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Experimental and Numerical Study of Open Channel Flow with T-Section Artificial Bed Roughness

Experimental and numerical studies have been conducted on the effects of bed roughness elements such as cubic and T-section elements that are regularly half-channel arrayed on one side of the river on turbulent flow characteristics and bed erosion downstream of the roughness elements. The experimental study has been done for two types of bed roughness elements (cubic and T-section shape) to study the effect of these elements on the velocity profile downstream the elements with respect to different water flow discharges and water depths. A comparison between the cubic and T-section artificial bed roughness showed that the velocity profile downstream the T-section increased in smooth side from the river and decrease in the rough side from it compared with the case when a cubic artificial bed roughness is used. By comparing the results for the element shapes, it can be notices that the T-section bed roughness element more effective compared to cubic shape for both sides of the channel. The numerical method has been done using Computational Fluid Dynamic (CFD) method. A validation for the CFD model with the experimental study have been carried out for a specific flow discharge and water depth. The results indicated that the velocity distribution profiles downstream the bed roughness elements in both sides shown very good agreement for manning coefficients between the numerical and experimental studies. The range of errors between the experimental and numerical study have been calculated using Root Mean Square Error (RMSE) approach, which is found that the RMSE is approximately equal to 1 in case of cubic bed roughness and the RMSE is about 1.5 in case of T-section bed roughness for both smooth and rough sides. Furthermore, the influence of the velocity profile and the bed erosion downstream of the T-section element under the effect of tides have been investigated using the CFD method, which is commonly happened in Shat al-Arab south of Iraq. The results show that the tide of the flow has a reverse effect on the velocity profiles for both sides. Since the velocity profile downstream of bed roughness region increase in the rough side and decrease in the smooth side compared with the normal flow of the river.

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Numerical Modeling of Water Movement from Buried Vertical Ceramic Pipes through Coarse Soils

Problem of water scarcity is becoming common in many parts of the world.  Thus to overcome this problem proper management of water and an efficient irrigation systems are needed.  Irrigation with buried vertical ceramic pipe is known as a very effective in management of irrigation water.  The two- dimensional transient flow of water from a buried vertical ceramic pipe through homogenous porous media is simulated numerically using the software HYDRUS/2D to predict empirical formulas that describe the predicted results accurately.   Different values of pipe lengths and hydraulic conductivity were selected.  In addition, different values of initial volumetric soil water content were assumed in this simulation a

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
Numerical Simulation of Immiscible CO2-Assisted Gravity Drainage Process to Enhance Oil Recovery

The Gas Assisted Gravity Drainage (GAGD) process has become one of the most important processes to enhance oil recovery in both secondary and tertiary recovery stages and through immiscible and miscible modes.  Its advantages came from the ability to provide gravity-stable oil displacement for improving oil recovery, when compared with conventional gas injection methods such as Continuous Gas Injection (CGI) and Water – Alternative Gas (WAG).

Vertical injectors for CO2   gas were placed at the top of the reservoir to form a gas cap which drives the oil towards the horizontal oil producing wells which are located above the oil-water-contact. The GAGD process was developed and tested in vertical wel

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY OF SOME GROWTH CRITERIA AND YIELD OF SOYBEAN CROP WITH THE EFFECT OF BORON AND SOME GROWTH REGULATORS: STUDY OF SOME GROWTH CRITERIA AND YIELD OF SOYBEAN CROP WITH THE EFFECT OF BORON AND SOME GROWTH REGULATORS

The study was conducted at research station A, department of field crops, college of agricultural engineering sciences, university of Baghdad during summer 2021 to evaluate the effect of boron and some growth regulators on some growth criteria and yield of soybean crop (cv. shimaa). The experiment  was carried out according to split plots by using randomized complete block design with three replications. The main plots included three concentrations of boron (75, 150 and 225) mg.L-1, the sub-plots included three levels of growth regulators, spraying kinetin (100 mg. L-1), spraying ethrel (200 mg.L-1) and spraying kinetin (100 mg.L-1) + spraying ethrel (200 mg.L-1) as

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
The combined effectiveness of magnetic force and heat\mass transfer on peristaltic transportation “Hyperbolic Tangent” Nanofluid in a Slopping Non-Regular Non-symmetric Channel.
Abstract<p>in the present article, we present the peristaltic motion of “Hyperbolic Tangent nanofluid” by a porous area in a two dimensional non-regular a symmetric channel with an inclination under the impact of inclination angle under the impact of inclined magnetic force, the convection conditions of “heat and mass transfer” will be showed. The matter of the paper will be further simplified with the assumptions of long wave length and less “Reynolds number”. we are solved the coupled non-linear equations by using technical analysis of “Regular perturbation method” of series solutions. We are worked out the basic equations of continuity, motion, temperature, and volume fraction</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil

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Publication Date
Wed Apr 03 2024
Journal Name
International Journal Of Economics And Finance Studies
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON ACCOUNTING PERFORMANCE: SUSTAINABLE DEVELOPMENT AS A MEDIATING VARIABLE

The UN plans to achieve several development objectives by 2030. These objectives address global warming, a major issue. This method aims to improve sustainable accounting performance (AP). In this circumstance, AI is being applied in various fields, notably in economic, social, and environmental (ESE) domains. This research investigates how sustainable development (SD) influences AI methodologies and AP improvement. The research examined a sample of Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2022. AI was measured by ATM and POS prevalence. A three-dimensional approach examined economic, social, and environmental (ESE) sustainability. Meanwhile, the performance of sustainable accounting was measured through the return on asse

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Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of Artificial Aging Test on PEEK CAD/CAM Fabricated Orthodontic Fixed Lingual Retainer

Background: The purpose of this study was to evaluate the effect of in vitro long-term simulation of oral conditions on the bond strength of PEEK CAD/CAM lingual retainers.

Material and methods: The sample consisted of 12 PEEK CAD/CAM retainers each composed of 2 centrally perforated 3x4mm pads joined by a connector. They were treated by 98% sulfuric acid for 1 minute and then conditioned with Single Bond Universal and bonded to the lingual surface of premolar teeth by 3M Transbond TM System. Half of the retainers were artificially aged using a 30-day water storage and 5000 thermocycling protocol before bond strength testing to compare with the non-aged specimens.

Results: The artificially aged retainers showed a marginally

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
Smart Doctor: Performance of Supervised ART-I Artificial Neural Network for Breast Cancer Diagnoses

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.

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