Grain Size Distribution Research Articles

PAG TUKOY SA URI NG LUPA SA PAMAMAGITAN NG DEEP LEARNING MODEL

The distribution of grain sizes in different soil samples is essential for agriculture and geotechnics, providing high-resolution soil maps crucial for land use planning. Traditional methods for soil texture analysis are reliable but often time-consuming and inconsistent. With that, this study aims to create an efficient predictive model for soil texture classification using deep learning techniques. A dataset of 4,556 images was extensively pre-processed and trained, with a model chosen for validation due to its low MSE value of 1.18. The model's performance, evaluated through Precision, Recall, and F1 Score, showed weighted averages of 88%, 78%, and 74%, respectively, and an overall accuracy of 94.56%. Validation using 456 images revealed high accuracy for Sandy and Clayey Soils but varying results for Loamy and Silty Soils. In Trial 1, the model achieved over 91% accuracy for all soil textures, with 100% accuracy for Sandy Soil. However, Trials 2 and 3 exhibited decreased accuracy for Loamy and Silty Soils, with the lowest accuracies at 61.40% and 65.78%, respectively. These results suggest that while the model is effective for certain soil textures, it requires further refinement and additional diverse training data to consistently match the reliability of traditional methods.

Ultraviolet scattering polarization from space particles entering Earth’s atmosphere

ABSTRACT Space material from leftovers of comets and asteroids is daily entering the Earth’s atmosphere. Traditionally, this influx has been characterized from ground-based observations or through meteorite searches. However, cosmic dust and small meteoroids (below a grain size of 1 cm) are not easily detectable with the current facilities and there is scant information about them. In this work, we analyse the feasibility of characterizing the low-mass end of the dust size distribution using observations at ultraviolet wavelengths from space. For this purpose, we have computed the expected scattered ultraviolet radiation and polarization produced by space dust falling on Earth using the Monte Carlo code radmc-3d. We have built a density model attending to the features and parameters obtained from measurements of meteorites, meteor showers, and cometary dust observations. We show that silicate grains will be easily distinguishable from carbonates and irons based on polarization measurements. Moreover, the polarization reversals produced in the resonance scattering regime can be used to study the details of the size distribution of small dust grains. We point out the dependence of the modelled polarization on the way of discretizing the particle size distribution.

Physics-Based Probabilistic Permeability Prediction in Thin-Layered Reservoirs: Transport Theory, Dielectric Dispersion Logging and Core-to-Log Bayesian Statistics

Accurate permeability prediction is probably the most challenging issue in reservoir characterization, and, at the same time, it is one of the most desired targets. Conventionally, a permeability profile is inferred from core-calibrated algorithms applied at the well location to different openhole logs. However, as the models are not exact, and the assumptions are not always satisfied, the uncertainty attached to the results is high. This uncertainty is even higher in thin-layered reservoirs characterized by bed thicknesses well below the resolution capabilities of standard logging tools. In this respect, the paper deals with a novel physics-based probabilistic methodology for high-resolution permeability estimation. This relies on core data and dielectric dispersion logging (DDL)—its cm-scale vertical resolution and the related fit-for-purpose petrophysical model make the DDL tool response suitable to capture and describe the permeability heterogeneity of these very thin-laminated scenarios. The approach is presented through a study performed on several wells drilled and cored into gas-bearing distal turbidite reservoirs. Their exploration and production are particularly challenging due to the presence of thinly bedded sections with individual laminations sometimes thinner than 1 cm. DDL can be a useful tool to characterize these thin-layered scenarios since the response of rock to electromagnetic (EM) fields at different frequencies is a good indicator of its components and microscopic structure. A dedicated interpretation model has been developed to invert DDL data and obtain high-resolution (cm-scale) estimates of shallow water volume fraction, shallow water salinity, and a textural parameter that is correlated to cation exchange capacity (CEC). Permeability is then computed from a physics-based analytical model taking advantage of transport phenomena in composite materials, effective medium theory, dielectric dispersion modeling, and selected core data (i.e., grain-size distribution and CEC). All the input parameters of the proposed methodology come from DDL outcomes embedded into a core-to-log Bayesian framework. This generates a high-resolution permeability profile, together with the associated uncertainty. The match with core measurements in key wells proves to be very accurate. The prediction capability has also been demonstrated on dozens of wells by comparing DDL-based permeability to wireline formation tester (WFT) results (considering the differences in scale and lateral extent of the techniques). It is worth noting that the major strength of the method relies on the fact that no additional calibrations and/or adjustable parameters are needed. Given the high vertical resolution of the DDL tool, it is one of the few methods suitable for thin-layered reservoirs.

Size Distribution of Small Grains in the Inner Zodiacal Cloud

The Parker Solar Probe (PSP) spacecraft has transited the innermost regions of the zodiacal cloud and detects impacts to the spacecraft body via its electric field instrument. Multiple dust populations have been proposed to explain the PSP dust impact rates. PSP’s unique orbit allows us to identify a region where the impact rates are likely dominated by α-meteoroids, small zodiacal grains on approximately circular, bound orbits. From the distribution of voltage signals generated by dust impacts to PSP in this region, we find the cumulative mass index for grains with radii of ∼0.6–1.4 μm (masses of 3 × 10−15 kg to 3 × 10−14 kg) to be α = 1.1 ± 0.3 from 0.1 to 0.25 au. The cumulative mass index increases toward the Sun, with even smaller fragments generated closer to the Sun. The derived size distribution is steeper than previously estimated, and in contrast to expectations, we find that most of the dust mass resides in the smallest fragments and not in large grains inside 0.15 au. As the innermost regions of the zodiacal cloud are likely collisionally evolved, these results place new constraints on how the solar system’s zodiacal cloud and, by extension, astrophysical debris disks are partitioned in mass.

The radiative torque spin-up efficiency of ballistic dust-grain aggregates

Aims. It is quintessential for the analysis of the observed dust polarization signal to understand the rotational dynamics of interstellar dust grains. Additionally, high rotation velocities may rotationally disrupt the grains, which impacts the grain-size distribution. We aim to constrain the set of parameters for an accurate description of the rotational spin-up process of ballistic dust grain aggregates driven by radiative torques (RATs). Methods. We modeled the dust grains as complex fractal aggregates grown by the ballistic aggregation of uniform spherical particles (monomers) of different sizes. A broad variation of dust materials, shapes, and sizes were studied in the presence of different radiation sources. Results. We find that the canonical parameterization for the torque efficiency overestimates the maximum angular velocity ωRAT caused by RATs acting on ballistic grain aggregates. To resolve this problem, we propose a new parameterization that predicts ωRAT more accurately. We find that RATs are most efficient for larger grains with a lower monomer density. This manifests itself as a size- and monomer-density dependence in the constant part of the parameterization. Following the constant part, the parameterization has two power laws with different slopes that retain universality for all grain sizes. The maximum grain rotation does not scale linearly with radiation strength because different drag mechanisms dominate, depending on the grain material and environment. The angular velocity ωRAT of individual single dust grains has a wide distribution and may even differ from the mean by up to two orders of magnitude. Even though ballistic aggregates have a lower RAT efficiency, strong sources of radiation (stronger than ≈100 times the typical interstellar radiation field) may still produce rotation velocities high enough to cause the rotational disruption of dust grains.

The ADDRESS of a grain: Sediment particle tracking as an approach to assessing ecosystem quality in dammed reservoirs

The ADDRESS of a grain: Sediment particle tracking as an approach to assessing ecosystem quality in dammed reservoirs

Estimation of 3-D hydraulic conductivity fields from fictive grain-size distributions derived from 3-D geological modeling

Hydraulic conductivity (K) is a crucial parameter in hydrogeology but is highly heterogeneous and anisotropic due to variations in sediment texture, making its large-scale estimation challenging. Traditional laboratory and empirical methods based on grain-size distribution (GSD) analysis from limited data provide local K measurements, resulting in a poor representation of aquifer heterogeneity. In contrast, pumping tests estimate an integrated K value over a section of the aquifer within the cone of depression but still lack the spatial resolution needed to reveal detailed variations in K across larger aquifer extents. In this study, the Di models method was used to simulate local GSD in three-dimensional (3-D) detrital systems. The focus was to explore the potential to estimate K through simulated particle-size fractions derived from a 3-D geological model of the City of Munich. By employing log-cubic interpolation, a complete and accurate representation of the fictive GSD enabled the application of multiple empirical relationships for K estimation. The resulting 3-D K fields preserved the variability in K within each aquifer system. When averaged for each separate aquifer system across different lateral extents, i.e., 50–150 and 550 m, the predicted K values showed success rates of 44–47% with deviations of at least one order of magnitude in 15–19% of cases when compared to 364 K values derived from pumping-test data. The results highlight the ability of the approach to successfully estimate K while accounting for spatial heterogeneity, suggesting its potential for groundwater modeling, aquifer yield assessments and groundwater heat pump system design.

Extent of Benthic Habitat Disturbance by Offshore Infrastructure

The effects of the interaction between sandy, mobile, low-relief (sorted) bedforms and two sewage outfalls were investigated along the south shore of Long Island, NY. Sand bedforms at scales from ripples to ridges are common on continental shelves. In dynamic environments, these features can migrate 10s to 100s of meters per year, especially during storms. Beyond engineering considerations, little is known of the interaction between these mobile features and anthropogenic structures. Modification of bedform topography and sediment grain-size distribution can be expected to alter the species composition, abundance, and diversity of the benthic community. At the study site, the interaction increased the scour of modern fine- to medium-grained sediments extending out to a kilometer and uncovered coarser-grained late Pleistocene sediments. This alteration of the seafloor in turn resulted in changes in composition, higher abundance, and lower diversity in the species assemblage found in the impacted area. The most advantaged species was Pseudunciola obliquua, a sightless, tube-building, surface deposit-feeding amphipod that is known to prefer a dynamic coarse sand habitat. Overall, the ecological effects of artificial structures on a wave-dominated seabed with sorted bedforms have not been adequately assessed. In particular, and of great importance, is the pending large-scale development of wind farms off the East Coast of the U.S.

Investigation of microstructure, mechanical performance, and corrosion resistance of thin-walled titanium welded pipe by annealing process

Investigation of microstructure, mechanical performance, and corrosion resistance of thin-walled titanium welded pipe by annealing process

Grain-size distribution in suspension through open channel turbulent flow using space-fractional ADE

Grain-size distribution in suspension through open channel turbulent flow using space-fractional ADE

A Comprehensive Microstructure-Aware Electromigration Modeling Framework; Investigation of the Impact of Trench Dimensions in Damascene Copper Interconnects.

As electronic devices continue to shrink in size and increase in complexity, the current densities in interconnects drastically increase, intensifying the effects of electromigration (EM). This renders the understanding of EM crucial, due to its significant implications for device reliability and longevity. This paper presents a comprehensive simulation framework for the investigation of EM in nano-interconnects, with a primary focus on unravelling the influential role of microstructure, by considering the impact of diffusion heterogeneity through the metal texture and interfaces. As such, the resulting atomic flux and stress distribution within nano-interconnects could be investigated. To this end, a novel approach to generate microstructures of the conductor metal is presented, whereby a predefined statistical distribution of grain sizes obtained from experimental texture analyses can be incorporated into the presented model, making the model predictive under various scales and working conditions with no need for continuous calibration. Additionally, the study advances beyond the state-of-the-art by comprehensively simulating all stages of electromigration including stress evolution, void nucleation, and void dynamics. The model was employed to study the impact of trench dimensions on the dual damascene copper texture and its impact on electromigration aging, where the model findings were corroborated by comparing them to the available experimental findings. A nearly linear increase in normalized time to nucleation was detected as the interconnect became wider with a fixed height for aspect ratios beyond 1. However, a saturation was detected with a further increase in width for lines of aspect ratios below 1, with no effective enhancement in time to nucleation. An aspect ratio of 1 seems to maximize the EM lifetime for a fixed cross-sectional area by fostering a bamboo-like structure, where about a 2-fold of increase was estimated when going from aspect ratio 2 to 1.

Probability analysis of shallow landslides in varying vegetation zones with random soil grain-size distribution

Probability analysis of shallow landslides in varying vegetation zones with random soil grain-size distribution

The East Asian monsoon variability in the Nihewan Basin, northern China, during the Early Pleistocene: A grain size end-member modelling analysis

The East Asian monsoon variability in the Nihewan Basin, northern China, during the Early Pleistocene: A grain size end-member modelling analysis

Effects of Zn2+/Si4+ co-doping on the cation distribution, crystal structure, and microwave dielectric characteristics of spinel-structured MgAl2O4 ceramics

Effects of Zn2+/Si4+ co-doping on the cation distribution, crystal structure, and microwave dielectric characteristics of spinel-structured MgAl2O4 ceramics

Study of the rheological properties and nautical depth assessment of fine sediments in Iranian ports

Sediments containing more than 10% clay particles by mass can exhibit cohesive properties. Cohesive sediments are commonly found in coastal areas worldwide, including the southern shore of the Caspian Sea and the northern/northwestern beaches of the Persian Gulf. These cohesive sediments can form a layer of soft to extremely soft mud, known as fluid mud, covering the seabed. The study examined the properties of natural mud samples collected from different depths and locations within three Iranian ports: Anzali Port (Caspian Sea), and Khorramshahr and Bushehr Ports (Persian Gulf). The laboratory analyses included determining the sediment grain-size distribution, density, carbonate content, organic matter content, and rheological properties at different water content ratios. Disregarding the impact of variations in organic matter and carbonate contents in the samples, water content ratio was the main factor affecting the rheological properties of sediments.

Thermodynamics of Giant Molecular Clouds: The Effects of Dust Grain Size

The dust grain size distribution (GSD) likely varies significantly across star-forming environments in the Universe, but its impact on star formation remains unclear. This ambiguity arises because the GSD interacts nonlinearly with processes like heating, cooling, radiation, and chemistry, which have competing effects and varying environmental dependencies. Processes such as grain coagulation, expected to be efficient in dense star-forming regions, reduce the abundance of small grains and increase that of larger grains. Motivated by this, we investigate the effects of similar GSD variations on the thermochemistry and evolution of giant molecular clouds (GMCs) using magnetohydrodynamic simulations spanning a range of cloud masses and grain sizes, which explicitly incorporate the dynamics of dust grains within the full-physics framework of the STARFORGE project. We find that grain size variations significantly alter GMC thermochemistry: the leading-order effect is that larger grains, under fixed dust mass, GSD dynamic range, and dust-to-gas ratio, result in lower dust opacities. This reduced opacity permits interstellar radiation field and internal radiation photons to penetrate more deeply. This leads to rapid gas heating and inhibited star formation. Star formation efficiency is highly sensitive to grain size, with an order-of-magnitude reduction when grain size dynamic range increases from 10−3–0.1 μm to 0.1–10 μm. Additionally, warmer gas suppresses low-mass star formation, and decreased opacities result in a greater proportion of gas in diffuse ionized structures.

Fluid flow in three-dimensional porous systems shows power law scaling with Minkowski functionals

Integral geometry uses four geometric invariants—the Minkowski functionals—to characterize certain subsets of three-dimensional (3D) space. The question was, how is the fluid flow in a 3D porous system related to these invariants? In this work, we systematically study the dependency of permeability on the geometrical characteristics of two categories of 3D porous systems generated: (i) stochastic and (ii) deterministic. For the stochastic systems, we investigated both normal and lognormal size distribution of grains. For the deterministic porous systems, we checked for a cubic arrangement and a hexagonal arrangement of grains of equal size. Our studies reveal that for any three-dimensional porous system, ordered or disordered, permeability k follows a unique scaling relation with the Minkowski functionals: (a) volume of the pore space, (b) integral mean curvature, (c) Euler characteristic, and (d) critical cross-sectional area of the pore space. The cubic and the hexagonal symmetrical systems formed the upper and lower bounds of the scaling relations, respectively. The disordered systems lay between these bounds. Moreover, we propose a combinatoric F that weaves together the four Minkowski functionals and follows a power-law scaling with permeability. The scaling exponent is independent of particle size and distribution and has a universal value of 0.428 for 3D porous systems built of spherical grains.

Frost weathering in contemporary active-layer deposits—micro-scale records from Kaffiøyra Plain (NW Spitsbergen)

Frost weathering in contemporary active-layer deposits—micro-scale records from Kaffiøyra Plain (NW Spitsbergen)

A finite mixture distribution to model genetic architecture of image‐based oat grain morphology

Abstract The multi‐floral oat (Avena sativa L.) inflorescence influences grain size and shape distributions, affecting the physical attributes of grain quality such as plumpness, size, and uniformity. While the grain size and shape distribution has been characterized as multi‐modal, very little is known about the genetic determinants of those distributions and their properties. The goal of this study was to model grain size and shape distribution using a finite mixture distribution approach and propose new distributional traits (i.e., emerging distributional traits) to characterize genotypes. We evaluated 47 oat genotypes in four highly replicated field experiments. Grains of three panicles per plot were individually threshed and scanned. Grain area, length, width, and roundness were obtained from each grain‐based image, while emerging distributional traits were evaluated using a finite mixture distribution approach. Finally, grain size distributions from hand‐threshed panicles (representing the full biological distribution) were compared with the grain size distributions of grains harvested with a combine harvester representing commercial harvest where small grains may be blown out. The heritability of all grain traits was high (0.89–0.94), and trait distributions differed among genotypes. Grain area and length show bi‐ and trimodal distributions, while grain width and roundness are uni‐ and bimodal. Although the full biological distribution of grains differed from the combine‐harvested grains, their genetic correlations were high, suggesting the combine‐harvested distributions can be used as a proxy for full biological distributions. This study proposes a straightforward methodological approach to model grain attributes that can aid in quality evaluations for genetic studies, breeding decisions, and industry characterization.

Microstructure evolution, elemental diffusion behavior, and bonding strength of TA1/AZ31B laminated composite fabricated by hot pressing

Microstructure evolution, elemental diffusion behavior, and bonding strength of TA1/AZ31B laminated composite fabricated by hot pressing