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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multiscale spatial analysis of fracture arrangement and pattern reconstruction using Ripley's K-function

This work presents novel multiscale spatial data analytics using Ripley's K-function, as a measure of spatial interaction, to study one-dimensional arrangement of fractures. Fracture spatial arrangements are classified into clustered, anticlustered, or indistinguishable from random by testing statistical significance of the calculated Ripley's K-function. Characterizations of fracture arrangements are performed as a function of length scale and position. Analysis of the K-function along the study interval identifies where fracture clustering and anticlustering occur. Here, a simulation technique is also introduced here to statistically reconstruct spatial arrangements and to generate fracture realizations that are spatially similar to the fractures observed in the field. With this simulation technique, one can also fill spatial gaps in fracture measurements where data are absent, unreliable, or unused. Synthetic as well as field-measured 1D fracture datasets are used for testing and demonstration. Methods introduced in this work can be readily applied to fracture datasets observed in outcrops, borehole image logs, and cores.

58 GEOSCIENCES↗
NASA NTRS1988

Rocks, resolution, and the record at the terrestrial K/T boundary, eastern Montana and western North Dakota

Reconstructions of mass extinction events are based upon faunal patterns, reconstructed from numerical and diversity data ultimately derived from rocks. It follows that geological complexity must not be subsumed in the desire to establish patterns. This is exemplified at the Terrestrial Cretaceous-Tertiary (K/T) boundary in eastern Montana and western North Dakota, where there are represented all of the major indicators of the terrestrial K/T transition: dinosaurian and non-dinosaurian vertebrate faunas, pollen, a megaflora, iridium, and shocked quartz. It is the patterns of these indicators that shape ideas about the terrestrial K/T transition. In eastern Montana and western North Dakota, the K/T transition is represented lithostratigraphically by the Cretaceous Hell Creek Formation, and the Tertiary Tullock Formation. Both of these are the result of aggrading, meandering, fluvial systems, a fact that has important consequences for interpretations of fossils they contain. Direct consequences of the fluvial depositional environments are: facies are lenticular, interfingering, and laterally discontinuous; the occurrence of fossils in the Hell Creek and Tullock formations is facies-dependent; and the K/T sequence in eastern Montana and western North Dakota is incomplete, as indicated by repetitive erosional contacts and soil successions. The significance for faunal patterns of lenticular facies, facies-dependent preservation, and incompleteness is discussed. A project attempting to reconstruct vertebrate evolution in a reproducible manner in Hell Creek-type sediments must be based upon a reliable scale of correlations, given the lenticular nature of the deposits, and a recognition of the fact that disparate facies are not comparable in terms of either numbers of preserved vertebrates or depositional rates.

Fastovsky, D. E.↗
DOE OSTI2021

Measurement of electronic structure and surface reconstruction in the superionic Cu 2-x Te

Recently, layered copper chalcogenides Cu 2 X family (X=S, Se, Te) has attracted tremendous research interests due to their high thermoelectric performance, which is partly due to the superionic behavior of mobile Cu ions, making these compounds "phonon liquids."Here, we systematically investigate the electronic structure and its temperature evolution of the less studied single crystal Cu 2-x Te by the combination of angle resolved photoemission spectroscopy (ARPES) and scanning tunneling microscope/spectroscopy (STM/STS) experiments. While the band structure of the Cu 2-x Te shows agreement with the calculations, we clearly observe a 2×2 surface reconstruction from both our low temperature ARPES and STM/STS experiments which survives up to room temperature. Interestingly, our low temperature STM experiments further reveal multiple types of reconstruction patterns, which suggests the origin of the surface reconstruction being the distributed deficiency of liquidlike Cu ions. Our findings reveal the electronic structure and impurity level of Cu 2 Te, which provides knowledge about its thermoelectric properties from the electronic degree of freedom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1988

Nonuniform Sampling Of Radiation From Antennas

Far-field patterns reconstructed. Nonuniform-sampling technique uses interpolation algorithm to obtain far-field radiation pattern of antenna at any point u, v based on measurements at few sampling points. Applicable to any components of electric field "E" at measurement locations in spherical coordinate system centered at antenna.

Rahmat-Samii, Y.↗
NASA NTRS1987

Nonuniform sampling techniques for antenna applications

A two-dimensional sampling technique, which can employ irregularly spaced samples (amplitude and phase) in order to generate the complete far-field patterns is presented. The technique implements a matrix inversion algorithm, which depends only on the nonuniform sampled data point locations and with no dependence on the actual field values at these points. A powerful simulation algorithm is presented to allow a real-life simulation of many reflector/feed configurations and to determine the usefulness of the nonuniform sampling technique for the copolar and cross-polar patterns. Additionally, an overlapped window concept and a generalized error simulation model are discussed to identify the stability of the technique for recovering the field data among the nonuniform sampled data. Numerical results are tailored for the pattern reconstruction of a 20-m offset reflector antenna operating at L-band. This reflector is planned to be used in a proposed measurement concept of large antenna aboard the Space Shuttle, whereby it would be almost impractical to accurately control the movement of the Shuttle with respect to the RF source in prescribed directions in order to generate uniform sampled points. Also, application of the nonuniform sampling technique to patterns obtained using near-field measured data is demonstrated. Finally, results of an actual far-field measurement are presented for the construction of patterns of a reflector antenna from a set of nonuniformly distributed measured amplitude and phase data.

Rahmat-Samii, Yahya↗
NASA NTRS1989

Context dependent anti-aliasing image reconstruction

Image Reconstruction has been mostly confined to context free linear processes; the traditional continuum interpretation of digital array data uses a linear interpolator with or without an enhancement filter. Here, anti-aliasing context dependent interpretation techniques are investigated for image reconstruction. Pattern classification is applied to each neighborhood to assign it a context class; a different interpolation/filter is applied to neighborhoods of differing context. It is shown how the context dependent interpolation is computed through ensemble average statistics using high resolution training imagery from which the lower resolution image array data is obtained (simulation). A quadratic least squares (LS) context-free image quality model is described from which the context dependent interpolation coefficients are derived. It is shown how ensembles of high-resolution images can be used to capture the a priori special character of different context classes. As a consequence, a priori information such as the translational invariance of edges along the edge direction, edge discontinuity, and the character of corners is captured and can be used to interpret image array data with greater spatial resolution than would be expected by the Nyquist limit. A Gibb-like artifact associated with this super-resolution is discussed. More realistic context dependent image quality models are needed and a suggestion is made for using a quality model which now is finding application in data compression.

Beaudet, Paul R.↗
DOE OSTI2026

Development of a pattern recognition algorithm for reconstructing multi-particle events in the Mu2e detector

Mu2e is an upcoming experiment at Fermilab and its main goal is to search for the Charged Lepton Flavor Violation (CLFV) in the coherent transition of a muon into an electron on an Al target. In Mu2e, multi-particle events can occur simultaneously within the same time region and it is crucial to accurately identify each particle track, including signals, to improve the robustness of track finding methods and enhance reconstruction efficiency. ¯p annihilation is one of the background events and produces multiple particles that can mimic signal events. Additionally, photons from radiative pion captures can produce a γ → $e+e−$ pair, which can be used to calibrate the Mu2e momentum scale and the resolution. The Mu2e track reconstruction sequence begins by grouping hits produced in the tracker based on time and z coordinate information, called TimeCluster, and selected hits are processed to reconstruct helices and determine their momentum. The current pattern recognition algorithms identify a single helix per TimeCluster for single track events. A new pattern recognition algorithm is being developed to reconstruct multi-particle events and its features for finding multiple tracks and the current evaluation results are reported.

Kitagawa, H. [Pisa U.]↗
DOE OSTI2022

Wire-cell 3D pattern recognition techniques for neutrino event reconstruction in large LArTPCs: algorithm description and quantitative evaluation with MicroBooNE simulation

Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated charge are reconstructed prior to the pattern recognition stage. Pattern recognition techniques, including track trajectory and dQ/dx (ionization charge per unit length) fitting, 3D neutrino vertex fitting, track and shower separation, particle-level clustering, and particle identification are then applied on these 3D space points as well as the original 2D projection measurements. A deep neural network is developed to enhance the reconstruction of the neutrino interaction vertex. Compared to traditional algorithms, the deep neural network boosts the vertex efficiency by a relative 30% for charged-current ν e interactions. Therefore, this pattern recognition achieves 80–90% reconstruction efficiencies for primary leptons, after a 65.8% (72.9%) vertex efficiency for charged-current ν e (ν μ ) interactions. Based on the resulting reconstructed particles and their kinematics, we also achieve 15-20% energy reconstruction resolutions for charged-current neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A Common Tracking Software Project

Abstract The reconstruction of the trajectories of charged particles, or track reconstruction, is a key computational challenge for particle and nuclear physics experiments. While the tuning of track reconstruction algorithms can depend strongly on details of the detector geometry, the algorithms currently in use by experiments share many common features. At the same time, the intense environment of the High-Luminosity LHC accelerator and other future experiments is expected to put even greater computational stress on track reconstruction software, motivating the development of more performant algorithms. We present here A Common Tracking Software (ACTS) toolkit, which draws on the experience with track reconstruction algorithms in the ATLAS experiment and presents them in an experiment-independent and framework-independent toolkit. It provides a set of high-level track reconstruction tools which are agnostic to the details of the detection technologies and magnetic field configuration and tested for strict thread-safety to support multi-threaded event processing. We discuss the conceptual design and technical implementation of ACTS, selected applications and performance of ACTS, and the lessons learned.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Stochastic reconstruction of fracture network pattern using spatial point processes

Fracture spatial patterns can strongly affect fluid flow in the subsurface. Proximity and distribution of fractures control reservoir flow behavior over various length scales. In many studies, however, simplified geometrical patterns are generated for fractures which may lead to unrealistic subsurface models. Here we introduce a new method for characterization and modeling of fracture spatial patterns based on outcrop observations. We use Ripley's K-function to characterize the arrangement of fracture barycenters and intersection points over various length scales. In addition, we use semivariograms to quantify spatial correlation in fracture intensity maps. Using this information, we develop a stochastic algorithm that generates two-dimensional fracture network realizations with spatial properties similar to those of a real fracture network measured in the field. Numerical simulation models indicate that the generated fracture realizations exhibit similar flow behaviors as that of the original fracture network. Furthermore, such modeling tools expand and improve our capability in building representative fracture models and in quantification of uncertainty in naturally and hydraulically fractured reservoirs.

58 GEOSCIENCES↗
DOE OSTI2022

Progress towards an investigation of the MiniBooNE Low Energy Excess using neutral-current Delta-like single photons in MicroBooNE with Wire-Cell 3D reconstruction algorithms

This note presents progress towards a Neutral-Current (NC) Delta-like single photon search in MicroBooNE using Wire-Cell 3D reconstruction and pattern recognition algorithms. This analysis will help address the question of the MiniBooNE Low Energy Excess (LEE). The selections are similar to the previously published Pandora-based single photon selections in many ways, but here we use independent reconstruction and selection tools and examine a larger phase space (including charged pions and multiple protons). In the future, we will significantly reduce systematic uncertainties via the use of constraining sideband observations in order to statistically test specific models of the MiniBooNE LEE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Progress Towards an Investigation of the MiniBooNE Low Energy Excess Using Neutral-Current Delta-Like Single Photons in MicroBooNE with Wire-Cell 3D Reconstruction Algorithms

This note presents progress towards a Neutral-Current (NC) Delta-like single photon search in MicroBooNE using Wire-Cell 3D reconstruction and pattern recognition algorithms. This analysis will help address the question of the MiniBooNE Low Energy Excess (LEE) [1]. The selections are similar to the previously published Pandora-based single photon selections [2] in many ways, but here we use independent reconstruction and selection tools and examine a larger phase space (including charged pions and multiple protons). In the future, we will significantly reduce systematic uncertainties via the use of constraining sideband observations in order to statistically test specific models of the MiniBooNE LEE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Formation and retrieval of cell assemblies in a biologically realistic spiking neural network model of area CA3 in the mouse hippocampus

The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of cell assemblies enable these functions. Yet, how cell assemblies are formed and retrieved in a full-scale spiking neural network (SNN) of CA3 that incorporates the observed diversity of neurons and connections within this circuit is not well understood. Here, we demonstrate that a data-driven SNN model quantitatively reflecting the neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, and long-term plasticity of the mouse CA3 is capable of robust auto-association and pattern completion via cell assemblies. Our results show that a broad range of assembly sizes could successfully and systematically retrieve patterns from heavily incomplete or corrupted cues after a limited number of presentations. Furthermore, performance was robust with respect to partial overlap of assemblies through shared cells, substantially enhancing memory capacity. These novel findings provide computational evidence that the specific biological properties of the CA3 circuit produce an effective neural substrate for associative learning in the mammalian brain.

hetero-association↗
DOE OSTI2023

The large-area hybrid-optics CLAS12 RICH: First years of data-taking

The CLAS12 deep-inelastic scattering experiment at the upgraded 12 GeV continuous electron beam accelerator facility of Jefferson Lab conjugates luminosity and wide acceptance to study the 3D nucleon structure in the yet poorly explored valence region, and to perform precision measurements in hadron spectroscopy. A large area ring-imaging Cherenkov detector has been designed to achieve the required hadron identification in the momentum range from 3 GeV/c to 8 GeV/c, with the kaon rate about one order of magnitude lower than the rate of pions and protons. The adopted solution comprises aerogel radiator and composite mirrors in a novel hybrid optics design, where either direct or reflected light could be imaged in a high-packed and high-segmented photon detector. The first RICH module was assembled during the second half of 2017 and installed at the beginning of January 2018, in time for the start of the experiment. The second RICH module, planned with the goal to be ready for the beginning of the operation with polarized targets, has been timely built despite the complications caused by the pandemic crisis and successfully installed in June 2022. Finally, the detector performance is here discussed with emphasis on the operation and stability during the data-taking, calibration and alignment procedures, reconstruction and pattern recognition algorithms, and particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Directionally supervised cellular automaton for the initial peopling of Sahul

Reconstructing the patterns of Homo sapiens expansion out of Africa and across the globe has been advanced using demographic and travel-cost models. However, modelled routes are ipso facto influenced by migration rates, and vice versa. We combined movement ‘superhighways’ with a demographic cellular automaton to predict one of the world's earliest peopling events — Sahul between 75000 and 50000 years ago. Novel outcomes from the superhighways-weighted model include (i) an approximate doubling of the predicted time to continental saturation (~10,000 years) compared to that based on the directionally unsupervised model (~5000 years), suggesting that rates of migration need to account for topographical constraints in addition to rate of saturation; (ii) a previously undetected movement corridor south through the centre of Sahul early in the expansion wave based on the scenarios assuming two dominant entry points into Sahul; and (iii) a better fit to the spatially de-biased, Signor-Lipps-corrected layer of initial arrival inferred from dated archaeological material. Our combined model infrastructure provides a data-driven means to examine how people initially moved through, settled, and abandoned different regions of the globe.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Solving complex nanostructures with ptychographic atomic electron tomography

Abstract Transmission electron microscopy (TEM) is essential for determining atomic scale structures in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined from thousands of identical particles using phase-contrast TEM. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform ptychographic electron tomography from 34.5 million diffraction patterns to reconstruct an atomic resolution tilt series of a double wall-carbon nanotube (DW-CNT) encapsulating a complex ZrTe sandwich structure. Class averaging the resulting tilt series images and subpixel localization of the atomic peaks reveals a Zr 11 Te 50 structure containing a previously unobserved ZrTe 2 phase in the core. The experimental realization of atomic resolution ptychographic electron tomography will allow for the structural determination of a wide range of beam-sensitive nanomaterials containing light elements.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predicting wind-driven spatial deposition through simulated color images using deep autoencoders

Abstract For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to explain relationships in data. Powerful new algorithms can enable computers to learn physics by observing images and videos. Inspired by this idea, instead of training machine learning models using physical quantities, we used images, that is, pixel information. For this work, and as a proof of concept, the physics of interest are wind-driven spatial patterns. These phenomena include features in Aeolian dunes and volcanic ash deposition, wildfire smoke, and air pollution plumes. We use computer model simulations of spatial deposition patterns to approximate images from a hypothetical imaging device whose outputs are red, green, and blue (RGB) color images with channel values ranging from 0 to 255. In this paper, we explore deep convolutional neural network-based autoencoders to exploit relationships in wind-driven spatial patterns, which commonly occur in geosciences, and reduce their dimensionality. Reducing the data dimension size with an encoder enables training deep, fully connected neural network models linking geographic and meteorological scalar input quantities to the encoded space. Once this is achieved, full spatial patterns are reconstructed using the decoder. We demonstrate this approach on images of spatial deposition from a pollution source, where the encoder compresses the dimensionality to 0.02% of the original size, and the full predictive model performance on test data achieves a normalized root mean squared error of 8%, a figure of merit in space of 94% and a precision-recall area under the curve of 0.93.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗