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Results for “porosity analysis”

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 OSTI2021

X-ray computed tomography-based porosity analysis: Algorithms and application for porous woody biomass

The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.

42 ENGINEERING↗
DOE OSTI2018

Glass-bonded iodosodalite waste form for immobilization of 129I

Immobilization of radioiodine (e.g., 129I, 131I) is an important need for current and future nuclear fuel cycles. For the current work, iodosodalite [Na8(AlSiO4)6I2] was synthesized hydrothermally from metakaolin, NaI, and NaOH. Following hydrothermal treatment, dried unwashed powders were used to make glass-bonded iodosodalite waste forms by heating pressed pellets at 650, 750, or 850 °C with two different types of sodium borosilicate glass binders, i.e., NBS-4 and SA-800. These heat-treated specimens were characterized with X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, energy dispersive spectroscopy, thermal analysis, porosity and density measurements, neutron activation analysis, and inductively-coupled plasma mass spectrometry. The pellets mixed with 10 mass% of NBS-4 or SA-800 and heat-treated at 750 °C contained relatively high percentage iodine retention (~44-47 % of the maximum iodine loading) with relatively low porosities, while other pellets with higher percentages iodine retention either contained higher porosity or were not completely sintered. ASTM C1308 chemical durability tests of monolithic specimens showed a large initial release of Na, Al, Si, and I on the first day, possibly from water-soluble salt crystals or non-durable amorphous phases. Release rates of Na and Si were higher than for Al and I, probably due to a poorly durable Na-Si-O phase from the glass bonding matrix. The cumulative normalized release of iodine was 12.5 g m-2 for the first 10 1-d exchanges, suggestive of coherent dissolution. The average release rate from 10-24 days during the 7-d exchange intervals was 0.2336 g m-2 d-1.

sodalite, iodosodalite, waste forms, iodine↗
DOE OSTI2016

Measurement and Analysis of Porosity in Al-10Si-1Mg Components Additively Manufactured by Selective Laser Melting

Aluminum alloys are candidate materials for weight critical applications because of their excellent strength and stiffness to weight ratio. However, defects such as voids decrease the strength and fatigue life of these alloys, which can limit the application of Selective Laser Melting. In this study, the average volume fraction, average size, and size distribution of pores in Al10-Si-1Mg samples built using Selective Laser Melting have been characterized. Synchrotron high energy X-rays were used to perform computed tomography on volumes of order one cubic millimeter with a resolution of approximately 1.5 μm. Substantial variations in the pore size distributions were found as a function of process conditions. Even under conditions that ensured that all locations were melted at least once, a significant number density was found of pores above 5 μm in diameter.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗
DOE OSTI2015

NMR relaxation and exchange in metal-organic frameworks for surface area screening

We describe a robust screening technique that correlates the surface area of metal organic frameworks to the proton T-2 relaxation behavior of imbibed solvent at low field (13 MHz). In frameworks with small pore sizes (<1 nm) or strong solvent-framework interactions, diffusional exchange between the pore-confined and inter-particle solvent populations remains slow compared to the T-2 of the pore-confined solvent, allowing for a direct porosity analysis of the T-2 spectrum obtained from Laplace inversions. Increases in framework pore-size (>1 nm) lead to corresponding increases in the rate of solvent exchange, as confirmed by T-2 relaxation exchange (REXSY) experiments; increases in the pore size also increases the T-2 of the pore-confined solvent. The combination of these two effects results in comparable rates of relaxation and exchange, which precludes the direct analysis of Laplace inversions. Thus, two- and three-site kinetics models were applied to extract porosity from relaxation decays, thereby improving the utility of the porosity screening tool. (C) 2014 Elsevier Inc. All rights reserved.

Chen, JJ↗
DOE OSTI2025

Influence of Process Parameter and Build Rate Variations on Defect Formation in Laser Powder Bed Fusion SS316L

Laser powder bed fusion (LPBF) is an additive manufacturing process that has gained interest for its material fabrication due to multiple advantages, such as the ability to print parts with small feature sizes, good mechanical properties, reduced material waste, etc. However, variations in the key process parameters in LPBF may result in the instantiation of porosity defects and variation in build rate. Particularly, volumetric energy density (VED) is a variable that encapsulates a number of those parameters and represents the amount of energy input from the laser source to the feedstock. VED has been traditionally used to inform the quality of the printed part but different values of VED are presented as optimal values for certain material systems. An optimal VED value can be maintained by changing the key process parameters so that various combinations yield a constant value. In this study, an optimal constant VED value is maintained while printing SS316L with variable key processing parameters. Porosity analysis is performed using optical microscopy, as well as X-ray computed tomography, to reveal the volume density and distribution of those pores. Two primary defect categories are identified, namely lack of fusion and porosity induced by balling defects. The findings indicate that, even at optimal VED, variations in process parameters can significantly influence defect type, underscoring the sensitivity of defect formation to the variation of these parameters. Furthermore, a minor change in the build rate, driven by adjustments in process parameters, was found to influence defect categories. These findings emphasize that fine tuning the process parameters and build rate is essential to minimize defects. Finally, fiducial marks have been identified as a source of unintentional porosity defects. These results enable the refinement of process parameters, ultimately optimizing LPBF to achieve enhanced material density and expedite the printing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unveiling the porosity effect of superbase ionic liquid-modified carbon sorbents in CO 2 capture from air

Direct air capture (DAC) of CO 2 represents one of the most promising technologies to achieve negative carbon emissions. In this work, the superbase ionic liquids (ILs)-modified carbon substrates were developed for DAC of CO 2 by harnessing the strong CO 2 binding capability of IL and the ordered porous channels of the carbon supports. Detailed porosity analysis revealed that the IL with an aromatic cation and an oxygenate anion preferred to fill the micropores, and a thin layer was created on the surface of the mesopores. Strong π-π interaction between the IL layer and the carbon surface was disclosed by wide-angle X-ray scattering (WAXS) analysis, leading to enhanced thermal stability of the IL phase. For the same lL coating amount, the DAC of CO 2 evaluation revealed that a larger mesopore size and pore volume in the carbon/IL composite materials led to higher CO 2 uptake capacity by exposing more active sites to integrate CO 2 from diluted sources. Further, the thermodynamic analysis confirmed the critical role of IL coating in providing strong chemisorption sites and significantly improved selectivity to enrich the diluted CO 2 from the air atmosphere. This work provides guidance on leveraging the scaffolds' surface properties and porosities of the scaffolds to optimize DAC of CO 2 behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Experiments, Statistical Analysis, and Modeling to Evaluate the Porosity Influence in SPS Coatings

Suspension plasma spray (SPS) is far more complicated than conventional plasma spray and requires a deep knowledge about the influence of process parameters and their correlations. In this study, YSZ coatings were manufactured by SPS with six different process parameters such as plasma power, suspension mass load, original powder size, substrate surface topology, spray distance, and spray step. Then, the porosity of as-prepared coatings was investigated by image method and X-ray transmission technique. A multivariate analysis on the collected experimental data was carried out by employing mathematical statistics methods. The results showed that: 1) Coating porosity has a negative correlation with plasma power and suspension mass load and a positive correlation with the original powder size, spray distance, spray step, and substrate roughness; 2) Spraying distance is the main factor affecting to coating porosity, followed by suspension mass load and substrate surface roughness, respectively. A linear model for porosity prediction was developed and was verified by experiments. Furthermore, the mechanism by which process parameters influence coating porosity is additionally discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Structural analysis of cortical porosity applied to HR-pQCT data

Purpose: The investigation of cortical porosity is an important aspect of understanding biological, pathoetiological, and biomechanical processes occurring within the skeleton. With the emergence of HR-pQCT as a noninvasive tool suitable for clinical use, cortical porosity at appendicular sites can be directly visualizedin vivo. The aim of this study was to introduce a novel topological analysis of the cortical pore network for HR-pQCT data and determine the influence of resolution on measures of cortical pore network microstructure and topology. Methods: Cadaveric radii were scanned using HR-pQCT at two different voxel sizes (41 and 82μm) and also using μCT at a voxel size of 18 μm. HR-pQCT and μCT image sets were spatially coregistered. Segmentation and quantification of cortical porosity (Ct.Po) and mean pore diameter (Ct.Po.Dm) were achieved using an established extended cortical analysis technique. Topological classification of individual pores was performed using topology-preserving skeletonization and multicolor dilation algorithms. Based on the pore skeleton topological classification, the following parameters were quantified: total number of planar surface-skeleton canals (N.Slabs), tubular curve-skeleton canals (N.Tubes), and junction elements (N.Junctions), mean slab volume (Slab.Vol), mean tube volume (Tube.Vol), mean slab orientation (Slab.θ), mean tube orientation (Tube.θ), N.Slabs/N.Tubes, and integral (total) slab volume/integral tube volume (iSlab.Vol/iTube.Vol). An in vivo reproducibility study was also conducted to assess short-term precision of the topology parameters. Precision error was characterized using root mean square coefficient of variation (RMSCV%). Results: Correlations toμCT values for Ct.Po were significant for both the 41 and 82 μm HR-pQCT data (41: r{sup 2} = 0.82, p < 0.001, 82: r{sup 2} = 0.75, p < 0.001). For Ct.Po.Dm, only the 41 μm data were significantly predictive of μCT values (r{sup 2} = 0.72, p < 0.01) Data at both HR-pQCT voxel sizes were strongly predictive of the μCT values for N.Slabs (41: r{sup 2} = 0.93, p < 0.001; 82: r{sup 2} = 0.84, p < 0.001), N.Tubes (41: r{sup 2} = 0.94, p < 0.001; 82: r{sup 2} = 0.84, p < 0.001), and N.Junctions (41: r{sup 2} = 0.93, p < 0.001; 82: r{sup 2} = 0.78, p < 0.001), though proportional bias was evident in these correlations. Weak correlations were seen for iSlab.Vol/iTube.Vol at both voxel sizes (41: r{sup 2} = 0.52, p < 0.01; 82: r{sup 2} = 0.39, p < 0.05). Slab.Vol was significantly correlated to μCT data at 41 μm (r{sup 2} = 0.60, p < 0.01) but not at 82 μm, while Tube.Vol was significantly correlated at both voxel sizes (41: r{sup 2} = 0.79, p < 0.001; 82: r{sup 2} = 0.68, p < 0.01). In vivo precision error for these parameters ranged from 2.31 to 9.68 RMSCV%. Conclusions: Strong correlations betweenμCT- and HR-pQCT-derived measurements were found, particularly in HR-pQCT images obtained at 41 μm. These data are in agreement with our previous study investigating the effect of voxel size on standard HR-pQCT metrics of trabecular and cortical microstructure, and extend our previous findings to include topological descriptors of the cortical pore network.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗