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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 OSTI2018

The impact of carbonation on bulk and ITZ porosity in microconcrete materials with fly ash replacement

Scanning electron microscopy was used to evaluate the porosity patterns found in microconcrete materials to better understand the gaseous diffusion pathways and reaction of CO{sub 2} within the bulk cement paste and interfacial transition zone (ITZ) of microconcrete materials containing different fly ash replacement types. Image segmentation was applied to evaluate the porosity as a function of distance from an exposed surface in the bulk cement paste and from aggregate boundaries in the ITZ in both carbonated and non-carbonated microconcrete materials. The ITZ region remained more porous compared to the bulk cement paste for all microconcrete types after carbonation despite a change in the porosity profile across the ITZ region. Results indicate that both the carbonation reaction capacity and porosity before carbonation impact the decrease in porosity observed as a result of carbonation in the ITZ and bulk cement paste regions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An Assessment of the Error Due to Computing Waste Isolation Pilot Plant Porosity Using the Porosity Response Surface Approach

The Waste Isolation Pilot Plant Performance Assessment (WIPP PA) must predict the likelihood that radionuclides will escape into the biosphere via mechanisms that depend on geohydraulic flow. Ideally, one would predict the geohydraulic flow using coupled geohydraulic and geomechanical simulations, but such coupled simulations are not computationally tractable. Instead, Sandia has historically used a look-up table of porosities for a given fluid pressure and time, called the porosity response surface, but this approach can introduce porosity errors because it largely ignores the porosity’s dependence on the past fluid pressure history. This report discusses efforts to quantify these porosity errors for both the legacy and new porosity response surfaces. Six hundred different fluid pressure histories were fed through the legacy/new geomechanical model and the legacy/new porosity response surface to generate six hundred porosity error histories. The error associated with the legacy porosity surface was substantial, while the error associated with the new porosity surface was typically small, except when fluid pressures exceeded the lithostatic pressure at the repository. In response to the errors at high pressures, a preliminary study of the WIPP PA’s sensitivity to these porosity errors was conducted. The study found that reducing the porosity errors at high pressures negligibly affected predictions of radionuclide releases. Finally, an initial machine-learned model for porosity was developed. This ML model significantly reduced the porosity error at high pressures, but sizable errors remained, so more development is necessary before coupling an ML model to the geohydraulic model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared imaging thermal feature porosity probability maps

We report that local thermal history can significantly vary in parts during metal Additive Manufacturing (AM), leading to local defects. However, the sequential layer-by-layer nature of AM facilitates in-situ part voxelmetric observations that can be used to detect and correct these defects for part qualification and quality control. The challenge is to relate this local radiometric data with local defect information to estimate process error likelihood in future builds. This paper uses a Short-Wave Infrared (SWIR) camera to record the temperature history for parts manufactured with Laser Powder Bed Fusion (LPBF) processes. The porosity from a cylindrical specimen is measured by ex-situ micro-computed tomography (μCT). Specimen data from the SWIR camera, combined with the μCT data, are used to generate thermal feature-based porosity probability maps. The porosity predictions made by various SWIR thermal feature-porosity probability maps of a specimen with a complex geometry are scored against the true porosity obtained via μCT. The receiver operating characteristic curves constructed from the predictions for the complex sample demonstrate the porosity probability mapping methodology’s potential for in-situ based porosity detection.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A scale-consistent method for imaging porosity and micrite in dual-porosity carbonate rocks

Unlike many other clastic rocks, relating velocity and permeability to porosity for micrite-bearing carbonate rocks has been largely unsuccessful. Recent studies have shown that additional parameters, most notably the distribution and/or proportion of micrite, can be used to parameterize the velocity and permeability behavior. However, there is currently no scale-consistent, 3D methodology for differentiating macroporosity and microporosity from the total porosity measured on bench-top laboratory equipment. Previous studies estimated microporosity and micrite content by combining total porosity measurements conducted on whole 50 mm cores with measurements of phase volumes on 1 mm digital rocks (i.e., scale-inconsistent). As a step forward from those, we imaged dual-porosity carbonate rocks using X-ray microcomputed tomography and then leveraged a recently developed, optimization-based technique, called data-constrained modeling, to map the macroporosity and microporosity distribution of our samples. We evaluate the volumetric proportions of macropores, micropores, and coarse-grained calcite as a function of micrite content — with their respective uncertainties — all measured on the same digital rock and with the same method. Finally, we determine how measurements of the volumetric phase proportions could be extended using standard effective medium models to predict reservoir physical properties. Here, the sensitivity of these models to the proportion of micrite and microporosity within the micrite is evidence that the nonuniqueness among permeability, velocity, and porosity that is commonly observed of micrite-bearing carbonate rocks can be explained by a variation of micrite content and microporosity at a similar porosity.

58 GEOSCIENCES↗
DOE OSTI2014

Implementation and evaluation of permeability-porosity and tortuosity-porosity relationships linked to mineral dissolution-precipitation

Changes of porosity, permeability, and tortuosity due to physical and geochemical processes are of vital importance for a variety of hydrogeological systems, including passive treatment facilities for contaminated groundwater, engineered barrier systems (EBS), and host rocks for high-level nuclear waste (HLW) repositories. Due to the nonlinear nature and chemical complexity of the problem, in most cases, it is impossible to verify reactive transport codes analytically, and code intercomparisons are the most suitable method to assess code capabilities and model performance. This paper summarizes model intercomparisons for six hypothetical scenarios with generally increasing geochemical or physical complexity using the reactive transport codes CrunchFlow, HP1, MIN 3 P, PFlotran, and TOUGHREACT. Benchmark problems include the enhancement of porosity and permeability through mineral dissolution, as well as near complete clogging due to localized mineral precipitation, leading to reduction of permeability and tortuosity. Processes considered in the benchmark simulations are advective-dispersive transport in saturated media, kinetically controlled mineral dissolution-precipitation, and aqueous complexation. Porosity changes are induced by mineral dissolution-precipitation reactions, and the Carman-Kozeny relationship is used to describe changes in permeability as a function of porosity. Archie’s law is used to update the tortuosity and the pore diffusion coefficient as a function of porosity. Results demonstrate that, generally, good agreement is reached amongst the computer models despite significant differences in model formulations. As a result, some differences are observed, in particular for the more complex scenarios involving clogging; however, these differences do not affect the interpretation of system behavior and evolution.

58 GEOSCIENCES↗
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 OSTI2017

Image binarization to calculate porosity of porous anodic oxides and derivation of porosity vs current

Highlights: • A facile method based on image binarization is introduced to calculate porosity. • The method is compared with two popular methods, to show higher accuracy. • The method is tested to show robustness under different brightness and contrast. • Mathematical derivation of porosity vs current is provided. - Abstract: Current methods to calculate porosity of tubular or porous structures are either inaccurate or complicated for operation. We introduce a facile method (M7) based on image binarization of top-view specimen images from scanning electron microscopy. M7 is both accurate and convenient, and shows high robustness regardless of external parameters like brightness or contrast. Relation between porosity and applied current during galvanostatic anodization is derived. The porosity-current relation differs in aqueous and organic solution, which can be explained as different conductivity of two electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Low-Defect and Low-Porosity Hard Carbon with High Coulombic Efficiency and High Capacity for Practical Sodium Ion Battery Anode

Hard carbon is regarded as the most promising anode material for commercialization of Na ion batteries because of its high capacity and low cost. At present, the practical utilization of hard carbon anodes is largely limited by the low initial Coulombic efficiency (ICE). Na ions have been found to adopt an adsorption–insertion storage mechanism. In this paper a systematic way to control the defect concentration and porosity of hard carbon with similar overall architectures is shown. This study elucidates that the defects in the graphite layers are directly related to the ICE as they would trap Na ions and create a repulsive electric field for other Na ions so as to shorten the low-voltage intercalation capacity. The obtained low defect and porosity hard carbon electrode has achieved the highest ICE of 86.1% (94.5% for pure hard carbon material by subtracting that of the conductive carbon black), reversible capacity of 361 mA h g-1, and excellent cycle stability (93.4% of capacity retention over 100 cycles). This result sheds light on feasible design principles for high performance Na storage hard carbon: suitable carbon layer distance and defect free graphitic layers.

Xiao, Lifen↗
DOE OSTI2018

Importance of filter’s microstructure in dynamic filtration modeling of gasoline particulate filters (GPFs): Inhomogeneous porosity and pore size distribution

The state-of-the-art multiscale modeling of GPFs including channel scale, wall scale, and pore scale is described. The microstructures of two GPFs were experimentally characterized. The pore size distributions of the GPFs were determined by mercury porosimetry. The porosity was measured by X-ray computed tomography (CT) and found to be inhomogeneous across the substrate wall. The significance of pore size distribution with respect to filtration performance was analyzed. The predictions of filtration efficiency were improved by including the pore size distribution in the filtration model. A dynamic heterogeneous multiscale filtration (HMF) model was utilized to simulate particulate filtration on a single channel particulate filter with realistic particulate emissions from a spark-ignition direct-injection (SIDI) gasoline engine. The dynamic evolution of filter’s microstructure and macroscopic filtration characteristics including mass- and number-based filtration efficiencies and pressure drop were predicted and discussed. The microstructure of the GPF substrate including inhomogeneous porosity and pore size distribution is found to significantly influence local particulate deposition inside the substrate and macroscopic filtration performance and is recommended to be resolved in the filtration model to simulate and evaluate the filtration performance of GPFs.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

A Method for Determining Bulk Density, Material Density, and Porosity of Melter Feed During Nuclear Waste Vitrification

Glassmelting efficiency largely depends on heat transfer to reacting glass batch (melter feed), which in turn is influenced by the bulk density (ρ b ) and porosity (ϕ) of the reacting feed as functions of temperature ( T ). Neither ρ b ( T ) nor ϕ( T ) functions are readily accessible from direct measurements. For the determination of ρ b , we monitored the profile area of heated feed pellets and calculated the pellet volume using numerical integration. For the determination of ϕ, we measured the material density of feeds quenched at various stages of conversion via pycnometry and then computed the feed density at heat‐treatment temperature using thermal expansion values of basic feed constituents.

Hilliard, Zachary↗