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Effects of Pressure and Moisture Content on Bulk Density of Triticale Grain under Compaction
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Highlights

Compaction of triticale grain with three moisture contents (8%, 12%, and 16% wet basis) was measured at five applied pressures (0, 7, 14, 34, and 55 kPa).

Bulk density increased with increasing pressure for all moisture contents and was significantly (p < 0.0001) dependent on both moisture content and applied pressure.

A Verhulst logistic equation was found to model the changes in bulk density of triticale grain with R2 of 0.986.

The model showed similar behavior to that of wheat and rye, indicating that the results of this study can be used with the methods of ASABE Standard S413 to predict the quantity of triticale grain stored in bins.

Abstract. The objective of this study was to determine the combined effects of moisture content (MC) and pressure on the changes in bulk density of triticale grain under compaction at conditions typical of those seen in storage structures and to develop mathematical models to describe the compression behavior. Triticale compaction was measured at three MCs (8%, 12%, and 16% wet basis) and four compaction pressures (7, 14, 34, and 55 kPa) using a square metal box based on the design used in an earlier study by Thompson and Ross. Data from the compaction tests were used to calculate bulk densities for the three MCs and four pressures. Bulk densities were found to be significantly (p < 0.0001) dependent on both MC and pressure. Bulk densities varied with increasing MC, as has been observed in similar studies for other agricultural grains such as rye and wheat. These results provide guidance for estimating the bulk density of triticale in bins and other storage structures. The Verhulst logistic equation was found to best describe the changes in bulk density of triticale caused by rearrangement of the grain kernels at lower pressures for the three MCs. At higher pressures, the grain was observed to be more compliant, and Hooke’s law was used to accurately describe the observed changes. Data from the compaction tests were used to estimate the model parameters, with a correlation coefficient (R2) of 0.986. The model was then used in WPACKING to compare the results of this study to pack factor predictions for triticale and wheat. WPACKING is a computer program that is the basis for ASABE Standard S413. The results of this comparison showed that this method can be used with the methods of ASABE Standard S413 to predict the quantity of triticale grain stored in bins. Keywords: Bulk density, Interaction, Moisture content, Pressure, Triticale, Verhulst logistic equation.

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Tue Aug 03 2021
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Study the Behavior of Castellated Steel Column Encasing by Different Reactive Powder Concrete Thickness with Laced Reinforcement
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Castellated columns are structural members that are created by breaking a rolled column along the center-line by flame after that rejoining the equivalent halves by welding such that for better structural strength against axial loading, the total column depth is increased by around 50 percent. The implementation of these institutional members will also contribute to significant economies of material value. The main objectives of this study are to study the enhancement of the load-carrying capacity of castellated columns with encasement of the columns by Reactive Powder Concrete (RPC) and lacing reinforcement, and serviceability of the confined castellated columns. The Castellated columns with RPC and Lacing Reinforcement improve com

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Improving the performance of evolutionary multi-objective co-clustering models for community detection in complex social networks
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Stable Dispersion of Coal Fines during Hydraulic Fracturing Flowback in Coal Seam Gas Reservoirs—An Experimental Study
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Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
The measurements of neutron Fermi Age for selected Nuclear Reactor shielding materials using the Indium foil technique
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Publication Date
Thu Feb 01 2018
Journal Name
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Comparison of Slice inverse regression with the principal components in reducing high-dimensions data by using simulation
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This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

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Developing Human Capital according to the Communities of Practice: A comparative study by using Data Envelopment Analysis
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Publication Date
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Prediction of Hydraulic Flow Units for Jeribe Reservoir in Jambour Oil Field Applying Flow Zone Indicator Method
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   This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized por

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