Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect becomes more significant although the heavy oil-stocks is spiked with hydrocarbons like (gas oil, toluene and reformate). Blending of Heavy oil-stocks with hydrocarbons spikes (gas oil, toluene and reformate) form non-ideal mixtures, for which excess volume can be positive or negative depending on nature species. Spiking of Heavy oil-stocks with either gas oil or reformate resulted in negative excess volume. This shrinkage is greater for the lowest boiling point spike as in the case of reformate, While, the presence of methyl groups in aromatic rings results in a positive excess volume, as shown in toluene when blended with 40 stock but a negative excess volume was found when blended with 60 stock and 150 stock. The API gravity of heavy oil-stocks has an effect on excess volume when the oil-stocks spiked with hydrocarbons like (gas oil, toluene and reformate). This 40 stocks as a typical light types resulted in minimum negative excess volume of -0.47 at 30 °C, when it was spiked with the gas oil; while the spiked heavy oil-stock with kerosene shows a maximum excess volume of -15.56 at 40 °C.
Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of
... Show More
Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a
... Show More
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show More
(2)
(3)
CdSe quantum dots possess a tuning energy gap which can control gap values according to the size of the quantum dots, this is made the material able to absorb the wavelengths within visible light. A simple model is provided for the absorption coefficient, optical properties, and optical constants for CdSe quantum dots from the size 10nm to 1nm with the range of visible region between (300-730) nm at room temperature. It turns out that there is an absorption threshold for each wavelength, CdSe quantum dots begin to absorb the visible spectrum of 1.4 nm at room temperature for a wavelength of 300 nm. It has been noted that; when the wavelength is increased, the absorption threshold also increases. This applies to the optical propertie
... Show More
In the present work effect of recycled heating and cooling on the values of concrete compressive strength due to high temperature of 4000C was studied.
The tests show that the percent of reduction in compressive strength of the samples which exposed to a temperature of 4000C for one cycle was 32.5%, while the reduction was 52.7% for the samples which were exposed to recycled heating and cooling of ten times .
Moreover a study of the effect of specimen sizes on the percentages of compressive strength reduction due to high temperature
... Show More
(54)
(46)
(2)
A method was developed that offers a rapid, simple and accurate technique for the determination of chlorophenols at trace levels in aqueous samples with very limited volumes of organic solvents. These compounds were acetylated, then preliminarily extracted with n-hexane. The enriched chlorophenols were directly analyzed using gas chromatography with an electron-capture detector. The detection limits were in the range of 0.001–0.005 mg/L, except for 2-chlorophenol, which was always above 0.013 mg/L. Relative standard deviation for the spiked water samples ranged from 2.2 to 6.1%, while relative recoveries were in the range of 67.1 to 101.3%.
(15)
(11)
In this research thin films from SnO2 semiconductor have been prepared by using chemical pyrolysis spray method from solution SnCl2.2H2O at 0.125M concentration on glass at substrate temperature (723K ).Annealing was preformed for prepared thin film at (823K) temperature. The structural and sensing properties of SnO2 thin films for CO2 gas was studied before and after annealing ,as well as we studied the effect temperature annealing on grain size for prepared thin films .