In recent decades, tremendous success has been achieved in the advancement of chemical admixtures for Portland cement concrete. Most efforts have concentrated on improving the properties of concrete and studying the factors that influence on these properties. Since the compressive strength is considered a valuable property and is invariably a vital element of the structural design, especially high early strength development which can be provide more benefits in concrete production, such as reducing construction time and labor and saving the formwork and energy. As a matter of fact, it is influenced as a most properties of concrete by several factors including water-cement ratio, cement type and curing methods employed.
Because of acce

The effect of micro-and nano silica particles (silica SiO2 (100 μm), Fused silica (12nm)) on some mechanical properties of epoxy resin was investigated (Young's modulus, Flexural strength). The micro-and nano composites were prepared by using three steps process with different volume fraction of micro-and nano particles (1, 2, 3, 4, 5, 7, 10, 15, and 20 vol. %). Flexural strength and Young's modulus of nano composites were increased at low volume fraction (max. enhancement at 4 vol.% ). However at higher volume fraction both Young's modulus and flexural strength decrease. Moreover, above, the mechanical properties are enhanced more than that of neat epoxy resin. The flexural strength decreases with increasing the volume fraction of micr

The mechanical properties and microstructure of hot-rolled steel are critical in determining its performance in industrial applications, particularly when exposed to elevated temperatures. This study examines the effects of varying temperatures and soaking times on these properties through a series of controlled experiments. The primary objective was to optimize the key response parameters, including tensile strength, yield strength, and elongation, by analyzing the influence of temperature and time. A full factorial design approach was used, applying the desirability function theory to explore all possible combinations and identify optimal processing conditions. The experimental results showed that the soaking time played a critica

This study involves the synthesis of a new class of silicon polymers, designated as P1-P7, derived from dichlorodimethylsilane (DCDMS) in combination with various organic compounds (Schiff bases prepared from different amines and appropriate aldehydes or ketones) [I-V] through condensation polymerization. The structures of all monomers and polymers were characterization by FTIR and 1HNMR spectroscopy (for some polymers). The results of thermogravimetric analysis (TGA) and differential scanning calorimetry DSC test show stable thermal behaviour. Polymers with a higher concentration of aromatic rings in their repeating structural units exhibited a higher temperature for weight loss, indicating increased thermal stability. Thermal meas

This study involves the synthesis of a new class of silicon polymers, designated as P1-P7, derived from dichlorodimethylsilane (DCDMS) in combination with various organic compounds (Schiff bases prepared from different amines and appropriate aldehydes or ketones) [I-V] through condensation polymerization. The structures of all monomers and polymers were characterization by FTIR and 1HNMR spectroscopy (for some polymers). The results of thermogravimetric analysis (TGA) and differential scanning calorimetry DSC test show stable thermal behaviour. Polymers with a higher concentration of aromatic rings in their repeating structural units exhibited a higher temperature for weight loss, indicating increased thermal stability. Thermal meas

In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m