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At least 1,225 records · Page 68

Scale Dependence of Magnetic Helicity in the Solar Wind

We determine the magnetic helicity, along with the magnetic energy, at high latitudes using data from the Ulysses mission. The data set spans the time period from 1993 to 1996. The basic assumption of the analysis is that the solar wind is homogeneous. Because the solar wind speed is high, we follow the approach first pioneered by Matthaeus et al. by which, under the assumption of spatial homogeneity, one can use Fourier transforms of the magnetic field time series to construct one-dimensional spectra of the magnetic energy and magnetic helicity under the assumption that the Taylor frozen-in-flow hypothesis is valid. That is a well-satisfied assumption for the data used in this study. The magnetic helicity derives from the skew-symmetric terms of the three-dimensional magnetic correlation tensor, while the symmetric terms of the tensor are used to determine the magnetic energy spectrum. Our results show a sign change of magnetic helicity at wavenumber k approximately equal to 2AU(sup -1) (or frequency nu approximately equal to 2 microHz) at distances below 2.8AU and at k approximately equal to 30AU(sup -1) (or nu approximately equal to 25 microHz) at larger distances. At small scales the magnetic helicity is positive at northern heliographic latitudes and negative at southern latitudes. The positive magnetic helicity at small scales is argued to be the result of turbulent diffusion reversing the sign relative to what is seen at small scales at the solar surface. Furthermore, the magnetic helicity declines toward solar minimum in 1996. The magnetic helicity flux integrated separately over one hemisphere amounts to about 10(sup 45) Mx(sup 2) cycle(sup -1) at large scales and to a three times lower value at smaller scales.

Brandenburg, Axel↗

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

big data↗

Navier-Stokes Simulation of UH-60A Rotor/Wake Interaction Using Adaptive Mesh Refinement

High-resolution simulations of rotor/vortex-wake interaction for a UH60-A rotor under BVI and dynamic stallconditions were carried out with the OVERFLOW Navier-Stokes code.a. The normal force and pitching moment variation with azimuth angle were in good overall agreementwith flight-test data, similar to other CFD results reported in the literature.b. The wake-grid resolution did not have a significant effect on the rotor-blade airloads. This surprisingresult indicates that a wake grid spacing of (Delta)S=10% ctip is sufficient for engineering airloads predictionfor hover and forward flight. This assumes high-resolution body grids, high-order spatial accuracy, anda hybrid RANS/DDES turbulence model.c. Three-dimensional dynamic stall was found to occur due the presence of blade-tip vortices passing overa rotor blade on the retreating side. This changed the local airfoil angle of attack, causing stall, unlikethe 2D perspective of pure pitch oscillation of the local airfoil section.

CFD Validation↗

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

MBSE↗

Evaluation of Methods for Molecular Dynamics Simulation of Ionic Liquid Electric Double Layers

We investigate how systematically increasing the accuracy of various molecular dynamics modeling techniques influences the structure and capacitance of ionic liquid electric double layers (EDLs). The techniques probed concern long-range electrostatic interactions, electrode charging (constant charge versus constant potential conditions), and electrolyte polarizability. Our simulations are performed on a quasi-two-dimensional, or slab-like, model capacitor, which is composed of a polarizable ionic liquid electrolyte, [EMIM][BF4], interfaced between two graphite electrodes. To ensure an accurate representation of EDL differential capacitance, we derive new fluctuation formulas that resolve the differential capacitance as a function of electrode charge or electrode potential. The magnitude of differential capacitance shows sensitivity to different long-range electrostatic summation techniques, while the shape of differential capacitance is affected by charging technique and the polarizability of the electrolyte. For long-range summation techniques, errors in magnitude can be mitigated by employing two-dimensional or corrected three dimensional electrostatic summations, which lead to electric fields that conform to those of a classical electrostatic parallel plate capacitor. With respect to charging, the changes in shape are a result of ions in the Stern layer (i.e. ions at the electrode surface) having a higher electrostatic affinity to constant potential electrodes than to constant charge electrodes. For electrolyte polarizability, shape changes originate from induced dipoles that soften the interaction of Stern layer ions with the electrode. The softening is traced to ion correlations vertical to the electrode surface that induce dipoles that oppose double layer formation. In general, our analysis indicates an accuracy dependent differential capacitance profile that transitions from the characteristic camel shape with coarser representations to a more diffuse profile with finer representations.

Haskins, Justin B.↗

Magnetic reconnection and kinetic waves generated in the Earth's quasi-parallel bow shock

Magnetic reconnection in quasi-parallel shocks, relevant to the Earth's bow shock, is studied by means of two-dimensional full particle-in-cell simulations. As the Alfvénic Mach number increases, the propagation direction of the waves excited in the transition region changes, and the shock becomes more turbulent with more reconnection sites. In the higher Mach number shock, abundant electron-only reconnection sites are generated with scales on the order of the ion skin depth or less. Non-reconnecting current sheets can also generate electron jets and energy dissipation can occur there as well. However, non-reconnecting current sheets with the magnetic field reversal typically show a smaller energy dissipation rate than reconnecting current sheets. In the shock transition region, two types of waves are responsible for driving reconnection: one has a wavelength around three ion skin depths (di), and the other has a wavelength less than 1 di. Electron and ion distribution functions show that in regions where the former type of waves is excited, there are two ion beams and a single-peaked electron distribution. In contrast, in regions where the latter type of waves is excited, there are multiple electron and ion beams. The waves propagating obliquely to the magnetic field bend the magnetic field lines, and magnetic reconnection occurs where oppositely directed field lines come into contact.

N. Bessho↗

Hippocampal place-cell firing during movement in three-dimensional space

"Place" cells of the rat hippocampus are coupled to "head direction" cells of the thalamus and limbic cortex. Head direction cells are sensitive to head direction in the horizontal plane only, which leads to the question of whether place cells similarly encode locations in the horizontal plane only, ignoring the z axis, or whether they encode locations in three dimensions. This question was addressed by recording from ensembles of CA1 pyramidal cells while rats traversed a rectangular track that could be tilted and rotated to different three-dimensional orientations. Cells were analyzed to determine whether their firing was bound to the external, three-dimensional cues of the environment, to the two-dimensional rectangular surface, or to some combination of these cues. Tilting the track 45 degrees generally provoked a partial remapping of the rectangular surface in that some cells maintained their place fields, whereas other cells either gained new place fields, lost existing fields, or changed their firing locations arbitrarily. When the tilted track was rotated relative to the distal landmarks, most place fields remapped, but a number of cells maintained the same place field relative to the x-y coordinate frame of the laboratory, ignoring the z axis. No more cells were bound to the local reference frame of the recording apparatus than would be predicted by chance. The partial remapping demonstrated that the place cell system was sensitive to the three-dimensional manipulations of the recording apparatus. Nonetheless the results were not consistent with an explicit three-dimensional tuning of individual hippocampal neurons nor were they consistent with a model in which different sets of cells are tightly coupled to different sets of environmental cues. The results are most consistent with the statement that hippocampal neurons can change their "tuning functions" in arbitrary ways when features of the sensory input or behavioral context are altered. Understanding the rules that govern the remapping phenomenon holds promise for deciphering the neural circuitry underlying hippocampal function.

Non-NASA Center↗

The Effect of Climate Change on Ozone Depletion through Changes in Stratospheric Water Vapour

Several studies have predicted substantial increases in Arctic ozone depletion due to the stratospheric cooling induced by increasing atmospheric CO2 concentrations. But climate change may additionally influence Arctic ozone depletion through changes in the water vapor cycle. Here we investigate this possibility by combining predictions of tropical tropopause temperatures from a general circulation model with results from a one-dimensional radiative convective model, recent progress in understanding the stratospheric water vapor budget, modelling of heterogeneous reaction rates and the results of a general circulation model on the radiative effect of increased water vapor. Whereas most of the stratosphere will cool as greenhouse-gas concentrations increase, the tropical tropopause may become warmer, resulting in an increase of the mean saturation mixing ratio of water vapor and hence an increased transport of water vapor from the troposphere to the stratosphere. Stratospheric water vapor concentration in the polar regions determines both the critical temperature below which heterogeneous reactions on cold aerosols become important (the mechanism driving enhanced ozone depletion) and the temperature of the Arctic vortex itself. Our results indicate that ozone loss in the later winter and spring Arctic vortex depends critically on water vapor variations which are forced by sea surface temperature changes in the tropics. This potentially important effect has not been taken into account in previous scenarios of Arctic ozone loss under climate change conditions.

Kirk-Davidoff, Daniel B.↗

Entangled two-plasmon generation in carbon nanotubes and graphene-coated wires

Here, we investigate the two-plasmon spontaneous decay of a quantum emitter near single-walled carbon nanotubes (SWCNTs) and graphene-coated wires (GCWs). We demonstrate efficient, enhanced generation of two-plasmon entangled states in SWCNTs due to the strong coupling between tunable guided plasmons and the quantum emitter. We predict two-plasmon emission rates more than twelve orders of magnitude higher than in free space, with average lifetimes of a few dozen nanoseconds. Given their low dimensionality, these systems could be more efficient for generating and detecting entangled plasmons in comparison to extended graphene. Indeed, we achieve a tunable spectrum of emission in GCWs, where sharp resonances occur precisely at the plasmons' minimum excitation frequencies. We show that by changing the material properties of the GCW's dielectric core, one could tailor the dominant modes and frequencies of the emitted entangled plasmons while keeping the decay rate ten orders of magnitude higher than in free space. By unveiling the unique properties of two-plasmon spontaneous emission processes in the presence of low-dimensional carbon-based nanomaterials, our findings set the basis for a novel material platform with applications to on-chip quantum information technologies.

36 MATERIALS SCIENCE↗

Reconnection in Three Dimensions

Analyzing the qualitative three-dimensional magnetic structure of a plasmoid, we were led to reconsider the concept of magnetic reconnection from a general point of view. The properties of relatively simple magnetic field models provide a strong preference for one of two definitions of magnetic reconnection that exist in the literature. Any concept of magnetic reconnection defined in terms of magnetic topology seems naturally restricted to cases where the magnetic field vanishes somewhere in the nonideal (diffusion) region. The main part of this paper is concerned with magnetic reconnection in nonvanishing magnetic fields (finite-B reconnection), which has attracted less attention in the past. We show that the electric field component parallel to the magnetic field plays a crucial physical role in finite-B reconnection, and we present two theorems involving the former. The first states a necessary and sufficient condition on the parallel electric field for global reconnection to occur. Here the term "global" means the generic case where the breakdown of magnetic connection occurs for plasma elements that stay outside the nonideal region. The second theorem relates the change of magnetic helicity to the parallel electric field for cases where the electric field vanishes at large distances. That these results provide new insight into three-dimensional reconnection processes is illustrated in terms of the plasmoid configuration, which was our starting point.

Hesse, Michael↗

Evaluation of the GEOS-Chem UCX Stratosphere in the GEOS Composition Forecast System

The NASA GEOS Composition Forecast (GEOS-CF) system provides 3-dimensional atmospheric composition analyses and forecasts to the public in near-real time at the high spatial resolution of 25 km. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model (v12) used in this system includes the UCX stratospheric chemistry mechanism. Here, we describe the GEOS-CF system and provide comparisons against remote-sensed observations for stratospheric composition, including measurements of HCl, ClO, NO2, and O3. The GEOS-CF nudges the stratospheric ozone towards the GEOS Forward Processing (GEOS FP) assimilated ozone product; as a result the stratospheric ozone analysis in theGEOS-CF agrees well with observations. Additionally, with the inclusion of the GEOS-Chem UCX stratospheric chemistry mechanism in GEOS-CF, 5-day forecasts, especially during the abnormal 2020 NH polar spring, capture the chemical and dynamical changes missed by the GEOS FP system, which tends towards climatology. The GEOS-CF is a new tool for the research community providing near-real time 3-dimensional gridded information on atmospheric composition throughout the troposphere and stratosphere.

Stratosphere↗

3-D Modeling of Induced Seismicity Along Multiple Faults: Magnitude, Rate, and Location in a Poroelasticity System

Understanding of the potential to injection–induced seismicity along faults requires the response of fault zone system to spatiotemporal perturbations in pore pressure and stress. In this study, three–dimensional (3–D) model system consisting of the caprock, reservoir, and basement is intersected by vertical strike–slip faults. We examine the full poroelastic behavior of the formation and perform the mechanical analysis along each fault zone using the Coulomb stress change. The magnitude, rate, and location of potential earthquakes are predicted using the spatial distribution of stresses and pore pressure over time. Rapid diffusion of pore pressure into conductive faults initiates failure, but the majority of induced seismicity occurs at deep fault zones due to poroelastic stabilization near the injection interval. Less permeable faults can be destabilized by either delayed pore pressure diffusion or poroelastic stressing. A two–dimensional (2–D) horizontal model, representing the interface between the reservoir and the basement, limits diffusion of pore pressure and deformation of the formation in the vertical direction that may overestimate or underestimate the potential of earthquakes along the fault. Lastly, our numerical results suggest that the 3–D modeling of faulting system including poroelastic coupling can reduce the uncertainty in the seismic hazard prediction by considering the hydraulic and mechanical interaction between faults and bounding formations.

3‐D modeling↗

Atomic Structure, Dynamics, Changes in Chemical Bonding and Semiconductor-Metal Transition in Sb 2 Se 3 : A Remarkable Material for Quantum Networks and Energy Applications

Antimony sesquiselenide has become an outstanding functional material for photovoltaics, energy storage and transformation, memory and photonic applications. Sb 2 Se 3 is one of the most successful emerging solar light absorbers and has also been identified as a highly promising ultralow-loss phase-change material (PCM) for next-generation coherent nanophotonic processors, photonic tensor cores, quantum and neuromorphic networks. Unlike benchmark telluride PCMs, Sb 2 Se 3 features a quasi-one-dimensional (1D) crystalline structure consisting of (Sb 4 Se 6 ) ∞ ribbons, lacks the typical PCM chemical bonding, and undergoes an extended semiconductor-metal transition above the melting point. Consequently, the origin of high optical contrast between crystalline (SET) and amorphous (RESET) logic states remains elusive and presents a significant challenge. Using high-energy X-ray diffraction and Raman spectroscopy over a wide temperature range, supported by first-principles simulations and complemented by thermal, optical and electrical measurements, as well as by 121 Sb-Mossbauer spectroscopy, the quasi-1D network of orthorhombic antimony sesquiselenide was found to undergo significant evolution in amorphous and supercooled Sb 2 Se 3 , leading to lower coordination, shorter interatomic distances and a higher p-electron density on antimony, indicating changes in chemical bonding. The observed novel Sb 2 Se 3 nanocrystalline polymorph, characterized by trigonal antimony coordination and more isolated Sb-Se ribbons, could help reduce multiple trapping defect states in the bandgap, which are typical of orthorhombic Sb 2 Se 3 , thereby enhancing the power-conversion efficiency of photovoltaic devices. Semimetallic and metallic liquid Sb 2 Se 3 exhibit a gradual transformation into a denser 2D and/or 3D network with higher antimony coordination. Localized electron states in the pseudogap are becoming extended, leading to an increase in electronic conductivity σ following the relationship σ ∝ N(E F ) 2 . Liquid Sb 2 Se 3 also appears to be strongly fragile, with a nonmonotonic change in viscosity and higher atomic mobility in the metallic liquid. Furthermore, these results explain extraordinary functionalities of Sb 2 Se 3 for photonic and energy applications.

antimony↗

One-Dimensional (1D) Nanostructured Materials for Energy Applications

At present, the world is at the peak of production of traditional fossil fuels. Much of the resources that humanity has been consuming (oil, coal, and natural gas) are coming to an end. The human being faces a future that must necessarily go through a paradigm shift, which includes a progressive movement towards increasingly less polluting and energetically viable resources. In this sense, nanotechnology has a transcendental role in this change. For decades, new materials capable of being used in energy processes have been synthesized, which undoubtedly will be the cornerstone of the future development of the planet. In this review, we report on the current progress in the synthesis and use of one-dimensional (1D) nanostructured materials (specifically nanowires, nanofibers, nanotubes, and nanorods), with compositions based on oxides, nitrides, or metals, for applications related to energy. Due to its extraordinary surface–volume relationship, tunable thermal and transport properties, and its high surface area, these 1D nanostructures have become fundamental elements for the development of energy processes. The most relevant 1D nanomaterials, their different synthesis procedures, and useful methods for assembling 1D nanostructures in functional devices will be presented. Applications in relevant topics such as optoelectronic and photochemical devices, hydrogen production, or energy storage, among others, will be discussed. The present review concludes with a forecast on the directions towards which future research could be directed on this class of nanostructured materials.

Machín, Abniel (ORCID:0000000341343344)↗

Real-time dynamics and structures of supported subnanometer catalysts via multiscale simulations

Understanding the performance of subnanometer catalysts and how catalyst treatment and exposure to spectroscopic probe molecules change the structure requires accurate structure determination under working conditions. Experiments lack simultaneous temporal and spatial resolution and could alter the structure, and similar challenges hinder first-principles calculations from answering these questions. Here, we introduce a multiscale modeling framework to follow the evolution of subnanometer clusters at experimentally relevant time scales. We demonstrate its feasibility on Pd adsorbed on CeO 2 (111) at various catalyst loadings, temperatures, and exposures to CO. We show that sintering occurs in seconds even at room temperature and is mainly driven by free energy reduction. It leads to a kinetically (far from equilibrium) frozen ensemble of quasi-two-dimensional structures that CO chemisorption and infrared experiments probe. CO adsorption makes structures flatter and smaller. High temperatures drive very rapid sintering toward larger, stable/metastable equilibrium structures, where CO induces secondary structure changes only.

36 MATERIALS SCIENCE↗

Chemical vapor transport growth of two-dimensional transition-metal dichalcogenides

A two-dimensional transition-metal dichalcogenide layer is grown by reacting a non- or low-volatile source material with a volatilized halogen or halide compound to produce a volatilized composition comprising at least one reaction product. The volatilized composition is flowed through an open chamber of a tube furnace with a temperature gradient, wherein the temperature changes along a path through which the volatilized composition flows through the open chamber of the tube furnace. Where the temperature along the path in the open chamber is in a reaction-temperature range, the volatilized composition is deposited as a two-dimensional crystalline transition-metal dichalcogenide layer.

Modtland, Brian J.↗

Three-dimensional strain imaging of irradiated chromium using multi-reflection Bragg coherent diffraction

Abstract Radiation-induced materials degradation is a key concern in limiting the performance of nuclear materials. The formation of nanoscale void and gas bubble superlattices in metals and alloys under radiation environments can effectively mitigate radiation-induced damage, such as swelling and aid the development of next generation radiation tolerant materials. To effectively manage radiation-induced damage via superlattice formation, it is critical to understand the microstructural changes and strain induced by such superlattices. We utilize multi-reflection Bragg coherent diffraction imaging to quantify the full strain tensor induced by void superlattices in iron irradiated chromium substrate. Our approach provides a quantitative estimation of radiation-induced three-dimensional (3D) strain generated at the microscopic level and predicts the number density of defects with a high degree of sensitivity. Such quantitative evaluation of 3D strain in nuclear materials can have a major impact on predicting materials behavior in radiation environments and can revolutionize design of radiation tolerant materials.

36 MATERIALS SCIENCE↗

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗