Feedstock particle size distribution and water content dynamic in a pellet mill production process and comparative sieving performance of horizontal 3.15-mm mesh and 3.15-mm hole sieves

2019 ◽  
Author(s):  
Sebastian Paczkowski ◽  
Christian Sauer ◽  
Anja Anetzberger ◽  
Marta Paczkowska ◽  
Michael Russ ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Production Process ◽  
Water Content ◽  
Size Distribution

scholarly journals Pedotransfer functions to estimate water retention parameters of soils in northeastern Brazil

2013 ◽  
Vol 37 (2) ◽  
pp. 379-391 ◽  
Author(s):  
Alexandre Hugo Cezar Barros ◽  
Quirijn de Jong van Lier ◽  
Aline de Holanda Nunes Maia ◽  
Fábio Vale Scarpare
Keyword(s):  
Particle Size ◽  
Organic Matter ◽  
Particle Size Distribution ◽  
Water Content ◽  
Size Distribution ◽  
Water Retention ◽  
Northeastern Brazil ◽  
Pedotransfer Functions ◽  
Residual Water ◽  
Specific Pressure

Pedotransfer functions (PTF) were developed to estimate the parameters (α, n, θr and θs) of the van Genuchten model (1980) to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa) and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf), totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward) to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter), and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R) and Willmott index (d). To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE). The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter content.

scholarly journals Characterization of the Relationship between the Loess Moisture and Image Grayscale Value

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7983
Author(s):  
Qingbing Liu ◽  
Jinge Wang ◽  
Hongwei Zheng ◽  
Tie Hu ◽  
Jie Zheng
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Water Content ◽  
Size Distribution ◽  
Dry Density ◽  
Model Parameters ◽  
Light Reflection ◽  
Rate Of Increase ◽  
Three Stages ◽  
The Relationship

This paper presents a model for estimating the moisture of loess from an image grayscale value. A series of well-controlled air-dry tests were performed on saturated Malan loess, and the moisture content of the loess sample during the desiccation process was automatically recorded while the soil images were continually captured using a photogrammetric device equipped with a CMOS image sensor. By converting the red, green, and blue (RGB) image into a grayscale one, the relationship between the water content and grayscale value, referred to as the water content–gray value characteristic curve (WGCC), was obtained; the impacts of dry density, particle size distribution, and illuminance on WGCC were investigated. It is shown that the grayscale value increases as the water content decreases; based on the rate of increase of grayscale value, the WGCC can be segmented into three stages: slow-rise, rapid-rise, and asymptotically stable stages. The influences that dry density and particle size distribution have on WGCC are dependent on light reflection and transmission, and this dependence is closely related to soil water types and their relative proportion. Besides, the WGCC for a given soil sample is unique if normalized with illuminance. The mechanism behind the three stages of WGCC is discussed in terms of visible light reflection. A mathematical model was proposed to describe WGCC, and the physical meaning of the model parameters was interpreted. The proposed model is validated independently using another six different types of loess samples and is shown to match well the experimental data. The results of this study can provide a reference for the development of non-contact soil moisture monitoring methods as well as relevant sensors and instruments.

scholarly journals Predicting the soil water retention curve from the particle size distribution based on a pore space geometry containing slit-shaped spaces

2018 ◽  
Vol 22 (9) ◽  
pp. 4621-4632
Author(s):  
Chen-Chao Chang ◽  
Dong-Hui Cheng
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Water Content ◽  
Size Distribution ◽  
Soil Water ◽  
Water Retention ◽  
Water Retention Curve ◽  
Soil Water Retention Curve ◽  
Soil Water Retention ◽  
Retention Curve

Abstract. Traditional models employed to predict the soil water retention curve (SWRC) from the particle size distribution (PSD) always underestimate the water content in the dry range of the SWRC. Using the measured physical parameters of 48 soil samples from the UNSODA unsaturated soil hydraulic property database, these errors were proven to originate from an inaccurate estimation of the pore size distribution. A method was therefore proposed to improve the estimation of the water content at high suction heads using a pore model comprising a circle-shaped central pore connected to slit-shaped spaces. In this model, the pore volume fraction of the minimum pore diameter range and the corresponding water content were accordingly increased. The predicted SWRCs using the improved method reasonably approximated the measured SWRCs, which were more accurate than those obtained using the traditional method and the scaling approach in the dry range of the SWRC.

scholarly journals Lactose Caking: Influence of the Particle Size Distribution and the Water Content

2015 ◽  
Vol 102 ◽  
pp. 114-122 ◽  
Author(s):  
Chloé Modugno ◽  
Anthony H.J. Paterson ◽  
Jeremy McLeod
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Water Content ◽  
Size Distribution

scholarly journals Physical and Hydraulic Properties of Commercial Pine-bark Substrate Products Used in Production of Containerized Crops

HortScience ◽  
2018 ◽  
Vol 53 (12) ◽  
pp. 1883-1890 ◽  
Author(s):  
James E. Altland ◽  
James S. Owen ◽  
Brian E. Jackson ◽  
Jeb S. Fields
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Water Content ◽  
Size Distribution ◽  
Hydraulic Properties ◽  
Fine Fraction ◽  
Total Porosity ◽  
Pine Bark ◽  
Residual Water ◽  
Eastern United States

Pine bark is the primary constituent of nursery container media (i.e., soilless substrate) in the eastern United States. Pine bark physical and hydraulic properties vary depending on the supplier due to source (e.g., lumber mill type) or methods of additional processing or aging. Pine bark can be processed via hammer milling or grinding before or after being aged from ≤1 month (fresh) to ≥6 month (aged). Additionally, bark is commonly amended with sand to alter physical properties and increase bulk density (Db). Information is limited on physical or hydraulic differences of bark between varying sources or the effect of sand amendments. Pine bark physical and hydraulic properties from six commercial sources were compared as a function of age and amendment with sand. Aging bark, alone, had little effect on total porosity (TP), which remained at ≈80.5% (by volume). However, aging pine bark from ≤1 to ≥6 months shifted particle size from the coarse (>2 mm) to fine fraction (<0.5 mm), which increased container capacity (CC) 21.4% and decreased air space (AS) by 17.2% (by volume) regardless of source. The addition of sand to the substrate had a similar effect on particle size distribution to that of aging, increasing CC and Db while decreasing AS. Total porosity decreased with the addition of sand. The magnitude of change in TP, AS, CC, and Db from a nonamended pine bark substrate was greater with fine vs. coarse sand and varied by bark source. When comparing hydrological properties across three pine bark sources, readily available water content was unaffected; however, moisture characteristic curves (MCC) differed due to particle size distribution affecting the residual water content and subsequent shift from gravitational to either capillary or hygroscopic water. Similarly, hydraulic conductivity (i.e., ability to transfer water within the container) decreased with increasing particle size.

scholarly journals Predicting the soil water characteristic curve from the particle size distribution based on a pore space geometry containing slit-shaped spaces

2017 ◽  
Author(s):  
Chen-chao Chang ◽  
Dong-hui Cheng
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Water Content ◽  
Size Distribution ◽  
Soil Water ◽  
Pore Volume ◽  
Pore Diameter ◽  
Volume Fraction ◽  
Characteristic Curve ◽  
Pore Volume Fraction

Abstract. Abstract. Traditional models employed to predict the soil water characteristic curve (SWC) from the particle size distribution (PSD) always underestimate the water content in the dry range of the SWC. Using the measured physical parameters of 48 soil samples from the UNSODA unsaturated soil hydraulic property database, these errors were proven to originate from the underestimation of the pore volume fraction of the minimum pore diameter range. A method was therefore proposed to improve the estimation of the water content in the high suction range using a pore model comprising a circle-shaped central pore connected to slit-shaped spaces; in this model, the pore volume fraction of the minimum pore diameter range and the corresponding water content were accordingly increased. The SWCs predicted using the improved method reasonably approximated the measured SWCs, and which were more accurate than those obtained using traditional method in the dry range of the SWC.

Effects of Particle Size Distribution on Corrosion Rate of Carbon Steel in Soil

2020 ◽  
Vol 69 (4) ◽  
pp. 102-106
Author(s):  
Shota Ohki ◽  
Shingo Mineta ◽  
Mamoru Mizunuma ◽  
Soichi Oka ◽  
Masayuki Tsuda
Keyword(s):  
Particle Size ◽  
Carbon Steel ◽  
Corrosion Rate ◽  
Particle Size Distribution ◽  
Size Distribution
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