The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficient between the actual and predicted values for fluoride concentration at the six locations, Al-Karakh, East Tigris, Al-Wathbah, AL-Karamah, Al-Rashid and Al-Wahda WTP intakes, was 0.93, 0.82, 0.86, 0.90, 0.83 and 0.89, respectively. Model verification results indicated that the model forecasting outputs rationally estimated the actual monthly fluoride content in the selected locations.
In the present study, 1-ethyl -3-methyllimidazolium acetate ionic liquid is introduced for extractive desulfurization of Iraqi kerosene (1622ppm) and compared with 1-ethyl -3- methyllimidazolium tetrafloroborate. The effect of ionic liquid/ fuel ratio (1/9, 1/4, 1/2), temperature (25, 30,40oC), stirring speed (300,450rpm) and time (10, 30, 90, 180, 360 min) were studied. Sulfur compound analysis was performed using X-Ray fluorescence. The ionic liquid with acetate anion (OAc) showed better performance than tetrafloborate (BF4). The maximum extraction efficiency was 32% achieved at 1/2 IL/Fuel and 40oC after 90min. The oxidation step using hydrogen peroxide (8ml/200ml), catalyzed by acetic acid (2ml) and followed by ionic liquid extraction h
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
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This research adopts the estimation of mass transfer coefficient in batch packed bed distillation column as function of physical properties, liquid to vapour molar rates ratio (L / V), relative volatility (α), ratio of vapour and liquid diffusivities (DV / DL), ratio of vapour and liquid densities (ρV / ρL), ratio of vapour and liquid viscosities (μV/ μL).
The experiments are done using binary systems, (Ethanol Water), (Methanol Water), (Methanol Ethanol), (Benzene Hexane), (Benzene Toluene). Statistical program (multiple regression analysis) is used for estimating the overall mass transfer coefficient of vapour and liquid phases (KOV and KOL) in a correlation which represented the data fairly well.
KOV = 3.3 * 10-10
... Show MoreThe gas chromatography (GC) method in analytical chemistry is a quick and accurate method to detect volatile components like ethanol. A method for determining volatile components known as Headspace chromatography (HS-GC) was developed along with an internal standard method (ISM) to identify ethanol in fermented broth in the laboratory. The aim of this research is determining the concentration of ethanol in fermented broth using capillary column (ZB-1). This method can analyze ethanol concentrations in the fermented medium broth ranging from 10 to 200 g/L. The validation of this method was done in order to obtain the results to be of high precision and the significant, precision was represented as the relative standard deviation (RSD) which
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The aim of this study was to investigate antibiotic amoxicillin removal from synthetic pharmaceutical wastewater. Titanium dioxide (TiO2) was used in photocatalysis treatment method under natural solar irradiation in a tubular reactor. The photocatalytic removal efficiency was evaluated by the reduction in amoxicillin concentration. The effects of antibiotics concentration, TiO2 dose, irradiation time and the effect of pH were studied. The optimum conditions were found to be irradiation time 5 hr, catalyst dosage 0.6 g/L, flow rate 1 L/min and pH 5. The photocatalytic treatment was able to destruct the amoxicillin in 5 hr and induced an amoxicillin reduction of about 10% with 141.8 kJ/L accumulate
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