Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The prediction models of the turbidity removal are presented. Results found that the estimating of the turbidity removal efficiency by ANN and MLR model could be successful. Moreover, results showed that influent and effluent turbidity concentration have more effect on removal efficiency predicting from the other parameters. Finally, the ANN model could be more accurate than the MLR model according to the coefficient of correlation (0.925).
The study was conducted over the period of Oct 2018 to Apr 2019 and is aimed for the detection and estimation of four hazardous Volatile Organic Compounds VOC (benzene, toluene, ethylbenzene, and xylene) so-called (BTEX) in samples collected from the produced water in the Al-Ahdab oil field in Iraq also to track their availability in the important natural water sources around the field. These compounds pose a risk to human health as well as environment. To avoid the laborious and tiresome conventional extraction methods, water samples were collected and concentrated using solid-phase extraction technique (SPE) which is a robust and cost-effective method of sample extraction with minimal exposure and handling of solvents and then to be analy
... Show MoreThe Al Mishraq site has been the subject of many scientific studies for the period before and
after the fire in 2003. Five visits to the site were conducted twice in 2003 for general fact-finding, twice
in 2004, and once in 2005 for detailed sampling and monitoring. Desk-based research and laboratory analysis of soil and water samples results indicate that surface water and groundwater pollution from Al Mishraq site was significant at the time of its operation. The primary pollution source was the superheated water injection process, while the principal receptor is the River Tigris. Now that the plant is idle, this source is absent. Following the June 2003 sulphur fire, initial investigations indicate that short damage to
vegeta
Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.
This research aimed to examine the effect of concentration of dyes stuff, contact time, temperature and ratio of adsorbent weight in (gm) to volume of solution in (ml) on the percentage removal. Two dyes were used; direct blue 6 and direct yellow and the adsorbent was the maize cob. Batch experiments were performed by contacting different weights of adsorbent with 50 ml of solution of desired concentration with continuous stirring at various temperatures. The percentage of removal was calculated and the maximum percentage of removal was 80%. And as the concentration of solution, contact time, temperature and the ratio of adsorbent to volume of solution increase the percentage of removal increase.
The removal of boron from aqueous solution was carried out by electrocoagulation (EC) using magnesium electrodes as anode and stainless steel electrodes as cathode. Several operating parameters on the removal efficiency of boron were investigated, such as initial pH, current density, initial boron ion concentration, NaCl concentration, spacing between electrodes, electrode material, and presence of carbonate concentration. The optimum removal efficiency of 91. 5 % was achieved at a current density of 3 mA/cm² and pH = 7 using (Mg/St. St. ) electrodes, within 45 min of operating time. The concentration of NaCl was o. 1 g/l with a 0.5cm spacing between the electrodes. First and second order rate equation were applied to study adsorp
... Show MoreA significant amount of apiaries is destroyed in most areas of Iraq by attacking of the hornet
There is poverty because of the difference in capacity and material resources, Previously poverty known on the basis of disparity between income and inadequate income. It realize later that fare wore effects of poverty is the erosion of human capital. The human poverty is the loss of food, education, health care and shelter.
In order to provide a database that target the poor , it have been propped a document on the features of poverty and the whereabouts of the poor and the rate of disparity between provinces.
Here the goal of the research is the identify the factors affecti
... Show MoreThe large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o
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