There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardness, Calcium, Magnesium, Total Solids, Nitrite, Nitrates, Ammonia, and Silica are to be used to construct the specific model, while pH, Fluoride, Aluminium, Nitrite, Nitrate, Ammonia, Silica, and Orthophosphate of the treated water were eliminated from the analysis. For modeling the coagulation and flocculation process temperature, Alkalinity and pH of raw water were the depended variables of the model. As for the modeling process turbidity of the treated water was used as the output variable. In general, the linear models including model-driven type, (Multivariate multiple regression, MMR and Multiple linear regression, MLR) have slightly higher prediction efficiencies than the, data-driven type (artificial neural network, ANNM). The coefficients of determination (R2) reached 66 to 85% for the MMR and MLR models and 65 to 81% for the ANN models.
Turbidity is a visual property of water that expresses the amount of suspended substances in the water. Its presence in quantities more significant than the permissible limit makes the water undrinkable and reduces the effectiveness of disinfectants in treating pathogens. On this basis, turbidity is used as a basic indicator for measuring water quality. This study aims to evaluate the removal efficiency of AL- Muthanna WTP. Water turbidity was used as a basic parameter in the evaluation, using performance improvement evaluation and data from previous years (2016 to 2020). The average raw water turbidity was 26.7 NTU, with a minimum of 14 NTU, with a maximum of 48 NTU. Water turbidity value for 95% of settling daily reading data was
... Show MoreTurbidity is a visual property of water that expresses the amount of suspended substances in the water. Its presence in quantities more significant than the permissible limit makes the water undrinkable and reduces the effectiveness of disinfectants in treating pathogens. On this basis, turbidity is used as a basic indicator for measuring water quality. This study aims to evaluate the removal efficiency of AL- Muthanna WTP. Water turbidity was used as a basic parameter in the evaluation, using performance improvement evaluation and data from previous years (2016 to 2020). The average raw water turbidity was 26.7 NTU, with a minimum of 14 NTU, with a maximum of 48 NTU. Water turbidity value for 95% of settling daily readi
... Show MoreAl-Rustamiya sewage treatment plant (WWTP) serves the east side of Baghdad city (Rusafa) and is considered one of the largest projects.It consists of three parts (old project F0, first extension F1, and second extension F2) that treat wastewater and the
effluent is discharged into Diyala river and thus into the Tigris River. These plants are designed and constructed with an aim to manage wastewater to reachIraqi effluent standard for BOD5, COD, TSS and chloride concentrations of 40, 100, 60 and 600
mg/L respectively. The data recordedfrom March till December 2011 provided from Al-RustamiyaWWTP, were considered in this study to evaluate the performance of the plant. The results indicated that the strength of the wastewater enterin
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Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from Al- Rustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and t
... Show MoreThis study aims to evaluate drinking water quality at the Al Wahda plant (WTP) in Baghdad city. A conventional water treatment plant with an average flow rate of 72.82 MLD. Water samples were taken from the influent and effluent of the treatment plant and analyzed for some physicochemical and biological parameters during the period from June to November 2020. The results of the evaluation indicate that treated water has almost the same characteristics as raw water; in other terms, the plant units do not remove pollutants as efficiently as intended. Based on this, the station appears to be nothing more than a series of water passage units. However, apart from Total dissolved solids, the mean values of all parameters in the study were
... Show MoreMost 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 predict
Microservice architecture offers many advantages, especially for business applications, due to its flexibility, expandability, and loosely coupled structure for ease of maintenance. However, there are several disadvantages that stem from the features of microservices, such as the fact that microservices are independent in nature can hinder meaningful communication and make data synchronization more challenging. This paper addresses the issues by proposing a containerized microservices in an asynchronous event-driven architecture. This architecture encloses microservices in containers and implements an event manager to keep track of all the events in an event log to reduce errors in the application. Experiment results show a decline in re
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