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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.
3D-Laser-Scanning Technique Applied to Bulk Density Measurements of Apollo Lunar Samples
In order to better interpret gravimetric data from orbiters such as GRAIL and LRO to understand the subsurface composition and structure of the lunar crust, it is import to have a reliable database of the density and porosity of lunar materials. To this end, we have been surveying these physical properties in both lunar meteorites and Apollo lunar samples. To measure porosity, both grain density and bulk density are required. For bulk density, our group has historically utilized sub-mm bead immersion techniques extensively, though several factors have made this technique problematic for our work with Apollo samples. Samples allocated for measurement are often smaller than optimal for the technique, leading to large error bars. Also, for some samples we were required to use pure alumina beads instead of our usual glass beads. The alumina beads were subject to undesirable static effects, producing unreliable results. Other investigators have tested the use of 3d laser scanners on meteorites for measuring bulk volumes. Early work, though promising, was plagued with difficulties including poor response on dark or reflective surfaces, difficulty reproducing sharp edges, and large processing time for producing shape models. Due to progress in technology, however, laser scanners have improved considerably in recent years. We tested this technique on 27 lunar samples in the Apollo collection using a scanner at NASA Johnson Space Center. We found it to be reliable and more precise than beads, with the added benefit that it involves no direct contact with the sample, enabling the study of particularly friable samples for which bead immersion is not possible
Meteoroid Bulk Density and Ceplecha Types
The determination of asteroid bulk density is an important aspect of Near Earth Object (NEO) characterization. A fraction of meteoroids originate from asteroids (including some NEOs), thus in lieu of mutual perturbations, satellites, or expensive spacecraft missions, a study of meteoroid bulk densities can potentially provide useful insights into the densities of NEOs and PHOs (Potentially Hazardous Objects). Meteoroid bulk density is still inherently difficult to measure, and is most often determined by modeling the ablation of the meteoroid. One approach towards determining a meteoroid density distribution entails using a more easily measured proxy for the densities, then calibrating the proxy with known densities from meteorite falls, ablation modelling, and other sources. An obvious proxy choice is the Ceplecha type, KB (Ceplecha, 1958), which is thought to indicate the strength of a meteoroid and often correlated to different bulk densities in literature. KB is calculated using the air density at the beginning height of the meteor, the initial velocity, and the zenith angle of the radiant; quantities more readily determined than meteoroid bulk density itself. Numerical values of K(sub B) are sorted into groups (A, B, C, etc.), which have been matched to meteorite falls or meteor showers with known composition such as the porous Draconids. An extensive survey was conducted to establish the strength of the relationship between bulk density and K(sub B), specifically looking at those that additionally determined K(sub B) for the meteors. In examining the modeling of high-resolution meteor data from Kikwaya et al. (2011), the correlation between K(sub B) and bulk density was not as strong as hoped. However, a distinct split by dynamical type was seen with Jovian Tisserand parameter (T(sub J)), with meteoroids from Halley Type comets (T(sub J) < 2) exhibiting much lower bulk densities than those originating from Jupiter Family comets and asteroids (T(sub J) > 2). Therefore, this work indicates that the dynamical classification of a meteoroid is a better indicator of the density than the strength proxy, a somewhat surprising result.
Meteoroid Bulk Density and Ceplecha Types
Determination of asteroid bulk density is an important aspect of NEO characterization, yet difficult to measure. As a fraction of meteoroids originate from asteroids (including some NEOs), a study of meteoroid bulk densities can potentially provide useful insights into the densities of NEOs and PHOs in lieu of mutual perturbations, satellite, or expensive spacecraft missions. NASA's Meteoroid Environment Office characterizes the meteoroid environment for the purpose of spacecraft risk and operations. To accurately determine the risk, a distribution of meteoroid bulk densities are needed. This is not trivial to determine. If the particle survives to the ground the bulk density can be directly measured, however only the most dense particles land on the Earth. The next best approach is to model the meteor's ablation, which is not straightforward. Clear deceleration is necessary to do this and there are discrepancies in results between models. One approach to a distribution of bulk density is to use a measured proxy for the densities, then calibrate the proxy with known densities from meteorite falls, ablation modelling, and other sources. An obvious proxy choice is the Ceplecha type, K(sub B), thought to indicate the strength of a meteoroid. KB is frequented cited as a good proxy for meteoroid densities, but we find it is poorly correlated with density. However, a distinct split by dynamical type was seen with Jovian Tisserand parameter, T(sub J), with meteoroids from Halley Type comets (T(sub J less than 2 ) exhibiting much lower densities than those originating from Jupiter and asteroids (T(sub J greater than 2).
Synthesizing Bulk Density for Soils with Abundant Rock Fragments
Bulk density is a fundamental soil property that is difficult to determine for gravelly to extremely gravelly soils because results vary significantly with sample volume. For such coarse soils, the representative volume (for whole-soil bulk density) should be large, but guidelines for selecting an appropriate sample volume do not exist.
Soil bulk density and texture data collected during field survey associated with NEON AOP survey, East River, CO 2018
The purpose of soil core sampling was to determine soil bulk density, volumetric water content, and soil texture across the sites that were sampled in association with the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) in 2018. Soil cores were collected from surface (2.5-7.5 cm) and subsurface (50-55cm) depths at sampling sites across East River, Washington Gulch, Slate River, and Coal Creek watersheds in Gunnison, Colorado during the summer of 2018. Surface samples were weighed for determination of soil water content prior to dry down for bulk density calculations. For all samples, we measured dry weight and weight of < 2mm fraction and conducted soil textural analysis. We provide metadata for the samples, raw data files, python code that was used to calculate bulk density, water content, and texture fraction densities from primary datasets, and a final csv file with the calculated soil bulk density, volumetric water content, and soil texture data. Additional associated site metadata and vegetation fractional cover information can be found in the associated data release.
EXPERIMENTAL DETERMINATION OF THE BULK DENSITY OF BOILING LIQUID OXYGEN
Bulk density of boiling liquid oxygen
Recalculation of Soil Bulk Density Used in the Scorpius MCNP6 Model
The soil composition used in the Scorpius MCNP6.2 (Ref. 1) model was recently recalculated. Originally, it was “determined using the United States Geological Survey (USGS) Mercury Core Library and the Nevada National Security Site U.S. Geological Survey Databases (NNSS USGS) and Nevada National Security Site Petrographic, Geochemical, and Geophysical Database (NNSS PGG),” but the details had been lost. Reference 2 documents the updated soil composition determination. Reference 2 estimated the grain density of the soil instead of the bulk density. This report corrects that error. I am indebted to Garrett Euler (EES-17) for reading Ref. 2, pointing out its errors, and guiding me through the correct calculations. This report is organized as follows. For completeness, the composition calculations from Ref. 2 are repeated: Sec. II discusses the data that are reported in the PGG Access database, and Sec. III uses the data in the PGG Access database to compute the composition of the soil. Section IV estimates the bulk density of the soil. Section V evaluates the soil wall thickness in the Scorpius model. Section VI estimates the effect of the soil density change on previously calculated results. Section VII presents a summary and conclusions. Input files and output files are listed in appendices.
Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation
Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.
Effects of dry bulk density and particle size fraction on gas transport parameters in variably saturated landfill cover soil
Highlights: > The effects of soil physical properties on gas transport parameters were investigated. > Higher values of D{sub p} and k{sub a} exhibited in the '+gravel' than the '-gravel' fraction at same soil-air content ({epsilon}). > Recent power law models for D{sub p} (WLR) and k{sub a} (RPL) were modified. > Model parameters were linearly related to easily measurable dry bulk density ({rho}{sub b}). - Abstract: Landfill sites are emerging in climate change scenarios as a significant source of greenhouse gases. The compacted final soil cover at landfill sites plays a vital role for the emission, fate and transport of landfill gases. This study investigated the effects of dry bulk density, {rho}{sub b}, and particle size fraction on the main soil-gas transport parameters - soil-gas diffusivity (D{sub p}/D{sub o}, ratio of gas diffusion coefficients in soil and free air) and air permeability (k{sub a}) - under variably-saturated moisture conditions. Soil samples were prepared by three different compaction methods (Standard and Modified Proctor compaction, and hand compaction) with resulting {rho}{sub b} values ranging from 1.40 to 2.10 g cm{sup -3}. Results showed that D{sub p} and k{sub a} values for the '+gravel' fraction (<35 mm) became larger than for the '-gravel' fraction (<2 mm) under variably-saturated conditions for a given soil-air content ({epsilon}), likely due to enhanced gas diffusion and advection through less tortuous, large-pore networks. The effect of dry bulk density on D{sub p} and k{sub a} was most pronounced for the '+gravel' fraction. Normalized ratios were introduced for all soil-gas parameters: (i) for gas diffusivity D{sub p}/D{sub f}, the ratio of measured D{sub p} to D{sub p} in total porosity (f), (ii) for air permeability k{sub a}/k{sub a,pF4.1}, the ratio of measured k{sub a} to k{sub a} at 1235 kPa matric potential (=pF 4.1), and (iii) for soil-air content, the ratio of soil-air content ({epsilon}) to total porosity (f) (air saturation). Based on the normalized parameters, predictive power-law models for D{sub p}({epsilon}/f) and k{sub a}({epsilon}/f) models were developed based on a single parameter (water blockage factor M for D{sub p} and P for k{sub a}). The water blockage factors, M and P, were found to be linearly correlated to {rho}{sub b} values, and the effects of dry bulk density on D{sub p} and k{sub a} for both '+gravel' and '-gravel' fractions were well accounted for by the new models.
EFFECTIVE POROSITY IMPLIES EFFECTIVE BULK DENSITY IN SORBING SOLUTE TRANSPORT
The concept of an effective porosity is widely used in solute transport modeling to account for the presence of a fraction of the medium that effectively does not influence solute migration, apart from taking up space. This non-participating volume or ineffective porosity plays the same role as the gas phase in single-phase liquid unsaturated transport: it increases pore velocity, which is useful towards reproducing observed solute travel times. The prevalent use of the effective porosity concept is reflected by its prominent inclusion in popular texts, e.g., de Marsily (1986), Fetter (1988, 1993) and Zheng and Bennett (2002). The purpose of this commentary is to point out that proper application of the concept for sorbing solutes requires more than simply reducing porosity while leaving other material properties unchanged. More specifically, effective porosity implies the corresponding need for an effective bulk density in a conventional single-porosity model. The reason is that the designated non-participating volume is composed of both solid and fluid phases, both of which must be neglected for consistency. Said another way, if solute does not enter the ineffective porosity then it also cannot contact the adjoining solid. Conceptually neglecting the fluid portion of the non-participating volume leads to a lower (effective) porosity. Likewise, discarding the solid portion of the non-participating volume inherently leads to a lower or effective bulk density. In the author's experience, practitioners virtually never adjust bulk density when adopting the effective porosity approach.
Bulk density, grain size, carbon, and nitrogen content of floodplain fine sediment along the East River, Colorado collected from 2014 to 2017
The dataset is comprised of grain size, bulk density, carbon and nitrogen content of soils sampled on the floodplain of the East River 4 to 11 km downstream of Gothic, CO near Crested Butte. This dataset was collected to characterize the sedimentological properties and carbon inventory of the East River floodplain. The data help quantify the flux and storage of sediment and carbon between the East River and the alluvial floodplain bounding the river. The samples were collected between 2014 and 2017. The soil samples come from a total of 156 locations and were sampled in the upper 40 to 60 cm of the floodplain and in abandoned channel segments or oxbows. Not all samples were analyzed for all properties, but 26 samples were analyzed for bulk density, full particle size distribution, carbon, and nitrogen content. An additional 48 samples were analyzed for particle size fraction greater than and less than 2 mm and total organic content determined by loss on ignition. The dataset is comprised of a total of six separate data files based on the sample type and analysis and another file lists the sample identifications and locations of samples with a complete suite of analyses.
Bulk density, grain size, carbon content and isotopes, and nitrogen content of floodplain sediment along the Koyukuk River, Alaska collected in Summer 2018.
The dataset is comprised of grain size, bulk density, carbon and nitrogen content, stable carbon isotopes, and radiocarbon content of soils sampled on the floodplain of the Koyukuk River near Huslia, AK. This dataset was collected to characterize sediment properties and floodplain organic carbon stocks in the discontinuous permafrost floodplain of the Koyukuk River. The data help quantify the flux and storage of sediment and carbon between the Koyukuk River and the surrounding floodplain as the river migrates laterally. The samples were collected in June 27 - July 9, 2018. The soil samples come from a total of 24 locations and were sampled in the upper 490 cm of the river cutbanks, point bars, and floodplain. Samples were analyzed for bulk density, full particle size distribution, nitrogen content and carbon content and isotopes, though not all samples were included in each analysis. An additional 10 samples of floodplain woody debris were measured for radiocarbon content. Data, detailed methods, analyses, and interpretations were previously published at: Douglas, M. M., Lingappa, U. F., Lamb, M. P., Rowland, J. C., West, A. J., Li, G., et al. (2021). Impact of river channel lateral migration on microbial communities across a discontinuous permafrost floodplain. Applied and Environmental Microbiology, 87(20), AEM.01339-21. https://doi.org/10.1128/AEM.01339-21 Douglas, M. M., Li, G. K., Fischer, W. W., Rowland, J. C., Kemeny, P. C., West, A. J., et al. (2022). Organic carbon burial by river meandering partially offsets bank erosion carbon fluxes in a discontinuous permafrost floodplain. Earth Surface Dynamics, 10(3), 421–435. https://doi.org/10.5194/esurf-10-421-2022 The dataset is comprised of a total of three separate data files based on the sample type and analysis, including a file that lists the sample locations, permafrost presence, and geomorphic landform.
Lunar soil bulk density as determined from Surveyor data and laboratory tests
Lunar soil bulk density and coefficient of friction derived from laboratory tests and Surveyor data
Gross-fragmentation of meteoroids and bulk density of Geminids from photographic fireball records
The explicit solution of the drag and ablation equations of a single nonfragmenting meteoroid moving in any actual atmosphere was published several years ago. The solution yields the theoretical relation of l, the distance flown by the meteoroid in its trajectory, as a function of time, t, assuming that the height, h, is a known function of l. The photographic records of meteors and fireballs are coded by time marks, using a rotating shutter or a similar device to break the moving image. Time is, thus, the independent variable and for each time mark on a meteoroid trajector, the observed distance along the trajectory, l sub obs, as well as the double- or multiple- station photographs of the same meteoroid. Applying this solution to all available Prairie Network (PN) fireball-records, we recognized that the majority of them gave good solutions with standard deviations somewhat bigger than the intrinsic geometrical precision of the data. We also noticed that, on an average, previous methods of evaluation of the meteoroid velocities (interpolation polynomials, numerical differenciation of the observed l sub obs) used up to only several tens of percent of the intrinsic precision of the PN observational data. When residuals of these solutions, i.e. l sub obs - l sub com, were represented as a function of time for about 75 percent of solutions. The remaining 25 percent of residuals showed systematic changes with time exceeding one standard deviation. We tried to explain these systematic time course of residuals by using different meteoroids first computed theoretically and then analyzed by the same model as the natural PN fireballs were. The conclusion of these model computations is that systematic time changes of residuals in the nonfragmenting model exceeding one standard of deviation are caused by sudden gross fragmentation at one or more trajectory points. Thus, we generalized the explicit solution of the drag and ablation equations of a single nonfragmenting meteoroid by allowing for one or more points, where sudden gross fragmentation can occur. Using this generalized solution, the distances along the meteoroid trajectory can be computed for any choice of input parameters and compared with the observed distances flown by the meteoroid. For the most precise and long fireball trajectories, the least-squares solution can, thus, yield the initial velocities, the ablation coefficients, the dynamical masses, the positions of gross-fragmentation points, and the terminal mass. At a gross-fragmentation point, the ratio of the main mass to all the remaining fragments can be compared with the dynamic mass determined from our gross-fragmentation model and, thus, the meteoroid bulk density can be evaluated. We applied the gross-fragmentation model to sever PN fireballs showing time changes of residuals, and we recognized that, in all these cases, the new computed bulk densities of meteoroids resulted higher in comparison with the meteoroid densities determined with the non-gross-fragmentation model. Other aspects of the study are discussed.
Exploratory Experiments to Probe the Effect of Bulk Density and Porosity on The Morphology and Ejecta Kinematics of Impact Craters
The morphometry of relatively small impact craters are influenced by the physical properties of the target. To investigate the control of bulk density and porosity on the crater-formation processing the gravity regime, we conducted a series of impact experiments, varying each these target parameters while holding the other constant. Three different sands were used to construct cohesionless targets: quartz (0.4-0.8 mm), garnet (0.425-1.0 mm), and alumina (0.297-0.71mm), representing a range of intrinsic grain densities from 2.65 to 4.02 g cm-3. High-porosity targets were constructed by carefully pouring the sand into the center of a cylindrical PVC target bucket (inner diameter 26.2 cm, height 12 cm) and allowing it to fill the bucket at the angle of repose before being leveled flat at the top of the bucket. Low-porosity targets were obtained by pluviation of the granular material through a 1 mm sieve that was set directly above the target bucket. With the disparate intrinsic densities of the sand in combination with the variations of the packing technique, we attained differences in the bulk-target density of up to 32%while keeping porosity constant. The impact experiments were conducted with the vertical gun in the Experimental Impact Laboratory at NASA Johnson Space Center; using 3/16” (4.76 mm) diameter aluminum projectiles launched at1.55 ± 0.03 km s-1. The ejecta were observed using the laser-based Ejection Velocity Measurement System, providing data on launch positions and velocities of ejected particles. Submillimeter topographic data of the resulting craters were collected after each experiment with a NextEngine 3D scanner. Regardless of target material or density, all craters exhibited a simple bowl shape, but a trend of increasing depth-diameter ratio with increasing target porosity is observed across the entire experimental suite. Despite these morphometric differences, ejecta launch angles and speeds remain remarkably similar amongst all of the target configurations.
Estimating Compressional Velocity and Bulk Density Logs in Marine Gas Hydrates Using Machine Learning
Compressional velocity (Vp) and bulk density (ρb) logs are essential for characterizing gas hydrates and near-seafloor sediments; however, it is sometimes difficult to acquire these logs due to poor borehole conditions, safety concerns, or cost-related issues. We present a machine learning approach to predict either compressional Vp or ρb logs with high accuracy and low error in near-seafloor sediments within water-saturated intervals, in intervals where hydrate fills fractures, and intervals where hydrate occupies the primary pore space. We use scientific-quality logging-while-drilling well logs, gamma ray, ρb, Vp, and resistivity to train the machine learning model to predict Vp or ρb logs. Of the six machine learning algorithms tested (multilinear regression, polynomial regression, polynomial regression with ridge regularization, K nearest neighbors, random forest, and multilayer perceptron), we find that the random forest and K nearest neighbors algorithms are best suited to predicting Vp and ρb logs based on coefficients of determination (R2) greater than 70% and mean absolute percentage errors less than 4%. Given the high accuracy and low error results for Vp and ρb prediction in both hydrate and water-saturated sediments, we argue that our model can be applied in most LWD wells to predict Vp or ρb logs in near-seafloor siliciclastic sediments on continental slopes irrespective of the presence or absence of gas hydrate.