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Influence of Nanofluid Flooding on Oil Displacement in Porous Media
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Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at different conditions. In addition, contact angle measurements on quartz surfaces were also conducted at similar conditions to understand the flow behavior in the porous media. Further, zeta potential and particle size distribution measurements were conducted to examine the stability of the injected nanofluids. Results revealed that the injection of nanofluids into oil-wet pore space can significantly enhance the recovery rate of hydrocarbon by altering the wettability of the porous media. However, salinity, particularly at high nanoparticles concentration (≥ 0.005) can dramatically reduce the efficiency of nanofluid. Further, increased aging time can improve the ability of nanofluid to alter the wettability of the surface, and thus more oil can be displaced. Thus, nanofluid can efficiently enhance oil recovery if correctly formulated.

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Publication Date
Sun Nov 23 2025
Journal Name
Journal Of Physical Education
Analytical Study Of Teaching Efficiency According To Herman Module For Baghdad Governorate Physical Educators
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The importance of the current research lies in the importance of teaching competencies and the ability of the teacher to deal and success in his educational career. The research aimed to identify the degree of teaching competencies according to Hermann model of physical education teachers in Baghdad governorate. The descriptive method using the survey method was used on a randomly selected sample of 462 teachers and 314 school principals. After the completion of the survey, the Hermann scale forms were distributed to the teachers. The forms of the teaching competency scale were distributed to their school principals as the direct supervisors of the teachers' evaluation. After completing the survey, the results of each scale were classified

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Publication Date
Mon Feb 02 2015
Journal Name
Journal Of Engineering, University Of Baghdad
'Impact Analysis of Reinforced Concrete Columns with Side Openings Subjected to Eccentric Axial Loads
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Publication Date
Fri Jan 01 2021
Journal Name
Fme Transactions
FAT-based adaptive backstepping control of an electromechanical system with an unknown input coefficient
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This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used

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Publication Date
Tue Jan 01 2019
Journal Name
Opcion
Enhancing Islamic Concepts through English Children's Lit-erature: Al- Ibtila, The Test of Patience
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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Synthesis, description and bacteriological valuation of metal complexes including an amoxicillin−based Schiff base
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Using GPR Technique Assessment for Study the Sub-Grade of Asphalt and Concrete Conditions
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The Ground Penetrating Radar (GPR) is frequently used in pavement engineering
for road pavement inspection. The main objective of this work is to validate
nondestructive, quick and powerful measurements using GPR for assessment of subgrade
and asphalt /concrete conditions. In the present study, two different antennas
(250, 500 MHz) were used. The case studies are presented was carried in University
of Baghdad over about 100m of paved road. After data acquisition and radar grams
collection, they have been processed using RadExplorer V1.4 software
implementing different filters with the most effective ones (time zero adjustment and
DC removal) in addition to other interpretation tool parameters.
The interpretatio

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Publication Date
Wed Jul 01 2020
Journal Name
Iop Conf. Series: Materials Science And Engineering
Structural Performance of Slender RC Columns with Cross and Square-Shaped under Compression Load
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Abstract<p>The idea of using slender Reinforced Concrete (RC) columns with cross-shaped (+-shaped) instead of columns with square-shaped was discussed in this paper. The use of +-shaped columns provides many architectural and structural advantages, such as avoiding prominent columns edges and improved the structural response of member. Therefore, this study explores the structural response of slender +-shaped columns experimentally and numerically by nonlinear finite element analysis using Abaqus simulation tools. The results showed an excellent convergence in strength between numerical and test results with an average standard deviation of 0.05 and 0.07. Besides that, the use of +-shaped column</p> ... Show More
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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Thu Jan 13 2022
Journal Name
Medical &amp; Biological Engineering &amp; Computing
An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs
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