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Asphaltene Precipitation Modeling of Sadi Formation in Halfaya Iraqi Oil Field
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Asphaltene is a component class that may precipitate from petroleum as a highly viscous and sticky material that is likely to cause deposition problems in a reservoir, in production well, transportation, and in process plants. It is more important to locate the asphaltene precipitation conditions (precipitation pressure and temperature) before the occurring problem of asphaltene deposition to prevent it and eliminate the burden of high treatment costs of this problem if it happens. There are different models which are used in this flow assurance problem (asphaltene precipitation and deposition problem) and these models depend on experimental testing of asphaltene properties. In this study, the used model was equation of state (EOS) model and this model depends on PVT data and experimental data of asphaltene properties (AOP measurement) and its content (asphaltene weight percent). The report of PVT and flow assurance of the live oil from the well (HFx1) of the zone of case study (Sadi formation in Halfaya oil field) showed that there is a problem of asphaltene precipitation depending on asphaltene onset pressure (AOP) test from this report which showed high AOP greater than local reservoir pressure. Therefore this problem must be studied and the conditions of forming it determined. In the present work, the asphaltene precipitation of Halfaya oil field was modeled based on the equation of state (EOS) by using Soave-Redlich-Kwong (SRK) equation which gave the best matching with the experimental data. The main result of this study was that the reservoir conditions (pressure and temperature) were located in the asphaltene precipitation region which means that the asphaltene was precipitated from the oil and when the pressure of the reservoir decreases more with oil production or with time it will cause asphaltene deposition in the reservoir by plugging the pores and reducing the permeability of the formation.

 

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Publication Date
Tue Mar 16 2021
Journal Name
2021 4th International Conference On Energy Conservation And Efficiency (icece)
Finite Element Modeling Of Finned Double-Pass Solar Air Heaters
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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Numerical Modeling of Renal Ionic Equilibrium for Implantable Kidney Applications
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The human kidney is one of the most important organs in the human body; it performs many functions
and has a great impact on the work of the rest of the organs. Among the most important possible treatments is
dialysis, which works as an external artificial kidney, and several studies have worked to enhance the
mechanism of dialysate flow and improve the permeability of its membrane. This study introduces a new
numerical model based on previous research discussing the variations in the concentrations of sodium,
potassium, and urea in the extracellular area in the blood during hemodialysis. We simulated the differential
equations related to mass transfer diffusion and we developed the model in MATLAB Simu

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sun Dec 30 2018
Journal Name
Advances In Remote Sensing And Geo Informatics Applications
Correlation Between Surface Modeling and Pulse Width of FWF-Lidar
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Publication Date
Sun Oct 02 2022
Journal Name
Engineering, Technology & Applied Science Research
Statistical Modeling for Traffic Noise: The Case of Kirkuk City
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The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that

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Publication Date
Sun Jan 08 2017
Journal Name
International Journal Of Information Technology And Computer Science
Adaptive Modeling of Urban Dynamics during Armada Event using CDRs
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Publication Date
Wed Dec 11 2019
Journal Name
Journal Of The College Of Education For Women
Terrorism and Internal Displacement in Iraq: A Field Study in Baghdad
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    Terrorism is a serious problem for many societies today. This research aims to identify the impact of terrorism and displacement crisis on human security, which was a shock to the Iraqi society in terms of its impact on the psychological, social and economic conditions of the individual, family, and society. The variety of methods of carrying out the terrorist operations that resulted from the phenomenon of human displacement witnessed by Iraq since the middle of 2014. This phenomenon has its demographic, political and social dimensions.

    In order to achieve the goal of this study and the importance of the subject, the social survey method was used by selecting a sample of 200 IDPs in a compou

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Publication Date
Mon May 29 2023
Journal Name
Russian Law Journal
LEGAL RULES GOVERNING THE DURATION OF THE CONTRACT IN ITS PERIOD OF FORMATION (COMPARATIVE LEGAL STUDY)
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The duration of the contract is a legal term first provided for in French Amendment Decree No. 131/2016, and given the increasing importance of time in contracts, we have chosen to study the legal rules governing time at the formative stage by drawing on changes in French law compared to both Iraqi and Egyptian laws. Article 1102 of French Amendment Decree No. 131/2016 stipulates that: "Everyone is free to contract or not to contract, to choose the person with whom he contracts, and to determine the content and form of the contract within the limits established by law." Contractual freedom does not permit a breach of the rules relating to public order), as well as article 1104, which provides for (contracts must be nego

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Molecular Identification of Fusobacterium Isolates and limitation of Biofilm Formation Adhesion Gene (fadA) in Dental Outpatients
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 Fusobacterium are compulsory anaerobic gram-negative bacteria, long thin with pointed ends, it causes several illnesses to humans like pocket lesion gingivitis and periodontal disease; therefore our study is constructed on molecular identification and detection of the fadA gene which is responsible for bacterial biofilm formation. In this study, 10.2% Fusobacterium spp. were isolated from pocket lesion gingivitis. The isolates underwent identification depending on several tests under anaerobic conditions and biochemical reactions. All isolates were sensitive to Imipenem (IPM10) 42.7mm/disk, Ciprofloxacin (CIP10) 27.2mm/disk and Erythromycin (E15) 25mm/disk, respectively. 100% of

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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