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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 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 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 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↗
NASA NTRSDate not supplied

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗
NASA NTRSDate not supplied

Porosity Area Fraction Analysis of Bonded Borosilicate Specimens From in-Situ Optical Imagery

Image segmentation methods are routinely used to analyze data derived in nondestructive testing scenarios. A typical problem in this area is to estimate porosity from X-ray Computed Tomography (CT) inspections. This investigation aims to understand the effectiveness of open-source image segmentation methods for porosity estimation from optical images in the context of strength analysis of bonded materials and provides a benchmark of performance against a standard commercial software package. The rank ordering of the specimens by porosity area fraction is consistent across both methods.

Porosity area fraction↗
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↗
DOE OSTI2025

Benchmarking image processing techniques for porosity measurement in polymer additive manufacturing: Review and experimental analysis

An image processing workflow is proposed for porosity measurement in polymer additive manufacturing. Various techniques, including global and local thresholding, region growing, and K-means clustering, were applied to microscopic images of carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) and benchmarked for their ability to accurately measure porosity. Global methods included Otsu, minimum error, iterative, and entropy-based thresholding, while local methods included Niblack, Bernsen, Sauvola, and Bradley-Roth algorithms. Artificial uneven illumination was introduced to test local adaptive thresholds. Results showed significant differences in porosity values across methods. Otsu, region growing, and K-means clustering excelled under uniform illumination, while Sauvola and Bradley-Roth performed better with uneven illumination. Comparison with X-ray computed tomography (XCT) revealed slightly lower porosity values (2.55 %) than optimized methods (2.73–2.79 %) due to XCT's lower resolution excluding smaller pores. While XCT offers finer pore detection, it limits sample volume and underestimates porosity due to spatial variation. Validation using artificial grayscale images with 5 % porosity confirmed that Otsu, Bradley-Roth, region growing, and Sauvola algorithms produced accurate results. Although tested on a single material system, these methods can be adapted to others with optimization. In conclusion, given XCT's high computational and time costs, this study highlights suitable image processing techniques as cost-effective alternatives for porosity analysis in polymer composites.

Additive manufacturing↗
DOE OSTI2020

AFIP6-MkII and RERTR-12 Porosity Data Collection and Analysis for Modeling and Simulation

Gathering data for the improvement of nuclear fuel modeling and simulation efforts is the primary driver for this work. Mechanistic models allow for a better understanding of the material on a micro- and macrostructural level while saving time and money over traditional experiment efforts. Historically, summarized data and correlations are the inputs for empirical material models and model validation. When improving these models for nuclear fuels with experimental results, there is a lack of reliable data readily available. Experiments - RERTR-12 and AFIP6-MkII - were conducted to understand the irradiation behavior of metallic U-10Mo monolithic fuels for use in extreme reactor environments such as research reactors like the Advanced Test Reactor (ATR) or the High Flux Isotope Reactor (HFIR). Microstructural characteristics of fission gas pores (FGP) in each experiment are collected using an automated image analysis technique developed at the University of Florida and presented here. A series of statistical tests are performed to explore the reliability of the results, as well as understand where the data is lacking and what future data collection is necessary to provide sufficient information to assist modeling efforts. The focus is on the porosity, pore size, and eccentricity of FGPs formed during irradiation in three AFIP6-MkII samples and one RERTR-12 sample. From the analysis, it is clear there are substantial impacts of fission density on the pore structure, but there also exist also underlying connections between each sample and the behavior observed in the pores. Further analyses of the pre- and post-irradiation microstructure are needed to improve the understanding of these connections. An early method for microstructural data analysis is presented within and is currently being expanded to include other microstructure data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2006

Computational Analysis of the Effect of Porosity on Shock Cell Strength at Cruise

A computational flow field analysis is presented of the effect of core cowl porosity on shock cell strength for a modern separate flow nozzle at cruise conditions. The goal of this study was to identify the primary physical mechanisms by which the application of porosity can reduce shock cell strength and hence the broadband shock associated noise. The flow is simulated by solving the asymptotically steady, compressible, Reynoldsaveraged Navier-Stokes equations on a structured grid using an implicit, up-wind, flux-difference splitting finite volume scheme. The standard two-equation k - epsilon turbulence model with a linear stress representation is used with the addition of a eddy viscosity dependence on total temperature gradient normalized by local turbulence length scale. Specific issues addressed in this study were the optimal area required to weaken a shock impinging on the core cowl surface and the optimal level of porosity and placement of porous areas for reduction of the overall shock cell strength downstream. Two configurations of porosity were found to reduce downstream shock strength by approximately 50%.

Massey, Steven J.↗
DOE OSTI2019

Parametric Analysis and Modeling for the Porosity Prediction in Suspension Plasma-Sprayed Coatings

The porous architecture of suspension plasma-sprayed coatings has a significant influence on the coating performances and thus should be properly designed for the intended applications. In this study, YSZ coatings were manufactured by suspension plasma spray (SPS), and a parametric study was performed with five different process parameters: suspension mass load, original powder particle size, substrate surface topology, spray distance, and spray step. Afterward, the porosity of the as-prepared coatings was investigated by imaging and x-ray transmission technique. A multivariate analysis on the collected experimental data was carried out. We report the results indicated that: (1) The total porosity of SPS coatings increases with the decrease in suspension mass load, while it shows the opposite trend by decreasing the spray distance, original powder particle size, substrate roughness, and spray step; (2) The main factor affecting coating total porosity is spray distance. Finally, a predictive model for coating total porosity was developed and was verified by experiments. Control of total porosity by using the predictive model was presented and explained as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Evaluation of LPBF Steels for Nuclear Applications

This report provides an update on the prioritization of existing reactor materials for advanced manufacturing. This report is a Milestone 3 deliverable in FY2023, under work package CT-23AN130401 to support research and qualification activities supported by the Advanced Materials and Manufacturing Technologies (AMMT) program here at Argonne National Laboratory (ANL). The focus of FY23 for ANL included the determination of a decision criteria matrix for the prioritization of existing materials, the literature review of a select few Fe-based alloys, and working with vendors to obtain customized powders. The work package also includes fabricating test samples in a Renishaw AM400 Laser Powder Bed Fusion (LPBF) system and optimizing the process parameters. The major outcomes of this work package are: With collaborations from PNNL, ORNL, and INL, we were able to establish a decision criteria matrix containing a total of 6 categories and 31 different criteria. These will be used to downselect alloys for further evaluation; As part of that, 6 different Fe-based alloys were selected, 3 austenitic stainless steels (A709, D9, AFA) and 3 ferritic/martensitic steels (HT9, Grade 91, Grade 92). Customized powders were obtained from vendors in small quantities to fabricate initial prints to check printability of these specific alloys; A total of 72 single track experiments were performed on two alloy systems, 1 austenitic stainless steel (A709) and 1 ferritic/martensitic steel (Grade 91) in order to optimize the process parameters for the full 3d prints. The optimization led to the selection of 20 different processing conditions, 10 for each class of alloys; D9 and AFA alloys showed extensive cracking and porosity in the samples. This was due to less-than-ideal conditions present in the chamber during the deposition. A709 printed using the same process parameters showed almost fully dense samples with no noticeable porosity or any other defects. SEM and EBSD analysis revealed single phase FCC microstructure with cellular structure within the grains; HT9, Grade 91, Grade 92 alloys also showed no noticeable signs of cracking and ImageJ analysis showed porosity <0.5% in all conditions. While Grade 91 and Grade 92 showed single phase BCC microstructures, the presence of martensite laths was noted in HT9 alloy; Future work will include further characterization of these alloys to better understand the microstructural evolution during the 3d printing process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗