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Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as temperature, the inclusion of additives such as fly ash and silica fume, adjustments in water-to-cement ratio, selection of aggregates, and the integration of various admixtures. One important discovery is that models that predict compressive strength based on 28-day water immersion do not accurately represent the actual strength because of the substantial impact of local curing conditions. Furthermore, concrete that was cured in polyethylene bags exhibited noticeable differences in moisture retention and temperature properties when compared to alternative methods. Understanding and evaluating curing conditions is crucial for accurate strength predictions. The study also found that compressive strength decreases with temperatures above 30°C and below 15°C.</p>
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Publication Date
Fri Jun 30 2006
Journal Name
Tikrit Journal Of Engineering Sciences
Curvature Ductility of Reinforced Concrete Column Sections Under Different strain Rates
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This paper presents theoretical parametric study of the curvature ductility capacity for reinforced concrete column sections. The study considers the behavior of concrete and reinforcing steel under different strain rates. A computer program has been written to compute the curvature ductility taking into account the spalling in concrete cover. Strain rate sensitive constitutive models of steel and concrete were used for predicting the moment-curvature relationship of reinforced concrete columns at different rate of straining. The study parameters are the yield strength of main reinforcement, yield strength of transverse reinforcement, compressive strength of concrete, spacing of ties and the axial load. The results indicated that hi

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Publication Date
Tue Jan 15 2002
Journal Name
Abhath Al- Yarmouk [basic Sciences And Engineering]
Computer Program for Predicting Ultimate Strength of Structural Concrete Sections of General Shape
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Publication Date
Tue Jan 19 2021
Journal Name
Sn Applied Sciences
Post-fire serviceability and residual strength of composite post-tensioned concrete T-beams
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Abstract<p>In this study, the response of ten composite post-tensioned concrete beams topped by a reinforced concrete deck with adequate reinforcing shear connectors is investigated. Depending on the concrete compressive strength of the deck slab (20, 30, and 40 MPa), beams are grouped into three categories. Seven of these beams are exposed to a fire attack of 700 and 800 °C temperature simultaneously with or without the presence of a uniformly distributed sustained static loading. After cooling back to ambient temperature, these composite beams are loaded up to failure, using a force control module, by monotonic static loading in a four-point-bending setup with two symmetrical concentrated loads applied in </p> ... Show More
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Publication Date
Tue Jan 19 2021
Journal Name
Sn Applied Sciences
Post-fire serviceability and residual strength of composite post-tensioned concrete T-beams
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Abstract<p>In this study, the response of ten composite post-tensioned concrete beams topped by a reinforced concrete deck with adequate reinforcing shear connectors is investigated. Depending on the concrete compressive strength of the deck slab (20, 30, and 40 MPa), beams are grouped into three categories. Seven of these beams are exposed to a fire attack of 700 and 800 °C temperature simultaneously with or without the presence of a uniformly distributed sustained static loading. After cooling back to ambient temperature, these composite beams are loaded up to failure, using a force control module, by monotonic static loading in a four-point-bending setup with two symmetrical concentrated loads applied in </p> ... Show More
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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Beneficial Role of Some Bone Markers in Evaluating Women with Osteoporosis under Different Therapeutic Regimens
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Osteoporosis is a systemic disease of the skeleton, characterized by low bone mass and alteration in the micro-architecture of the bone tissue that lead to an increase in brittleness with the ensuing predisposition to bone fracture. Global statistics shows that women are more exposed to this disease than men and in particular at menopause. This study was designed to evaluate the use of some bone markers: serum osteocalcin (Ost), alkaline phosphatase (ALP), as bone formation markers, also parathyroid hormone (PTH), calcium and inorganic phosphate level, for the assessment of patients with osteoporosis and to evaluate their role in monitoring of several types of therapeutic interventions (such as bisphosphonates, hormonal replacement thera

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Publication Date
Thu Apr 05 2018
Journal Name
Acs Applied Nano Materials
Direct Formation of 2D-MnO<sub><i>x</i></sub> under Conditions of Water Oxidation Catalysis
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We describe the synthesis and characterization of a novel 2D-MnOx material using a combination of HR-TEM, XAS, XRD, and reactivity measurements. The ease with which the 2D material can be made and the conditions under which it can be made implies that water oxidation catalysts previously described as “birnessite-like” (3D) may be better thought of as 2D materials with very limited layer stacking. The distinction between the materials as being “birnessite-like” and “2D” is important because it impacts on our understanding of the function of these materials in the environment and as catalysts. The 2D-MnOx material is noted to be a substantially stronger chemical oxidant than previously noted for other birnessite-like manganese oxi

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Publication Date
Wed Jun 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of the Forming Conditions in the Production of Gamma Alumina Catalyst Support on the Crushing Strength Property
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An investigation was conducted for the determination of the effects of the forming conditions in the production of Gamma Alumina catalyst support on the crushing strength property. Eight variables were studied , they are ;binder content which is the sodium silicate , Solvent content which is the water, speed of mixing , time of mixing, drying temperature , drying time , calcinations temperature and the calcinations time
Design of the experiments was made by using the response Surface method in Minitab 15 software which supply us 90 experiments .
The results of this investigation show that the crushing strength for the dried Gamma alumina extrudate was affected by the drying temperature and the drying time only and there is no inter

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Publication Date
Fri Apr 30 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
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According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

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Scopus (21)
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