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CO2-wettability of sandstones exposed to traces of organic acids: Implications for CO2 geo-storage
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Wettability of CO2-brine-mineral systems plays a vital role during geological CO2-storage. Residual trapping is lower in deep saline aquifers where the CO2 is migrating through quartz rich reservoirs but CO2 accumulation within a three-way structural closure would have a high storage volume due to higher CO2 saturation in hydrophobic quartz rich reservoir rock. However, such wettability is only poorly understood at realistic subsurface conditions, which are anoxic or reducing. As a consequence of the reducing environment, the geological formations (i.e. deep saline aquifers) contain appreciable concentrations of various organic acids. We thus demonstrate here what impact traces of organic acids exposed to storage rock have on their wettability. Technically, we tested hexanoic acid, lauric acid, stearic acid and lignoceric acid and measured wettability as a function of organic acid concentration at realistic storage conditions (i.e. 25 MPa and 323 K (50 °C)). In addition, measurements were also conducted at ambient conditions in order to quantify the incremental pressure effect on wettability. Clearly, the quartz surface turned significantly less water-wet with increasing organic acid concentrations, even at trace concentrations. Importantly, we identified a threshold concentration at ˜10−6 M organic acid, above which quartz wetting behaviour shifts from strongly water-wet to an intermediate-wet state. This wettability shift may have important consequences for CO2 residual trapping capacities, which may be significantly lower than for traditionally assumed water-wet conditions where CO2 is migrating through quartz rich reservoirs.

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
Study of the Friction Stir Welding For A516 Low Carbon Steel
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The main objective of present work is to describe the feasibility of friction stir welding (FSW) for
joining of low carbon steel with dimensions (3 mm X 80 mm X 150 mm). A matrix (3×3) of welding
parameters (welding speed and tool rotational speed) was used to see influence of each parameter on
properties of welded joint .Series of (FSW) experiments were conducted using CNC milling machine
utilizing the wide range of rotational speed and transverse speed of the machine. Effect of welding
parameters on mechanical properties of weld joints were investigated using different mechanical tests
including (tensile and microhardness tests ). Micro structural change during (FSW) process was
studied and different welding zones

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
IMPLEMENTATION OF GYPSEOUS SOIL-ASPHALT STABILIZATION TECHNIQUE FOR BASE COURSE CONSTRUCTION
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The aim of this research work is to study the effect of stabilizing gypseous soil, which covers
vast areas in the middle, west and south parts of Iraq, using liquid asphalt on its strength properties
to be used as a base course layer replacing the traditional materials of coarse aggregate and broken
stones which are scarce at economical prices and hauling distances.
Gypseous soil brought from Al-Ramadi City, west of Iraq, with gypsum content of 66.65%,
medium curing cutback asphalt (MC-30), and hydrated lime are used in this study.
The conducted tests on untreated and treated gypseous soil with different percentages of medium
curing cutback asphalt (MC-30), water, and lime were: unconfined compression strength, and o

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Mon Oct 09 2023
Journal Name
2023 Ieee 34th International Symposium On Software Reliability Engineering Workshops (issrew)
Semantics-Based, Automated Preparation of Exploratory Data Analysis for Complex Systems
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Publication Date
Sat Mar 10 2018
Journal Name
Opción
The Effect of Cognitive Modeling Strategy in chemistry achievement for students
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The aim of the current research is to verify the effect of the cognitive modeling strategy on the achievement of the chemistry course for the students of the first intermediate grade. To achieve the objective of the research, the null hypothesis was formulated via cognitive modeling strategy. The results showed that the experimental group's students performed better than the students in the control group. In the light of the results, the researchers concluded: The impact of the cognitive modeling strategy in the achievement of students of first intermediate grade in chemistry.

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Publication Date
Mon Jan 02 2017
Journal Name
Al-academy
Structural elements of composition design for fabrics image Image footage model
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End of the twentieth century witnessed by the technological evolution Convergences between the visual arts aesthetic value and objective representation of the image in the composition of the design of the fabric of new insights and unconventional potential in atypical employment. It is through access to the designs of modern fabrics that address the employment picture footage included several scenes footage from the film, which focuses on research and analytical as a study to demonstrate the elements of the picture and the organization of its rules and how to functioning in the design of fabrics, Thus, it has identified the problem by asking the following: What are the elements of the picture footage and how the functioning of the struct

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Educational And Psychological Researches
Teaching Competencies Required For Teachers of History in the Preparatory Stage
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         This study attempts to determine the necessary teaching competencies for teachers and the level of their importance in the development of their performance professionally and scientifically, and the progress towards a better future to achieve an effective level. Accordingly, the research community consists of the morning-preparatory schools for boys at the General Directorate of Education of Baghdad \ Rusafa2. The study sample included (68) teachers constituted 88.31% of the total community of teachers. As for the research tools, the researcher adopted the descriptive method by using the observation method in which the researcher prepared a list of teaching. For verifying the re

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Publication Date
Sat Jan 13 2018
Journal Name
Journal Of Engineering
Performance Evaluation of RIPng, EIGRPv6 and OSPFv3 for Real Time Applications
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In this modern Internet era and the transition to IPv6, routing protocols must adjust to assist this transformation. RIPng, EIGRPv6 and OSPFv3 are the dominant IPv6 IGRP (Interior Gateway Routing Protocols). Selecting the best routing protocol among the available is a critical task, which depends upon the network requirement and performance parameters of different real time applications. The primary motivation of this paper is to estimate the performance of these protocols in real time applications. The evaluation is based on a number of criteria including:  network convergence duration, Http Page Response Time, DB Query Response Time, IPv6 traffic dropped, video packet delay variation and video packet end to end de

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Publication Date
Mon Feb 27 2023
Journal Name
Applied Sciences
Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

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Publication Date
Sun Jan 01 2023
Journal Name
Computational Thermal Sciences: An International Journal
EXPERIMENTAL AND NUMERICAL ANALYSIS FOR THERMAL PROBLEM OF FRICTIONAL BRAKE SYSTEM
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The present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake

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