Prediction of Unsaturated Soil Diffusivity Coefficient from SWCC and Saturated Permeability Tests

2014 ◽  
Author(s):  
Yi Tian ◽  
Rifat Bulut
Keyword(s):  
Unsaturated Soil ◽  
Diffusivity Coefficient

Empirical model approach for the evaluation of pH and conductivity on pollutant diffusion in soil environment

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Mathematical Model ◽  
Quadratic Equation ◽  
Diffusivity Coefficient ◽  
Soil Environment ◽  
Irreversible Reaction ◽  
Chemical Pollutant ◽  
The Mathematical Model ◽  
Coefficient Of Diffusion ◽  
Level Of Agreement ◽  
Model Approach

This work is aimed at developing a mathematical model equation that can be used to predict the fate of contaminant in the soil environment. The mathematical model was developed based on the fundamental laws of conservation and the equation of continuity given asand was resolved to obtain a quadratic equation of the form C(X) = DX2+vX+f. The developed equation was then used to fit the experimental data that were obtained from the Physio-chemical analysis of the soil samples which were obtained at various depths; within the vicinity of the H & H Asphalt plant Company, located at Enito 3 in Ahoada West L.G.A, River State, Nigeria. The Experimental and Model results obtained from the Calculation and Simulation of the developed models were compared numerically and graphically as presented in this work. It was observed that there is reasonable level of agreement between the three results. The polynomial of the curve was established to ascertain the validity of the model; this was done for all the parameters that were analyzed. From the findings the model developed can be used to predict the concentration of a chemical pollutant at various depths. The reliability of the model developed was established giving the fact that through this quadratic equation the diffusivity (coefficient of diffusion), the water velocity and the irreversible reaction decay rate could be determined.

Vapor Transport in Unsaturated Soil.

1997 ◽  
Author(s):  
Leonard W. Lion ◽  
Brent Alspach ◽  
Jason Gilbert ◽  
Sean Lorden
Keyword(s):  
Unsaturated Soil ◽  
Vapor Transport

Soil Strength Reduction Method Induced by Variation of Water Content

2012 ◽  
Vol 170-173 ◽  
pp. 847-852
Author(s):  
Peng Ming Jiang ◽  
Zhong Lei Yan ◽  
Peng Li
Keyword(s):  
Slope Stability ◽  
Unsaturated Soil ◽  
Unsaturated Soils ◽  
Characteristic Curve ◽  
Strength Reduction ◽  
Actual State ◽  
Soil Slope ◽  
Simple Method ◽  
The Common ◽  
The Stability

As the complexity of unsaturated soil theory, and it must have a long test period when we study the unsaturated soils, so the conventional design analysis software does not provide such analysis, so we can imagine that such a slope stability analysis does not accurately reflect the actual state of the slope. Based on the known soil moisture content，this paper use the soil water characteristic curve and strength theory of unsaturated soil to calculate the strength reduction parameters of soil which can calculate the stability of the soil slope when using the common calculation method. It is noticeable that this method can be extended and applied if we establish regional databases for this simple method, and these databases can improve the accuracy of the calculation of slope stability.

scholarly journals Optimization and Prediction of the Drying and Quality of Turnip Slices by Convective-Infrared Dryer under Various Pretreatments by RSM and ANFIS Methods

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 284
Author(s):  
Ebrahim Taghinezhad ◽  
Mohammad Kaveh ◽  
Antoni Szumny
Keyword(s):  
Energy Efficiency ◽  
Color Difference ◽  
Moisture Diffusivity ◽  
Effective Moisture Diffusivity ◽  
Diffusivity Coefficient ◽  
Drying Process ◽  
Anfis Model ◽  
Drying Time ◽  
Effective Moisture ◽  
Response Variables

Drying can prolong the shelf life of a product by reducing microbial activities while facilitating its transportation and storage by decreasing the product weight and volume. The quality factors of the drying process are among the important issues in the drying of food and agricultural products. In this study, the effects of several independent variables such as the temperature of the drying air (50, 60, and 70 °C) and the thickness of the samples (2, 4, and 6 mm) were studied on the response variables including the quality indices (color difference and shrinkage) and drying factors (drying time, effective moisture diffusivity coefficient, specific energy consumption (SEC), energy efficiency and dryer efficiency) of the turnip slices dried by a hybrid convective-infrared (HCIR) dryer. Before drying, the samples were treated by three pretreatments: microwave (360 W for 2.5 min), ultrasonic (at 30 °C for 10 min) and blanching (at 90 °C for 2 min). The statistical analyses of the data and optimization of the drying process were achieved by the response surface method (RSM) and the response variables were predicted by the adaptive neuro-fuzzy inference system (ANFIS) model. The results indicated that an increase in the dryer temperature and a decline in the thickness of the sample can enhance the evaporation rate of the samples which will decrease the drying time (40–20 min), SEC (from 168.98 to 21.57 MJ/kg), color difference (from 50.59 to 15.38) and shrinkage (from 67.84% to 24.28%) while increasing the effective moisture diffusivity coefficient (from 1.007 × 10−9 to 8.11 × 10−9 m2/s), energy efficiency (from 0.89% to 15.23%) and dryer efficiency (from 2.11% to 21.2%). Compared to ultrasonic and blanching, microwave pretreatment increased the energy and drying efficiency; while the variations in the color and shrinkage were the lowest in the ultrasonic pretreatment. The optimal condition involved the temperature of 70 °C and sample thickness of 2 mm with the desirability above 0.89. The ANFIS model also managed to predict the response variables with R2 > 0.96.

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