Search NASA⌕ Search

SEARCH · Search NASA

Results for “Pattern reconstruction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Insights Into Reconstructing REE Compositions of Melt From Zircon-Melt Partition Coefficients Using Zircon-Hosted Melt Inclusions From the Yellowstone Volcanic Province

Establishing the major and trace element composition of the Earth’s melts (Hadean to recent) is essential for understanding crustal evolution. Due to its physical-chemical resilience, zircon spans the complete age spectra of Earth’s history, and thus provides the only physical record from the early Earth. However, the petrological context i.e., the melt from which zircon crystallised, is often lost, except for inclusions of melt preserved within zircon. Melt inclusions in zircon (MI) provide a valuable tool to constrain zircon-melt REE partition coefficients (D REE ), which are used with the zircon REE chemistry to reconstruct melt compositions. Such reconstruction requires accurate partition coefficients, which are particularly sensitive to temperature, but also to pressure and melt composition. We determined the major and trace element compositions of 60 co-existing zircon-MI pairs from two ~ 2 Ma age rhyolites (the caldera-forming Huckleberry Ridge Tuff; HRT-C and the post-caldera Blue Creek Flow; BC-1) of the Yellowstone Plateau volcanic field by EPMA and SIMS, and calculated a set of 60 zircon-MI partition coefficients. The MI from both units are glassy with average silica contents of 78.30 ± 0.74 and 77.19 ± 1.11 wt %, and Ti-in-zircon crystallisation temperatures are 839 ± 36 and 835 ± 35 oC. Measured D REE patterns for each population (n = 30) are tightly constrained and exhibit a smooth pattern spanning ~ six orders of magnitude from La to Lu, (with exceptions at Ce and Eu), and for the HRT exhibit greater curvature (i.e., flatter) between the MREE to HREE compared to the BC-1. D REE patterns for the HRT have small to moderate Ce anomalies (Ce/Ce* Di 50 ± 40), whereas those in the BC-1 are larger (98 ± 45), and both units exhibit negligible to positive Eu anomalies (Eu/Eu* Di 1.07 ± 0.89 and 1.80 ± 2.01, respectively). We compare the trace element compositions of the MI to bulk-glass compositions from Yellowstone to assess any differences, which are small, then compare the measured MI compositions to those reconstructed using published partition coefficients (natural, empirical and experimental). The choice of D REE for reconstruction of the melt REE pattern results in differing petrogenetic interpretations.

Laura J. Crisp↗
DOE OSTI2022

Real-space texture and pole-figure analysis using the 3D pair distribution function on a platinum thin film

An approach is described for studying texture in nanostructured materials. The approach implements the real-space texture pair distribution function (PDF), txPDF, laid out by Gong & Billinge {(2018). arXiv:1805.10342 [cond-mat]}. It is demonstrated on a fiber-textured polycrystalline Pt thin film. The approach uses 3D PDF methods to reconstruct the orientation distribution function of the powder crystallites from a set of diffraction patterns, taken at different tilt angles of the substrate with respect to the incident beam, directly from the 3D PDF of the sample. A real-space equivalent of the reciprocal-space pole figure is defined in terms of interatomic vectors in the PDF and computed for various interatomic vectors in the Pt film. Furthermore, it is shown how a valid isotropic PDF may be obtained from a weighted average over the tilt series, including the measurement conditions for the best approximant to the isotropic PDF from a single exposure, which for the case of the fiber-textured film was in a nearly grazing incidence orientation of ∼10°. Finally, an open-source Python software package, FouriGUI , is described that may be used to help in studies of texture from 3D reciprocal-space data, and indeed for Fourier transforming and visualizing 3D PDF data in general.

3D pair distribution functions↗
DOE OSTI2023

Generalizing mkFit and its Application to HL-LHC

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. mkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and high-level code changes required for the HL-LHC geometry are presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Accurately modeling and constructing a geologically realistic subsurface model remains an outstanding problem as the morphology controls the flow behaviors. Particularly, one of the pattern-based methods, namely cross-correlation based simulation, has been proved to be an effective way to reconstruct a realistic model, at both small and large scales. However, conditioning to point data in the large-scale problems is still a crucial issue in these algorithms, since there is always a trade-off between the quality of the realizations and the degree of point data reproduction. Specifically, it is not practical to build a training image (TI) which includes all the possibilities and variabilities. Therefore, finding a pattern that can represent the point data and, at the same time, preserving the connectivities is difficult. This leads to producing highly-connected realizations with a significant mismatch or poor models with a reasonable degree of point data reproduction. To accurately reproduce the densely distributed hard data, pixel-based methods can also produce some unrealistic artifacts around the hard data. In this paper, to overcome this challenge, however, we use pattern-based methods as they often produce more disconnected geobodies when dealing with dense hard data, and proposed a hybrid algorithm using the pattern-based methods and convolutional neural network (CNN). The trained CNN model is utilized to improve the quality of conditioning to point data for the original realizations generated by the pattern-based algorithm. As such, the mismatch locations are identified, and the same regions are used in the training of CNN to mimic the procedure through which a missing region can be filled. To evaluate the performance of the proposed hybrid algorithm, it is tested on cases with different dimensions and different numbers of facies. Then, the newly improved realizations are compared with the initial realizations generated by the pattern-based algorithm. The comparison is also conducted by the flow simulation test. And it indicates that the proposed hybrid algorithm can better reproduce the point data, while the connectivities are better preserved.

58 GEOSCIENCES↗
DOE OSTI2025

Multi-channel, multi-template event reconstruction for SuperCDMS data using machine learning

SuperCDMS SNOLAB uses kilogram-scale germanium and silicon detectors to search for dark matter. Each detector has Transition Edge Sensors (TESs) patterned on the top and bottom faces of a large crystal substrate, with the TESs electrically grouped into six phonon readout channels per face. Noise correlations are expected among a detector's readout channels, in part because the channels and their readout electronics are located in close proximity to one another. Moreover, owing to the large size of the detectors, energy deposits can produce vastly different phonon propagation patterns depending on their location in the substrate, resulting in a strong position dependence in the readout-channel pulse shapes. Both of these effects can degrade the energy resolution and consequently diminish the dark matter search sensitivity of the experiment if not accounted for properly. We present a new algorithm for pulse reconstruction, mathematically formulated to take into account correlated noise and pulse shape variations. This new algorithm fits N readout channels with a superposition of M pulse templates simultaneously - hence termed the N$\times$M filter. We describe a method to derive the pulse templates using principal component analysis (PCA) and to extract energy and position information using a gradient boosted decision tree (GBDT). We show that these new N$\times$M and GBDT analysis tools can reduce the impact from correlated noise sources while improving the reconstructed energy resolution for simulated mono-energetic events by more than a factor of three and for the 71Ge K-shell electron-capture peak recoils measured in a previous version of SuperCDMS called CDMSlite to $<$ 50 eV from the previously published value of $\sim$100 eV. These results lay the groundwork for position reconstruction in SuperCDMS with the N$\times$M outputs.

Albakry, M. F. [British Columbia U.; TRIUMF]↗
DOE OSTI2025

Bottom-Up Simulation, Reconstruction, and Quantification of Macromolecule Sequences from Experimental Polymerizations

Motivated by the canonical sequence–structure–function paradigm, tools to characterize chemical patterning in natural biomacromolecules, from proteins to nucleic acids, have grown exponentially in recent years. However, analogous strategies for synthetic macromolecules remain in nascent stages, complicated by sequence polydispersity and analytical limitations. To address this, we have developed a comprehensive and open-source Python package, PRISM (polymer rate insights and sequence modeling), an end-to-end workflow that provides a path from experimental kinetics measurements to quantitative and qualitative metrics for describing chemical patterning in stochastic polymers. First, a numerical integration strategy was constructed to simulate and fit experimental data from reversible addition–fragmentation chain transfer (RAFT) polymerization kinetics, enabling the facile estimation of relevant reactivity ratios. These ratios were then used in a mechanism-specific stochastic kinetic simulation strategy to simulate sequence ensembles corresponding to model systems spanning experimental copolymers, classes of statistical polymers (e.g., alternating, block, and gradient), and multiblock copolymers. Lastly, inspired by sequence homology metrics from bioinformatics, we introduce visualization strategies and quantitative metrics to facilitate comparisons of different sequence ensembles. As the sequence–structure–function paradigm becomes increasingly central in de novo design of synthetic macromolecules, this toolkit provides a first step toward accurate and representative sequence description and featurization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Charged particle tracking in real-time using a full-mesh data delivery architecture and associative memory techniques

We present a flexible and scalable approach to address the challenges of charged particle track reconstruction in real-time event filters (Level-1 triggers) in collider physics experiments. The method described here is based on a full-mesh architecture for data distribution and relies on the Associative Memory approach to implement a pattern recognition algorithm that quickly identifies and organizes hits associated to trajectories of particles originating from particle collisions. We describe a successful implementation of a demonstration system composed of several innovative hardware and algorithmic elements. The implementation of a full-size system relies on the assumption that an Associative Memory device with the sufficient pattern density becomes available in the future, either through a dedicated ASIC or a modern FPGA. We demonstrate excellent performance in terms of track reconstruction efficiency, purity, momentum resolution, and processing time measured with data from a simulated LHC-like tracking detector.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Bragg coherent diffraction imaging by simultaneous reconstruction of multiple diffraction peaks

Bragg coherent diffractive imaging (BCDI) is a non-invasive microscopy technique that can visualize the morphology and internal lattice deviations of crystals with nanoscale spatial resolution and picometer deformation sensitivity. While BCDI has been successfully applied in various studies of materials, it is less successful for highly-strained crystals. Specifically, it is difficult to correctly reconstruct the electron density of a highly-strained object using conventional phase retrieval algorithms. Although various algorithms have been developed to overcome this challenge, most of them require a priori knowledge that is not always available in practice. Here we report on a new phase retrieval workflow that can invert diffraction patterns from multiple Bragg peaks simultaneously. The new workflow is explored via simulated diffraction from crystals with various strain conditions. Furthermore, reconstructions from the new workflow consistently demonstrate more accurate electron density maps, in comparison with the conventional method. For highly-strained crystals, the new workflow improves the reliability and consistency of BCDI phase retrieval significantly.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Bethe-Ansatz approach to the $$ \mathcal{N} $$ = 4 superconformal index at finite rank

We investigate the Bethe-Ansatz approach to the superconformal index of $$ \mathcal{N} $$ N = 4 supersymmetric Yang-Mills with SU( N ) gauge group in the context of finite rank, N . We explicitly explore the role of the various types of solutions to the Bethe-Ansatz Equations in recovering the exact index for N = 2 , 3. We classify the Bethe-Ansatz Equations solutions as standard (corresponding to a freely acting orbifold T 2 /Z m × Z n ) and non-standard. For N = 2, we find that the index is fully recovered by standard solutions and displays an interesting pattern of cancellations. However, for N ≥ 3, the standard solutions alone do not suffice to reconstruct the index. We present quantitative arguments in various regimes of fugacities that highlight the challenging role played by the continuous families of non-standard solutions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals

We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in contrast to the work (Daubechies et al., Pure Appl. Math. 57(11), 1413–1457, 2004), where the single vector signal can be infinite-dimensional, and (Fornasier and Rauhut, SIAM J. Numer. Anal. 46(2), 577613, 2008), which extends the aforementioned work to the joint sparse recovery of finite number of infinite-dimensional vectors. In our case, to take account of the joint sparsity and promote the coupling of nonvanishing components, we employ a convex relaxation approach with mixed norm penalty ℓ 2,1 . This paper discusses the computation of the solutions of linear inverse problems with such relaxation by a forward-backward splitting algorithm. However, since the solution matrix possesses infinitely many columns, the arguments of Daubechies et al. (Pure Appl. Math. 57(11), 1413–1457, 2004) no longer apply. As such, we establish new strong convergence results for the algorithm, in particular when the set of jointly sparse vectors is infinite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Inferring the scrape-off layer heat flux width in a divertor with a low degree of axisymmetry

Plasma facing components (PFCs) in the next generation of tokamak devices will operate in challenging environments, with heat loads predicted to exceed 10 MWm -2 . The magnitude of these heat loads is set by the width of the channel, the ‘scrape-off layer’ (SOL), into which heat is exhausted, and can be characterised by an e-folding length scale for the decay of heat flux across the channel. It is expected this channel will narrow as tokamaks move towards reactor relevant conditions. Understanding the processes involved in setting the SOL heat flux width is imperative to be able to predict the heat loads PFCs must handle in future devices. Measurements of the SOL width are performed on the high-field spherical tokamak, ST40, using a newly commissioned infrared thermography system. With its high on-axis toroidal magnetic field (≥1.5 T) ST40 is uniquely positioned to investigate the influence of toroidal field on the heat flux width in spherical tokamaks, whilst also extending measurements of the SOL width in spherical tokamaks to increased poloidal field (≥0.3 T). Due to the divertor on ST40 having a low degree of axisymmetry, it is necessary for a set of radial measurements of the heat flux to be taken across the divertor, made possible using an automated toolchain that fully incorporates its 3D geometry. These radial profiles are combined with the magnetic geometry of the plasma to infer the width of the SOL, with both Eich and double exponential profiles of heat flux observed. A reduction in the heat flux is observed toroidally across part of the divertor, along with increased heat loads observed locally around the edges of the tiles. Future work in characterising the impact of tile misalignment and uncertainties in the reconstructed divertor magnetic geometry is required in order to further understand the observed heat flux patterns, as are additional investigations into the role potentially being played by an inhomogeneous sheath electric field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2018

Increased Snowfall over the Antarctic Ice Sheet Mitigated Twentieth-Century Sea-Level Rise

Changes in accumulated snowfall over the Antarctic Ice Sheet have an immediate and time-delayed impact on global mean sea level. The immediate impact is due to the instantaneous change in freshwater storage over the ice sheet, whereas the time-delayed impact acts in opposition through enhanced ice dynamic flux into the ocean. Here, we reconstruct 200 years of Antarctic-wide snow accumulation by synthesizing a newly compiled database of ice core records using reanalysis derived spatial coherence patterns. The results reveal that increased snow accumulation mitigated twentieth-century sea-level rise by approximately 10 millimeters since 1901, with rates increasing from 1.1 mm per decade between 1901 and 2000 to 2.5 mm per decade after 1979. Reconstructed accumulation trends are highly variable in both sign and magnitude at the regional scale, and linked to the trend towards a positive Southern Annular Mode since 1957. Because the observed Southern Annular Mode trend is accompanied by a decrease in Antarctic Ice Sheet accumulation, changes in the strength and location of the circumpolar westerlies cannot explain the reconstructed increase, which may instead be related to stratospheric ozone depletion. However, our results indicate that a warming atmosphere cannot be excluded as a dominant force in the underlying increase.

Antarctic↗
NASA NTRS2018

Increased snowfall over the Antarctic Ice Sheet mitigated twentieth-century sea-level rise

Changes in accumulated snowfall over the Antarctic Ice Sheet have an immediate and time-delayed impact on global mean sea level. The immediate impact is due to the instantaneous change in freshwater storage over the ice sheet, whereas the time-delayed impact acts in opposition through enhanced ice-dynamic flux into the ocean1. Here, we reconstruct 200 years of Antarctic-wide snow accumulation by synthesizing a newly compiled database of ice core records2 using reanalysis-derived spatial coherence patterns. The results reveal that increased snow accumulation mitigated twentieth-century sea-level rise by ~10 mm since 1901, with rates increasing from 1.1 mm decade−1 between 1901 and 2000 to 2.5 mm decade−1 after 1979. Reconstructed accumulation trends are highly variable in both sign and magnitude at the regional scale, and linked to the trend towards a positive Southern Annular Mode since 19573. Because the observed Southern Annular Mode trend is accompanied by a decrease in Antarctic Ice Sheet accumulation, changes in the strength and location of the circumpolar westerlies cannot explain the reconstructed increase, which may instead be related to stratospheric ozone depletion4. However, our results indicate that a warming atmosphere cannot be excluded as a dominant force in the underlying increase.

B Medley↗
DOE OSTI2022

Deeply learning deep inelastic scattering kinematics

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q 2 and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2017

Kepler Commissioning Data for Measurement of the Pixel Response Function and Focal Plane Geometry

This document describes the Kepler PRF/FPG data release. This data was taken on April 27-29, 2009, during Kepler's commissioning phase in order to measure the pixel response function (PRF) (Bryson et al., 2010a) and focal plane geometry (FPG) (Tenenbaum and Jenkins, 2010). 33,424 stellar targets were observed for 243 long cadences, each with a duration of 14.7 minutes (half the duration of a normal Kepler long cadence). During these 243 cadences the Kepler photometer was moved, pointing in a dither pattern to facilitate PRF measurement. Motion occurred during the even cadences (second, fourth, etc.), with the telescope in stable fine point at each pointing in the dither pattern during the odd cadences (first, third, etc.). The first and last cadences were at the center of the dither pattern. Motion cadences are included in this release, but they do not contain any data. For details on how this data was used to derive the Kepler PRF and FPG models, see Bryson et al. (2010a) and Tenenbaum and Jenkins (2010). Descriptions of the PRF and FPG models are found in Thompson et al. (2016), x2.3.5.17 and x2.3.5.16 respectively. The data in this release can be used to recompute the Kepler PRF and FPG. Such a reconstruction, however, would not reflect measured seasonal changes in the PRF described in Van Cleve et al. (2016b), x5.2.The dither pattern is shown in Figure 1. The crosses show the commanded pointings and the circles show the measured pointings. Measured pointings are different from the commanded pointings due to the early state of calibration of the fine guidance sensors during commissioning (Van Cleve et al., 2016a). The measured offsets from the center of the pattern are given in RADEC offsets and pixel offsets in Table 1. The order of the offsets was randomized during data collection to avoid time-dependent systematics.

Kepler↗
DOE OSTI2025

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Seeing in with X-rays: 4D Strain and Thermometry Measurements for Thermal-Mechanical Testing

Understanding temperature-dependent material decomposition and structural deformation induced by combined thermal-mechanical environments is critical for safety qualification of hardware under accident scenarios. Seeing in with X-rays elucidated the physics necessary to develop X-ray strain and thermometry diagnostics for use in optically opaque environments. Two parallel thermometry schemes were explored: X-ray fluorescence and X-ray diffraction of inorganic doped ceramics– colloquially known as thermographic phosphors. Two parallel surface strain techniques–Path-Integrated Digital Image Correlation and Frequency Multiplexed Digital Image Correlation–were demonstrated. Finally, preliminary demonstration of time-resolved digital volume correlation was performed by taking advantage of limited view reconstruction techniques. Additionally, research into blended ceramic-metal coatings was critical to generating intrinsic thermographic patterns for the future combination of X-ray strain and thermometry measurements.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Flow visualization and motion analysis for a series of four sequential brush seals

Applying the Full Flow Field Tracking (FFFT) method, the flow patterns and the accompanying fluid velocities inside a series of brushes were nonintrusively determined and graphically reconstructed. The visualized flow field revealed regions that are characteristically river-jetting, vortical, and crossflow, and exist upstream, downstream, or within the seal. These flows are especially engendered by variations in fiber void that are spatial and temporal and affect changes in seal leakage and stability. The deformation of the upper half of each of the four sequential brushes as a function of upstream pressure and mass flow was determined. The axial pressure variation across the set of four brushes and the mass flow as a function of the pressure drops are also presented.

Braun, M. J.↗