of experiments that propose maximally informative feeds, we identify the underlying reaction network with minimal laboratory runs. Here, we introduce chemistry-probabilistic graphical modeling and Boolean reaction circuits to statistically quantify which reactions occur from effluent concentrations. Our methodology accurately discerns active reactions, as showcased upon a laboratory network of cross-ketonization of furoic and lauric acid and validated upon simulated networks of thermal and CO 2 -assisted ethane dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the circularly polarized luminescence of individual triplet sublevels

Here, we discuss the possibility of using circularly polarized luminescence (CPL) as a tool to probe individual triplet spin sublevels that are populated nonadiabatically following photoexcitation. This study is motivated by a mechanism proposed for chirality-induced spin selectivity in which coupled electronic-nuclear dynamics may lead to a non-statistical population of the three triplet sublevels in chiral systems. We find that low-temperature CPL should aid in quantifying the exact spin state/s populated through coupled electronic-nuclear motion in chiral molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multimodal Instrument Concepts for Chemical Sciences at Second Target Station

The development of advanced chemical and energy systems is inherently complex, relying heavily on their unique pathways. Because no two catalysts or batteries follow exactly the same kinetic trajectories, conventional sequential measurements often obscure crucial relationships between structure and dynamics through statistical averaging. This report introduces two neutron scattering instrument concepts for the Second Target Station (STS) specifically designed to overcome this barrier: the Extended Q-range Diffractometer (EQD) and the Multimodal Chemical Spectrometer (MCS).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA standard: Trend analysis techniques

This Standard presents descriptive and analytical techniques for NASA trend analysis applications. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. Use of this Standard is not mandatory; however, it should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend Analysis is neither a precise term nor a circumscribed methodology, but rather connotes, generally, quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this Standard. The document presents the basic ideas needed for qualitative and quantitative assessment of trends, together with relevant examples. A list of references provides additional sources of information.

Source record↗

Space debris characterization in support of a satellite breakup model

The Space Kinetic Impact and Debris Branch began an ambitious program to construct a fully analytical model of the breakup of a satellite under hypervelocity impact. In order to provide empirical data with which to substantiate the model, debris from hypervelocity experiments conducted in a controlled laboratory environment were characterized to provide information of its mass, velocity, and ballistic coefficient distributions. Data on the debris were collected in one master data file, and a simple FORTRAN program allows users to describe the debris from any subset of these experiments that may be of interest to them. A statistical analysis was performed, allowing users to determine the precision of the velocity measurements for the data. Attempts are being made to include and correlate other laboratory data, as well as those data obtained from the explosion or collision of spacecraft in low earth orbit.

Fortson, Bryan H.↗

Suppression of Random Dopant-Induced Threshold Voltage Fluctuations in Sub-0.1-(micron)meter MOSFET's with Epitaxial and (delta)-Doped Channels

A detailed three-dimensional (3-D) statistical 'atomistic' simulation study of fluctuation-resistant sub-0.1-(micron)meter MOSFET architectures with epitaxial channels and delta doping is presented. The need for enhancing the fluctuation resistance of the sub-0.1-(micron)meter generation transistors is highlighted by presenting summarized results from atomistic simulations of a wide range of conventional devices with uniformly doped channel. According to our atomistic results, the doping concentration dependence of the random dopant-induced threshold voltage fluctuations in conventional devices is stronger than the analytically predicted fourth-root dependence. As a result of this, the scaling of such devices will be restricted by the "intrinsic" random dopant-induced fluctuations earlier than anticipated. Our atomistic simulations confirm that the introduction of a thin epitaxial layer in the MOSFET's channel can efficiently suppress the random dopant-induced threshold voltage fluctuations in sub-0.1-(micron)meter devices. For the first time, we observe an "anomalous" reduction in the threshold voltage fluctuations with an increase in the doping concentration behind the epitaxial channel, which we attribute to screening effects. Also, for the first time we study the effect of a delta-doping, positioned behind the epitaxial layer, on the intrinsic threshold voltage fluctuations. Above a certain thickness of epitaxial layer, we observe a pronounced anomalous decrease in the threshold voltage fluctuation with the increase of the delta doping. This phenomenon, which is also associated with screening, enhances the importance of the delta doping in the design of properly scaled fluctuation-resistant sub-0.1-(micron)meter MOSFET's. Index Terms-Doping, fluctuations, MOSFET, semiconductor device simulation, silicon devices, threshold.

Asenov, Asen↗

Upstreamness and downstreamness in input–output analysis from local and aggregate information

Abstract Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I–O tables, but only relying on local and aggregate information, e.g., the total intermediate demand per sector. Our method, based on a rank-1 approximation to the I–O table, shows consistently good performance in reconstructing rankings (i.e., upstreamness and downstreamness measures for countries and sectors) when tested on empirical data from the world input–output database. Moreover, we connect the accuracy of our approximate framework with the spectral properties of the I–O tables, which ordinarily exhibit relatively large spectral gaps. Our approach provides a fast and analytically tractable framework to rank constituents of a complex economy without the need of matrix inversions and the knowledge of finer intersectorial details.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Stochastic Vector Techniques in Ground-State Electronic Structure

Herein we review a suite of stochastic vector computational approaches for studying the electronic structure of extended condensed matter systems. These techniques help reduce algorithmic complexity, facilitate efficient parallelization, simplify computational tasks, accelerate calculations, and diminish memory requirements. While their scope is vast, we limit our study to ground-state and finite temperature density functional theory (DFT) and second-order many-body perturbation theory. More advanced topics, such as quasiparticle (charge) and optical (neutral) excitations and higher-order processes, are covered elsewhere. We start by explaining how to use stochastic vectors in computations, characterizing the associated statistical errors. Next, we show how to estimate the electron density in DFT and discuss effective techniques to reduce statistical errors. Finally, we review the use of stochastic vectors for calculating correlation energies within the second-order Møller-Plesset perturbation theory and its finite temperature variational form. Example calculation results are presented and used to demonstrate the efficacy of the methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Verification of MCNP Critical Benchmark Model of U233-COMP-THERM-004 [Slides]

The verification of U233-COMP-THERM-004 contributed to the LANL centralized repository that’s currently under development. Revisions made to the MCNP model were statistically significant. Magnitude of bias is relatively small in comparison to other uranium benchmark biases and thus will likely have not a significant effect on the USL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Validation of New MCNP6.3 Features for Critical and Subcritical Benchmark Simulations [Slides]

A separate MCNP6.3 V&V document reports on all the default calculations for all test suites was introduced. Here, we look at new optional features of the MCNP6.3 code. Then, Fission-matrix-based options with Convergence and population testing and Automated acceleration of the fission source and Doppler Broadening Resonance Correction and HDF5 Particle Track Output (PTRAC) and Validation benchmarks: criticality, Rossi-α, and subcritical multiplication. All the new MCNP6.3 options give statistically equivalent results and should be considered for default usage in criticality and subcritical multiplication calculation work. Discussed are two separate papers at the upcoming 2023 International Conference on Nuclear Criticality Safety (ICNC 2023) that give more details on the results presented here.

97 MATHEMATICS AND COMPUTING↗