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Rutting prediction of hot mix asphalt mixtures reinforced by ceramic fibers
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One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to study the effect of added CF on asphalt mixture performance. Scanning electron microscopy (SEM) and field emission scanning electron microscopy (FESEM) were also used to investigate the morphologies of CF and reinforced asphalt mixtures and to identify the mechanism of improvement .According to the study results, the ideal ceramic fiber content was 1.5%, which yielded an improve in Marshall stability and reduced rut depth by 22.05% and 27.71% at temperatures of 50°C and 60°C, respectively, when compared to asphalt mixtures without CF. Microscopic analyses clearly revealed the surface properties, particle diameter size, and fiber distribution of the reinforced mixture, including the network structure and strength mechanism, which improved the performance of the asphalt mixture by forming a three-dimensional network.

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
Flexural Behavior of Reinforced Rubberized Reactive Powder Concrete Beams under Repeated Loads
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Non-biodegradability of rubber tires contributes to pollution and fire hazards in the natural environment. In this study, the flexural behavior of the Rubberized Reactive Powder Concrete (RRPC) beams that contained various proportions and sizes of scrap tire rubber was investigated and compared to the flexural behavior of the regular RPC. Fresh properties, hardened properties, load-deflection relation, first crack load, ultimate load, and crack width are studied and analyzed. Mixes were made using micro steel fiber of the straight type, and they had an aspect ratio of 65. Thirteen beams were tested under two loading points (Repeated loading) with small-scale beams (1100 mm, 150 mm, 100 mm) size.

The fine aggregate

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Publication Date
Thu Mar 10 2022
Journal Name
Buildings
Behavior of One-Way Reinforced Concrete Slabs with Polystyrene Embedded Arched Blocks
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This study presents experimental and numerical investigations on seven one-way, reinforced concrete (RC) slabs with a new technique of slab weight reduction using polystyrene-embedded arched blocks (PEABs). All slabs had the same dimensions, steel reinforcement, and concrete compressive strength. One of these slabs was a solid slab, which was taken as a control slab, while the other six slabs were cast with PEABs. The main variables were the ratio of the length of the PEABs to the length of the slab (lp/L) and the ratio of the height of the PEABs to the total slab depth (hP/H). The minimum decrease in the ultimate load capacity was about 6% with a minimum reduction in the slab weight of 15%. In contrast, the maximum decrease in the

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Publication Date
Tue Aug 01 2023
Journal Name
Civil Engineering Journal
Structural Strengthening of Insufficiently Designed Reinforced Concrete T-Beams using CFRP Composites
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This study aims to compare the response of reinforced concrete (RC) T-beams strengthened with carbon fibre-reinforced polymer (CFRP) composite with that of non-strengthened control beams when subjected to monotonic two-point loading until failure for flexural once and shear again. The experimental programme tested eight RC T-beams, which included two reference beams without strengthening and six strengthened beams. The eight beams were divided into two main groups according to strengthening (flexural and shear). Experimental analysis was performed to study the effect of the CFRP laminate width in the flexural group and the spacing of CFRP U-wrap sheets in the shear group on the ultimate load capacity, load-strain relationship, and l

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Structural Behavior of Reinforced Concrete Hollow Beams under Partial Uniformly Distributed Load
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A Longitudinal opening is used to construct hollow core beam is a cast in site or precast or pre stressed concrete member with continuous voids provided to reduce weight, cost and, as a side benefit, to use for concealed electrical or mechanical runs. Primarily is used as floor beams or roof deck systems. This study investigate the behavior of six beams (solid or with opening) of dimension (length 1000 x height 180 x width120mm) simply support under partial uniformly distributed load, four of these beam contain long opening of varied section (40x40mm) or (80x40mm). The effect of vertical steel reinforcing, opening size and orientations are investigated to evaluate the response of beams. The experimental behavior based on load-deflection

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Publication Date
Wed Oct 01 2025
Journal Name
Civil Engineering Journal
Study on Shear Behavior of Reinforced Concrete Beams Confined with Reinforcing Meshes
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This study reveals the results of a numerical simulation performed using the ABAQUS/CAE finite element program. The study aimed to provide a simulation model that can forecast the shear behavior of reinforced concrete beams confined with reinforcing meshes. Limited numerical studies have been conducted using geogrid or FRP mesh as shear reinforcement, with limited representation accuracy and limited material quality. The results were compared to published experimental findings in the literature. The finding of the finite element model and the experimental results were highly comparable; consequently, the model was determined to be valid. Following this, the domain of numerical analyses was broadened to include the investigation of m

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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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