This research presents a new study in reactive distillation by using consecutive reaction: the saponification reaction of diethyl adipate (DA) with sodium hydroxide solution .

The effect of three parameters were studied through a design of experiments applying 2³ factorial design . These parameters were : the mole ratio of DA to NaOH solution (0.1 and 1) , NaOH solution concentration (3 N and 8 N) , and batch time (1.5 hr. and 3.5 hr.) . The conversion of DA to sodium monoethyladipate(SMA)(intermediate product) was the effect of these parameters which was detected . Also , the percentage purity of the intermediate product was recorded . The results showed that increasing mole ratio of DA to NaOHsolutio

The kinetics of nickel removal from aqueous solutions using a bio-electrochemical reactor with a packed bed rotating cylinder cathode was investigated. The effects of applied voltage, initial nickel concentration, the rotation speed of the cathode, and pH on the reaction rate constant (k) were studied. The results showed that the cathodic deposition occurred under mass transfer control for all values of the applied voltage used in this research. Accordingly, the relationship between concentration and time can be represented by a first-order equation. The rate constant was found to be dependent on the applied voltage, initial nickel concentration, pH, and rotation speed. It was increased as the applied voltage increased and decreased as t

The Theoretical bases of women's rights in Islamic shariate

The syntheses, characterizations and structures of three novel dichloro(bis{2-[1-(4-methoxyphenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})metal(II), [M(L)2Cl2], complexes (metal = Mn, Co and Ni) are presented. In the solid state the molecules are arranged in infinite hydrogen-bonded 3D supramolecular structures, further stabilized by weak intermolecular π…π interactions. The DFT results for all the different spin states and isomers of dichloro(bis{2-[1-phenyl-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})metal(II) complexes, [M(L1)2Cl2], support experimental measurements, namely that (i) d5 [Mn(L1)2Cl2] is high spin with S = 5/2; (ii) d7 [Co(L1)2Cl2] has a spin state of S = 3/2, (iii) d8 [Ni(L1)2Cl2] has a spin state of S =

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

 Calculations and predication a theoretical formulas for the electron drift velocity in a gas medium are achieved to deduced the electron distribution function for different gas concentrations. The calculations are achieved by using the numerical solution for  Boltzmann transport equation in two term approximation, using the NOMAD  program for the drift velocity in a gas medium. It's necessary to note that the solution is essentially depending upon the elastic and inelastic collision cross section. In order to fixe a good accuracy for the using cross section it's necessary to calculate the electron distribution function and therefore study their behavior. Results about the electron drift velocity show that a decreasing pro

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation