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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
Sun Jan 01 2023
Journal Name
E3s Web Of Conferences
Mitigation of Reflection Cracking in Asphalt Concrete Overlay on Rigid Pavements
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Reflective cracking is one of the primary forms of deterioration in pavements. It is widespread when Asphalt concrete (AC) overlays are built over a rigid pavement with discontinuities on its surface. Thus, this research work aims to reduce reflection cracks in asphalt concrete overlay on the rigid pavement. Asphalt Concrete (AC) slab specimens were prepared in three thicknesses (4, 5, and 6 cm). All these specimens were by testing machine designed and manufactured at the Engineering Consulting Office of the University of Baghdad to examine for the number of cycles and loads needed to propagate the reflection cracking in the asphalt concert mixture at three temperatures (20, 30, and 30°C). It was noticed that the higher thickness A

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Publication Date
Mon Sep 01 2025
Journal Name
Thermal Science And Engineering Progress
Active mixing strategies for energy-efficient water dispensers: Comparative experimental study of impeller and bubble injection in hot climates
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Publication Date
Fri Mar 01 2024
Journal Name
Results In Engineering
Experimental and analytical study of the energy and exergy performance for different evaporative pads in hot and dry climate
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In this work, effects of using different evaporative cooling pads (ECPs) on the energetic and exergetic efficiency of a direct evaporative air cooler (DEAC) have been theoretically and experimentally investigated. Three types of ECPs were used, i.e., honeycomb cellulose cooler pad (HCCP), shading-cloth cooler pad (SCCP), and aspen wood wool cooler pad (AWWCP). For SCCP and AWWCP, a 3-cm pad thickness was used, while for the HCCP, three different values of pad thickness were used, i.e., 3, 5, and 7 cm. Tests were carried out using air velocities of 8, 14, and 19 m/s, measured at the DEAC outlet. Engineering equation solver (EES) used for performing the required calculations of the various parameters affecting the thermal performance of the D

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Publication Date
Sat Jun 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction and Correlations of Residual Entropy of Superheated Vapor for Pure Compounds
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Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Semi-Analytical Prediction of Flank Tool Wear in Orthogonal Cutting of Aluminum
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This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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Publication Date
Mon Feb 06 2023
Journal Name
Journal Of Kufa-physics
No-Core optical fibers sensor for detecting hemoglobin concentration (HB) based on the Surface Plasmon resonance.
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In this work, a fiber-optic biomedical sensor was manufactured to detect hemoglobin percentages in the blood. SPR-based coreless optical fibers were developed and implemented using single and multiple optical fibers. It was also used to calculate refractive indices and concentrations of hemoglobin in blood samples. An optical fiber, with a thickness of 40 nanometers, was deposited on gold metal for the sensing area to increase the sensitivity of the sensor. The optical fiber used in this work has a diameter of 125μm, no core, and is made up of a pure silica glass rod and an acrylate coating. The length of the fiber was 4cm removed buffer and the splicing process was done. It is found in practice that when the sensitive refractive i

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Tue Oct 24 2023
Journal Name
Chemical Engineering & Technology
Electrodeposition of Manganese Dioxide under Different Conditions: Application of MnO<sub>2</sub>/Carbon Fibers in the Electrosorption Process
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Abstract<p>Anodic electrodeposition was used to synthesize a composite electrode of nanostructured manganese dioxide/carbon fiber (CF) galvanostatically. Different characterization results of the nanostructured MnO<sub>2</sub> were obtained by varying the H<sub>2</sub>SO<sub>4</sub> concentration and the current density. Field emission scanning electron microscopy, X‐ray diffraction, and atomic force microscopy were utilized to characterize the prepared composite electrodes. The best conditions were: 0.3 mA cm<sup>−2</sup> current density and 0.64 M H<sub>2</sub>SO<sub>4</sub> concentration. The electrosorption performance of the MnO<sub></sub></p> ... Show More
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