A mathematical model and associated computer program were developed to simulate the steady state operation of wiped film evaporators for the concentration of glycerol-water solution. In this model, various assumptions were made to facilitate the mathematical model of the wiped film evaporator. The fundamental phenomena described were: sensible heating of the solution and vaporization of water. Physical property data were coded into the computer program, which performs the calculations of this model. Randomly selected experiments were carried out in a small scale wiped film evaporator from ALVAL COMPANY, using different concentrations of the glycerol solution (10, 30 and 50 Wt. %) for different feed rates (30, 50, 80, 100 and 120 l/h) and two values of steam jacket pressure (2 and 4 atm) to compare between experimental and simulation results. The statistical analysis gave correlation coefficient of 0.9972, average absolute error of 2.2527 % and F-test of 0.9639 which showed the high accuracy of the simulation work.
This paper is submitted as anew approach to simulate manufacturing control & planning system to define the problem of designing control system on the needs for materials.
Production planning & control is a total and complex operation, resides in the essence of manufacturing companies operations. The successful process of production planning and control systems is critical for the staying of manufacturing organizations in markets leading to the increasing consumer competition and which dominate most of manufacturing sectors because of the market oriented economy , thus , what has happened previously , that the companies possessed a great inventory of crude material, components, and groupings and they use in flexible techni
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In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .
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Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
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Abstract: In this paper, a U-shaped probe with a curvature diameter of half a centimeter was implemented using plastic optical fibers. A layer of the outer shell of the fibers was removed by polishing to a D-section. The sensor was tested by immersing it in a sodium chloride solution with variable refractive index depending on solution concentrations ranging from 1.333 to 1.363. In this design, the sensor experienced a decrease in its intensity as the concentration of the solution increased. The next step The sensor was coated with a thin layer of gold with a thickness of 20 nm, and the sensor was tested with the same solutions which resulted in a shift in wavelengths where the shift in wavelength was 5.37 nm and sensiti
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