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Analysis of Recorded Inflow Data of Ataturk Reservoir
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Since the beginning of the last century, the competition for water resources has intensified dramatically, especially between countries that have no agreements in place for water resources that they share. Such is the situation with the Euphrates River which flows through three countries (Turkey, Syria, and Iraq) and represents the main water resource for these countries. Therefore, the comprehensive hydrologic investigation needed to derive optimal operations requires reliable forecasts. This study aims to analysis and create a forecasting model for data generation from Turkey perspective by using the recorded inflow data of Ataturk reservoir for the period (Oct. 1961 - Sep. 2009). Based on 49 years of real inflow data from the Euphrates River recorded at Ataturk, a spilt-sample approach was adopted for testing homogeneity. The  autoregressive model of order one [AR(1)] was found to be the best for the forecasting as it accurately reproduced the means, standard deviations, and skewness coefficients observed in the generated records forecast at the Ataturk reservoir. Ten sets of 100 years data have been forecasted.

In Iraq, optimization of the operation of all reservoirs is necessary after operating new reservoirs in Turkey.

 

 

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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Publication Date
Tue Jun 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Neural Network in the Identification of the Cumulative Production from AB unit in Main pays Reservoir of South Rumaila Oil Field.
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A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited g

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Publication Date
Fri Mar 31 2017
Journal Name
Journal Of Engineering
Hydraulic Analysis of the Samarra-Al Tharthar System
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Low incoming discharge upstream of Samarra-Al Tharthar System leads to sediment accumulation and forming islands, especially an island upstream of Al Tharthar Regulator. This island and the sedimentation threaten the stability of the structure and reduce the efficiency of the system. This study aims to hydraulically identify the sedimentation problem mentioned above, to find solutions of how to control the sediment problems, and to develop the capacity of
the system for 500 years return period flood of 15060 m3/s. Surface Water Modeling System (SMS10.1) with two dimensional depth average models (RMA-2) software were used to simulate and analyze the system. The results of analysis showed that the maximum permissible discharge through t

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Fatigue Analysis of Hip Prosthesis
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The present work covers the analytical design process of three dimensional (3-D) hip joint prosthesis with numerical fatigue stress analysis. The analytical generation equations describing the different stem constructive parts (ball, neck, tour, cone, lower ball) have been presented to reform the stem model in a mathematical feature. The generated surface has been introduced to FE solver (Ansys version 11) in order to simulate the induced dynamic stresses and investigate the effect of every design parameter (ball radius, angle of neck, radius of neck, neck ratio, main tour radius, and outer tour radius) on the max. equivalent stresses for hip prosthesis made from titanium alloy. The dynamic loading case has been studied to a stumbling ca

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Wed Feb 22 2017
Journal Name
Geological Society, London, Special Publications
Role of facies diversity and cyclicity on the reservoir quality of the mid-Cretaceous Mishrif Formation in the southern Mesopotamian Basin, Iraq
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Publication Date
Wed Nov 08 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment, And Sustainability: Tmrees23fr
Analysis of x-ray diffraction lines of cuprous oxide nanoparticles by using variance analysis method
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In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models
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Abstract<p>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 Hardn</p> ... Show More
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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data
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Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

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Publication Date
Thu Mar 29 2018
Journal Name
Construction Research Congress 2018
Validation of Time-Safety Influence Curve Using Empirical Safety and Injury Data—Poisson Regression
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