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Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
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The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , water concentration and temperature. The output is average corrosion rate .The performance of the two training algorithms, gradient descent with momentum and Levenberg-Marquardt, are compared to select the most suitable training algorithm for corrosion rate model. The model can be used to calculate the average corrosion rate properties of carbon steel alloy as functions of Reynolds number, water concentration and temperature. Accordingly, the combined influence of these effective parameters and the average corrosion rate is simulated. The results show that the corrosion rate increases with the increase of temperature, Reynolds number and the increase of water concentration.

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Publication Date
Mon May 04 2020
Journal Name
Environmental Engineering Research
Experimental and modeling study of water defluoridation using waste granular brick in a continuous up-flow fixed bed
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Contamination of surface and groundwater with excessive concentrations of fluoride is of significant health hazard. Adsorption of fluoride onto waste materials of no economic value could be a potential approach for the treatment of fluoride-bearing water. This experimental and modeling study was devoted to investigate for the first the fluoride removal using unmodified waste granular brick (WGB) in a fixed bed running in continuous mode. Characterization of WGB was carried out by FT-IR, SEM, and EDX analysis. The batch mode experiments showed that they were affected by several parameters including contact time, initial pH, and sorbent dosage. The best values of these parameters that provided maximum removal percent (82%) with the in

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Publication Date
Tue May 01 2018
Journal Name
International Journal Of Computer Trends And Technology
Two Phase Approach for Copyright Protection and Deduplication of Video Content in Cloud using H.264 and SHA-512
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Cloud computing offers a new way of service provision by rearranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in the cloud. Traditional deduplication schemes cannot work on encrypted data. Among these data, digital videos are fairly huge in terms of storage cost and size; and techniques that can help the legal aspects of video owner such as copyright protection and reducing the cloud storage cost and size are always desired. This paper focuses on v

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Optics And Applications
Modeling and Analysis of a Miniaturized Ring Modulator Using Silicon-Polymer-Metal Hybrid Plasmonic Phase Shifter. Part I: Theoretical Framework
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This paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Optics And Applications
Modeling and Analysis of a Miniaturized Ring Modulator Using Silicon-Polymer-Metal Hybrid Plasmonic Phase Shifter. Part II: Performance Predictions
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The ring modulator described in part I of this paper is designed here for two operating wavelengths 1550nm and 1310nm. For each wavelength, three structures are designed corresponding to three values of polymer slot widths (40, 50 and 60nm). The performance of these modulators are simulated using COMSOL software (version 4.3b) and the results are discussed and compared with theoretical predictions. The performance of intensity modulation/direct detection short range and long rang optical communication systems incorporating the designed modulators is simulated for 40 and 100Gb/s data rates using Optisystem software (version 12). The results reveal that an average energy per bit as low as 0.05fJ can be obtained when the 1550nm modulator is d

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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Engineering
Rigid trunk sewer deterioration prediction models using multiple discriminant and neural network models in Baghdad city, Iraq
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The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

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Publication Date
Sun Mar 20 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Numerical Modeling of Circular Tunnel Alignment Under Seismic Loading
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The continuous increase in population has led to the development of underground structures like tunnels to be of great importance due to several reasons. One of these reasons is that tunnels do not affect the living activities on the surface, nor they interfere with the existing traffic network. More importantly, they have a less environmental impact than conventional highways and railways. This paper focuses on using numerical analysis of circular tunnels in terms of their behavior during construction and the deformations that may occur due to overburden and seismic loads imposed on them. In this study, the input data are taken from an existing Cairo metro case study; results were found for the lateral and vertical displacements, the Peak

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Publication Date
Wed Apr 15 2020
Journal Name
Journal Of Engineering Science And Technology
INFLUENCE OF A RIVER WATER QUALITY ON THE EFFICIENCY OF WATER TREATMENT USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Evaluation the Effect of Vibration on the Corrosion Rate of Automotive Paints
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This paper studies the influence of temperature on the corrosion rate of coated AA6111 aluminum alloy used in vehicle bodies under static and vibration states. The vibration test system was collected laboratory and used for testing of five different types of paints (EASI, Numix, Lesonal, DENSO and Polaron paints) in the 5 % NaCl solution using immersion test method. Lesonal paint provided the best corrosion protection, while DENSO paints show large values of corrosion rate, other coatings exhibit moderate values. Model of paints corrosion was developed to characterize the corrosion processes occur at the surfaces. It is found that corrosion rate obtained at vibration cases is larger than static cases and vibration effect

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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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