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At least 631 records · Page 35

MinMap: An imaging spectrometer for high resolution compositional mapping of the Moon

MinMap has been selected by the Lunar Scout program to characterize and map the mineral composition of the Moon. The instrument will be built as a collaborative effort between Brown University, SETS Technology Inc., and Ball Aerospace Corp. MinMap is a visible to near-infrared imaging spectrometer that contains 192 spectral channels from 0.35-2.4 microns with signal to noise greater than 200 and 256 cross-track spatial elements. The spectrometer design has a 6 deg field of view (FOV) and utilizes grating dispersive elements and two dimensional detectors (no moving parts). An 'image cube' of data is produced that contains two dimensions of spatial information and one dimension of spectral information. All spectral channels and cross-track spatial elements are recorded simultaneously with spacecraft motion scanning the second spatial dimension. The high spectral resolution and continuous spectral range of MinMap are designed to measure the diagnostic absorption features of principal lunar minerals and their lithologic mixtures. Since the optical properties of lunar materials change in a regular manner upon exposure to the space environment, this spectral range is also quite sensitive to variations in exposure history (soil maturity). Nominal measurement stragegy is to obtain full global data of the Moon at 180 m/pixel from a 450 km polar orbit during the first month or two of operation. A 100 km orbit is anticipated for the remaining part of a 1 year mission allowing higher resolution data (approx. 80 m/pixel) to be obtained for targeted regions. MinMap exceeds LE x SWG's measurement recommendations and will provide the highest spatial resolution compositional map of lunar rocks and soils currently planned for orbital missions. Since all spectral channels are co-registered and obtained simultaneously, 'image cube' data swaths will be available for analysis almost immediately.

Pieters, C. M.↗

Thermodynamics of the dipole-octupole pyrochlore magnet Ce 2 Hf 2 O 7 in applied magnetic fields

The recently discovered dipole-octupole pyrochlore magnet Ce 2 Hf 2 O 7 is a promising three-dimensional quantum spin liquid candidate which shows no signs of ordering at low temperature. Here we investigate the thermodynamic response to magnetic fields applied along the global [110] direction using specific heat measurements and fits using numerical methods, and solve the corresponding magnetic structure using neutron diffraction. Specific heat data in moderate fields are reproduced well, however, at high fields the agreement is not satisfactory. We especially observe a two-step release of entropy, a finding that demands a review of both theory and experiment. We address it within the framework of three possible scenarios, including an analysis of the crystal field Hamiltonian not restricted to the two-dimensional single-ion doublet subspace. We conclusively rule out two of these scenarios and find qualitative agreement with a simple model of field misalignment with respect to the crystalline direction. As a result, we discuss the implications of our findings for [111] applied fields and for future experiments on Ce 2 Hf 2 O 7 and its sister compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Comparison of Flow-Dependent and Static Error Correlation Models in the DAO Ozone Data Assimilation System

In a data assimilation system the forecast error covariance matrix governs the way in which the data information is spread throughout the model grid. Implementation of a correct method of assigning covariances is expected to have an impact on the analysis results. The simplest models assume that correlations are constant in time and isotropic or nearly isotropic. In such models the analysis depends on the dynamics only through assumed error standard deviations. In applications to atmospheric tracer data assimilation this may lead to inaccuracies, especially in regions with strong wind shears or high gradient of potential vorticity, as well as in areas where no data are available. In order to overcome this problem we have developed a flow-dependent covariance model that is based on short term evolution of error correlations. The presentation compares performance of a static and a flow-dependent model applied to a global three- dimensional ozone data assimilation system developed at NASA s Data Assimilation Office. We will present some results of validation against WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres and in the troposphere. We will also discuss statistical characteristics of both models; in particular we will argue that including evolution of error correlations leads to stronger internal consistency of a data assimilation ,

Wargan, K.↗

Comparing Gravity Waves in a Kilometer‐Scale Run of the IFS to AIRS Satellite Observations and ERA5

Abstract Atmospheric gravity waves (GWs) impact the circulation and variability of the atmosphere. Sub‐grid scale GWs, which are too small to be resolved, are parameterized in weather and climate models. However, some models are now available at resolutions at which these waves become resolved and it is important to test whether these models do this correctly. In this study, a GW resolving run of the European Center for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), run with a 1.4 km average grid spacing (TCo7999 resolution), is compared to observations from the Atmospheric Infrared Sounder (AIRS) instrument, on NASA's Aqua satellite, to test how well the model resolves GWs that AIRS can observe. In this analysis, nighttime data are used from the first 10 days of November 2018 over part of Asia and surrounding regions. The IFS run is resampled with AIRS's observational filter using two different methods for comparison. The ECMWF ERA5 reanalysis is also resampled as AIRS, to allow for comparison of how the high resolution IFS run resolves GWs compared to a lower resolution model that uses GW drag parametrizations. Wave properties are found in AIRS and the resampled models using a multi‐dimensional S‐Transform method. Orographic GWs can be seen in similar locations at similar times in all three data sets. However, wave amplitudes and momentum fluxes in the resampled IFS run are found to be significantly lower than in the observations. This could be a result of horizontal and vertical wavelengths in the IFS run being underestimated.

Meteorology & Atmospheric Sciences↗

3-D CFD in a day - The laser digitizer project

The computation of airflow over complex configurations requires a complete description of the geometry. This can be obtained from CAD data, from blueprints, or from actual models. In any case, the time required is currently estimated at 4 to 6 months. It is proposed to shorten this time by a factor of 10 to 100 through the use of automated software, a fast, highly parallel computer and a three-dimensional laser digitizer. This device can provide (x,y,z) coordinates of surface points at rates exceeding 14,500/sec. Thus, it is possible to digitize an entire model in a few minutes. The accuracy of measurement on a flat white surface is better than 0.005 inches. Higher accuracy is available at higher cost. This work discusses the challenges which remain to be addressed. In particular, the surface point data need to be converted into a surface description, the surface description needs to be made into a surface grid, and the surface grid used to make a volume grid for the flow solver. Algorithms are kept in place or in mind for all of these problems. Integration of the more mature flow solution and visualization algorithms then allows generation of solution graphics directly from a wind tunnel model.

Merriam, Marshal↗

A high resolution spatial and temporal multiple Doppler analysis of a microburst and its application to aircraft flight simulation

Multiple Doppler radar data collected during the Joint Airport Weather Studies (JAWS) Project is used to synthesize the three-dimensional wind in the region of a microburst. The particular microburst used in this study is the strongest one to date for which three-dimensional winds have been recovered. As a diagnostic tool, a six-DOF numerical aircraft model having characteristics similar to 727 series aircraft is used to investigate jet transport aircraft response to observed microburst winds during simulated approaches and departures. Simple pilot control laws are used to adjust thrust, pitch, roll, and yaw so as to maintain given approach or departure parameters. Generally, when horizontal wind shear along the approach or departure path is 0.01/s or greater, the model is unable to maintain the desired approach path and suffers a significant reduction in climb performance during a go-around or departure. Although the mean wind shear along a path gives a good qualitative measure of the wind shear threat to a jet transport, different paths with similar mean shears can yield markedly different results, as do the same paths through the microburst at different times. These findings are a direct consequence of the fine temporal and spatial scale of microburst winds. During any given modeled aircraft traverse through the region of highest horizontal shear, time variations in the microburst wind field are shown to have an insignificant effect on the modeled flight path. This is because the traverse period is short (30 s) compared to the lifetime of a microburst (300-600 s).

Elmore, K. L.↗

The solution of the three-dimensional viscous-compressible Navier-Stokes equations on a vector computer

The development of a vectorized computer code for the solution of the three-dimensional viscous-compressible Navier-Stokes equations is described. The code is applied on the CDC STAR-100 vector computer which is capable of achieving high result rates when a high degree of parallelism is present in the computations. The computational technique is an explicit time-split MacCormack predictor-corrector algorithm. Since a large volume of data is processed and virtual memory utilized, a data management scheme based on interleaving is used. The program has been applied to obtain the solution of the laminar supersonic flow about a family of three-dimensional corners. The equations of motion are expressed in a generalized form relative to a uniform rectangular computational domain. The metric coefficient and boundary conditions must be supplied for the corresponding physical domain. For calculations with 30,000 grid points, a computational rate of 0.00015 seconds per grid point per time step is observed.

Smith, R. E.↗

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗

Can cluster environment modify the dynamical evolution of spiral galaxies?

Over the past decade many effects of the cluster environment on member galaxies have been established. These effects are manifest in the amount and distribution of gas in cluster spirals, the luminosity and light distributions within galaxies, and the segregation of morphological types. All these effects could indicate a specific dynamical evolution for galaxies in clusters. Nevertheless, a more direct evidence, such as a different mass distribution for spiral galaxies in clusters and in the field, is not yet clearly established. Indeed, Rubin, Whitmore, and Ford (1988) and Whitmore, Forbes, and Rubin (1988) (referred to as RWF) presented evidence that inner cluster spirals have falling rotation curves, unlike those of outer cluster spirals or the great majority of field spirals. If falling rotation curves exist in centers of clusters, as argued by RWF, it would suggest that dark matter halos were absent from cluster spirals, either because the halos had become stripped by interactions with other galaxies or with an intracluster medium, or because the halos had never formed in the first place. Even if they didn't disagree with RWF, other researchers pointed out that the behaviour of the slope of the rotation curves of spiral galaxies (in Virgo) is not so clear. Amram, using a different sample of spiral galaxies in clusters, found only 10% of declining rotation curves (2 declining vs 17 flat or rising) in opposition to RWF who find about 40% of declining rotation curves in their sample (6 declining vs 10 flat or rising), we will hereafter briefly discuss the Amram data paper and compare it to the results of RWF. We have measured the rotation curves for a sample of 21 spiral galaxies in 5 nearby clusters. These rotation curves have been constructed from detailed two-dimensional maps of each galaxy's velocity field as traced by emission from the Ha line. This complete mapping, combined with the sensitivity of our CFHT 3.60 m. + Perot-Fabry + CCD observations, allows the construction of high-quality rotation curves. Details concerning the acquisition and reduction procedures of the data are given in Amram. We present and discuss our preliminary analysis and compare them with RWF's results.

Amram, P.↗

Global Aeroheating Measurements of Shock-Shock Interactions on a Swept Cylinder

The effects of fin leading-edge radius and sweep angle on peak heating rates due to shock-shock interactions were investigated in the NASA Langley Research Center 20-Inch Mach 6 Air Tunnel. The cylindrical leading-edge fin models, with radii varied from 0.25 to 0.75 inches, represent wings or struts on hypersonic vehicles. A 9deg wedge generated a planar oblique shock at 16.7deg. to the flow that intersected the fin bow shock, producing a shock-shock interaction that impinged on the fin leading edge. The fin sweep angle was varied from 0deg (normal to the free-stream) to 15deg and 25deg swept forward. These cases were chosen to explore three characterized shock-shock interaction types. Global temperature data were obtained from the surface of the fused silica fins using phosphor thermography. Metal oil flow models with the same geometries as the fused silica models were used to visualize the streamline patterns for each angle of attack. High-speed zoom-schlieren videos were recorded to show the features and any temporal unsteadiness of the shock-shock interactions. The temperature data were analyzed using a one-dimensional semi-infinite method, as well as one- and two-dimensional finite-volume methods. These results were compared to determine the proper heat transfer analysis approach to minimize errors from lateral heat conduction due to the presence of strong surface temperature gradients induced by the shock interactions. The general trends in the leading-edge heat transfer behavior were similar for each explored shock-shock interaction type regardless of the leading-edge radius. However, the dimensional peak heat transfer coefficient augmentation increased with decreasing leading-edge radius. The dimensional peak heat transfer output from the two-dimensional code was about 20% higher than the value from a standard, semi-infinite one-dimensional method.

Mason, Michelle L.↗

On-board Neural Processor Design for an Intelligent Multi-sensor Microspacecraft

A compact VLSI neural processor based on the Optimization Cellular Neural Network (OCNN)has been under development to provide a wide range of support for an intelligent remote sensing microspacecraft which requires both high bandwidth communication and high-performance computing for on-board data analysis, thematic data reduction, synergy of multiple types of sensors, and other smart-sensor functions. The OCNN architecture is a programmable multi-dimensional array of neurons which are locally connected with their local neurons. The OCNN operation theory, architecture, design and implementation, prototype chip, and system applications have been investigated in detail and presented in this paper.

array↗

Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning

We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity partial differential equation (PDE) models governed by autonomous dynamical systems, leading to large-scale forward problems; (2) they solve a linear inverse problem to assimilate observational data to infer uncertain model components followed by a forward prediction of the evolving dynamics; and (3) the entire end-to-end, data-to-inference-to-prediction computation is carried out without approximation and in real time through a Bayesian framework that rigorously accounts for uncertainties. Several challenges must be overcome to realize this framework, including the large scale of the forward problem, the high dimensionality of the parameter space, and for a class of problems including those we target, the slow decay of the singular values of the parameter-to-observable map. Here we introduce a methodology to overcome these challenges by exploiting the autonomous structure of the forward model to decompose the solution of the inverse problem into a one-time-only offline phase in which the PDE model is solved a limited number of times (equal to the number of sensors), and an online phase that maps well onto GPUs and computes the parameter inference and prediction of quantities of interest in real time, given observational data. Our ultimate goal is to apply this framework to construct digital twins for subduction zones, including Cascadia, to provide early warning for tsunamis generated by megathrust earthquakes. To this end, we demonstrate how our methodology can be used to employ seafloor pressure observations, along with the coupled acoustic–gravity wave equations, to infer the earthquake-induced spatiotemporal seafloor motion (discretized with $\mathscr{O}$ (10 9 ) parameters) and forward predict the tsunami propagation. We present results of an end-to-end inference, prediction, and uncertainty quantification for a representative test problem with $\mathscr{O}$ (10 8 ) inversion parameters for which goal-oriented Bayesian inference is accomplished exactly and in real time, that is, in a matter of seconds.

97 MATHEMATICS AND COMPUTING↗

An experimental investigation of a low Reynolds number turbulent boundary layer subject to an adverse pressure gradient

A very low Reynolds number turbulent boundary layer subject to an adverse pressure gradient is studied. The aim is to obtain highly accurate mean-flow and turbulence measurements under conditions that can be closely related to the numerical simulations of Philippe Spalart for the purposes of CFD validation. Much of the Boundary Layer Wind Tunnel was completely rebuilt with a new wider contraction and working section which will improve compatibility with the simulations. A unique sophisticated high-speed computer controlled 3-D probe traversing mechanism was integrated into the test section. Construction of the tunnel and traverse is discussed in some detail. The hardware is now complete, and measurements are in progress. The mean-flow data indicate that a suitably two-dimensional base flow was established. Automation of the probe positioning and data acquistion have led to a decreased running time for total pressure measurements. However, the most significant benefits are expected to occur when using hot-wire probes. Calibrations can be performed automatically and there is no need to handle fragile probes when moving between measuring stations. Techniques are being developed which require sampling of the signals from moving hot-wire probes on the basis of their position in the flow. Measurements can be made in high intensity turbulence by flying probes upstream at high speed so that the relative magnitude of the turbulent velocity fluctuations are reduced. In regions, where the turbulence intensity is not too large, the probe can also be repetitively scanned across very dense spatial grids in other directions. With this technique, a complete profile can be measured in about 1/3 the time and with a spatial density about 50 times that obtainable using a stationary probe.

Watmuff, Jonathan H.↗

A fast and accurate domain decomposition nonlinear manifold reduced order model

Here, this paper integrates nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD). NM ROMs approximate the full order model (FOM) state in a nonlinear-manifold by training a shallow, sparse autoencoder using FOM snapshot data. These NM-ROMs can be advantageous over linear-subspace ROMs (LS-ROMs) for problems with slowly decaying Kolmogorov n-width. However, the number of NM-ROM parameters that need to be trained scales with the size of the FOM. Moreover, for “extreme-scale” problems, the storage of high-dimensional FOM snapshots alone can make ROM training expensive. To alleviate the training cost, this paper applies DD to the FOM, computes NM-ROMs on each subdomain, and couples them to obtain a global NM-ROM. This approach has several advantages: Subdomain NM-ROMs can be trained in parallel, involve fewer parameters to be trained than global NM-ROMs, require smaller subdomain FOM dimensional training data, and can be tailored to subdomain specific features of the FOM. The shallow, sparse architecture of the autoencoder used in each subdomain NM-ROM allows application of hyper-reduction (HR), reducing the complexity caused by nonlinearity and yielding computational speedup of the NM-ROM. This paper provides the first application of NM-ROM (with HR) to a DD problem. In particular, this paper details an algebraic DD reformulation of the FOM, training a NM-ROM with HR for each sub domain, and a sequential quadratic programming (SQP) solver to evaluate the coupled global NM-ROM. Theoretical convergence results for the SQP method and a priori and a posteriori error estimates for the DD NM-ROM with HR are provided. The proposed DD NM-ROM with HR approach is numerically compared to a DD LS-ROM with HR on the 2D steady-state Burgers’ equation, showing an order of magnitude improvement in accuracy of the proposed DD NM-ROM over the DD LS-ROM.

97 MATHEMATICS AND COMPUTING↗

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗

DESI DR1 Ly α 1D power spectrum: Validation of estimators

The Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI) is the largest sample to date for small-scale Lyα forest cosmology, accessed through its one-dimensional power spectrum (P 1D ). The Lyα forest P 1D is extracted from quasar spectra that are highly inhomogeneous (both in wavelength and between quasars) in noise properties due to intrinsic properties of the quasar, atmospheric and astrophysical contamination, and also sensitive to low-level details of the spectral extraction pipeline. We employ two estimators in DR1 analysis to measure P 1D : the optimal estimator and the fast Fourier transform (FFT) estimator. To ensure robustness of our DR1 measurements, we validate these two power spectrum and covariance matrix estimation methodologies against the challenging aspects of the data. First, using a set of 20 synthetic 1D realizations of DR1, we derive the masking bias corrections needed for the FFT estimator and the continuum fitting bias needed for both estimators. We demonstrate that both estimators, including their covariances, are unbiased with these corrections using the Kolmogorov-Smirnov test. Second, we substantially extend our previous suite of CCD image simulations to include 675,000 quasars, allowing us to accurately quantify the pipeline's performance. This set of simulations reveals biases at the highest k values, corresponding to a resolution error of a few percent. We base the resolution systematics error budget of DR1 P 1D on these values, but do not derive corrections from them since the simulation fidelity is insufficient for precise corrections.

Lyman alpha forest↗

Investigation of arterial gas occlusions

The effect of noncondensable gases on high-performance arterial heat pipes was investigated both analytically and experimentally. Models have been generated which characterize the dissolution of gases in condensate, and the diffusional loss of dissolved gases from condensate in arterial flow. These processes, and others, were used to postulate stability criteria for arterial heat pipes under isothermal and non-isothermal condensate flow conditions. A rigorous second-order gas-loaded heat pipe model, incorporating axial conduction and one-dimensional vapor transport, was produced and used for thermal and gas studies. A Freon-22 (CHCIF2) heat pipe was used with helium and xenon to validate modeling. With helium, experimental data compared well with theory. Unusual gas-control effects with xenon were attributed to high solubility.

Saaski, E. W.↗

Unveiling the nature of Ga-based chalcogenides for electrical switching selectors

Three-dimensional phase-change memory with stackable crossbar architecture is a promising technology to meet the urgent demands for high-density storage and rapid information processing in the era of explosive data growth. The performance depends strongly on the properties of ovonic threshold switching (OTS) selectors, which control the on/off states of memory units. Amorphous GaS serves as an outstanding OTS material, distinguished by its sizable mobility gap and high crystallization temperature, while the underlying mechanism continues to be inadequately comprehended. Here, in this work, we systematically studied the structural and electronic properties of amorphous Ga-X (X = S/Se/Te) using first-principles calculations. The results show that Ga atoms adopt tetrahedral motifs, while S/Se/Te atoms predominantly exhibit the structure of a distorted triangular pyramid. This structural arrangement is ascribed to the substantial dative bonds formed by the lone-pair electrons of the anions and the vacant sp3 orbitals around Ga atoms. Large mobility gaps (e.g., GaS: 2.43 eV, GaSe: 1.76 eV, GaTe: 1.26 eV) and distinct mid-gap states (e.g., ∼0.66 eV above valence band tail) ensure that these three chalcogenide glasses can be switched on under an external electric field while effectively suppressing leakage current without a bias, and the defect electronic states originate from short, robust Ga-Ga bonds due to the formation of distorted chain-like local structures. Our research elucidates the mechanisms of amorphous Ga-X as OTS materials, enriching the spectrum of electrical switching selectors by incorporating III-VI chalcogenides. This inclusion offers novel opportunities for the refinement and optimization of high-density integrated memory systems.

36 MATERIALS SCIENCE↗