Particle Size Distribution Properties Research Articles

Study on coal pulverization characteristics and gas desorption mechanism based on impact crushing experiment

The coal's particle size distribution properties after pulverization and the gas desorption behavior driven by pulverization are of profound meaning to the study of coal and gas outburst mechanism. In this paper, based on the impact crushing experiment, the tectonic coal and primary coal are crushed under different impact energy conditions. After screening the broken coal, the particle size distribution law is analyzed, and the characterization function suitable for the particle size distribution of coal particles after crushing is determined. The relationship between crushing work and new surface area and fractal dimension of coal body is discussed. The consequences indicated that the mass proportion of tectonic coal below 0.074 mm particle size is much huger than that of raw coal. G-S, R–R, and fractal distribution model describe the best particle size distribution of the two coals in the scope of 0.074∼4 mm. The new surface area added increases with the crushing work, and the tectonic coal is 1.34–1.96 times that of the raw coal. The fractal dimension diminishes first and then increases with the crushing work ratio. In addition, the gas desorption amount of coal particles with different particle sizes after coal pulverization was measured, and a dynamic model suitable for coal pulverization-driven gas desorption was established, and the experimental results were verified. The research results of this paper can provide experimental and theoretical basis for the analysis of energy dissipation in coal and gas outburst.

Characterization of suspended particles at different glacial bays at Spitsbergen

Particle size distribution (PSD) and concentration of mineral-suspended sediment released from melting glaciers are important factors affecting the local marine ecosystem, e.g. affecting the light availability in water columns, thus changing underwater light climate for photosynthetic organisms. We examined the characteristics of various samples of natural mineral assemblages suspended in different glacial bays in Hornsund and Kongsfjord at Spitsbergen. The concentrations of the total mass of particles (TSM) in suspended sediment as well as particular organic matter (POM) and particular inorganic matter mass (PIM) together with mineralogical composition and particular size distribution (PSD) were determined.In this study, we investigated the PSD properties and variability in the front of different tidewater glaciers based, laser diffractometer measurements (LISST-100x), and XRD – techniques to obtain the mineralogical composition of the particles. The sampled sites are under the strong influence of freshwater discharge from the glacier. At each station, inorganic particulate matter contributed up to 98% to total suspended matter with the particle concentration of the particle reaches up to 111 mg/l with mean surface PSD slopes ranging from 3.24 to 3.85. The result provides valuable baseline information on the observed range of variability of the size of suspended particles due to glacial runoff and the presence of particles of different mineral origin in the glacial bays.

New Estimate of Organic Carbon Export From Optical Measurements Reveals the Role of Particle Size Distribution and Export Horizon

AbstractExport of sinking particles from the surface ocean is critical for carbon sequestration and to provide energy to the deep biosphere. The magnitude and spatial patterns of this export have been estimated in the past by in situ particle flux observations, satellite‐based algorithms, and ocean biogeochemical models; however, these estimates remain uncertain. Here, we use a recent machine learning reconstruction of global ocean particle size distributions (PSDs) from Underwater Vision Profiler 5 measurements to estimate carbon fluxes by sinking particles (35 μm–5 mm equivalent spherical diameter) from the surface ocean. We combine global maps of PSD properties with empirical relationships constrained against in situ flux observations to calculate particulate carbon export from the euphotic zone (5.8 ± 0.1 Pg C y−1) and annual maximum mixed layer depths (6.1 ± 0.1 Pg C y−1). The new flux reconstructions suggest a less variable seasonal cycle in the tropical ocean and a more persistent export in the Southern Ocean than previously recognized. Smaller particles (less than 418 μm) contribute most of the flux globally, while larger particles become more important at high latitudes and in tropical upwelling regions. Export from the annual maximum mixed layer exceeds that from the euphotic zone over most of the low‐latitude ocean, suggesting shallow particle recycling and net heterotrophy in the deep euphotic zone. These estimates open the way to fully three‐dimensional global reconstructions of particle fluxes in the ocean, supported by the growing database of in situ optical observations.

Experimental Study on Fractal Characteristics of Particle Size Distribution by Repeated Compaction of Road Recycling Crushed Stone

In order to investigate the compaction characteristics of graded crushed stone under repeated utilization, it is necessary to improve the utilization rate of road recycling crushed stone and maintain its strength and stability during recycling. In the present study, repeated compaction characteristic curves of graded crushed stone were developed using repeated compaction and screening of the graded crushed stone. The correlations between the fractal dimension of particle size distribution and repeated compaction times, water content, and dry density were analyzed. The experimental results indicate that both the maximum dry density and the optimal water content increase as the repeated compaction times increase. The fractal dimension of the particle size distribution of the graded crushed stone used in this test is 2.33 to 2.57. The obtained results show that as the fractal dimension increases, the maximum dry density of the graded crushed stone increases. At a constant repeated compaction time, the fractal dimension of the particle size distribution of graded crushed stone increased and then decreased as the water content increased. In summary, the compaction performance of the structural layer of graded crushed stone can be tuned by adjusting the fractal dimension of the particle size distribution of the recycled pavement structural layer in practical applications. Moreover, the optimal graded materials can be prepared under the guidance of the fractal dimension, thereby achieving an optimized working performance of the recycled pavement structural layer.

Effect of aggregate size distribution and confining pressure on mechanical property and microstructure of cemented gangue backfill materials

The use of gangue, cementitious materials, and water mixed to make cemented gangue backfill material (CGBM) can achieve solid waste recycling while reducing environmental problems caused by its accumulation. In this paper, the fractal dimension of particle size distribution (PSD) and the confining pressure were investigated on the compressive strength, elastic modulus, stress–strain behavior, dilatancy deformation, and failure mode of CGBM using uniaxial compression, conventional triaxial compression, and microscopic scanning tests. The mechanism of the PSD fractal dimension on the mechanical properties of CGBM was revealed from a microscopic perspective. The results demonstrate that the compressive strength and elastic modulus of CGBM are quadratic polynomial and positively linearly related to the PSD fractal dimension and confining pressure respectively, with the PSD fractal dimension characterizing the maximum compressive strength of CGBM ranging between 2.4150 and 2.6084. The volume strain variation of CGBM diminishes as the PSD fractal dimension grows and increases dramatically when the confining pressure rises. The PSD fractal dimension has a quadratic polynomial relationship with both the cohesive force and the internal friction angle of CGBM. A reasonable PSD fractal dimension can optimize the microstructure of CGBM, reduce the distribution of defects such as microcracks and micropores, and enable hydration products to effectively fill the defects, guaranteeing that the CGBM has sufficient load-bearing capacity.

Variability of Marine Particle Size Distributions and the Correlations with Inherent Optical Properties in the Coastal Waters of the Northern South China Sea

Particle size distribution (PSD), which is an important characteristic of marine suspended particles, plays a role in how light transfers in the ocean and impacts the ocean’s inherent optical properties (IOPs). However, PSD properties and the correlations with IOPs are rarely reported in coastal waters with complex optical properties. This study investigated the PSD variabilities both for the surface water and the water in vertical planes, and the correlations between PSD and the backscattering coefficient (bbp), scattering coefficient (bp), and attenuation coefficient (cp), based on in situ PSD observations (within a size range of 2.05–297 μm) and IOPs in the coastal northern South China Sea. The results show a large variety of PSDs, with a range of 41.06–263.02 μm for the median particle diameter (Dv50) and a range of 2.61–3.74 for the PSD slope. In addition, the predominance of small particles is most likely to appear in the nearshore shallow water and estuaries with a large amount of sediment discharge, and vice versa. For the variabilities of IOPs, the particle concentration in a cross-sectional area (AC) is the first driving factor of the variations of bbp, bp, and cp, and the product of the mean particle diameter (DA) and the apparent density (ρa) can explain most variations of the mass-specific bbp (bbp/SPM), bp (bp/SPM), and cp (cp/SPM). In this study, we found that particle size is strongly correlated with volume-specific bbp (bbp/VC), bp (bp/VC), and cp (cp/VC), and the 10th percentile diameter of the accumulated volume concentration (Dv10) can better explain the variations of bbp/VC. These findings suggest a potential PSD retrieval method utilizing the bbp or bp, which may be determined by remote sensing observations.

Snow microphysical retrieval from the NASA D3R radar during ICE-POP 2018

Abstract. A method is developed to use both polarimetric and dual-frequency radar measurements to retrieve microphysical properties of falling snow. It is applied to the Ku- and Ka-band measurements of the NASA dual-polarization, dual-frequency Doppler radar (D3R) obtained during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign and incorporates the Atmospheric Radiative Transfer Simulator (ARTS) microwave single-scattering property database for oriented particles. The retrieval uses optimal estimation to solve for several parameters that describe the particle size distribution (PSD), relative contribution of pristine, aggregate, and rimed ice species, and the orientation distribution along an entire radial simultaneously. Examination of Jacobian matrices and averaging kernels shows that the dual-wavelength ratio (DWR) measurements provide information regarding the characteristic particle size, and to a lesser extent, the rime fraction and shape parameter of the size distribution, whereas the polarimetric measurements provide information regarding the mass fraction of pristine particles and their characteristic size and orientation distribution. Thus, by combining the dual-frequency and polarimetric measurements, some ambiguities can be resolved that should allow a better determination of the PSD and bulk microphysical properties (e.g., snowfall rate) than can be retrieved from single-frequency polarimetric measurements or dual-frequency, single-polarization measurements. The D3R ICE-POP retrievals were validated using Precipitation Imaging Package (PIP) and Pluvio weighing gauge measurements taken nearby at the May Hills ground site. The PIP measures the snow PSD directly, and its measurements can be used to derived the snowfall rate (volumetric and water equivalent), mean volume-weighted particle size, and effective density, as well as particle aspect ratio and orientation. Four retrieval experiments were performed to evaluate the utility of different measurement combinations: Ku-only, DWR-only, Ku-pol, and All-obs. In terms of correlation, the volumetric snowfall rate (r=0.95) and snow water equivalent rate (r=0.92) were best retrieved by the Ku-pol method, while the DWR-only method had the lowest magnitude bias for these parameters (−31 % and −8 %, respectively). The methods that incorporated DWR also had the best correlation to particle size (r=0.74 and r=0.71 for DWR-only and All-obs, respectively), although none of the methods retrieved density particularly well (r=0.43 for All-obs). The ability of the measurements to retrieve mean aspect ratio was also inconclusive, although the polarimetric methods (Ku-pol and All-obs) had reduced biases and mean absolute error (MAE) relative to the Ku-only and DWR-only methods. The significant biases in particle size and snowfall rate appeared to be related to biases in the measured DWR, emphasizing the need for accurate DWR measurements and frequent calibration in future D3R deployments.

Scaling Properties of Particle-Size Distributions of Purple Soils in a Small-Sized Agricultural Catchment: A Multifractal Analysis

Scaling Properties of Particle-Size Distributions of Purple Soils in a Small-Sized Agricultural Catchment: A Multifractal Analysis

Impacts of 21-year field warming on soil erodibility in the Qinghai-Tibetan Plateau, China

Terrestrial ecosystems are significantly impacted by global warming. To determine the effects of long-term warming on soil structure and erodibility in the Qinghai-Tibetan Plateau (China), a 21-year field warming experiment was conducted, where the soil response to temperature changes was investigated for two vegetation types (shrubland and grassland). The measured parameters included the fractal dimension (Dv) of aggregates, mean weight diameter (MWD), geometric mean diameter (GMD), multifractal dimensions of particle size distribution [capacity dimension (D0), information dimension (D1), information dimension/capacity dimension ratio (D1/D0), and correlation dimension (D2)], and soil erodibility value (K). The results show that warming significantly increases the erodibility of the topsoil (0–2 cm). Among them, the larger particles (0.2–2 mm aggregates, sand) decreased, the K factor, Dv, and multifractal dimension (D0) increased, and the MWD and GMD of the soil aggregates decreased. Long-term warming affected the amounts of soil organic carbon, total nitrogen, and total phosphorus. Furthermore, warming weakened microbial activity and led to a reduction in the aboveground biomass of plants. With increasing soil depth, the effect of warming on the erodibility of underlying soil (2–12 cm) gradually weakened. Warming exhibited different effects on the erodibility of the shrubland and grassland because of their different soil aggregates and particle size distributions. These results confirm that long-term warming has obvious soil layering effects on different soil depths. Soil properties, plants, and microorganisms respond to warming and have direct or indirect effects on soil erodibility. The results of this study provide important insights into changes in soil structure and erodibility at high altitudes, especially under global warming.

Comparative Study on the Macroscopic and Microscopic Properties of UHPC Mixed with Limestone Powder and Slag Powder

This paper explores the development laws of the fluidity, compressive strength, and autogenous shrinkage of ultrahigh performance cement (UHPC) mixed with limestone powder (LP) and highly active ground slag powder (SP). A microscopic analysis was conducted on the hydration products and pore structures. Through quantitative research on the packing density and fractal dimension of particles in different systems, the relationship between particle characteristics and UHPC properties was established. As a result, the packing densities of the UHPC mixed solely with LP (binary system) and UHPC mixed with LP and silica fume (ternary system) are higher than those of UHPC mixed with the same amount of SP and the benchmark UHPC system; fractal dimension of particle size distribution is closely related to packing density. The LP-cement-silica fume ternary system was lowly hydrated, but it has a good grain composition and high density of slurry, which improved the compressive strength of UHPC. The compressive strength of UHPC mixed with 50% LP witnessed a more obvious decline than that of the ternary system and the one with the same amount of SP. The reason lies in the decrease in slurry due to a lack of sufficient active constituents, and the hydration products were far from enough to fill the pores in the system. LP can also inhibit autogenous shrinkage to the greatest degree for the LP-mixed binary system performed best in such inhibition.

ZnO-CuO nanocomposites: synthesis, characterization and antibacterial activity

Nanotechnology deals with the study of manipulation of the materials on molecular or an atomic scale. Nanomaterials and nanocomposites possess unique characteristics such as miniature particle sizes with a close particle size distribution properties and pose as a highly dispersed and non-agglomerative mass. The typical blend and diverse characteristics of these particles prove to be of added advantage in typical applications such as medical and pharmaceutical treatments for bacterial infections. This paper describes the detailed process of synthesizing nanocomposite oxide mixtures of copper and zinc through the sol-gel formulation route technique. The particle size distribution is assessed using Brunauer-Emmett-Teller and Scanning Electron Microscopy analysis. The mineralogical analysis of the nano-composite is carried out using X-Ray Fluorescence and X-Ray Diffraction techniques. The synthesized ZnO-CuO particles possess antibacterial properties against both gram-(positive/negative) bacteria and hence, they exhibited good results on E.coli, Staphylococcus aureus and Pseudomonas aeruginosa.

Model Technics to Predict the Impact of the Particle Size Distribution (PSD) of the Sand on the Mechanical Properties of the Cement Mortar Modified with Fly Ash

Despite many of the research studies on the effect of the particle size distribution of the sand and fly ash content on the mechanical behavior of the cement mortar, there has not been a comprehensive study investigating the effect of particle size distribution curve corresponding to 10% of finer (d10), fly ash content, curing time, sand particle size distribution properties (d10), and water to cement ratio (w/c) on the compressive (σc), tensile (σt), and flexural (σf) strengths of cement mortar. Therefore, this study investigates the subject which could be beneficial for the geotechnical and building and construction field. In this study, more than 1000 data on the mechanical properties of the cement mortar modified with different percentages of fly ash varied from 5 to 75% (by dry weight of the cement) collected from the literature. Statistical analysis and modeling were performed on the collected data. Vipulanandan p-q model was used and compared to the Logistic Growth model to predict the particle size distribution of sands used in the cement mortar. The water to cement ratio (w/c) of the cement mortar ranged between 0.20–0.80 percent and the compressive strength (σc), tensile strength (σt) and flexural strength (σf) of cement mortar modified with fly ash up to 90 days of curing were ranged between 15–88 MPa, 0.4–5 MPa, and 1–10 MPa, respectively. Vipulanandan correlation model was also used and compared with the Hoek–Brown model to correlate the mechanical properties of cement mortar modified with fly ash. The analysis and modeling results of the present study showed that there is a good relationship between the compressive strength (σc) with w/c, curing time, fly ash content and d10. Based on the coefficient of determination (R2) and root mean square error (RMSE) the compressive strength (σc), flexural strength (σf) and tensile strength (σt) of cement mortar quantified well as a function of w/c, the percentage of fly ash, curing time, and d10 using nonlinear relationship.

G-delta-L approximation software and its application tests for atmospheric scattering phase function

The expansion approximation of scattering phase function is one of the key steps to solve the atmospheric radiative transfer equation, and a scattering phase function approximation frame model (G-delta-L approximation) has been proposed by the author in 2015. This paper summarizes the design idea of G-delta-L approximation. The composition and application process of G-delta-L approximation FORTRAN software are introduced briefly. The software application tests are made for different phase functions with different properties of particle size distribution and complex refractive index. The suitable parameter sets of G-delta-L approximation are recommended for several typical phase functions when they are to be approximated with different expansion streams.

Fractal Features of Soil Particle Size Distributions and Their Implications for Indicating Enclosure Management in a Semiarid Grassland Ecosystem

Soil particle size distribution (PSD) is becoming an increasingly useful tool for the objective description of soil structure and intrinsic links between soil and the environment. Here we examined the fractal features of PSD and its correlation with soil physiochemical properties in grasslands under grazing and protected from grazing (enclosure) animals, before and after plant growing periods in a semiarid grassland ecosystem, in northern China. Our results showed that sand content was significantly higher in grassland soils under grazing compared with the enclosure at both sampling times (May and September), whereas their silt and clay contents followed the reverse pattern. The fractal dimensions of PSD (Dm) under enclosure were significantly greater than those found under grazing. The soil clay, silt contents and Dm were positively correlated with soil total N, total C, soil pH, and moisture content. By contrast, the soil sand content declined with increasing total N, total C, pH, and moisture content of soil. The soil fractal dimension of PSD had a positive correlation with soil clay and silt content, whereas it had a negatively correlated with sand content. From these results, we conclude installing enclosures can promote soil clay, silt, and soil particles' fractal dimension, with the latter could be used as a quantitative indicator of soil fertility characteristics. But it is unnecessary to use the fractal dimension of PSD as an index to evaluate the effects of enclosure management on degraded grassland.

Predictive Modeling and Multi-response Optimization of Physical and Mechanical Properties of SCC Based on Sand’s Particle Size Distribution

This paper focuses on the modeling and optimization of the physical and mechanical properties of self-compacting concrete (SCC), prepared using the modified packing model design, taking into consideration sand’s particle size distribution (PSD) and fineness modulus (FM). The optimization is predicated using the response surface methodology. The analysis of variance is exploited to determine the statistical significance of the PSD on the studied properties of SCC. For that, we studied twenty-four SCC mixtures, using three kinds of sands with different FM and particle shapes: dune sand, river sand, and crushed sand. The results show that PSD properties of used sand, despite its shape, are good predictors for SCC fresh properties, but less predictive for compressive strength. The multi-response optimization allowed the estimation of sand’s PSD parameters that give the optimal physical and mechanical properties of SCC, with an overall desirability of 0.923.

Microstructural properties and compressive strength of lime or/and cement solidified silt: a multi-scale study

Because of its poor engineering properties, silt often needs to be treated to meet the design requirements. Solidification using binder is one of the most common methods to improve the engineering properties of silt. Lime or/and cement are often used to treat silt. However, the mechanical properties of soil are closely related to its microstructure. Although much research has been done on the mechanical properties and stabilization mechanism of lime or/and cement solidified silt, the multi-scale research between the microstructure and macroscopic mechanics properties of solidified silt has received no attention. Therefore, in this paper, unconfined compression, mercury intrusion, and scanning electron microscope (SEM) tests were conducted on lime, cement, and lime and cement mixtures (LC) solidified silt. The microstructure parameters of particle, pore, and contact zone were extracted from SEM images. Meanwhile, the effect of curing time and binder dosage on the microstructure parameters was analyzed. In addition, the relationship between micro-parameters and macro-mechanical strength was established. The results showed that the particle diameter, particle area, contact zone diameter, and contact zone area increased with increasing curing time and binder dosage, while the pore ratio, fractal dimension of particle size distribution (PSD), and fractal dimension of contact zone size distribution (CZSD) decreased with increasing binder dosage. The unconfined compressive strength (UCS) decreased with the increase of particle roundness, pore area, pore diameter, pore ratio, and fractal dimension of PSD, and increased with increasing fractal dimension of pore size distribution (PPSD). In addition, there were no obvious relationships between UCS and pore roundness, contact zone area, and fractal dimension of CZSD.

Thermo-Optical and Particle Number Size Distribution Characteristics of Smoldering Smoke from Biomass Burning

Controlled laboratory combustion experiments were conducted in the fire test room to mimic freshly emitted smoldering smoke of biomass burning in China. The biomass components were determined by ultimate analysis and proximate analysis before experiments. The particle number size distribution (PNSD) between 5 and 1000 nm of smoke was measured by a high sampling frequency size spectrometer. A cavity-enhanced aerosol albedometer with wavelength of 532 nm was used to measure scattering coefficients, extinction coefficients, and single scattering albedo (SSA) of smoldering smoke. The PNSDs of smoldering smoke from the burning of agricultural straw could be fitted with a bimodal lognormal distribution as modes around 10 nm (nucleation mode) and 60 nm (Aitken mode). The PNSDs of wood sawdust could be fitted with a trimodal lognormal distribution, while the two modes were in nucleation mode, and one was in Aitken mode. The bulk optical properties (scattering and extinction coefficients) of smoldering smoke had strong correlations with particle number concentrations of sizes bigger than 100 nm. The correlation between SSA and fixed carbon (FC) was strong (the correlation coefficient is 0.89), while the correlation between SSA and volatile matter (VM) or ash was weak. The relationship between SSA and N (or S) showed a positive correlation, while that of SSA and C showed a negative correlation. The relationship between SSA and VM/FC (or N) showed a strong linear relationship (r2 > 0.8). This paper could improve understanding of the relationship between the optical and particle size distribution properties of smoke from biomass burning and the components of biomass materials under similar combustion conditions.

Rehabilitation time has greater influences on soil mechanical composition and erodibility than does rehabilitation land type in the hilly-gully region of the Loess Plateau, China.

BackgroundThe major landscape in the hilly-gully region of the Loess Plateau is greatly affected by vegetation rehabilitation on abandoned cropland. Although many studies have shown that the rehabilitation have greatly improved soil conditions and protected them from erosion, these effectiveness were not always in consensus possibly due to the land type of vegetation or to the rehabilitation time. To close this gap, we conducted a long term experiment as follows.MethodsIn this study, we analysed four land types of vegetation rehabilitation (shrub land, woodland, naturally revegetated grassland, and orchard land) with different rehabilitation times and investigated the mechanical composition and erodibility of the soil. Areas of slope croplandand natural forest were selected as controls.ResultsThe results showed that soil depth, rehabilitation time and rehabilitation land type had strong impacts on soil mechanical composition, micro-aggregation and erodibility. Following rehabilitation, naturally revegetated grassland and shrub land had lower fractal dimensions of particle size distribution (fractal dimensions of PSD), fractal dimensions of micro-aggregation, and erodibility (K factor) than did cropland. Compared to the positive effects of rehabilitation mainly happened in the topsoil layer at other rehabilitation land type, that of woodland happened in the deeper soil layer. Besides, the indispensable rehabilitation time for the significant improvement of soil condition was shorter at naturally revegetated grassland than that at shrub land and woodland.DiscussionAlthough rehabilitation time was more influential than was rehabilitation land type or soil depth, the differences among the rehabilitation land types showed that naturally revegetated grassland with native plants is the most time-saving rehabilitation vegetation for the Loess Plateau in the conversion from slope cropland. The success of rehabilitation in this forestry practice was mainly contributed by the suited species of rehabilitation land type to the local climate and soil. Based on the differences of rehabilitation effectiveness resulting from land type, we should be cautious to choose land types for the rehabilitation of soil conditions in the Loess Plateau.

Fitting soil particle-size distribution (PSD) models by PSD curve fitting software

This paper describes a particle-size distribution (PSD) curve fitting software for analyzing the soil PSD and soil physical properties. A better characterization of soil texture can be obtained by describing the soil PSD using mathematical models. The mathematical equations of soil PSD are mainly used as a basis to estimate the soil hydraulic properties. Until now, many attempts are made to represent PSD curves using mathematical models, but selecting the best PSD model requires fitting all models to the PSD data, which would be difficult and time-consuming. So far, no specific program has been developed to fit the PSD models to the experimental data. A practical user-friendly software called "PSD Curve Fitting Software" was developed and introduced to program a simultaneous fitting of all models on soil PSD data of all samples. Some of the capabilities of this software are calculating evaluation statistics for all models and soils and their statistical properties such as average, standard deviation, minimum and maximum for all models, the amount of models’ fitting parameters and their statistical properties for all soil samples, soil water retention curve by Arya and Paris (1981) and Meskini-Vishkaee et al. (2014) methods, soil hydraulic conductivity by Arya et al. (1999) method, different textural and hydraulic properties, specific surface area, and other descriptive statistics of PSD for all soil samples. All calculated parameters are presented in an output Excel file format by the software. The software runs under Windows XP/7/8/10.

Estimating the efficiency of the sandy soils-cement based grout interactions from Particle size distribution (PSD)

ABSTRACT The particle size distribution of the soil fines content and mean particle size (d50) are used in a number of soil property relationships and in the soil classification. To analyze and model particle size distribution (PSD) using a modified version of Vipulanandan p-q model, some data collected from several research studies and the results of prediction were compared with the Fredlund and Logistic Growth models used in the literature. The Vipulanandan p-q model parameters were correlated very well to various indices of PSDs such as the diameter in the particle size distribution curve corresponding to 10%, 30%, 60%, and 90% of finer (d10, d30, d60, and d90 respectively), mean particle size the diameter in the particle size distribution curve corresponding to 50% finer (d50), and fines content (F%). There was no correlation between Fredlund model and Logistic Growth model parameters with soil PSD properties. Based on the coefficient of determination (R2) and root mean square error (RMSE), the proposed Vipulanandan p-q model was in a very good agreement with the experimental results. The relationship between fines content and d50 were also generalized using the Vipulanandan p-q model to quantify the upper and lower groutability limits for sandy soils.