In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm). The footing was tested in all parameters at the surface and at 50 mm depth below model surface. Meanwhile the investigated parameters of the soil condition included dry and saturated sand for two relative densities 30% and 80%. The response of the soil to dynamic loading includes measuring the stresses inside the soil using piezoelectric sensors as well as measuring the excess pore water pressure by using pore water pressure transducers. It was found that the rate of increase in excess pore water pressure ratio decreased remarkably at a depth of 0.5 B–1.5 B (B is the footing width) for medium and loose dense sand, respectively. Moreover, excess pore water pressure ratio increases with increasing the eccentricity of dynamic load. The generated pore water pressure is always greater under the point of load application. Its value reduces with a certain percentages at any point away from the point of load application. In addition, the rate of variation of pore water pressure with eccentricity for loose sand is less than that for medium dense sand. The dynamic stress increments resulting from the dynamic load on the foundation reduce with depth. In addition, the dynamic stresses under the corner are slightly greater than the stresses at the center by a percentage of about 10.0%. The excess pore water pressure increases with increasing the relative density of the sand, the amplitude of dynamic loading and the operating frequency. In contrast, the rate of dissipation of the excess pore water pressure during dynamic loading is more in the case of loose sand.
Highway embankments stability during its service period represents an important factor for the safety of highway users and vehicles. Consequently, the cost of construction of these embankments should be adequate to maintain the safety and durability during this period through proper estimation of the loading on asphalt pavement, slope stability, horizontal and vertical deformation, etc. Slope stability of the embankment mainly depends on the shear strength of the soil layers materials; this shear strength is affected by the water table level through the contribution of the capillary water. Negative pore water pressure above the water table level evolves matric suction in the unsaturated zone above water table; this matric suction increases
... Show MoreNano materials have a great potential for enhanced oil recovery applications. The present research investigated the effect of nanoparticles on interfacial tension and wettability alteration. The silica oxide nanoparticles with different size 52, 65 and 5nm were used. The wettability alteration was evaluated by dipping the limestone rock in different concentrations of Nano silica (0.01-1wt. %) for a certain silica size suspended in salinity water. Measurements performed in three phase system (oil/water/solid) using pandel droplet and sessile drop method respectively by opitical-tensiometer. Results showed that Nano fluid can significantly reduce contact angle and alterated rock wettabi
Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreBackground Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti
... Show MoreThis work aimed to design, construct and operate a new laboratory scale water filtration system. This system was used to examine the efficiency of two ceramic filter discs as a medium for water filtration. These filters were made from two different ceramic mixtures of local red clay, sawdust, and water. The filtration system was designed with two rotating interfered modules of these filters. Rotating these modules generates shear force between water and the surfaces of filter discs of the filtration modules that works to reduce thickness of layer of rejected materials on the filters surfaces. Each module consists of seven filtration units and each unit consists of two ceramic filter discs. The average measured hy
... Show MoreThe support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample
... Show MoreIt can be said that the Security of water in Basra from the visual task vital strategic issues of concern to the attention of researchers in various attributions and those interested in water, environmental, economic, social, cultural and political affairs ... etc. This view of the great importance of the issue of water in the occupied Basra, which is characterized by parochialism and scarcity, When looking at the sources of our daily lives and in our reality today. We find that millions of people living on the two main exporters Tabaaan oil and water. And depleted oil wealth However Manfred him the most attention because we entered it surpasses all other sources of income, but is not it a littl
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