Premature failure in asphalt concrete pavement has been the main concern for pavement construction companies and engineers in recent years because of the large rise in traffic volume and loads and the temperature extremes in the summer and winter. The use of modifiers in asphalt concrete mixtures has attracted much attention to increase the performance and lifespan of pavements. As nanotechnology developed, several researchers concentrated on how these materials can help increase pavement serviceability by minimizing rutting and moisture damage. This study evaluates the Hydrated Lime (HL) effect by two methods (wet and dry hydrated lime) on the durability of the warm mix asphalt. The first method, HL, has been supplemented to the asphalt binder with three ratios (0.5%, 1%, and 1.5%) by weight of asphalt (Wet HL). Then, the second method was added via the aggregate weight as a replacement filler using three percentages (1%, 2%, and 3%) (Dry HL). The mechanical qualities, including Marshall Mix design, moisture susceptibility, and permanent deformation, were evaluated through experimental tests. Results showed that the mechanical characteristics and the fineness of the HL particle sizes are positively correlated.
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
... Show MoreUsing 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
... Show MoreIn this paper, the reliability of the stress-strength model is derived for probability P(Y<X) of a component having its strength X exposed to one independent stress Y, when X and Y are following Gompertz Fréchet distribution with unknown shape parameters and known parameters . Different methods were used to estimate reliability R and Gompertz Fréchet distribution parameters, which are maximum likelihood, least square, weighted least square, regression, and ranked set sampling. Also, a comparison of these estimators was made by a simulation study based on mean square error (MSE) criteria. The comparison confirms that the performance of the maximum likelihood estimator is better than that of the other estimators.
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria