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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Does jackknife scale really matter for accurate large-scale structure covariances?

ABSTRACT The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings impact the precision of the covariance estimate on the correlation function multipoles and the error on the inferred baryon acoustic scale. We compare the measurement with the MultiDark Patchy mock galaxy catalogues, and we also validate it against a set of lognormal mocks with the same survey geometry. We build several jackknife configurations that vary in size and number of resamplings. We introduce the Hartlap factor in the covariance estimate that depends on the number of jackknife resamplings. We also find that it is useful to apply the tapering scheme to estimate the precision matrix from a limited number of resamplings. The results from CMASS and mock catalogues show that the error estimate of the baryon acoustic scale does not depend on the jackknife scale. For the shift parameter α, we find an average error of 1.6 per cent, 2.2 per cent and 1.2 per cent, respectively, from CMASS, Patchy, and lognormal jackknife covariances. Despite these uncertainties fluctuate significantly due to some structural limitations of the jackknife method, our α estimates are in reasonable agreement with published pre-reconstruction analyses. Jackknife methods will provide valuable and complementary covariance estimates for future large-scale structure surveys.

Favole, Ginevra (ORCID:000000028218563X)↗
DOE OSTI2023

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. Furthermore, we observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Joint iterative reconstruction and 3D rigid alignment for X-ray tomography

X-ray tomography is widely used for three-dimensional structure determination in many areas of science, from the millimeter to the nanometer scale. The resolution and quality of the 3D reconstruction is limited by the availability of alignment parameters that correct for the mechanical shifts of the sample or sample stage for the images that constitute a scan. In this paper we describe an algorithm for marker-free, fully automated and accurately aligned and reconstructed X-ray tomography data. Our approach solves the tomographic reconstruction jointly with projection data alignment based on a rigid-body deformation model. We demonstrate the robustness of our method on both synthetic phantom and experimental data and show that our method is highly efficient in recovering relatively large alignment errors without prior knowledge of a low resolution approximation of the 3D structure or a reasonable estimate of alignment parameters.

36 MATERIALS SCIENCE↗
NASA NTRS1994

An assessment of image reconstruction from balloon-borne and the IRAS data

Angular resolution and structural information from the far-infrared mapping of astronomical sources (Galactic star forming regions, spiral galaxies, etc.) made using the TIFR 1 m balloon-borne telescope and the IRAS have been compared. The effective wavelengths of the TIFR two-band photometer are 58 and 150 microns. From IRAS, the survey COADD data, additional observations (AO's) made with the survey detectors with different Macros (DPS, DSD, DPM), as well as the chopped photometric channel (CPC) data have been considered here. The observed signals have been processed using different deconvolution strategies, either based on a maximum entropy method (MEM) developed at TIFR or the HiRes package developed at IPAC. Relative merits of each of these, under different conditions of signal to noise ratio, are highlighted. The following sources have been selected for illustration: Carina complex, W31 region, IRAS 10361-5830 (all Galactic), M101 and M81 (extragalactic). The main conclusions are: far-infrared maps from MEM deconvolution of balloon-borne data have the best angular resolution; MEM deconvolution of IRAS AO's gives resolution comparable to HiRes but with less amount of computation, though the dynamic range in MEM maps is less than in HiRes maps.

Ghosh, S. K.↗
NASA NTRS1994

Testing the gravitational instability hypothesis?

We challenge a widely accepted assumption of observational cosmology: that successful reconstruction of observed galaxy density fields from measured galaxy velocity fields (or vice versa), using the methods of gravitational instability theory, implies that the observed large-scale structures and large-scale flows were produced by the action of gravity. This assumption is false, in that there exist nongravitational theories that pass the reconstruction tests and gravitational theories with certain forms of biased galaxy formation that fail them. Gravitational instability theory predicts specific correlations between large-scale velocity and mass density fields, but the same correlations arise in any model where (a) structures in the galaxy distribution grow from homogeneous initial conditions in a way that satisfies the continuity equation, and (b) the present-day velocity field is irrotational and proportional to the time-averaged velocity field. We demonstrate these assertions using analytical arguments and N-body simulations. If large-scale structure is formed by gravitational instability, then the ratio of the galaxy density contrast to the divergence of the velocity field yields an estimate of the density parameter Omega (or, more generally, an estimate of beta identically equal to Omega(exp 0.6)/b, where b is an assumed constant of proportionality between galaxy and mass density fluctuations. In nongravitational scenarios, the values of Omega or beta estimated in this way may fail to represent the true cosmological values. However, even if nongravitational forces initiate and shape the growth of structure, gravitationally induced accelerations can dominate the velocity field at late times, long after the action of any nongravitational impulses. The estimated beta approaches the true value in such cases, and in our numerical simulations the estimated beta values are reasonably accurate for both gravitational and nongravitational models. Reconstruction tests that show correlations between galaxy density and velocity fields can rule out some physically interesting models of large-scale structure. In particular, successful reconstructions constrain the nature of any bias between the galaxy and mass distributions, since processes that modulate the efficiency of galaxy formation on large scales in a way that violates the continuity equation also produce a mismatch between the observed galaxy density and the density inferred from the peculiar velocity field. We obtain successful reconstructions for a gravitational model with peaks biasing, but we also show examples of gravitational and nongravitational models that fail reconstruction tests because of more complicated modulations of galaxy formation.

Babul, Arif↗
NASA NTRS1979

Space shuttle active-pogo-suppressor control design using linear quadratic regulator techniques

Two methods of active pogo suppression (stabilization) for the space shuttle vehicle were studied analytically. The basis for both approaches was the linear quadratic regulator, state space technique. The first approach minimized root-mean-square pump inlet pressure by using either fullstate feedback, partial-state feedback, or output feedback with a Kalman filter. The second approach increased the modal damping associated with the critical structural modes by using either full-state feedback or reconstructed state feedback. A number of implementable controls were found by both approaches. The designs were analyzed with respect to sensitivity, complexity, and controller energy requirements, as well as controller performance. Practical controllers resulting from the two design approaches tended to use pressure and flow as feedback variables for the minimum-rms method and structural accelerations or velocities for the modal control method. Both approaches are suitable for the design of active pogo-suppression controllers.

Lehtinen, B.↗
DOE OSTI2023

Ringing Artifact Reduction Method for Ultrasound Reconstruction Using Multi-Agent Consensus Equilibrium

Non-destructive characterization of multi-layered structures that can be accessed from only a single side is important for applications such as well-bore integrity inspection. Existing methods related to Synthetic Aperture Focusing Technique (SAFT) rapidly produce acceptable results but with significant artifacts. Recently, ultrasound model-based iterative reconstruction (UMBIR) approaches have shown significant improvements over SAFT. However, even these methods produce ringing artifacts due to the high fractional-bandwidth of the excitation signal.In this paper, we propose a ringing artifact reduction method for ultrasound image reconstruction that uses a multi-agent consensus equilibrium (RARE-MACE) framework. Our approach integrates a physics-based forward model that accounts for the propagation of a collimated ultrasonic beam in multi-layered media, a spatially varying image prior, and a denoiser designed to suppress the ringing artifacts that are characteristic of reconstructions from high-fractional bandwidth ultrasound sensor data. We test our method on simulated and experimental measurements and show substantial improvements in image quality compared to SAFT and UMBIR.

Alanazi, Abdulrahman M↗
DOE OSTI2024

Alkali cation-induced cathodic corrosion in Cu electrocatalysts

The reconstruction of Cu catalysts during electrochemical reduction of CO 2 is a widely known but poorly understood phenomenon. Herein, we examine the structural evolution of Cu nanocubes under CO 2 reduction reaction and its relevant reaction conditions using identical location transmission electron microscopy, cyclic voltammetry, in situ X-ray absorption fine structure spectroscopy and ab initio molecular dynamics simulation. Our results suggest that Cu catalysts reconstruct via a hitherto unexplored yet critical pathway - alkali cation-induced cathodic corrosion, when the electrode potential is more negative than an onset value (e.g., –0.4 V RHE when using 0.1 M KHCO 3 ). Having alkali cations in the electrolyte is critical for such a process. Consequently, Cu catalysts will inevitably undergo surface reconstructions during a typical process of CO 2 reduction reaction, resulting in dynamic catalyst morphologies. While having these reconstructions does not necessarily preclude stable electrocatalytic reactions, they will indeed prohibit long-term selectivity and activity enhancement by controlling the morphology of Cu pre-catalysts. Alternatively, by operating Cu catalysts at less negative potentials in the CO electrochemical reduction, we show that Cu nanocubes can provide a much more stable selectivity advantage over spherical Cu nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modeling Nondestructive Defect Detection in Additively Manufactured Metallic Structures for Nuclear Applications

The future of quickly, economically produced metallic nuclear reactor parts with minimal supply-chain dependence lies in Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM): a 3D printing method involving laser melting and net shaping stainless steel and Inconel metallic powder into a solid structure. However, intrinsic features in LPBF frequently leads to the formation of materials defects, such as pores, within 3D printed structures. As safe long-term use in energy applications requires knowledge of all relevant defects before deployment in a reactor, we must develop methods for nondestructive detection of these defects. We are investigating Pulsed Thermal Tomography (PTT), which is a non-contact nondestructive imaging method scalable to arbitrary structure size. Thermal tomography (TT) is a computational method for 3D spatial reconstruction of material thermal effusivity from flash or pulsed thermography temperature data cube. Thermography data cube consists of 2D surface temperature measurements at different times. The objective of the present work is to investigate limits on defect detection in AM metallic structures with PTT. To this effect, we modeled PTT with COMSOL heat transfer computer simulations. We developed a layered media COMSOL simulation consisting of a Stainless Steel 316 (SS316) plate with an internal layer of un-sintered SS316 powder. Thermophysical properties of the powder layer were modeled with equivalent volume mixing model. To account for partial sintering at the boundary of the defect, the transition between solid and powder layers was modeled as a Gaussian. Using data from COMSOL simulations, we reconstructed depth-dependent thermal effusivity, which allowed defect visibility estimation. A series of parametric studies determined that at 1mm depth, 50µm is the smallest detectable defect. In addition, classification of the defects which can lead to early fatigue of the metallic structure in a reactor is briefly discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

LIF measurements of scalar mixing in turbulent shear layers

The structure of shear layer flows at high Reynolds numbers remains a very interesting problem. Straight mixing layers have been studied and yielded information on the probability density function (pdf) of a passive scalar across the layer. Konrad and Koochesfahani & Dimotakis measured the pdf of the mixture fraction for mixing layers of moderate Reynolds numbers, each about 25,000 (Re based on velocity difference and visual thickness). Their measurements showed a 'non-marching' pdf (central hump which is invariant from edge to edge across the layer), a result which is linked to the visualizations of the spanwise Kelvin-Helmholtz (K-H) instability mode, which is the primary instability for plane shear layer flows. A secondary instability mode, the Taylor-Gortler (T-G) instability, which is associated with streamwise vortical structures, has also been observed in shear layers. Image reconstruction by Jimenez et al. and volume renderings by Karasso & Mungal at low Re numbers have demonstrated that the K-H and the T-G instability modes occur simultaneously in a non-mutually destructive way, evidence that supports the quasi two-dimensional aspect of these flows and the non-marching character of the pdf at low Reynolds numbers. At higher Re numbers though, the interaction of these two instability modes is still unclear and may affect the mixing process. In this study, we perform measurements of the concentration pdf of plane mixing layers for different operating conditions. At a speed ratio of r = U(sub 1)/U(sub 2) = 4:1, we examine three Reynolds number cases: Re = 14,000, Re = 31,000, and Re = 62,000. Some other Re number cases' results, not presented in detail, are invoked to explain the behavior of the pdf of the concentration field. A case of r = 2.6:1 at Re = 20,000 is also considered. The planar laser-induced fluorescence technique is used to yield quantitative measurements. The different Re are obtained by changing the velocity magnitudes of the two streams. The question of resolution of these measurements is addressed. In order to investigate the effects of the initial conditions on the development and the structure of the mixing layer, the boundary layer on the high-speed side of the splitter plate is tripped. The average concentration and the average mixed fluid concentration are also calculated to further understand the changes in the shear layer for the different cases examined.

Karasso, Paris S.↗
DOE OSTI2025

Machine‐Learning‐Driven Exploration of Surface Reconstructions of Reduced Rutile TiO 2

Titanium dioxide (TiO 2 ) is widely used as a catalyst support due to its stability, tunable electronic properties, and surface oxygen vacancies, which are crucial for catalytic processes such as the reverse water-gas shift (RWGS) reaction. Reduced TiO 2 surfaces undergo complex surface reconstructions that endow unique properties but are computationally challenging to describe. In this study, we utilize machine-learning interatomic potentials (MLIPs) integrated with an active-learning workflow to efficiently explore reduced rutile TiO 2 surfaces. This approach enabled the prediction of a phase diagram as a function of oxygen chemical potential, revealing a variety of reconstructed phases, including a previously unreported subsurface shear plane structure. We further investigate the electronic properties of these surfaces and validate our results by comparing experimental and theoretical high-resolution transmission electron microscopy (HRTEM). Our findings provide new insights into how extreme surface reductions influence the structural and electronic properties of TiO 2 , with potential implications for catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural anisotropy in Sb thin films

Sb thin films have attracted wide interest due to their tunable band structure, topological phases, high electron mobility, and thermoelectric properties. We successfully grow epitaxial Sb thin films on a closely lattice-matched GaSb(001) surface by molecular beam epitaxy. We find a novel anisotropic directional dependence on their structural, morphological, and electronic properties. The origin of the anisotropic features is elucidated using first-principles density functional theory (DFT) calculations. The growth regime of crystalline and amorphous Sb thin films was determined by mapping the surface reconstruction phase diagram of the GaSb(001) surface under Sb 2 flux, with confirmation of structural characterizations. Crystalline Sb thin films show a rhombohedral crystal structure along the rhombohedral (211) surface orientation parallel to the cubic (001) surface orientation of the GaSb substrate. At this coherent interface, Sb atoms are aligned with the GaSb lattice along the [1̄10] crystallographic direction but are not aligned well along the [110] crystallographic direction, which results in anisotropic features in reflection of high-energy electron diffraction patterns, misfit dislocation formation, surface morphology, and transport properties. Our DFT calculations show that the preferential orientation of the rhombohedral Sb (211) plane may originate from the GaSb surface, where Sb atoms align with the Ga and Sb atoms on the reconstructed surface. The formation energy calculations confirm the stability of the experimentally observed structures. Our results provide optimal film growth conditions for further studies of novel properties of Bi 1-x Sb x thin films with similar lattice parameters and an identical crystal structure, as well as functional heterostructures of them with III–V semiconductor layers along the (001) surface orientation, supported by a theoretical understanding of the anisotropic film orientation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Physics-Informed Deep Learning for Reconstruction of Spatial Missing Climate Information in the Antarctic

Understanding the influence of the Antarctic on the global climate is crucial for the prediction of global warming. However, due to very few observation sites, it is difficult to reconstruct the rational spatial pattern by filling in the missing values from the limited site observations. To tackle this challenge, regional spatial gap-filling methods, such as Kriging and inverse distance weighted (IDW), are regularly used in geoscience. Nevertheless, the reconstructing credibility of these methods is undesirable when the spatial structure has massive missing pieces. Inspired by image inpainting, we propose a novel deep learning method that demonstrates a good effect by embedding the physics-aware initialization of deep learning methods for rapid learning and capturing the spatial dependence for the high-fidelity imputation of missing areas. We create the benchmark dataset that artificially masks the Antarctic region with ratios of 30%, 50% and 70%. The reconstructing monthly mean surface temperature using the deep learning image inpainting method RFR (Recurrent Feature Reasoning) exhibits an average of 63% and 71% improvement of accuracy over Kriging and IDW under different missing rates. With regard to wind speed, there are still 36% and 50% improvements. In particular, the achieved improvement is even better for the larger missing ratio, such as under the 70% missing rate, where the accuracy of RFR is 68% and 74% higher than Kriging and IDW for temperature and also 38% and 46% higher for wind speed. In addition, the PI-RFR (Physics-Informed Recurrent Feature Reasoning) method we proposed is initialized using the spatial pattern data simulated by the numerical climate model instead of the unified average. Compared with RFR, PI-RFR has an average accuracy improvement of 10% for temperature and 9% for wind speed. When applied to reconstruct the spatial pattern based on the Antarctic site observations, where the missing rate is over 90%, the proposed method exhibits more spatial characteristics than Kriging and IDW.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Four dimensional reconstruction and analysis of plume images

A number of methods have been investigated and are under current investigation for monitoring the health of the Space Shuttle Main Engine (SSME). Plume emission analysis has recently emerged as a potential technique for correlating the emission characteristics with the health of an engine. In order to correlate the visual and spectral signatures of the plume emission with the characteristic health monitoring features of the engine, the plume emission data must be acquired, stored, and analyzed in a manner similar to flame emission spectroscopy. The characteristic visual and spectral signatures of the elements vaporized in exhaust plume along with the features related to their temperature, pressure, and velocity can be analyzed once the images of plume emission are effectively acquired, digitized, and stored on a computer. Since the emission image varies with respect to time at a specified planar location, four dimensional visual and spectral analysis need to be performed on the plume emission data. In order to achieve this objective, feasibility research was conducted to digitize, store, analyze, and visualize the images of a subsonic jet in a cross flow. The jet structure was made visible using a direct injection flow visualization technique. The results of time-history based three dimensional reconstruction of the cross sectional images corresponding to a specific planar location of the jet structure are presented. The experimental set-up to acquire such data is described and three dimensional displays of time-history based reconstructions of the jet structure are discussed.

Dhawan, Atam P.↗
DOE OSTI2021

The growth of density perturbations in the last ~10 billion years from tomographic large-scale structure data

In order to investigate the origin of the ongoing tension between the amplitude of matter fluctuations measured by weak lensing experiments at low redshifts and the value inferred from the cosmic microwave background anisotropies, we reconstruct the evolution of this amplitude from z ~ 2 using existing large-scale structure data. To do so, we decouple the linear growth of density inhomogeneities from the background expansion, and constrain its redshift dependence making use of a combination of 6 different data sets, including cosmic shear, galaxy clustering and CMB lensing. We analyze these data under a consistent harmonic-space angular power spectrum-based pipeline. We show that current data constrain the amplitude of fluctuations mostly in the range 0.2 < z < 0.7, where it is lower than predicted by . This difference is mostly driven by current cosmic shear data, although the growth histories reconstructed from different data combinations are consistent with each other, and we find no evidence of systematic deviations in any particular experiment. In spite of the tension with , the data are well-described by the model, albeit with a lower value of S 8 ≡ σ 8 (Ω m /0.3) 0.5 . As part of our analysis, we find constraints on this parameter of S 8 = 0.7781 ± 0.0094 (68% confidence level), reaching almost percent-level errors comparable with CMB measurements, and 3.4σ away from the value found by .

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Multigrid properties of upwind-biased data reconstructions

The multigrid properties of two data reconstruction methods used for achieving second-order spatial accuracy when solving the two-dimensional Euler equations are examined. The data reconstruction methods are used with an implicit upwind algorithm which uses linearized backward-Euler time-differencing. The solution of the resulting linear system is performed by an iterative procedure. In the present study only regular quadrilateral grids are considered, so a red-black Gauss-Seidel iteration is used. Although the Jacobian is approximated by first-order upwind extrapolation, two alternative data reconstruction techniques for the flux integral that yield higher-order spatial accuracy at steady state are examined. The first method, probably most popular for structured quadrilateral grids, is based on estimating the cell gradients using one-dimensional reconstruction along curvilinear coordinates. The second method is based on Green's theorem. Analysis and numerical results for the two dimensional Euler equations show that data reconstruction based on Green's theorem has superior multigrid properties as compared to the one-dimensional data reconstruction method.

Warren, Gary P.↗
DOE OSTI2025

Machine‐Learning‐Driven Exploration of Surface Reconstructions of Reduced Rutile TiO 2

Abstract Titanium dioxide (TiO 2 ) is widely used as a catalyst support due to its stability, tunable electronic properties, and surface oxygen vacancies, which are crucial for catalytic processes such as the reverse water‐gas shift (RWGS) reaction. Reduced TiO 2 surfaces undergo complex surface reconstructions that endow unique properties but are computationally challenging to describe. In this study, we utilize machine‐learning interatomic potentials (MLIPs) integrated with an active‐learning workflow to efficiently explore reduced rutile TiO 2 surfaces. This approach enabled the prediction of a phase diagram as a function of oxygen chemical potential, revealing a variety of reconstructed phases, including a previously unreported subsurface shear plane structure. We further investigate the electronic properties of these surfaces and validate our results by comparing experimental and theoretical high‐resolution transmission electron microscopy (HRTEM). Our findings provide new insights into how extreme surface reductions influence the structural and electronic properties of TiO 2 , with potential implications for catalyst design.

Lee, Yonghyuk [Chemistry and Biochemistry Universi↗
DOE OSTI2021

Extended cycle life implications of fast charging for lithium-ion battery cathode

Enabling extreme fast charging (XFC, =10–15 min charging) requires a comprehensive understanding of its implications. While lithium plating is a key bottleneck for the anode, the full extent of limitations for the cathode are not well-understood, particularly in extended-cycle settings with well-defined battery designs and conditions. This article presents cycle-life implications of XFC on cathodes at multiple length scales, combining electrochemical analyses, degradation modeling, and post-test characterizations. The comprehensive test matrix includes 41 well-defined gr/NMC pouch cells under varied fast-charge rates (1–9C) and state-of-charges cycled up to 1000 times. Cathode issues remain minimal in early cycling, but begin to accelerate in later life, when distinct cracking is found and identified as a fatigue mechanism. The bulk structure of cathodes remains intact, but distinct particle surface reconstruction is observed; however, this shows less pronounced effect on cathode aging than does cracking.

25 ENERGY STORAGE↗