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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
Mon May 04 2020
Journal Name
Offshore Technology Conference
Hydrate Equilibrium Model for Gas Mixtures Containing Methane, Nitrogen and Carbon Dioxide
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Abstract<p>Gas hydrate formation is considered one of the major problems facing the oil and gas industry as it poses a significant threat to the production, transportation and processing of natural gas. These solid structures can nucleate and agglomerate gradually so that a large cluster of hydrate is formed, which can clog flow lines, chokes, valves, and other production facilities. Thus, an accurate predictive model is necessary for designing natural gas production systems at safe operating conditions and mitigating the issues induced by the formation of hydrates. In this context, a thermodynamic model for gas hydrate equilibrium conditions and cage occupancies of N2 + CH4 and N2 + CO4 gas mix</p> ... Show More
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Publication Date
Thu May 04 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Linear Prediction of Sum of Two Poisson Process
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Our goal from this work is to find the linear prediction of the sum of two Poisson process
) ( ) ( ) ( t Y t X t Z + = at the future time 0 ), ( ≥ + τ τ t Z and that is when we know the values of
) (t Z in the past time and the correlation function ) (τ βz

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Publication Date
Wed Mar 28 2018
Journal Name
Iraqi Journal Of Science
Hybrid Approach of Prediction Daily Maximum and Minimum Air Temperature for Baghdad City by Used Artificial Neural Network and Simulated Annealing
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     Temperature predicting is the utilization to forecast the condition of the temperature for an upcoming date for a given area. Temperature predictions are done by gathering quantitative data in regard to the current state of the atmosphere. In this study, a proposed hybrid method to predication the daily maximum and minimum air temperature of Baghdad city which combines standard backpropagation with simulated annealing (SA). Simulated Annealing Algorithm are used for weights optimization for recurrent multi-layer neural network system. Experimental tests had been implemented using the data of maximum and minimum air temperature for month of July of Baghdad city that got from local records of Iraqi Meteorological O

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Publication Date
Tue Dec 22 2020
Journal Name
Modern Applications Of Geotechnical Engineering And Construction Geotechnical Engineering And Construction
Numerical Modeling of Honeycombed Geocell Reinforced Soil
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Shallow foundations have been commonly used to transfer load to soil layer within the permissible limits of settlement based on the bearing capacity of the soil. For most practical cases, the shape of the shallow foundation is of slight significance. Also, friction resistance forces in the first layers of soils are negligible due to non-sufficient surrounding surface area and compaction conditions. However, the bearing capacity of a shallow foundation can be increased by several techniques. Geocell is one of the geosynthetic tool applied mainly to reinforce soil. This study presents a numerical approach of honeycombed geocell steel panels reinforcing the sandy soil under shallow foundation, and several parameters are investigated such as th

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Publication Date
Thu Sep 01 2022
Journal Name
Engineering Structures
Mesoscale analysis of Fiber-Reinforced concrete beams
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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Nano composites of PAM Reinforced with Al2O3
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         The aim of this investigation is to determine how different weight percentages of alumina nanoparticles, including 0.02, 0.04, and 0.06 percent wt, affect the physical characteristics of Poly Acrylamide (PAAM). Using a hot plate magnetic stirrer, 10 g of poly acrylamide powder was dissolved in 90 g of di-ionized distillate water for 4 hours to produce PAAM with a concentration of 0.11 g/ml. Four sections of the resulting solution, each with a volume of 20 ml, were created. Each solution was added independently with alumina nanoparticles in different ratios 0.0, 0.02, 0.04, and 0.06 to create four nano fluid solutions with different alumina nanoparticle contents based on each weight percent. The hand casting process for n

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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Optimal Prediction Using Artificial Intelligence Application
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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Recursive Prediction for Lossless Image Compression
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     This paper introduced an algorithm for lossless image compression to compress natural and medical images. It is based on utilizing various casual fixed predictors of one or two dimension to get rid of the correlation or spatial redundancy embedded between image pixel values then a recursive polynomial model of a linear base is used.

The experimental results of the proposed compression method are promising in terms of preserving the details and the quality of the reconstructed images as well improving the compression ratio as compared with the extracted results of a traditional linear predicting coding system.

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Thu Sep 01 2022
Journal Name
Computers And Electrical Engineering
Automatic illness prediction system through speech
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