Fine aggregate (Sand) is a necessary material used in concrete construction purposes, it’s naturally available and it’s widely used around the world for different parts of construction in any building mainly for filling the voids between gravel. Sand gradation is important for different composite materials, and it gives good cohesion when compared with coarse sand that provides strength for the building. Therefore, sand is necessary to be tested before it is used and mixed with other building materials in construction and the specimen must be selected carefully to represent the real material in the field. The specimen weight must be larger than the required weight for test. When the weight of the sand sample increases the approximate precision desired increases. In this study, an approximated multilinear function for Fuller’s curve on the logarithmic scale was used to simulate the fine aggregate (sand) numerically. In order to get the effect of different samples, a stochastic analysis was done by employing 100 realizations of specimens, has been conducted to study the effect of sampling on sieve analysis and the root mean square error (RMSE) for the variation between desired and sampled curves. Then the results were compared with available specifications recommendations.
Praise be to God, Lord of the Worlds, and the best blessings and peace be upon our master Muhammad and all his family and companions, and those who follow them with goodness until the Day of Judgment. . And after:
God created man in the best manner, and subjugated the universe to him and favored him over the rest of creation when he gave him a mind to contemplate and know how to distinguish between the harmful and the beneficial, the bad and the good, in order to exploit him in achieving the meaning of worship, because it is the highest goal of his creation. God Almighty said (And I did not create the jinn and mankind. Except that they worship them.” [Al-Dhariyat: 56]
If knowing what is harmful from what is beneficial a
... Show MoreGlobally, Sustainability is very quickly becoming a fundamental requirement of the construction industry as it delivers its projects; whether buildings or infrastructures. Throughout more than two decades, many modeling schemes, evaluation tools, and rating systems have been introduced en route to realizing sustainable construction. Many of these, however, lack consensus on evaluation criteria, a robust scientific model that captures the logic behind their sustainability performance evaluation, and therefore experience discrepancies between rated results and actual performance. Moreover, very few of the evaluation tools available satisfactorily address infrastructure projects. The res
A significant challenge arises in the characterization of urban systems, especially regarding the intricate structures of Central Business Districts (CBDs). Conventional models seem insufficient, failing to comprehend the non-linear, network-oriented structure of the city's economic and social dynamics. This creates a disparity between the city's physical, geographical structure and the unseen processes occurring within it. The fundamental inquiry is thus configurational: how can we systematically examine the inherent spatial logic of the CBD to develop a more efficient and predictive planning model? This paper presents a theoretical and methodological model to explore this inquiry, which focuses on Lower Manhattan as the primary su
... Show MoreA new mathematical model describing the motion of manned maneuvering targets is presented. This model is simple to be implemented and closely represents the motion of maneuvering targets. The target maneuver or acceleration is correlated in time. Optimal Kalman filter is used as a tracking filter which results in effective tracker that prevents the loss of track or filter divergency that often occurs with conventional tracking filter when the target performs a moderate or heavy maneuver. Computer simulation studies show that the proposed tracker provides sufficient accuracy.
Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
... Show MoreThe Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.