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Recycling of Waste Compact Discs in Concrete Mix: Lab Investigations and Artificial Neural Networks Modeling
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This study aimed to investigate the incorporation of recycled waste compact discs (WCDs) powder in concrete mixes to replace the fine aggregate by 5%, 10%, 15% and 20%. Compared to the reference concrete mix, results revealed that using WCDs powder in concrete mixes improved the workability and the dry density. The results demonstrated that the compressive, flexural, and split tensile strengths values for the WCDs-modified concrete mixes showed tendency to increase above the reference mix. However, at 28 days curing age, the strengths values for WCDs-modified concrete mixes were comparable to those for the reference mix. The leaching test revealed that none of the WCDs constituents was detected in the leachant after 180 days. The findings of this study indicated a sustainable alternative for diminution the effects on the environment posed by waste CDs. Significant agreement between experimental results and those predicted by the artificial neural networks (ANN) modeling was observed.

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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
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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
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 May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Sun Oct 02 2022
Journal Name
Engineering, Technology & Applied Science Research
Statistical Analysis of Component Deviation from Job Mix Formula in Hot Mix Asphalt
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The main objective of this research is to find out the effect of deviation in the aggregate gradients of asphalt mixtures from the Job Mix Formula (JMF) on the general mixture performance. Three road layers were worked on (wearing layer, binder layer, and base layer) and statistical analysis was performed for the data of completed projects in Baghdad city, and the sieve that carried the largest number of deviations for each layer was identified. No.8 sieve (2.36mm), No.50 sieve (0.3mm), and 3/8'' sieve (9.5mm) had the largest number of deviations in the wearing layer, the binder layer, and the base layer respectively. After that, a mixture called Mix 1, was made. This mixture was selected from a number of completed mixtures, and it

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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Publication Date
Mon May 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Some Properties of Mortar and Concrete Using Brick, Glass and Tile Waste as Partial Replacement of Cement
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The using of waste products as a recycled material was one of the most important studies for saving money and reduces the pollution. Mortar and concrete mixes with (10, 20 and 30)% of brick, glass and tile powder as replacement by weight of cement was investigated. The concrete mixes using brick or glass as 10%replacement of cement exhibited enhancement in compressive strength about (6, 4.7 and 2.0)% and (7.2, 5.6 and 2)% at age 7, 28 and 90 days respectively compared to reference mix. The 20% replacement of glass powder also showed an increase in the compressive strength up to (8, 6.3 and 4) %at age 7,28 and 90 days respectively compared to reference mix. Finally concrete mix using (10, 20 and 30) % tile powder as replacement of cement sho

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Publication Date
Wed May 24 2017
Journal Name
International Journal Of Science And Research (ijsr)
Some Properties of Mortar and Concrete Using Brick, Glass and Tile Waste as Partial Replacement of Cement
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The using of waste products as a recycled material was one of the most important studies for saving money and reduces the pollution. Mortar and concrete mixes with (10, 20 and 30)% of brick, glass and tile powder as replacement by weight of cement was investigated. The concrete mixes using brick or glass as 10%replacement of cement exhibited enhancement in compressive strength about (6, 4.7 and 2.0)% and (7.2, 5.6 and 2)% at age 7, 28 and 90 days respectively compared to reference mix. The 20% replacement of glass powder also showed an increase in the compressive strength up to (8, 6.3 and 4) %at age 7,28 and 90 days respectively compared to reference mix. Finally concrete mix using (10, 20 and 30) % tile powder as replacement of cement sho

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Publication Date
Mon May 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Some Properties of Mortar and Concrete Using Brick, Glass and Tile Waste as Partial Replacement of Cement
...Show More Authors

The using of waste products as a recycled material was one of the most important studies for saving money and reduces the pollution. Mortar and concrete mixes with (10, 20 and 30)% of brick, glass and tile powder as replacement by weight of cement was investigated. The concrete mixes using brick or glass as 10%replacement of cement exhibited enhancement in compressive strength about (6, 4.7 and 2.0)% and (7.2, 5.6 and 2)% at age 7, 28 and 90 days respectively compared to reference mix. The 20% replacement of glass powder also showed an increase in the compressive strength up to (8, 6.3 and 4) %at age 7,28 and 90 days respectively compared to reference mix. Finally concrete mix using (10, 20 and 30) % tile powder as replacement of cement sho

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Publication Date
Tue Mar 31 2020
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Extended Finite Element Analysis of Reinforced Concrete Beams Using Meso-Scale Modeling
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Four simply supported reinforced concrete (RC) beams were test experimentaly and analyzed using the extended finite element method (XFEM). This method is used to treat the discontinuities resulting from the fracture process and crack propagation in that occur in concrete. The Meso-Scale Approach (MSA) used to model concrete as a heterogenous material consists of a three-phasic material (coarse aggregate, mortar, and air voids in the cement paste). The coarse aggregate that was used in the casting of these beams rounded and crashed aggregate shape with maximum size of 20 mm. The compressive strength used in these beams is equal to 17 MPa and 34 MPa, respectively. These RC beams are designed to fail due to flexure when subjected to lo

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of Engineering
Finite Element Modeling and Parametric Study on Floor Steel Beam Concrete Slab System in Non-Composite Action.
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This study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.

The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.

After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re

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