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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 OSTI2021

pnnl/galas

Codebase for analyzing large atomistic simulation results using graph analytics. Analysis of large molecular simulations is difficult due to size and memory constrains in commonly used analysis software. This code was developed to analyze an ~8 million atom polycrystalline Al system under shear, with a particular emphasis on identifying defect structures. This code applies graph theory to reduce the system to components of interest and applies associated algorithms to characterize these components.

Pope, Jenna (Bilbrey)↗
DOE OSTI2019

Detection and quantitation of right ventricular reversible perfusion defects by stress SPECT myocardial perfusion imaging: A proof-of-principle study

Background: In patients with right dominant coronary circulation, the right ventricular (RV) myocardium and the inferior region of the left ventricular (LV) myocardium share a common source of blood flow. We hypothesized that stress/rest SPECT myocardial perfusion imaging (MPI) could detect reversible perfusion defects in the RV in some patients with LV inferior wall perfusion abnormalities. Material and Methods: We identified 2 groups of patients with LV inferior wall perfusion defects (with or without defects in other regions of LV myocardium) from our database. Patients in group 1 (n = 17) had reversible perfusion defects in the RV free wall by visual analysis, while patients in group 2 (n = 17) did not. The images were processed with filtered back projection and, separately, with iterative reconstruction. The images were then re-processed using an automated quantitative software that is specifically designed to include the RV in the region of interest. Results: There were 76% men in group 1 and 94% in group 2 (P <0.05). The mean age was 65±20 in group 1 vs. 63±18 years in group 2 (P < 0.05). The stress type was exercise in 30% in group 1 and 35% in group 2, with the remaining patients studied with pharmacological stress testing (P = NS). The presence of RV reversible perfusion defects using filtered back projection was more evident in 13 patients (75%), while it was better seen with iterative reconstruction in 4 patients (25%). By automated analysis, the RV reversible perfusion defect size was 19 ± 14% of RV myocardium. Conclusion: This proof-of-principle study demonstrates that reversible RV perfusion defects suggestive of ischemia can be detected by SPECT myocardial perfusion imaging in some patients with LV inferior ischemia by visual analysis and can be quantitated by automated programs. Further studies on the diagnostic and prognostic relevance of assessing RV ischemia on SPECT MPI are needed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Localized Deformation Investigation in Irradiated Materials via Electron Microscopy, EBSD, and In-Situ Mechanical Testing

This report describes the preliminary results of an analysis of dislocation defect structures in nondeformed and deformed austenitic stainless steels – materials of light water reactor internal components. The analysis was performed using an advanced modern approach: high-resolution electron backscatter diffraction (HR-EBSD). Work was performed at Oak Ridge National Laboratory’s Low Activation Materials Development and Analysis (LAMDA) facility. The report is divided into sections describing specific aspects of the project. Section 1 describes the necessity and importance of the defect microstructure analysis and demonstrates that there are very limited data regarding dislocation and defect population at the meso-level (i.e., a grain or group of interacting grains). Section 1 also introduces the HR-EBSD approach used in this research and provides a limited background. Section 2 describes the scanning electron microscope/EBSD systems available at the LAMDA facility, materials investigated in the present work, and hardware and software requirements for the HR-EBSD analysis. Section 3 provides preliminary HR-EBSD results for nonirradiated austenitic stainless steel in contrast to and in comparison with the conventional EBSD outcome. Section 4 describes the HR-EBSD results for austenitic stainless steel irradiated in a commercial-type nuclear power plant and subjected to in-situ mechanical testing. The analysis is focused on mapping and analyzing the geometrically necessary dislocations before and after deformation at small strain levels. As expected, the results will be beneficial for performing corrosion tests, including electrochemical microscopy, which is currently being performed within the Light Water Reactor Sustainability program at the University of California–Los Angeles (Dr. G. Sant). Section 5 summarizes the work performed, presents conclusions, and discusses future activities for this research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Mechanical Testing of Innovated Composite Polymer Material for using in Manufacture of Railway Sleepers

Faculty of Engineering at Shoubra has been funded to start a project for manufacturing railway sleepers from plastic wastes and iron slag to replace imported wooden sleepers. In this paper, performance of wooden sleepers in tracks of Egyptian Railways, including high cost and material defects as well as reasons to find out a new sleeper will be presented. Previous studies for using composite materials in manufacturing railway sleepers are illustrated. Mechanical testing has been carried out to determine the important properties of the new mixture; hence results are compared with the minimum requirements of the international railway standards. Linear analysis has been conducted using 3D-SAP2000 software to simulate the actual performance of the proposed sleeper. It is found that the testing results are larger than the required values. Thus; it is concluded that the tested material is effective and adequate to be used in manufacture of railway sleepers.

36 MATERIALS SCIENCE↗
DOE OSTI2018

New surface characterization tools for alumina based refractory material exposed to cavitation - Image analysis and pattern recognition approach

Highlights: • Surface degradation was monitored via mass loss measurement. • Observation of surface damage destruction was done using image analysis. • Shape parameters of surface defects change during cavitation. • Shape parameters changes are correlated to mass loss measurements. - Abstract: The aim of this study was to examine the influence of cavitation erosion on the morphology of defects formed on the surfaces of alumina-based materials. The alumina-based samples were exposed to cavitation erosion for 42 min. The damages that occurred were monitored at predefined time intervals by measuring the mass loss and observing the sample surfaces. Digital images of surfaces were processed using an image analysis software package to define morphological characteristics of the damages occurred. The calculated morphological parameters were subjected to analysis by pattern recognition techniques to correlate the appearance of particular morphological characteristics with the behavior of the material during cavitation erosion. The newly established method in describing cavitation erosion which uses pattern recognition approach for treatments of morphological parameters calculated for damages by image analysis tools gave the results efficient for material characterization as the traditional one.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterizing structural features of two-dimensional particle systems through Voronoi topology

This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range of nominally disordered systems, and robustly describe complex structures such as grain boundaries. This paper also introduces two-dimensional functionality into the open-source software program VoroTop which automates this analysis. This software package is built on a recently-introduced multithreaded version of V ORO ++, enabling the analysis of systems with billions of particles on high-performance computer architectures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗
DOE OSTI2018

A complex approach to assessing porous structure of structured ceramics obtained by SPS technique

Highlights: • A complex approach to microstructural analysis of nanostructured SPS ceramics was presented. • A bunch of gas, intrusion and microscopic methods were applied for open/closed porosity determination in nanoceramics. • Kinetic TPR analysis for structural changes in nanoceramic was carried out. • 3D pore visualization for nanoceramics was provided via SEM/FIB tomography • Porosity calculations were performed via BET, BJH, t-plot, Washburn equation, FEI Avizo 9.1 software results. - Abstract: Spark plasma sintering (SPS) is a highly prospective technology providing rapid consolidation of nano-disperse compositions into structured ceramics with complex structural organization. Characterizing pore structure of such systems remains a challenge due to different types, size and shape of the pores as well as structural defects occurring in the material, thus requiring special methods to quantify certain porosity type. The paper presents a complex approach to studying structure of SPS hematite-based structured ceramics. The method involves a number of gas, intrusion and electron microscopy probing techniques to characterize open and closed pores in the ceramics bulk. Low temperature nitrogen sorption has been implemented to estimate open micro- and mesoporosity in the size range 0.7–50 nm using BET, BJH and t-plot methods to process experimental data. Additionally, structural peculiarities of consolidated structured ceramics have been studied using temperature-programmed reduction (TPR) with the kinetic analysis of the results being carried out. Volume of macropores sized above 50 nm has been measured with mercury intrusion. Closed pores and structural defects have been quantified with SEM and FIB/SEM tomography. By comparing experimental and estimated results we have shown that addressing all porosity types provides a highly precise structural characterization of the material.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects

We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [1]. We focus here on test cases of physical interest where the dynamics of the system is modelled by the Langevin equation and is simulated using the molecular dynamics software LAMMPS. In this work, the parareal algorithm uses a family of machine-learning spectral neighbor analysis potentials (SNAP) as fine, reference, potentials and embedded-atom method potentials (EAM) as coarse potentials. We consider a self-interstitial atom in a tungsten lattice and compute the average residence time of the system in metastable states. Our numerical results demonstrate significant computational gains using the adaptive parareal algorithm in comparison to a sequential integration of the Langevin dynamics. We also identify a large regime of numerical parameters for which statistical accuracy is reached without being a consequence of trajectorial accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗
DOE OSTI2022

Three-Dimensional Permeability of Thick-Section Glass Fabric Reinforced Polymer Composite by Vacuum-Assisted Resin Infusion Molding

Abstract Determination of permeability of thick-section glass fabric preforms with fabric layers of different architectures is critical for manufacturing large, thick composite structures with complex geometry, such as wind turbine blades. The thick-section reinforcement permeability is inherently three-dimensional and needs to be obtained for accurate composite processing modeling and analysis. Numerical simulation of the liquid stage of vacuum-assisted resin infusion molding (VARIM) is important to advance the composite manufacturing process and reduce processing-induced defects. In this research, the 3D permeability of thick-section E-glass fabric reinforcement preforms is determined, and the results are validated by a comparison between flow front progressions from experiments and from numerical simulations using ansys fluent software. The orientation of the principal permeability axes were unknown prior to experiments. The approach used in this research differs from those in literature in that the through-thickness permeability is determined as a function of flow front positions along the principal axes and the in-plane permeabilities and is not dependent on the inlet radius. The approach was tested on reinforcements with fabric architectures which vary through-the-thickness direction, such as those in a spar cap of a wind turbine blade. The computational simulations of the flow-front progression through-the-thickness were consistent with experimental observations.

Engineering↗
DOE OSTI2016

Method for analyzing passive silicon carbide thermometry with a continuous dilatometer to determine irradiation temperature

Silicon carbide is used as a passive post-irradiation temperature monitor because the irradiation defects will anneal out above the irradiation temperature. The irradiation temperature is determined by measuring a property change after isochronal annealing, i.e., lattice spacing, dimensions, electrical resistivity, thermal diffusivity, or bulk density. However, such methods are time-consuming since the steps involved must be performed in a serial manner. This work presents the use of thermal expansion from continuous dilatometry to calculate the SiC irradiation temperature, which is an automated process requiring minimal setup time. Analysis software was written that performs the calculations to obtain the irradiation temperature and removes possible user-introduced error while standardizing the analysis. In addition, this method has been compared to an electrical resistivity and isochronal annealing investigation, and the results revealed agreement of the calculated temperatures. These results show that dilatometry is a reliable and less time-intensive process for determining irradiation temperature from passive SiC thermometry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

VTAnDeM: A python toolkit for simultaneously visualizing phase stability, defect energetics, and carrier concentrations of materials

Phase stability, defect formation energies, and carrier concentrations are closely interrelated features of semiconductors. Due to their joint dependence on the multidimensional chemical potential space, it is challenging to quantitatively establish patterns between these quantities in a given semiconductor, especially when the semiconductor is comprised of multiple elements. To enable synchronous visualization and analysis of these complementary material properties and their interdependence, we developed the Visualization Toolkit for Analyzing Defects in Materials (VTAnDeM). This python-based toolkit allows users to interactively explore how defect formation energies and carrier concentrations vary across the composition and chemical potential spaces of multicomponent semiconductors. Here, we illustrate the computational workflow that employs VTAnDeM as a post-processing tool for first-principles calculations and describe the data organization and theory underlying the visualization scheme. Furthermore, we believe that this software will serve as a useful tool for simultaneously visualizing the often complex and non-intuitive chemical potential – defect – carrier concentration phase space of semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Prognostic study of cardiac events in Japanese patients with chronic kidney disease using ECG-gated myocardial Perfusion imaging: Final 3-year report of the J-ACCESS 3 study

Background: Myocardial perfusion imaging (MPI) is considered useful for risk stratification among patients with chronic kidney disease (CKD), without renal deterioration by contrast media. Methods and Results: The Japanese Assessment of Cardiac Events and Survival Study by Quantitative Gated SPECT (J-ACCESS 3) is a multicenter, prospective cohort study investigating the ability of MPI to predict cardiac events in 529 CKD patients without a definitive coronary artery disease. All patients were assessed by stress and rest MPI with {sup 99m}Tc-tetrofosmin and data were analyzed using a defect scoring method and QGS software. Major cardiac events were analyzed for 3 years after registration. The mean eGFR was 29.0 ± 12.8 (mL/minute/1.73 m{sup 2}). The mean summed stress/rest/difference (SSS, SRS, SDS) scores were 1.9 ± 3.8, 1.1 ± 3.0, and 0.8 ± 1.8, respectively. A total of 60 cardiac events (three cardiac deaths, six sudden deaths, five nonfatal myocardial infarctions, 46 hospitalization cases for heart failure) occurred. The event-free survival rate was lower among patients with kidney dysfunction, higher SSS, and higher CRP values. Multivariate Cox regression analysis independently associated SSS ≥8, eGFR <15 (mL/minute/1.73 m{sup 2}), and CRP ≥0.3 (mg/dL) with cardiac events. Conclusions: Together with eGFR and CRP, MPI can predict cardiac events in patients with CKD.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Evaluation of δ-Phase ZrH1.4 to ZrH1.7 Thermal Neutron Scattering Laws Using Ab Initio Molecular Dynamics Simulations

Zirconium hydride is commonly used for next-generation reactor designs due to its excellent hydrogen retention capacity at temperatures below 1000 K. These types of reactors operate at thermal neutron energies and require accurate representation of thermal scattering laws (TSLs) to optimize moderator performance and evaluate the safety indicators for reactor design. In this work, we present an atomic-scale representation of sub-stoichiometric ZrH2−x(0.3≤x≤0.6), which relies on ab initio molecular dynamics (AIMD) in tandem with velocity auto-correlation (VAC) analysis to generate phonon density of states (DOS) for TSL development. The novel NJOY+NCrystal tool, developed by the European Spallation Source community, was utilized to generate the TSL formulations in the A Compact ENDF (ACE) format for its utility in neutron transport software. First, stoichiometric zirconium hydride cross sections were benchmarked with experiments. Then sub-stoichiometric zirconium hydride TSLs were developed. Significant deviations were observed between the new δ-phase ZrH2−x TSLs and the TSLs in the current ENDF release. It was also observed that varying the hydrogen vacancy defect concentration and sites did not cause as significant a change in the TSLs (e.g., ZrH1.4 vs. ZrH1.7) as was caused by the lattice transformation from ϵ- to δ-phase.

42 ENGINEERING↗
DOE OSTI2023

Computed Tomography (CT) Analysis of 3D Printed Lattice Structures

LATTICE structures are increasingly used in product design across different industries, including the Department of Energy (DOE), due to their high strength and lightweight properties. These structures possess qualities such as high stiffness, energy absorption, large surface area, and structural support. To ensure lattice structures' quality and symmetry, it is crucial to have defect-free structures. However, in some cases, traditional non-destructive evaluation methods may not be practical due to encasing lattice structures in material. To analyze the lattice structures' quality, this project will employ CT imaging to gain access to the encased structures and perform a detailed analysis of each section. Three 3D printed complex lattice cubes were created, with two exposed and one encased in material, for this project. The CT X-ray cabinet will be used to scan all three cubes, and the data collected will be reconstructed and evaluated using complex interpretation software. This analysis will allow for a detailed examination of the structure's porosity, inclusions, cracks, wall thickness, and symmetry in each section.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Characterization of topology optimized Ti-6Al-4V components using electron beam powder bed fusion

The use of manufacturing to generate topology optimized components shows promise for designers. However, designers who assume that additive manufacturing follows traditional manufacturing techniques may be misled due to the nuances in specific techniques. Since commercial topology optimization software tools are neither designed to consider orientation of the parts nor large variations in properties, the goal of this research is to evaluate the limitations of an existing commercial topology optimization software (i.e. Inspire®) using electron beam powder bed fusion (i.e. Arcam®) to produce optimized Ti-6Al-4V alloy components. Emerging qualification tools from Oak Ridge National Laboratory including in-situ near-infrared imaging and log file data analysis were used to rationalize the final performance of components. While the weight savings of each optimized part exceeded the initial criteria, the failure loads and locations proved instrumental in providing insight to additive manufacturing with topology optimization. In conclusion, this research has shown the need for a comprehensive understanding of correlations between geometry, additive manufacturing processing conditions, defect generation, and microstructure for characterization of complex components such as those designed by topology optimization.

42 ENGINEERING↗