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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nanofabrication of synthetic nanoporous geomaterials: from nanoscale-resolution 3D imaging to nano-3D-printed digital (shale) rock

Abstract Advances in imaging have made it possible to view nanometer and sub-nanometer structures that are either synthesized or that occur naturally. It is believed that fluid dynamic and thermodynamic behavior differ significantly at these scales from the bulk. From a materials perspective, it is important to be able to create complex structures at the nanometer scale, reproducibly, so that the fluid behavior may be studied. New advances in nanoscale-resolution 3D-printing offer opportunities to achieve this goal. In particular, additive manufacturing with two-photon polymerization allows creation of intricate structures. Using this technology, a creation of the first nano-3D-printed digital (shale) rock is reported. In this paper, focused ion beam-scanning electron microscopy (FIB-SEM) nano-tomography image dataset was used to reconstruct a high-resolution digital rock 3D model of a Marcellus Shale rock sample. Porosity of this 3D model has been characterized and its connected/effective pore system has been extracted and nano-3D-printed. The workflow of creating this novel nano-3D-printed digital rock 3D model is described in this paper.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
DOE OSTI2026

SoK: What does it Mean to Benchmark Database Forensics?

Relational Database Management Systems are the backbone of modern enterprises and public-sector services, and are thus frequent targets of security incidents, insider threats, and thorough regulatory audits. Consequently, databases have become key sources of digital evidence, requiring investigators to reconstruct past activity from audit logs, transaction logs, and backups. Although benchmarking frameworks such as those developed by the Transaction Processing Performance Council (TPC) are widely used to evaluate database performance, they do not capture forensic requirements such as evidentiary completeness, tamper-evidence, chain of custody, or regulatory compliance under GDPR and CCPA. This survey examines the emerging domain of forensic database benchmarking. We gathered prior research on database forensics, secure logging, and tamper-evident data structures; we analyze modern forensic-ready features in commercial and open-source systems (SQL Server Ledger, Oracle Blockchain Tables, PostgreSQL pgAudit, Db2 Audit, Aurora Database Activity Streams, Oracle Real Application Security and IBM Guardium) and assess why existing benchmarks are insufficient. We propose forensic workloads, metrics, and methodologies that incorporate adversarial stressors, deleted-record recovery, and backup analysis. We also identify open research problems and call for a community-driven forensic benchmark suite. The result is an idea for evaluating not only database performance but also forensic soundness, bridging the gap between system engineering, compliance, and digital investigations.

Lenard, Ben↗
DOE OSTI2025

Fiber-coupled digital photo sensors for large Time Projection Chambers

Here, this paper presents a novel approach to addressing challenges in neutrino event reconstruction within large Time Projection Chambers (TPCs). By integrating fiber-coupled digital silicon photomultipliers, we propose a design that enhances light detection and improves both energy resolution and event reconstruction. Advancements in power and signal over fiber technologies are leveraged to deploy digital sensors within the TPC bulk volume, enabling precise timing and robust particle identification.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Analysis of tow architecture variability in biaxially braided composite tubes

Spatial deviations in composite braid unit cell dimensions limit mechanical performance and are challenging to model. Full-field measurements of the irregular tow placement in biaxially braided composite tubes were obtained by digital image correlation. Analysis of the reconstructed tow paths showed long-range defects along the hoop direction with short-range defects dominating the biased tow direction. A route toward numerical simulation of the composite response is established by developing a 3D model of the composite using the measured tow trajectories. Finally, a comparison to previously-published triaxial braid results indicates axial tows work to constrain unit cells dimensions along the hoop direction.

3-Dimensional reinforcement↗
DOE OSTI2026

Event-Driven 3D Sensing Architecture

Some events happen too quickly to capture twice. Whether tracking satellites, monitoring aircraft, observing autonomous systems, or recording high speed industrial processes, imaging systems often have only one opportunity to collect the right information. If a camera is focused on the wrong distance, uses the wrong exposure, or cannot keep pace with rapid motion, important details may be lost forever. Los Alamos National Laboratory has developed an event-driven imaging architecture that preserves more information during data collection than a conventional camera. Instead of committing to a single image, the system captures data that can later be used to digitally adjust focus and exposure while reconstructing the scene in three dimensions. The result is a more flexible approach for imaging dynamic environments where conventional cameras can struggle.

42 ENGINEERING↗
DOE OSTI2020

CLUE: A Fast Parallel Clustering Algorithm for High Granularity Calorimeters in High-Energy Physics

One of the challenges of high granularity calorimeters, such as that to be built to cover the endcap region in the CMS Phase-2 Upgrade for HL-LHC, is that the large number of channels causes a surge in the computing load when clustering numerous digitized energy deposits (hits) in the reconstruction stage. In this article, we propose a fast and fully parallelizable density-based clustering algorithm, optimized for high-occupancy scenarios, where the number of clusters is much larger than the average number of hits in a cluster. The algorithm uses a grid spatial index for fast querying of neighbors and its timing scales linearly with the number of hits within the range considered. We also show a comparison of the performance on CPU and GPU implementations, demonstrating the power of algorithmic parallelization in the coming era of heterogeneous computing in high-energy physics.

Rovere, Marco↗
DOE OSTI2020

Report on Progress of correlation of in-situ and ex-situ data and the use of artificial intelligence to predict defects

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear components which will be assembled into a fully functional microreactor core. Compared with traditional manufacturing technologies, AM technologies allow (1) real-time observation of the manufacturing process at a much higher resolution using in-situ monitoring technologies to capture the sensor signatures that scientifically describe each event occurring over time and space and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on in-situ and ex-situ data correlation and associated data analytics results. Examples are provided to illustrate progress with respect to laser powder bed fusion (L-PBF), binder jetting, computed tomography (CT) reconstruction, and mechanical testing. Elements of the Digital Thread and data management infrastructure are discussed in the main document, and an extensive supplemental appendix is provided detailing the Digital Platform, as well as its implementation and subcomponents. In conclusion, the path forward for the next fiscal year is also discussed.

42 ENGINEERING↗
DOE OSTI2021

High-Resolution Scanning Coded-Mask-Based X-ray Multi-Contrast Imaging and Tomography

Near-field X-ray speckle tracking has been used in phase-contrast imaging and tomography as an emerging technique, providing higher contrast images than traditional absorption radiography. Most reported methods use sandpaper or membrane filters as speckle generators and digital image cross-correlation for phase reconstruction, which has either limited resolution or requires a large number of position scanning steps. Recently, we have proposed a novel coded-mask-based multi-contrast imaging (CMMI) technique for single-shot measurement with superior performance in efficiency and resolution compared with other single-shot methods. We present here a scanning CMMI method for the ultimate imaging resolution and phase sensitivity by using a coded mask as a high-contrast speckle generator, the flexible scanning mode, the adaption of advanced maximum-likelihood optimization to scanning data, and the multi-resolution analysis. Scanning CMMI can outperform other speckle-based imaging methods, such as X-ray speckle vector tracking, providing higher quality absorption, phase, and dark-field images with fewer scanning steps. Scanning CMMI is also successfully demonstrated in multi-contrast tomography, showing great potentials in high-resolution full-field imaging applications, such as in vivo biomedical imaging.

Qiao, Zhi (ORCID:0000000233928732)↗
DOE OSTI2026

Automatic Lane-Level Road Network Extraction from Aerial Imagery for Transportation Digital Twins

Accurate road networks are essential for credible traffic microsimulation and transportation digital twins, yet high-definition maps are often difficult to obtain due to limited availability, high cost, or proprietary restrictions. Some build networks from crowdsourced data, such as OpenStreetMap, but these sources often contain geometric and semantic inconsistencies. Others create networks manually, a process that is labor-intensive and difficult to scale. To address these limitations, this work presents an end-to-end pipeline that automatically extracts georeferenced, lane-level road networks from publicly available high-resolution satellite imagery and converts them into simulation-ready assets. The developed end-to-end pipeline has three primary modules: (1) A computer-vision-based module first detects directed lane geometries and intersection layouts. (2) A heuristic-based topology construction module then identifies approach and exit legs and establishes conflict-free lane-to-lane connections. (3) Finally, an automatic simulation-building module converts the extracted network into standard formats, e.g., OpenDRIVE, and generates routable SUMO networks. The framework supports both complete network construction from scratch and local-scale refinement of existing networks through lane-count correction, transition recovery, and geometric regularization. The proposed pipeline provides a practical pathway to generate traffic simulation networks from satellite imagery, significantly reducing manual reconstruction effort and enabling scalable, continuously updated transportation digital twins.

Guo, Hetian [University of Georgia, Athens] (ORCID↗
DOE OSTI2023

Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument

Abstract Millions of quasar spectra will be collected by the Dark Energy Spectroscopic Instrument (DESI), leading to a fourfold increase in the number of known quasars. High-accuracy quasar classification is essential to tighten constraints on cosmological parameters measured at the highest redshifts DESI observes ( z > 2.0). We present spectral templates for identification and redshift estimation of quasars in the DESI Year 1 data release. The quasar templates are comprised of two quasar eigenspectra sets, trained on spectra from the Sloan Digital Sky Survey. The sets are specialized to reconstruct quasar spectral variation observed over separate yet overlapping redshift ranges and, together, are capable of identifying DESI quasars from 0.05 < z < 7.0. The new quasar templates show significant improvement over the previous DESI quasar templates regarding catastrophic failure rates, redshift precision and accuracy, quasar completeness, and the contamination fraction in the final quasar sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation

Understanding the microstructure–property relationships of porous media is of great practical significance, based on which macroscopic physical properties can be directly derived from measurable microstructural informatics. However, establishing reliable microstructure–property mappings in an explicit manner is difficult, due to the intricacy, stochasticity, and heterogeneity of porous microstructures. In this paper, a data-driven computational framework is presented to investigate the inherent microstructure–permeability linkage for natural porous rocks, where multiple techniques are integrated together, including microscopy imaging, stochastic reconstruction, microstructural characterization, pore-scale simulation, feature selection, and data-driven modeling. A large number of 3D digital rocks with a wide porosity range are acquired from microscopy imaging and stochastic reconstruction techniques. A broad variety of morphological descriptors are used to quantitatively characterize pore microstructures from different perspectives, and they compose the raw feature pool for feature selection. Here high-fidelity lattice Boltzmann simulations are conducted to resolve fluid flow passing through porous media, from which reliable permeability references are obtained. The optimal feature set that best represents permeability is identified through a performance-oriented feature selection process, upon which a cost-effective surrogate model is rapidly fitted to approximate the microstructure-permeability mapping via data-driven modeling. This surrogate model exhibits great advantages over empirical/analytical formulas in terms of prediction accuracy and generalization capacity, which can predict reliable permeability values spanning four orders of magnitude. Besides, feature selection also greatly enhances the interpretability of the data-driven prediction model, from which new insights into the mechanism of how microstructural characteristics determine intrinsic permeability are obtained.

58 GEOSCIENCES↗
DOE OSTI2021

Reconstruction of the Room D, B, G, and Q Closure Histories at the Waste Isolation Pilot Plant

Experimental measurements of room closure in salt repositories are valuable for understanding the evolution of the underground and for validating geomechanical models. Room closure was measured during a number of experiments at the Waste Isolation Pilot Plant (WIPP) during the 1980's and 1990's. Most rooms were excavated using a multi-pass mining sequence, where each pass necessarily destroyed some of the mining sequence closure measurement points. These destroyed points were promptly reinstalled to capture the closure after the mining pass. After the room was complete, the mining sequence closure measurement stations were supplemented with remotely read closure measurement stations. Although many aspects of these experiments were thoroughly documented, the digital copies of the closure data were inadvertently destroyed, the non-trivial process of zeroing and shifting the raw closure measurements after each mining pass was not precisely described, the various closure measurements within a given room were not directly compared on the same plot, and the measurements were collected for several years longer than previously reported. Consequently, the hand-written mining sequence closure measurements for Rooms D, B, G, and Q were located in the WIPP archives, digitized, and reanalyzed for this report. The process of reconstructing the mining sequence closure histories was documented in detail and the raw data can be found in the appendices. Within the mid-section of a given room, the reconstructed closure histories were largely consistent with other mining sequence and remotely read closure histories, which builds confidence in the experiments and suggests that plane strain is an appropriate modeling assumption. The reconstructed closure histories were also reasonably consistent with previously published results, except in one notable case: the reconstructed Room Q closure histories 30 days after excavation were about 45 % less than the corresponding closures reported in Munson's 1997 capstone paper.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Public Data Set: Effects of Injected Current Streams on MHD Equilibrium Reconstruction of Local Helicity Injection Plasmas in a Spherical Tokamak

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in J.D. Weberski et al., 'Effects of Injected Current Streams on MHD Equilibrium Reconstruction of Local Helicity Injection Plasmas in a Spherical Tokamak,' Journal of Fusion Energy 43, 72 (2024).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

An Evaluation of Three Dimensional Scene Reconstruction Tools for Safeguards Applications

Over the past 5 years, advances in digital imaging and image processing have enabled everyday computing hardware, such as that found on laptops and even phones, to easily create 3D models of scenes from a series of still images. This field is broadly known as photogrammetry. For safeguards applications, a safeguards inspector could evaluate a 3D model of a facility (such as an enrichment plant or the top of a reactor) constructed from multiple photos instead of reviewing each photo individually. This report compares the detailed capabilities of a particular commercial offering (Quidient) that Oak Ridge National Laboratory (ORNL) has investigated in depth with the general capabilities provided in the industry and recommends areas where the general technology could be pursued for potential safeguards applications.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Optimal sensor placement for reconstructing wind pressure field around buildings using compressed sensing

Deciding how to optimally deploy sensors in a large, complex, and spatially extended structure is critical to ensure that the surface pressure field is accurately captured for subsequent analysis and design. In some cases, reconstruction of missing data is required in downstream tasks such as the development of digital twins. Here, this paper presents a data-driven sparse sensor selection algorithm, aiming to provide the most information contents for reconstructing aerodynamic characteristics of wind pressures over tall building structures parsimoniously. The algorithm first fits a set of basis functions to the training data, then applies a computationally efficient QR algorithm that ranks existing pressure sensors in order of importance based on the state reconstruction to this tailored basis. The findings of this study show that the proposed algorithm successfully re- constructs the aerodynamic characteristics of tall buildings from sparse measurement locations, generating stable and optimal solutions across a range of conditions. As a result, this study serves as a promising first step toward leveraging the success of data-driven and machine learning algorithms to supplement traditional genetic algorithms currently used in wind engineering.

42 ENGINEERING↗
DOE OSTI2021

Free-moving Quantitative Gamma-ray Imaging

The ability to map and estimate the activity of radiological source distributions in unknown three-dimensional environments has applications in the prevention and response to radiological accidents or threats as well as the enforcement and verification of international nuclear non-proliferation agreements. Such a capability requires well-characterized detector response functions, accurate time-dependent detector position and orientation data, a digitized representation of the surrounding 3D environment, and appropriate image reconstruction and uncertainty quantification methods. We have previously demonstrated 3D mapping of gamma-ray emitters with free-moving detector systems on a relative intensity scale using a technique called Scene Data Fusion (SDF). Here we characterize the detector response of a multi-element gamma-ray imaging system using experimentally benchmarked Monte Carlo simulations and perform 3D mapping on an absolute intensity scale. We present experimental reconstruction results from hand-carried and airborne measurements with point-like and distributed sources in known configurations, demonstrating quantitative SDF in complex 3D environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The ATLAS experiment at the CERN Large Hadron Collider: a description of the detector configuration for Run 3

The ATLAS detector is installed in its experimental cavern at Point 1 of the CERN Large Hadron Collider. During Run 2 of the LHC, a luminosity of ℒ = 2 × 10 34 cm -2 s -1 was routinely achieved at the start of fills, twice the design luminosity. For Run 3, accelerator improvements, notably luminosity levelling, allow sustained running at an instantaneous luminosity of ℒ = 2 × 10 34 cm -2 s -1 , with an average of up to 60 interactions per bunch crossing. The ATLAS detector has been upgraded to recover Run 1 single-lepton trigger thresholds while operating comfortably under Run 3 sustained pileup conditions. A fourth pixel layer 3.3 cm from the beam axis was added before Run 2 to improve vertex reconstruction and b-tagging performance. New Liquid Argon Calorimeter digital trigger electronics, with corresponding upgrades to the Trigger and Data Acquisition system, take advantage of a factor of 10 finer granularity to improve triggering on electrons, photons, taus, and hadronic signatures through increased pileup rejection. The inner muon endcap wheels were replaced by New Small Wheels with Micromegas and small-strip Thin Gap Chamber detectors, providing both precision tracking and Level-1 Muon trigger functionality. Trigger coverage of the inner barrel muon layer near one endcap region was augmented with modules integrating new thin-gap resistive plate chambers and smaller-diameter drift-tube chambers. Tile Calorimeter scintillation counters were added to improve electron energy resolution and background rejection. Upgrades to Minimum Bias Trigger Scintillators and Forward Detectors improve luminosity monitoring and enable total proton-proton cross section, diffractive physics, and heavy ion measurements. These upgrades are all compatible with operation in the much harsher environment anticipated after the High-Luminosity upgrade of the LHC and are the first steps towards preparing ATLAS for the High-Luminosity upgrade of the LHC. This paper describes the Run 3 configuration of the ATLAS detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗