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Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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Publication Date
Mon Feb 07 2022
Journal Name
Innovative Infrastructure Solutions
Chemical and rheological properties of reclaimed asphalt binders modified by waste engine oil
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Publication Date
Wed Dec 01 2021
Journal Name
Ain Shams Engineering Journal
Improving the rutting resistance of asphalt pavement modified with the carbon nanotubes additive
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Publication Date
Fri Jul 01 2022
Journal Name
Journal Of Engineering
A Review of the Asphalt Mixtures Containing Recycled Solid Waste Materials
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Landfill and incineration are the most common and widely used methods to dispose of solid wastes; both of these techniques are considered the main sources of pollution in the world due to the harmful toxic emissions that are considered an environmental problem. Because of the large areas used by landfills, they are not always considered an economical method. With the increase in the production of solid materials, solid wastes increase the pressure on incinerators and landfills, making the environmental pollution hazard more serious. Instead, these waste materials can be used in some other applications. One of the most important of these applications is asphalt pavements, which are the most used types of pavements in the

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Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Moisture Susceptibility of Hot Mix Asphalt Mixtures Modified by Nano Silica and Subjected to Aging Process
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Moisture damage is described as a reduction in stiffness and strength durability in asphalt mixtures due to moisture. This study investigated the influence of adding nano silica (NS) to the Asphalt on the moisture susceptibility of hot-mix-asphalt (HMA) mixtures under different aging conditions. NS was mixed with asphalt binder at concentrations of 2%, 4%, and 6% by weight of the binder. To detect the microstructure changes of modified Asphalt and estimate the dispersion of NS within the Asphalt, the field emission scanning electron microscope (FE-SEM) was used. To examine the performance of Asphalt mixed with NS at different aging stages (short-term and long-term aging), asphalt mixture tests such as Marshall stability,

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Sun Apr 28 2019
Journal Name
Civil Engineering Journal
Evaluation the Moisture Susceptibility of Asphalt Mixtures Containing Demolished Concrete Waste Materials
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The distress of moisture induced damage in flexible pavement received tremendous attention over the past decades. The harmful effects of this distress expand the deterioration of other known distresses such as rutting and fatigue cracking. This paper focused on the efficiency of using the waste material of demolished concrete to prepare asphalt mixtures that can withstand the effect of moisture in the pavement. For this purpose, different percentages of waste demolished concrete (0, 10, 20, 30, 50, 70 and 100) were embedded as a replacement for coarse aggregate to construct the base course. The optimum asphalt contents were determined depending on the Marshall method. Then after, two parameters were founded to evaluate the moisture

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Scopus (12)
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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Modified Elman Spike Neural Network for Identification and Control of Dynamic System
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Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
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The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Petroleum Research And Studies
Modeling of Oil Viscosity for Southern Iraqi Reservoirs using Neural Network Method
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The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

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