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Correlating Optimum Stage Pressure for Sequential Separator Systems
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Summary<p>A study to find the optimum separators pressures of separation stations has been performed. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid is discharged from a higher-pressure separator into the lower-pressure separator. The set of working separator pressures that yields maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures, which is the target of this work.</p><p>A computer model is used to find the optimum separator pressures. The model employs the Peng-Robinson equation of state (Peng and Robinson 1976) for volatile oil. The application of this model shows significant improvement of all objective functions for many oils (Hassan 2004).</p><p>Mathematical correlations for estimating optimum set of pressures have been deduced from the model to provide simple and quick tools to find the optimum stages pressures. Many tests have been achieved with many volatile samples at different conditions to prove the validity of these correlations.</p>
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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Value system and its impact on the morals of the public job of the individual
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         Values ​​are penetrating or interfering in the lives of individuals and groups and are connected to them in the sense of life itself, because they are closely linked to the motives of behavior, hopes and goals, and can be said that values ​​are everything. The concept of values ​​is one of the concepts that have received the attention of researchers from different disciplines. This has resulted in a kind of confusion and variation in use from one specialization to the other, and uses multiple uses within one specialization. Therefore, there is no uniform definition of values ​​because they relate to individuals. Individuals differ in many things, such as perception,

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Secure Smart Contract Based on Blockchain to Prevent the Non-Repudiation Phenomenon
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Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

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Publication Date
Wed Oct 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
ON DISCRETE WEIBULL DISTRIBUTION
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Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obta

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Synthesis, Characterization, and Investigation the Inhibitory Impact of Thiosemicarbazide Derivative toward the Corrosion of Mild Steel in Acidic Media
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        In this study we focused on the determination of influence the novel synthesized thiosemicarbazide derivative "2-(2-hydroxy-3-methoxybenzylidene) hydrazinecarbothioamide" (HMHC) influenced the corrosion inhibition of mild steel (MS) in a 1.0 M hydrochloric acid acidic solution.This is in an effort to preserve the metal material by maintaining it from corrosion.The synthesized inhibitor was characterized using elemental analysis, and NMR-spectroscopy. Then the corrosion inhibition capability of (HMHC) was studied on mild steel in an acidic medium by weight loss technique within variables [temperature, inhibitor concentration, and time]. The immersion periods were [1:00, 3:00, 5:00, 10:00, 24:00, and 72:00] hours and the tem

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Wed Mar 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, ANN and SVR models in time series hybridization with practical application
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Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

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Publication Date
Mon Nov 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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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 2016-201

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny

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