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At least 1,531 records · Page 85

Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials

Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of solid oxide fuel cell electrodes. The generated microstructures are visually, statistically, and topologically realistic, with distributions of microstructural parameters, including volume fraction, particle size, surface area, tortuosity, and triple phase boundary density, being highly similar to those of the original microstructure. These results are compared and contrasted with those from an established, grain-based generation algorithm (DREAM.3D). Importantly, simulations of electrochemical performance, using a locally resolved finite element model, demonstrate that the GAN generated microstructures closely match the performance distribution of the original, while DREAM.3D leads to significant differences. Finally, the ability of the generative machine learning model to recreate microstructures with high fidelity suggests that the essence of complex microstructures may be captured and represented in a compact and manipulatable form.

36 MATERIALS SCIENCE↗

Principal modes of variation of rain-rate probability distributions

Radar or satellite observations of an area generate sequences of rain-rate maps. From a gridded map a histogram of rain rates can be obtained representing the relative areas occupied by rain rates of various strengths. The histograms vary with time as precipitating systems in the area evolve and decay and amounts of convective and stratiform rain in the area change. A method of decomposing the histograms into linear combinations of a few empirical distributions with time-dependent coefficients is developed, using principal component analysis as a starting point. When applied to a tropical Atlantic dataset (GATE), two distributions emerge naturally from the analysis, resembling stratiform and convective rain-rate distributions in that they peak at low and high rain rates, respectively. The two 'modes' have different timescales and only the high-rain-rate mode has a statistically significant diurnal cycle. The ability of just two modes to describe rain variabiltiy over an area can explain why methods of estimating area-averaged rain rate from the area covered by rain rates above a certain threshold are so successful.

Bell, Thomas L.↗

A Systems Model for Power Technology Assessment

A computer model is under continuing development at NASA Glenn Research Center that enables first-order assessments of space power technology. The model, an evolution of NASA Glenn's Array Design Assessment Model (ADAM), is an Excel workbook that consists of numerous spreadsheets containing power technology performance data and sizing algorithms. Underlying the model is a number of databases that contain default values for various power generation, energy storage and power management and distribution component parameters. These databases are actively maintained by a team of systems analysts so that they contain state-of-art data as well as the most recent technology performance projections. Sizing of the power subsystems can be accomplished either by using an assumed mass specific power (W/kg) or energy (Wh/kg) or by a bottoms-up calculation that accounts for individual component performance and masses. The power generation, energy storage and power management and distribution subsystems are sized for given mission requirements for a baseline case and up to three alternatives. This allows four different power systems to be sized and compared using consistent assumptions and sizing algorithms. The component sizing models contained in the workbook are modular so that they can be easily maintained and updated. All significant input values have default values loaded from the databases that can be over-written by the user. The default data and sizing algorithms for each of the power subsystems are described in some detail. The user interface and workbook navigational features are also discussed. Finally, an example study case that illustrates the model's capability is presented.

Hoffman, David J.↗

Programmable random interval generator

Random pulse generator can supply constant-amplitude randomly distributed pulses with average rate ranging from a few counts per second to more than one million counts per second. Generator requires no high-voltage power supply or any special thermal cooling apparatus. Device is uniquely versatile and provides wide dynamic range of operation.

Lindsey, R. S., Jr.↗

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗

Influence of counterion substitution on the properties of imidazolium-based ionic liquid clusters

Due to their unique physiochemical properties that may be tailored for specific purposes, ionic liquids (ILs) have been investigated for various applications, including chemical separations, catalysis, energy storage, and space propulsion. The different cations and anions comprising ILs may be selected to optimize a range of desired properties, such as thermal stability, ionic conductivity, and volatility, leading to the designation of certain ILs as designer “green” solvents. The effect of counterions on the properties of ILs is of both fundamental scientific interest and technological importance. Herein, we report a systematic experimental and theoretical investigation of the size, charge, stability toward dissociation, and geometric/electronic structure of 1-ethyl-3-methyl imidazolium (EMIM)-based IL clusters containing two different atomic counterions (i.e., bromide [Br − ] and iodide [I − ]). This work extends our studies of EMIM + cations with atomic chloride (Cl − ) and molecular tetrafluoroborate (BF 4 − ) anions reported previously by Baxter et al. [Chem. Mater. 34, 2612 (2022)] and Zhang et al . [J. Phys. Chem. Lett. 11, 6844 (2020)], respectively. Distributions of anionic IL clusters were generated in the gas phase using electrospray ionization and characterized by high mass resolution mass spectrometry, energy-resolved collision-induced dissociation, and negative ion photoelectron spectroscopy experiments. The experimental results reveal anion-dependent trends in the size distribution, relative abundance, ionic charge state, stability toward dissociation, and electron binding energies of the IL clusters. Complementary global optimization theory provides molecular-level insights into the bonding and electronic structure of a selected subset of clusters, including their low energy structures and electrostatic potential maps, and how these fundamental characteristics are influenced by anion substitution. Collectively, our findings demonstrate how the fundamental properties of ILs, which determine their suitability for many applications, may be tuned by substituting counterions. These observations are critical in the sub-nanometer cluster size regime where phenomena do not scale predictably to the bulk phase, and each atom counts toward determining behavior.

cluster↗

GRID3D-v2: An updated version of the GRID2D/3D computer program for generating grid systems in complex-shaped three-dimensional spatial domains

In order to generate good quality systems for complicated three-dimensional spatial domains, the grid-generation method used must be able to exert rather precise controls over grid-point distributions. Several techniques are presented that enhance control of grid-point distribution for a class of algebraic grid-generation methods known as the two-, four-, and six-boundary methods. These techniques include variable stretching functions from bilinear interpolation, interpolating functions based on tension splines, and normalized K-factors. The techniques developed in this study were incorporated into a new version of GRID3D called GRID3D-v2. The usefulness of GRID3D-v2 was demonstrated by using it to generate a three-dimensional grid system in the coolent passage of a radial turbine blade with serpentine channels and pin fins.

Steinthorsson, E.↗

GENIE(++): A Multi-Block Structured Grid System

The computer code GENIE++ is a continuously evolving grid system containing a multitude of proven geometry/grid techniques. The generation process in GENIE++ is based on an earlier version. The process uses several techniques either separately or in combination to quickly and economically generate sculptured geometry descriptions and grids for arbitrary geometries. The computational mesh is formed by using an appropriate algebraic method. Grid clustering is accomplished with either exponential or hyperbolic tangent routines which allow the user to specify a desired point distribution. Grid smoothing can be accomplished by using an elliptic solver with proper forcing functions. B-spline and Non-Uniform Rational B-splines (NURBS) algorithms are used for surface definition and redistribution. The built in sculptured geometry definition with desired distribution of points, automatic Bezier curve/surface generation for interior boundaries/surfaces, and surface redistribution is based on NURBS. Weighted Lagrance/Hermite transfinite interpolation methods, interactive geometry/grid manipulation modules, and on-line graphical visualization of the generation process are salient features of this system which result in a significant time savings for a given geometry/grid application.

Williams, Tonya↗

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗

The photometric center of the Gegenschein

Model calculations are employed to assess two factors that determine the position of the photometric center of the Gegenschein: (1) the increased scattering efficiency of the interplanetary dust near backscattering (at scattering angles of 165 to 180 deg); and (2) the spatial density distribution of the dust. Computer-generated brightness contours are used to examine which of these two factors dominates. It is found that the effect of the enhanced scattering of light by dust in the backscattering region is more important than the effect of the spatial density distribution of the dust. This means that the photometric center should be observed at the antisolar point at all times, except possibly when the antisolar point is at its maximum displacement from the symmetry plane.

Misconi, N. Y.↗

A Scalable Gaussian Process Approach to Shear Mapping with MuyGPs

Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in turn provides us with information about the nature of dark energy. Conventional methods generate shear maps from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser–Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations—an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly scaling shear map construction alternative using a scalable Gaussian process prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest neighbors and fits hyperparameters using batched leave-one-out cross-validation. This work is the first step toward a full, scalable mass mapping method. We work in a simplified regime where we validate our method by interpolating and analyzing maps given noisy point-estimate data from all three shear fields, taken from a suite of N -body ray-tracing simulations. We also show that we can perform these operations at the scale of billions of galaxies on high-performance computing platforms.

79 ASTRONOMY AND ASTROPHYSICS↗

Plasma wave turbulence in the strong coupling region at comet Giacobini-Zinner

Within 100,000 km of comet Giacobini-Zinner's nucleus, strong plasma wave turbulence was detected by the ICE electric and magnetic field wave instruments. The spatial profiles of the wave amplitudes are compared with measurements of the heavy ion fluxes of cometary origin, the plasma electron density, and the magnetic field strength. The general similarity of the wave and heavy ion profiles suggest that the waves might be generated by free energy in the pick-up ion distribution function. However, the expected parallel streaming instability of electrostatic modes generates waves with frequencies that are too low to explain the observations. The observed low frequency magnetic turbulence is plausibly explained by the lower hybrid loss-cone instability of heavy ions.

Coroniti, F. V.↗

Mars Entry Atmospheric Data System Modelling and Algorithm Development

The Mars Entry Atmospheric Data System (MEADS) is being developed as part of the Mars Science Laboratory (MSL), Entry, Descent, and Landing Instrumentation (MEDLI) project. The MEADS project involves installing an array of seven pressure transducers linked to ports on the MSL forebody to record the surface pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the total pressure, dynamic pressure, Mach number, angle of attack, and angle of sideslip. Secondary objectives are to estimate atmospheric winds by coupling the pressure measurements with the on-board Inertial Measurement Unit (IMU) data. This paper provides details of the algorithm development, MEADS system performance based on calibration, and uncertainty analysis for the aerodynamic and atmospheric quantities of interest. The work presented here is part of the MEDLI performance pre-flight validation and will culminate with processing flight data after Mars entry in 2012.

Karlgaard, Christopher D.↗

Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results

The Mars Entry Atmospheric Data System is a part of the Mars Science Laboratory, Entry, Descent, and Landing Instrumentation project. These sensors are a system of seven pressure transducers linked to ports on the entry vehicle forebody to record the pressure distribution during atmospheric entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. Specifically, angle of attack, angle of sideslip, dynamic pressure, Mach number, and freestream atmospheric properties are reconstructed from the measured pressures. Such data allows for the aerodynamics to become decoupled from the assumed atmospheric properties, allowing for enhanced trajectory reconstruction and performance analysis as well as an aerodynamic reconstruction, which has not been possible in past Mars entry reconstructions. This paper provides details of the data processing algorithms that are utilized for this purpose. The data processing algorithms include two approaches that have commonly been utilized in past planetary entry trajectory reconstruction, and a new approach for this application that makes use of the pressure measurements. The paper describes assessments of data quality and preprocessing, and results of the flight data reduction from atmospheric entry, which occurred on August 5th, 2012.

Karlgaard, Christopher D.↗

The origin and propagation of chorus in the outer magnetosphere

Wave normals of chorus in the outer magnetosphere have been determined for the first time from data obtained with the Ogo 5 search coil magnetometer. These measurements combined with simultaneous information concerning geomagnetic field, plasma density, and the electron energy and pitch angle distributions provide a consistent picture of the generation, propagation, and subsequent damping of chorus in agreement with theory. Specifically, the data are consistent with chorus generation within 25 deg of the equatorial plane on the dayside and within 2 deg on the nightside. Chorus is generated by a Doppler-shifted cyclotron resonance with electrons between 5 and 150 keV but only when the pitch angle distribution is peaked at 90 deg to the local magnetic field and the anisotropy exceeds a critical value.

Burton, R. K.↗

Aerodynamic design of turbomachinery blading in three-dimensional flow - An application to radial inflow turbines

A computational method, based on a theory for turbomachinery blading design in three-dimensional inviscid flow, is applied to a parametric design study of a radial inflow turbine wheel. As the method requires the specification of swirl distribution, a technique for its smooth generation within the blade region is proposed. Excellent agreements have been obtained between the computed results from this design method and those from direct Euler computations, demonstrating the correspondence and consistency between the two. The computed results indicate the sensitivity of the pressure distribution to a lean in the stacking axis and a minor alteration in the hub/shroud profiles. Analysis based on Navier-Stokes solver shows no breakdown of flow within the designed blade passage and agreement with that from design calculation; thus the flow in the designed turbine rotor closely approximates that of an inviscid one. These calculations illustrate the use of a design method coupled to an analysis tool for establishing guidelines and criteria for designing turbomachinery blading.

Yang, Y. L.↗

TRIM: AI Guided Random Number Generation for Resource-Constrained IoT Systems

Random numbers often serve as the backbone for many security solutions in diverse domains such as cryptography, side channel leakage prevention, and moving target defense. However, generating true random numbers requires a physical source of entropy (e.g. hardware, quantum, environmental phenomenon) making it difficult to realize at a large scale and at a low cost. On the flip side, pseudorandom number generators (easy to implement) following a specific distribution (e.g. Gaussian) can be easily compromised given a sufficient amount of traces. In this work, we have developed a machine learning-guided generative approach that can be used to create portable, resource-efficient, and cost-effective random number generators with high throughput and true randomness characteristics. We implement the proposed approach as a highly parameterized framework and perform extensive evaluation for different settings. The framework was able to learn from true random sources such as irrational numbers and environmental audio noise and imitate those sources towards generating new good quality random numbers on demand. We have generated more than 1 billion bits and observed robust performance in terms of true randomness metrics obtained from NIST SP 800-22 and FIPS 140-1 randomness test suites achieving a throughput of up to 142.85 Mbps. Compared to the state-of-the-art (SOTA) technique, the iso-cost setup of our framework can achieve more than 500 Mbps in a distributed setting. We have evaluated the efficacy of running the true randomness imitation AI models on target edge devices such as Raspberry Pi 4 (Model B), Nvidia Jetson Nano, Nvidia Jetson Orin Nano and Nvidia Jetson Xavier. We have also looked at the security of the TRIM framework itself against different adversarial threat models.

Cybersecurity↗

Distribution and diagenesis of microfossils from the lower Proterozoic Duck Creek Dolomite, Western Australia

Two distinct generations of microfossils occur in silicified carbonates from a previously undescribed locality of the Lower Proterozoic Duck Creek Dolomite, Western Australia. The earlier generation occurs in discrete organic-rich clasts and clots characterized by microquartz anhedra; it contains a variety of filamentous and coccoidal fossils in varying states of preservation. Second generation microfossils consist almost exclusively of well-preserved Gunflintia minuta filaments that drape clasts or appear to float in clear chalcedony. These filaments appear to represent an ecologically distinct assemblage that colonized a substrate containing the partially degraded remains of the first generation community. The two assemblages differ significantly in taxonomic frequency distribution from previously described Duck Creek florules. Taken together, Duck Creek microfossils exhibit a range of assemblage variability comparable to that found in other Lower Proterozoic iron formations and ferruginous carbonates. With increasing severity of post-mortem alteration, Duck Creek microfossils appear to converge morphologically on assemblages of simple microstructures described from early Archean cherts. Two new species are described: Oscillatoriopsis majuscula and O. cuboides; the former is among the largest septate filamentous fossils described from any Proterozoic formation.

NASA Discipline Number 52-30↗