Formation of emulsions during oil production is a costly problem, and decreased water content in emulsions leads to increases productivity and reduces the potential for pipeline corrosion and equipment used. The chemical demulsification process of crude oil emulsions is one of the methods used for reducing water content. The demulsifier presence causes the film layer between water droplets and the crude oil emulsion that to become unstable, leading to the accelerated of water coalescence. This research was performed to study the performance of a chemical demulsifier Chimec2439 (commercial) a blend of non-ionic oil-soluble surfactants. The crude oils used in these experiments were Basrah and Kirkuk Iraqi crude oil. These

Abstract. Shock chlorination is a well-known practice in swimming pools and domestic wells. One of the limitations for using this technique in drinking water purification facilities is the difficulty of quickly removing high chlorine concentrations in water distribution systems or production facilities. In order to use this method in the drinking water industry a shock de-chlorination method should be introduced for producing microorganism and biocide free water. De-chlorination using natural stagnant aeration (leaving the water to lose the chlorine naturally) is the safest known method if compared with chemical and charcoaling methods. Unfortunately, stagnant aeration is a slow process. Therefore, developing a process for accelerat

Crude soybean peroxidase (SBP), isolated from soybean seed coats (hulls) at unusually low concentrations, catalyses the oxidative polymerisation of hazardous aqueous benzidine and its 3,3′-dichloro, 3,3′-dimethyl and 3,3′-dimethoxy derivatives in the presence of hydrogen peroxide. The optimum operating conditions for oxidation of 0·10 mM benzidine were investigated. At pH 5, the hydrogen peroxide-to-substrate concentration ratio was 1·5 and the minimum SBP concentration required to achieve at least 95% conversion of the benzidine in synthetic wastewater was 0·43 mU/ml. Progress curves were established for the conversion of the four substrates, and apparent first-order rate constants were derived. Enzyme-catalysed polym

In this paper, the Monte Carlo N-Particle extended  computer code (MCNP) were used to design a model of the European Sodium-cooled Fast Reactor. The multiplication factor, conversion factor, delayed neutrons fraction, doppler constant, control rod worth, sodium void worth, masses for major heavy nuclei, radial and axial power distribution at high burnup are studied. The results show that the reactor breeds fissile isotopes with a conversion ratio of 0.994 at fuel burnup 70 (GWd/T), and minor actinides are buildup inside the reactor core. The study aims to check the efficiency of the model on the calculation of the neutronic parameters of the core at high burnup.

The research aims to recognize the impact of the training program based on integrating future thinking skills and classroom interaction patterns for mathematics teachers and providing their students with creative solution skills. To achieve the goal of the research, the following hypothesis was formulated: There is no statistically significant difference at the level (0.05) between the mean scores of students of mathematics teachers whose teachers trained according to the proposed training program (the experimental group) and whose teachers were not trained according to the proposed training program (the control group) in Pre-post creative solution skills test. Research sample is consisted of (31) teachers and schools were distribut

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered