Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.
Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
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This study is conducted in order to, investigate the trophic state of Duhok Lake Dam located within Duhok city, Iraq. Water samples are collected seasonally from three monitored sites during 2011. The parameters used for assessing water quality and trophic status level include: water temperature, pH, EC, TDS, DO, BOD5, nutrients, Secchi disk transparency, and chlorophyll a. The results reveal that DO is above 5 mg.l-1 in all sites, BOD5 value is within permissible level for domestic uses. Water quality considered as a hard type. High sulfate concentration is recorded during the study period. Trophic state shows that water type is classified as mesotrophic during autumn season, while it is regarded as eutrophic in other seasons. TDN/TDP rati
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Although many technological improvements are occurring in power production worldwide, power plants in third world countries are still using old technologies that are causing thermal pollution to the water bodies. Power facilities that dump hot water into water bodies are damaging aquatic life. In the study, the impact of the Al Dora thermal power plant on a nearby stretch of Tigris River in Baghdad city was assessed by measuring the temperature of the disposed of hot water in various cross-sections of the selected stretch of Tigris River, including measuring the thermal mixing length. The measurements were conducted in winter, spring, and summer. For field measurements, it was found that the impact of recovery distances
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