Electro-kinetic remediation technology is one of the developing technologies that offer great promise for the cleanup of soils contaminated with heavy metals. A numerical model was formulated to simulate copper (Cu) transport under an electric field using one-dimensional diffusion-advection equations describing the contaminant transport driven by chemical and electrical gradients in soil during the electro-kinetic remediation as a function of time and space. This model included complex physicochemical factors affecting the transport phenomena, such as soil pH value, aqueous phase reaction, adsorption, and precipitation. One-dimensional finitedifference computer program successfully predicted meaningful values for soil pH profiles and Cu concentration profiles. The model considers that: (1) electrical potential in the soil is constant with the time; (2) the effect of temperature is negligible; and (3) dissolution of soil constituents is negligible. The predicted pH profiles and transport of copper in sandy loam soil during electrokinetic remediation were found to reasonably agree with the bench-scale electro-kinetic
experimental results. The predicted contaminant speciation and distribution (aqueous, adsorbed, and precipitated) allow for an understanding of the transport processes and chemical reactions that control electro-kinetic remediation.
The reaction of poly (vinyl alcohol) (PV A) with Urea in (DMSO) resulted in uerthanised oxim, wr,ich reacted with diacetylmonoxime in a (DY.ISOfmethanol) to give anew type (N2) polymeric bidentate imine oxime ligand [HL], The ligand was reacted with MCh (where M= Co, Cu, and Hg). Under reflux in a (DMF/Methanol) mixture with (I:1) ratio to give Complexes of the general formula [M (T.)2]X, (where M= Co,Hg, Cu). All .:ompouncs have been characterized by spectroscopic methods [IR, U.V.-Vis, A tomi<;absorption] microanalysis along with conductivity measurements, from the above:: data the proposed molecular structure for Co,Cu, and Hg is a distorted. Tetrahedml
In this paper, a mathematical model for the oxidative desulfurization of kerosene had been developed. The mathematical model and simulation process is a very important process due to it provides a better understanding of a real process. The mathematical model in this study was based on experimental results which were taken from literature to calculate the optimal kinetic parameters where simulation and optimization were conducted using gPROMS software. The optimal kinetic parameters were Activation energy 18.63958 kJ/mol, Pre-exponential factor 2201.34 (wt)-0.76636. min-1 and the reaction order 1.76636. These optimal kinetic parameters were used to find the optimal reaction conditions which
... Show MoreThe main objective of this study is to develop predictive models using SPSS software (version 18) for Marshall Test results of asphalt mixtures compacted by Hammer, Gyratory, and Roller compaction. Bulk density of (2.351) gm/cc, at OAC of (4.7) % was obtained as a benchmark after using Marshall Compactor as laboratory compactive effort with 75-blows. Same density was achieved by Roller and Gyratory Compactors using its mix designed methods.
A total of (75) specimens, for Marshall, Gyratory, and Roller Compactors have been prepared, based on OAC of (4.7) % with an additional asphalt contents of more and less than (0.5) % from the optimum value. All specimens have been subjected to Marshall Test. Mathematical model
... Show MoreIn this research, the kinetic studies of four isoenzymes of Asprtate aminotransferase, which partially purified from the urine of chronic renal failure patients were carried out .The four isoenzymes were obeyed Michaelis-Menton's equation and the optimum concentration of their substrate (Aspartic acid) was (166.5x10-3) mole/liter,and their Km values were determined. Four isoenzymesI,II,III,IV have shown an optimum pH at 7.4.The four isoenzymes obeyed Arrhenius equation up to 37º C and their Ea and Q10 constants were determined .
This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreThe health of Roadway pavement surface is considered as one of the major issues for safe driving. Pavement surface condition is usually referred to micro and macro textures which enhances the friction between the pavement surface and vehicular tires, while it provides a proper drainage for heavy rainfall water. Measurement of the surface texture is not yet standardized, and many different techniques are implemented by various road agencies around the world based on the availability of equipment’s, skilled technicians’ and funds. An attempt has been made in this investigation to model the surface macro texture measured from sand patch method (SPM), and the surface micro texture measured from out flow time (OFT) and British pendul
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