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Effect of Fly Ash on Some Properties of Reactive Powder Concrete
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To achieve sustainability in the field of civil engineering, there has become a great interest in developing reactive powder concrete RPC through the use of environmentally friendly materials to reduce the release of CO2 gas produced from cement factories as well as contribute to the recycling of industrial wastes that have a great impact on environmental pollution.

In this study, reactive powder concrete was prepared using total binder content of 800 kg/m3, water to binder ratio (0.275), and micro steel fibers  1% by volume of concrete. The experimental program included replacing fly ash with (8, 12, 16) % by cement weight to find the optimal ratio, which achieved the best mechanical properties of (RPC) at 7, 28, and 90 days with standard curing. Some mechanical properties of reactive powder concrete (flow, compressive strength, tensile strength, and density) were verified. The results at 28 days showed that the compressive strength (96.5) Mpa, tensile strength (9.38) Mpa, and density (2395 kg/m3). The results showed that the percentage of replacement of 8% of fly ash with cement is the optimal percentage, which achieved the highest resistance compared to the others. The results also indicated that it is possible to develop RPC using fly ash with a high withstand stress, tensile strength, and density.

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile position estimation using artificial neural network in CDMA cellular systems
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems
...Show More Authors

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

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