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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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At least 19 records

Crack detection in fuel cell electrodes using a spatial filtering technique for overcoming noisy backgrounds

Image processing is a powerful tool that allows for rapid and automated data parsing in settings that occupy large variable spaces and require large data sets. Feature detection on difficultly discerned backgrounds is a subset of image processing that facilitates the extraction of quantitative metrics from otherwise subjective data. Crack detection and quantification is an important capability in polymer electrolyte membrane fuel cell quality control, failure analysis, and optimization. This work presents a technique to perform crack detection and quantification which overcomes challenges faced by commonly used image segmentation techniques. We demonstrate the use of a geometrically filtered noise‐level detection technique to select a binary threshold value from which we then quantify how cracked a sample is. Furthermore, we demonstrate the accuracy of our technique using programmatically generated test images of known crack amounts and their performance on real‐world fuel cell catalyst layer samples.

30 DIRECT ENERGY CONVERSION↗

Filterscope Techniques for Parasitic Signal Screening

Here, the filterscope diagnostic uses bandpass filters and photomultiplier tubes (PMTs) to detect specific spectral emission lines. A filterscope was used to measure the W I 400.88 nm line emission as a function of ion energy on the Radio Frequency Plasma Interaction Experiment (RF PIE) for the purpose of assessing W erosion on plasma-facing components (PFCs). Different filter techniques are being explored and compared in order to effectively screen out nearby impurity lines, like the Ar II 401.39 nm line. The effectiveness of these techniques is determined by comparing the measurements to a high-resolution 1.0 m Czerny–Turner spectrometer with 0.012 nm spectral resolution. The ability to filter out nearby impurity emissions is useful when imaging PFCs in fusion devices including divertor and antenna guard limiters. Initial results with a helium plasma show little difference between the two techniques at higher bias voltages. In a helium plasma at lower dc bias voltages, a two-filter technique with filters at two separate wavelengths was shown to be more effective at screening out background signals. Data collected with an argon plasma however show the technique with overlapping filters on the line of interest is a closer match to spectrometer data at lower dc bias voltages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗

Consistent boundary conditions for PDE filter regularization in topology optimization

Abstract Design variables in density-based topology optimization are typically regularized using filtering techniques. In many cases, such as stress optimization, where details at the boundaries are crucially important, the filtering in the vicinity of the design domain boundary needs special attention. One well-known technique, often referred to as “padding,” is to extend the design domain with extra layers of elements to mitigate artificial boundary effects. We discuss an alternative to the padding procedure in the context of PDE filtering. To motivate this augmented PDE filter, we make use of the potential form of the PDE filter which allows us to add penalty terms with a clear physical interpretation. The major advantages of the proposed augmentation compared with the conventional padding is the simplicity of the implementation and the possibility to tune the boundary properties using a scalar parameter. Analytical results in 1D and numerical results in 2D and 3D confirm the suitability of this approach for large-scale topology optimization.

42 ENGINEERING↗

Surface Variability Mapping and Roughness Analysis of the Moon Using a Coarse–Graining Decomposition

The lunar surface contains a wide variety of topographic shapes and features, each with different distributions and scales, and any analysis technique to objectively measure roughness must respect these qualities. Coarse-graining is a naturally scale-dependent filtering technique that preserves scale-dependent symmetries and produces coarse elevation maps that gradually erase the smaller features from the original topography. In this study of the lunar surface, we present two surface variability metrics obtained from coarse-graining lunar topography: fine elevation and coarse curvature. Both metrics are isotropic, deterministic, slope-independent, and coordinate-agnostic. Fine (detrended) elevation is acquired by subtracting the coarse elevation from the original topography and contains features that are smaller than the coarse-graining length-scale. Coarse curvature is the Laplacian of coarsened topography, and naturally quantifies the curvature at any scale and indicates whether a location is elevated or depressed relative to its neighborhood at that scale. We find that highlands and maria have distinct roughness characteristics at all length-scales. Our topographic spectra reveal four scale-breaks that mark characteristic shifts in surface roughness: 100, 300, 1,000, and 4,000 km. Comparing fine elevation distributions between maria and highlands, we show that maria fine elevation is biased toward smaller-magnitude elevations and that the maria–highland discrepancies are more pronounced at larger length-scales. Here, we also provide local examples of selected regions to demonstrate that these metrics can successfully distinguish geological features of different length-scales.

58 GEOSCIENCES↗

Procrustean entanglement concentration in quantum-classical networking

The success of a future quantum internet will rest in part on the ability of quantum and classical signals to coexist in the same optical fiber infrastructure, a challenging endeavor given the orders of magnitude differences in flux of single-photon-level quantum fields and bright classical traffic. Here, we theoretically describe and experimentally implement Procrustean entanglement concentration for polarization-entangled states contaminated with classical light, showing significant mitigation of crosstalk noise in dense wavelength-division multiplexing. Our approach leverages a pair of polarization-dependent loss emulators to attenuate highly polarized crosstalk that results from imperfect isolation of conventional signals copropagating on shared fiber links. We demonstrate our technique both on the tabletop and over a deployed quantum local area network, finding a substantial improvement of two-qubit entangled state fidelity from approximately 75% to over 92%. This local filtering technique could be used as a preliminary step to reduce asymmetric errors, potentially improving the overall efficiency when combined with more complex error-mitigation techniques in future quantum repeater networks.

97 MATHEMATICS AND COMPUTING↗

TARDIS. I. A Constrained Reconstruction Approach to Modeling the z ~ 2.5 Cosmic Web Probed by Lyα Forest Tomography

Recent Lyα forest tomography measurements of the intergalactic medium (IGM) have revealed a wealth of cosmic structures at high redshift (z ~ 2.5). In this work, we present the Tomographic Absorption Reconstruction and Density Inference Scheme (TARDIS), a new chronocosmographic analysis tool for understanding the formation and evolution of these observed structures. Here, we use maximum likelihood techniques with a fast nonlinear gravitational model to reconstruct the initial density field of the observed regions. We find that TARDIS allows accurate reconstruction of smaller-scale structures than standard Wiener-filtering techniques. Applying this technique to mock Lyα forest data sets that simulate ongoing and future surveys such as CLAMATO, Subaru PFS, or the ELTs, we are able to infer the underlying matter density field at observed redshift and classify the cosmic web structures. We find good agreement with the underlying truth in both the characteristic eigenvalues and eigenvectors of the pseudo-deformation tensor, with the eigenvalues inferred from 30 m class telescopes correlated at r = 0.95 relative to the truth. As an output of this method, we are able to further evolve the inferred structures to late time (z = 0) and also track the trajectories of coeval z = 2.5 galaxies to their z = 0 cosmic web environments.

79 ASTRONOMY AND ASTROPHYSICS↗

Experimental Modal Analysis Using Phase Quantities from Phase-Based Motion Processing and Motion Magnification

Phase-based motion processing and the associated Motion Magnification that it enables has become popular not only for the striking videos that it can produce of traditionally stiff structures visualized with very large deflections, but also for its ability to pull information out of the noise floor of images so that they can be processed with more traditional optical techniques such as digital image correlation or feature tracking. While the majority of papers in the literature have utilized the Phase-based Image Processing approach as a pre-processor for more quantitative analyses, the technique itself can be used directly to extract modal parameters from an image, noting that the extracted phases are proportional to displacements in the image. Therefore, once phases are extracted, they can be fit using traditional experimental modal analysis techniques. This produces a mode “shape” where the degrees of freedom are phases instead of physical motions. These phases can be scaled to produce on-image visualizations of the mode shapes, rather than operational shapes produced by bandpass filtering. Modal filtering techniques can also be used to visualize motions from an environment on an image using the modal phases as a basis for the expansion.

47 OTHER INSTRUMENTATION↗

Resolved Dwarf Galaxy Searches within ~5 Mpc with the Vera Rubin Observatory and Subaru Hyper Suprime-Cam*

We present a preview of the faint dwarf galaxy discoveries that will be possible with the Vera C. Rubin Observatory and Subaru Hyper Suprime-Cam in the next decade. In this work, we combine deep ground-based images from the Panoramic Imaging Survey of Centaurus and Sculptor (PISCeS) and extensive image simulations to investigate the recovery of faint, resolved dwarf galaxies in the Local Volume with a matched-filter technique. We adopt three fiducial distances - 1.5, 3.5, 5 Mpc, and quantitatively evaluate the effects on dwarf detection of varied stellar backgrounds, ellipticity, and Milky Way foreground contamination and extinction. We show that our matched-filter method is powerful for identifying both compact and extended systems, and near-future surveys will be able to probe at least ~4.5 mag below the tip of the red giant branch (TRGB) for a distance of up to 1.5 Mpc, and ~2 mag below the TRGB at 5 Mpc. This will push the discovery frontier for resolved dwarf galaxies to fainter magnitudes, lower surface brightnesses, and larger distances. Our simulations show the secure census of dwarf galaxies down to $M_{V}$$\approx$-5, -7, -8, will be soon within reach, out to 1.5 Mpc, 3.5 Mpc, and 5 Mpc, respectively, allowing us to quantify the statistical fluctuations in satellite abundances around hosts, and parse environmental effects as a function of host properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of the 2021 Milford, Utah earthquake swarm: Enhanced earthquake catalog and migration patterns

An earthquake swarm occurred in Spring 2021 in south-central Utah near the town of Milford. The University of Utah Seismograph Stations located 125 earthquakes between March 19 and May 10 with magnitudes ranging from 0.5 to 3.2. We implement a matched-filter technique in order to identify additional earthquakes that went undetected during the routine network location. The 125 network-located earthquakes are used as templates and are cross-correlated with continuous data for the dates Feb 17—June 10. This time period corresponds to approximately 1 month before the earthquake swarm began through 1 month after it ended. For the matched-filter analysis, we rely heavily on station FOR1, which is located within 5 km of most template events. Four other stations within 20–30 km of most template events provide a supplement to the closest station. The matched-filter implementation results in the detection of over 600 earthquakes in addition to the original 125 catalog events. This is one of the largest swarms ever recorded in Utah, and no previous large swarms have been recorded in this location. We use HypoDD to obtain relative double-difference locations of the catalog events. Both routine locations and HypoDD relocations of the catalog events suggest a fault dipping west beneath the mountain range, opposite of typical Basin and Range normal faults that dip beneath alluvial valleys. Moment tensors for the largest five events show normal faulting consistent with the west-dipping fault seen in the seismicity. Hydrothermal features in the area, including a geothermal power plant, suggest that fluids may be a contributing factor to the earthquake swarm triggering. We examine the role of fluids by exploring bounds on diffusion parameters and investigating spatial migration characteristics of the swarm seismicity. We conclude that this swarm is the result of heterogenous stress conditions in a prefractured region.

58 GEOSCIENCES↗

Multiple Changepoint Detection for Non‐Gaussian Time Series

ABSTRACT This article combines methods from existing techniques to identify multiple changepoints in non‐Gaussian autocorrelated time series. A transformation is used to convert a Gaussian series into a non‐Gaussian series, enabling penalized likelihood methods to handle non‐Gaussian scenarios. When the marginal distribution of the data is continuous, the methods essentially reduce to the change of variables formula for probability densities. When the marginal distribution is count‐oriented, Hermite expansions and particle filtering techniques are used to quantify the scenario. Simulations demonstrating the efficacy of the methods are given and two data sets are analyzed: 1) the proportion of home runs hit by Major League Baseball batters from 1920 to 2023 and 2) a six‐dimensional series of tropical cyclone counts from the Earth's basins of generation from 1980 to 2023. In the first series, beta marginal distributions are used to describe the proportions; in the second, Poisson marginal distributions seem appropriate.

Lund, Robert [Department of Statistics University ↗

Existence of tidal tails for the globular cluster NGC 5824

Context: Several dynamically cold streams have been associated with certain globular clusters (GCs) based on orbital energies and angular momenta. Some of these streams are surprisingly far apart from their progenitors and one such pair is Triangulum and NGC 5824. Triangulum can be considered as a piece of the leading tail of NGC 5824 since the cluster’s future orbit matches well with the stream’s track. The existence of the leading tail of NGC 5824 is the motivation behind the search for its trailing tail. Aims: Our goal is to confirm the connection between Triangulum and NGC 5824. We also search for the trailing tail of the cluster. Methods: The selection of member stars of Triangulum is made through various cuts in metallicity, proper motions (PMs), radial velocity and a color–magnitude diagram (CMD). The selected members are compared in phase space to a mock stream that models the disruption of NGC 5824. We then try to detect the trailing tail of the cluster based on a modified matched-filter technique. Stars are assigned weights using their color differences from the cluster’s locus in the CMD. These weights are further scaled, based on the stars’ departures from expected PMs of the model stream. Results: A total of 26 member stars for Triangulum are obtained, 16 of which are newly identified. These members are consistent with the mock stream in the phase space, and their metalicity and position on the CMD are in good agreement with NGC 5824. By applying the matched filter, a tenuous trailing tail of the cluster is detected, spanning ~50° long on sky. The signature matches well with the mock stream’s trajectory. Conclusions: Our results support that the Triangulum stream acts as a part of the leading tail for NGC 5824. On the trailing side, we detected a 50° tail extending from the cluster. The existence of both leading and trailing tails for the GC NGC 5824 is verified.

79 ASTRONOMY AND ASTROPHYSICS↗

Predictions for the Detectability of Milky Way Satellite Galaxies and Outer-Halo Star Clusters with the Vera C. Rubin Observatory

We predict the sensitivity of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) to faint, resolved Milky Way satellite galaxies and outer-halo star clusters. We characterize the expected sensitivity using simulated LSST data from the LSST Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) accessed and analyzed with the Rubin Science Platform as part of the Rubin Early Science Program. We simulate resolved stellar populations of Milky Way satellite galaxies and outer-halo star clusters over a wide range of sizes, luminosities, and heliocentric distances, which are broadly consistent with expectations for the Milky Way satellite system. We inject simulated stars into the DC2 catalog with realistic photometric uncertainties and star/galaxy separation derived from the DC2 data itself. We assess the probability that each simulated system would be detected by LSST using a conventional isochrone matched-filter technique. We find that assuming perfect star/galaxy separation enables the detection of resolved stellar systems with $M_V$ = 0 mag and $r_{1/2}$ = 10 pc with >50% efficiency out to a heliocentric distance of ~250 kpc. Similar detection efficiency is possible with a simple star/galaxy separation criterion based on measured quantities, although the false positive rate is higher due to leakage of background galaxies into the stellar sample. When assuming perfect star/galaxy classification and a model for the galaxy-halo connection fit to current data, we predict that 89 +/- 20 Milky Way satellite galaxies will be detectable with a simple matched-filter algorithm applied to the LSST wide-fast-deep data set. Different assumptions about the performance of star/galaxy classification efficiency can decrease this estimate by ~7%-25%, which emphasizes the importance of high-quality star/galaxy separation for studies of the Milky Way satellite population with LSST.

79 ASTRONOMY AND ASTROPHYSICS↗

Improved noise performance from the next-generation buried-channel p-MOSFET SiSeROs

The Single electron Sensitive Read Out (SiSeRO) is a novel on-chip charge detector output stage for charge-coupled device (CCD) image sensors. Developed at MIT Lincoln Laboratory, this technology uses a p-MOSFET transistor with a depleted internal gate beneath the transistor channel. The transistor source-drain current is modulated by the transfer of charge into the internal gate. At Stanford, we have developed a readout module based on the drain current of the on-chip transistor to characterize the device. In our earlier work, we characterized a number of first prototype SiSeROs with the MOSFET transistor channels at the surface layer. An equivalent noise charge (ENC) of around 15 electrons root mean square (RMS) was obtained. In this work, we examine the first buried-channel SiSeRO. Here we have achieved substantially improved noise performance of around 4.5 electrons root mean square (RMS) and a full width half maximum (FWHM) energy resolution of 132 eV at 5.9 keV, for a readout speed of 625 kpixel/s. We also discuss how digital filtering techniques can be used to further improve the SiSeRO noise performance. Additional measurements and device simulations will be essential to further mature the SiSeRO technology. This new device class presents an exciting new technology for the next-generation astronomical X-ray telescopes requiring fast, low-noise, radiation-hard megapixel imagers with moderate spectroscopic resolution.

79 ASTRONOMY AND ASTROPHYSICS↗

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh–Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10 % accuracy. The limitation of the model and the required steps forward are discussed.

17 WIND ENERGY↗