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At least 811 records · Page 45

On the Existence of Fast Modes in Compressible Magnetohydrodynamic Turbulence

Abstract We study the existence and properties of fast magnetosonic modes in 3D compressible MHD turbulence by carrying out a number of simulations with compressible and incompressible driving conditions. We use two approaches to determine the presence of fast modes: mode decomposition based on spatial variations only and spatio-temporal 4D fast Fourier transform (4D FFT) analysis of all fluctuations. The latter method enables us to quantify fluctuations that satisfy the dispersion relation of fast modes with finite frequency. Overall, we find that the fraction of fast modes identified via the spatio-temporal 4D FFT approach in total fluctuation power is either tiny with nearly incompressible driving or ∼2% with highly compressible driving. We discuss the implications of our results for understanding the compressible fluctuations in space and astrophysical plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗

On the Existence of Fast Modes in Compressible Magnetohydrodynamic Turbulence

We study the existence and properties of fast magnetosonic modes in 3D compressible MHD turbulence by carrying out a number of simulations with compressible and incompressible driving conditions. We use two approaches to determine the presence of fast modes: mode decomposition based on spatial variations only and spatio-temporal 4D fast Fourier transform (4D FFT) analysis of all fluctuations. The latter method enables us to quantify fluctuations that satisfy the dispersion relation of fast modes with finite frequency. Overall, we find that the fraction of fast modes identified via the spatio-temporal 4D FFT approach in total fluctuation power is either tiny with nearly incompressible driving or ∼2% with highly compressible driving. We discuss the implications of our results for understanding the compressible fluctuations in space and astrophysical plasmas.

Zhaoming Gan↗

A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions

Neural network wavefunctions optimized using the variational Monte Carlo method have been shown to produce highly accurate results for the electronic structure of atoms and small molecules, but the high cost of optimizing such wavefunctions prevents their application to larger systems. We propose the Subsampled Projected-Increment Natural Gradient Descent (SPRING) optimizer to reduce this bottleneck. SPRING combines ideas from the recently introduced minimum-step stochastic reconfiguration optimizer (MinSR) and the classical randomized Kaczmarz method for solving linear least-squares problems. We demonstrate that SPRING outperforms both MinSR and the popular Kronecker-Factored Approximate Curvature method (KFAC) across a number of small atoms and molecules, given that the learning rates of all methods are optimally tuned. For example, on the oxygen atom, SPRING attains chemical accuracy after forty thousand training iterations, whereas both MinSR and KFAC fail to do so even after one hundred thousand iterations.

97 MATHEMATICS AND COMPUTING↗

A functional modeling approach for quality assurance in metal additive manufacturing

Purpose: Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. Here, a systematically integrated holistic view is proposed to achieve QA for AM. Design/methodology/approach: A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling. Findings: The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility. Research limitations/implications: A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study. Social implications: This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system. Originality/value: This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

36 MATERIALS SCIENCE↗

Thrust Characteristics of Multiple Lifting Jets in Ground Proximity

An investigation has been made to determine the thrust characteristics within ground proximity of a series of models which might represent vertical take-off-and-landing (VTOL) aircraft with multiple exit jet engines exhausting vertically downward beneath a lifting surface. Variations in simulated engine configurations were provided by a series of nozzle insert plugs in which the number of jet exits, located symmetrically on a fixed circle, was varied, or the diameter of the circle was varied for a given number of jet exits. represent lifting surfaces, and high-pressure air was used to simulate jet-engine exhaust. Plywood plates were used to The results of the investigation showed that increasing the number of exits, such that an annular jet configuration was approached, provided more favorable thrust characteristics within ground proximity than any other variation in the geometry of these multiple jets. Tests of a configuration with two nozzles approximating a fan-in-wing VTOL aircraft with fans located at different spanwise locations indicated that the augmentation in thrust within ground proximity was greater for the arrangement with the more inboard location of the nozzles.

Davenport, Edwin E.↗

A Proposal for Standardized MMOD Shielding for Robotic Spacecraft

NASA robotic spacecraft are required to assess the potential for small debris induced failure for all disposal-critical components. Additional shielding might then be necessary in order to meet the acceptable risk requirement for the overall mission. Traditionally this requirement had been met with little or no additional shielding. Since the introduction of a high density debris population in ORDEM 3.0, some missions, especially those in higher portions of Low Earth Orbit, have needed additional MMOD-specific shielding in order for the mission to meet the requirement. This is a costly design effort when performed late in the project life cycle, which adds unexpected mass to the spacecraft components during the integration phase, and could disrupt thermal management.A proposal is discussed to develop a more cost-effective approach to MMOD-shielding, which can be employed earlier in the hardware design phase. The development and adoption of standardized shielding assemblies allows early tailoring of the shielding around a component, so that the mass is accounted for, as well as the small particle penetration risk, at a point in the design phase when the cost and schedule impact are more manageable. A set of several assemblies can be developed with a range of protection thresholds, in order to control mass where less shielding is needed. Such shielding assemblies would be developed in collaboration with blanket assembly specialists and thermal control engineers to ensure manufacturability and thermal performance challenges are known and acceptable. One clear benefit of such an approach is that hypervelocity testing can be performed on each of the standard shield assemblies to refine and confirm their performance prior to use.The challenges inherent in designing supplemental MMOD shielding will be discussed, including variations in the orbital debris environment and performance prediction. The benefits of a standardized shielding approach and example applications will also be presented.

Hull, Scott M.↗

A Proposal for Standardized MMOD Shielding for Robotic Spacecraft

NASA robotic spacecraft are required to assess the potential for small debris induced failure for all disposal-critical components. Additional shielding might then be necessary in order to meet the acceptable risk requirement for the overall mission. Traditionally this requirement had been met with little or no additional shielding. Since the introduction of a high density debris population in ORDEM 3.0, some missions, especially those in higher portions of Low Earth Orbit, have needed additional MMOD-specific shielding in order for the mission to meet the requirement. This is a costly design effort when performed late in the project life cycle, which adds unexpected mass to the spacecraft components during the integration phase, and could disrupt thermal management. A proposal is discussed to develop a more cost-effective approach to MMOD-shielding, which can be employed earlier in the hardware design phase. The development and adoption of standardized shielding assemblies allows early tailoring of the shielding around a component, so that the mass is accounted for, as well as the small particle penetration risk, at a point in the design phase when the cost and schedule impact are more manageable. A set of several assemblies can be developed with a range of protection thresholds, in order to control mass where less shielding is needed. Such shielding assemblies would be developed in collaboration with blanket assembly specialists and thermal control engineers to ensure manufacturability and thermal performance challenges are known and acceptable. One clear benefit of such an approach is that hypervelocity testing can be performed on each of the standard shield assemblies to refine and confirm their performance prior to use.The challenges inherent in designing supplemental MMOD shielding will be discussed, including variations in the orbital debris environment and performance prediction. The benefits of a standardized shielding approach and example applications will also be presented.

Hull, Scott M.↗

Depth and Distribution of CO2 Snow on Mars

The dynamic role of volatiles on the surface of Mars has been a subject of longstanding interest. In the pre-Viking era, much of the debate was necessarily addressed by theoretical considerations. A particularly influential treatment by Leighton and Murray put forth a simple model relying on solar energy balance, and led to the conclusion that the most prominent volatile exchanging with the atmosphere over seasonal cycles is carbon dioxide. Their model suggested that due to this exchange, atmospheric CO2 partial pressure is regulated by polar ice. While current thinking attributes a larger role to H2O ice than did the occasional thin polar coating this model predicted, the CO2 cycle appears to be essentially correct. There are a number of observational constraints on the seasonal exchange of surface volatiles with the atmosphere. The growth and retreat of polar CO2 frost is visible from Earth-based telescopes and from spacecraft in Mars orbit, both at visible wavelengths and in thermal IR properties of the surface. Recently, variations in Gamma ray and neutron fluxes have also been used to infer integrated changes in CO2 mass on the surface. Measurements made by Viking's Mars Atmospheric Water Detector experiment were sensitive to atmospheric H2O vapor abundance. Surface condensates and their transient nature were detected by the Viking landers. The study here is motivated by recent data collected by the Mars Global Surveyor, affording the opportunity to not only detect the lateral distribution of volatiles, but also to constrain the variable volumes of the reservoirs. We elaborate on a technique first employed by Smith et al. By examining averages of a large number of topographic measurements collected by the Mars Orbiter Laser Altimeter (MOLA), that study showed that the zonal pattern of deposition and sublimation of CO2 can be determined. In their first approach, reference surfaces were fit to all measurements in narrow latitude annuli, and the time dependent variations about those mean surfaces were examined. In their second approach, height measurements from pairs of tracks that cross on the surface were interpolated and differenced, forming a set of crossover residuals. These residuals were then examined as a function of time and latitude. The initial studies averaged over longitude to maximize signal and minimize noise in order to isolate the expected small signal. In this follow-up study we now attempt to extract the elevation change pattern also as a function of longitude, and we focus on the crossover approach.

Aharonson, Oded↗

Deciphering controls on metal migration within floodplains: The critical role of redox environments on metal-organic complexes (Final Technical Report)

Our project elucidates the effect of differing hydrologic regimes on nutrient and contaminant dynamics within floodplains, and we explore the impact of varying sources of hydrologic extremes on nutrient-contaminant fate and transport. We use a combination of field measurements and laboratory experiments to examine the relationships between redox conditions, functionality of dissolved organic matter, metal speciation (specifically examining metal-ligand complexes), and nutrient-contaminant fate, particularly during hydrologic extremes. Floodplain biogeochemical variation through climatic extremes and beaver-induced hydrologic variation provide a unique look at controls on nutrient-contaminant fate and transport. Through our work, we have developed a novel approach that provides an unprecedented ability to resolve aqueous metal-organic complexes that reveals metal binding preferences for natural organic matter based on metal-ligand chemistry. We have developed novel methods to separate, quantify, and characterize organic-metal complexes in natural DOM that pair with field experiments comprising floodplains having systematic variation in biogeochemical conditions. We also developed a comprehensive computational approach for molecular characterization of metal-organic species that merges LC-coupled high resolution (HR) mass spectrometry and ICP-MS analysis. Importantly, we show that beaver dams have an outsized influence on hydrologic extremes, dwarfing the impact of climatic variation, that ultimate control biogeochemical conditions and water quality. Additionally, beaver dams impose a hydrologic driver that leads to improved, river water quality by divert water through soils and the hyporheic zone. We further show that iron(III) minerals have a dominant control on carbon mineralization across floodplains independent of hydrologic conditions, and that iron and aluminum associations with organic matter are a controlling factor in carbon mineralization. Ultimately, our work is helping to advancing a robust predictive understanding of how hydrologic changes in watersheds affect water quality and carbon and metal cycling in riparian zones.

54 ENVIRONMENTAL SCIENCES↗

Inversion of Gravity Fields From the Spacecraft Orbital Data Using an Adjoint Operator Approach

In perturbation approximation, the forward problem of orbital dynamics (equations with initial conditions) is linear with respect to variations of coordinates and/or velocities of the spacecraft and to corresponding variations of the gravity field in the models used. The linear operator adjoint to the linear operator of such forward problem turns out to be instrumental in inversion of differences between observed and predicted coordinates/velocities in terms of the updates of harmonics in the initial gravity field model. Based on this approach, the solution of resulting adjoint problem of orbital dynamics can be used to directly evaluate the matrix of partial derivatives of observable differences with respect to the gravity field harmonics. General discussion of the adjoint problem of orbital dynamics is given and an example of a mathematical formalism for the practical retrieval algorithm is presented.

Ustinov, E. A.↗

Solar wind theory and modelling

The outflow of coronal plasma into interplanetary space is a consequence of the coronal heating process. Therefore the formation of the corona and the acceleration of the solar wind should be treated as a single problem. Traditionally the mass or particle flux emanating from the extended corona has been thought of as being determined by the coronal temperature or scale height and the coronal (base) density. This argument follows from considerations of the momentum balance of the corona-wind system from which one obtains models of a close to hydrostatic corona out to the critical point where the flow becomes supersonic. With this approach to the acceleration of the wind is has been difficult to reconcile the relatively small variation observed in the proton flux at 1 AU with the predicted exponential dependence of the proton flux on the coronal temperature. In this talk we would like to emphasize another approach in which coronal energetics play the primary role. The deposition of energy into the corona through some 'mechanical' energy flux is balanced by the various energy sinks available to the corona and the sum of these processes determine the coronal structure, i.e. its temperature and density. The corona loses energy through heat conduction into the transition region, through radiative losses, and through the gravitational potential energy and kinetic energy put into the solar wind itself. We will show from a series of models of the chromosphere transition region-corona-solar wind system that most of the energy deposited in a magnetically open region will go into the solar wind, with roughly half going into kinetic energy and half into lifting the plasma out of the solar gravity field. The coronal base density will adjust itself in such a way that the heat conductive flux flowing into the transition region is radiated away in the upper chromosphere. The coronal temperature is set by the requirements that most of the deposited energy goes into accelerating the solar wind; the coronal scale height will adjust itself so that the solar wind energy losses conform to the amplitude of the input energy. These processes are modified by the 'mode' of energy deposition, and we will show the effects on coronal structure of changing the parameters describing coronal heating as well as the effects of including a helium fluid in the models. However, the location, scale height and/or form of the energy deposition (i.e. heating or direct acceleration) are not too important for the solar wind, the coronal density and temperature structure will vary with the 'mode' of energy deposition, but the solar wind mass flux depends mainly on the amplitude of the energy flux.

Hansteen, Viggo H.↗

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Soni, Vivak (ORCID:0000000294969562)↗

Probing atomic-scale symmetry breaking by rotationally invariant machine learning of multidimensional electron scattering

Abstract The 4D scanning transmission electron microscopy (STEM) method maps the structure and functionality of solids on the atomic scale, yielding information-rich data sets describing the interatomic electric and magnetic fields, structural and electronic order parameters, and other symmetry breaking distortions. A critical bottleneck is the dearth of analytical tools that can reduce complex 4D-STEM data to physically relevant descriptors. We propose an approach for the systematic exploration of 4D-STEM data using rotationally invariant variational autoencoders (rrVAE), which disentangle the general rotation of the object from other latent representations. The implementation of purely rotational rrVAE is discussed as are applications to simulated data for graphene and zincblende structures. The rrVAE analysis of experimental 4D-STEM data of defects in graphene is illustrated and compared to the classical center-of-mass analysis. This approach is universal for probing symmetry-breaking phenomena in complex systems and can be implemented for a broad range of diffraction methods.

36 MATERIALS SCIENCE↗

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

58 GEOSCIENCES↗

SNW 2000 Proceedings. Oxide Thickness Variation Induced Threshold Voltage Fluctuations in Decanano MOSFETs: a 3D Density Gradient Simulation Study

We use the density gradient (DG) simulation approach to study, in 3D, the effect of local oxide thickness fluctuations on the threshold voltage of decanano MOSFETs in a statistical manner. A description of the reconstruction procedure for the random 2D surfaces representing the 'atomistic' Si-SiO2 interface variations is presented. The procedure is based on power spectrum synthesis in the Fourier domain and can include either Gaussian or exponential spectra. The simulations show that threshold voltage variations induced by oxide thickness fluctuation become significant when the gate length of the devices become comparable to the correlation length of the fluctuations. The extent of quantum corrections in the simulations with respect to the classical case and the dependence of threshold variations on the oxide thickness are examined.

Asenov, Asen↗

Worst-Case Flutter Margins from F/A-18 Aircraft Aeroelastic Data

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, micron, computes a stability margin which directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The micron margins are robust margins which indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 SRA using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Lind, Rick↗

Robust Flutter Margin Analysis that Incorporates Flight Data

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, mu, computes a stability margin that directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The mu margins are robust margins that indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 Systems Research Aircraft using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Lind, Rick↗