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Prediction of the Bending Strength of a Composite Steel Beam–Slab Member Filled with Recycled Concrete
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This study investigated the structural behavior of a beam–slab member fabricated using a steel C-Purlins beam carrying a profile steel sheet slab covered by a dry board sheet filled with recycled aggregate concrete, called a CBPDS member. This concept was developed to reduce the cost and self-weight of the composite beam–slab system; it replaces the hot-rolled steel I-beam with a steel C-Purlins section, which is easier to fabricate and weighs less. For this purpose, six full-scale CBPDS specimens were tested under four-point static bending. This study investigated the effect of using double C-Purlins beams face-to-face as connected or separated sections and the effect of using concrete material that contains different recycled aggregates to replace raw aggregates. Test results confirmed that using double C-Purlins beams with a face-to-face configuration achieved better concrete confinement behavior than a separate configuration did; specifically, a higher bending capacity and ductility index by about +10.7% and +15.7%, respectively. Generally, the overall bending behavior of the tested specimens was not significantly affected when the infill concrete’s raw aggregates were replaced with 50% and 100% recycled aggregates; however, their bending capacities were reduced, at −8.0% and −11.6%, respectively, compared to the control specimen (0% recycled aggregates). Furthermore, a new theoretical model developed during this study to predict the nominal bending strength of the suggested CBPDS member showed acceptable mean value (0.970) and standard deviation (3.6%) compared with the corresponding test results.

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Thu Dec 05 2024
Journal Name
Shifaa
Evaluating alveolar bone thickness in upper and lower incisors from orthodontic perspective. A Cone beam computed tomography-based retrospective study
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Purpose: This study aimed to assess the thickness of alveolar bone of maxillary and mandibular incisors from orthodontics perspective. Materials and Method: A total of 73 Cone beam computed tomography for Iraqi patients (47 females and 26 males) were included in this study. The selected images were captured and imported to AutoCAD database software to perform the measurement. To measure alveolar bone thickness, a reference line was drawn through the long axis of each incisor, from the incisal edge to the root apex. Then, labial and lingual/palatal perpendicular lines were drawn to the reference line at 3, 6, and 9mm apically from the cemento-enamel junction (CEJ). Results: The buccal bone is generally thinner than the lingual/palata

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Publication Date
Fri Aug 18 2023
Journal Name
Journal Of Research In Medical And Dental Science
Morphologic Evaluation of the Permanent Mandibular First Molar within an Iraqi Population Using Cone Beam Computed Tomography (Retrospective Study)
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Publication Date
Mon Apr 01 2019
Journal Name
Biochem. Cell. Arch
Improvement the surface properties of metal valves used in agriculture engine by using CO<inf>2</inf> laser beam
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Publication Date
Sun Mar 21 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of the reliability system in model of stress- strength according to distribution of inverse Rayleigh
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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Geological Journal
A Predictive Model for Estimating Unconfined Compressive Strength from Petrophysical Properties in the Buzurgan Oilfield, Khasib Formation, Using Log Data
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Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Importance of New Use of Concrete in Iraq Analysis of Development And Use of Concrete in Architecture
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Since its invention by the Ancient Romans and later developed during the mid-18th century, the concrete structure and finish, has been considered as the most powerful, practical, economic and constructional material that meets the building’s architectural and aesthetical requirements. By creating unique architectural forms, the pioneer architects used concrete widely to shape up their innovative designs and buildings.

The pre-mixed ultra-high performance concrete which manufactured by Lafarge.

The transparent concrete and cement that allow the light beams to pass through them, introduces remarkable well-lit architectural spaces within the same structural criteria. This product is a recyclable, sustainab

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Development prediction algorithm of vehicle travel time based traffic data
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This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera

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Publication Date
Tue Mar 20 2018
Journal Name
Offshore Technology Conference Asia
Prediction of Hydrate Phase Equilibrium Conditions for Different Gas Mixtures
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Abstract<p>Gas hydrate formation poses a significant threat to the production, processing, and transportation of natural gas. Accurate predictions of gas hydrate equilibrium conditions are essential for designing the gas production systems at safe operating conditions and mitigating the problems caused by hydrates formation. A new hydrate correlation for predicting gas hydrate equilibrium conditions was obtained for different gas mixtures containing methane, nitrogen and carbon dioxide. The new correlation is proposed for a pressure range of 1.7-330 MPa, a temperature range of 273-320 K, and for gas mixtures with specific gravity range of 0.553 to 1. The nonlinear regression technique was applie</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of consolidation due to dewatering by using MATLAB software
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