This paper presents a comprehensive numerical analysis of the improvement in bearing capacity and settlement performance of hexagonal shallow footings with inclined skirts. Various numerical analyses were conducted using PLAXIS 3D to investigate the influence of skirt length-to-footing width (L/B) ratios and skirt inclination angles (θ) on hexagonal footings in loose sand. The models showed very good agreement with experimental data reported in previous studies, with an R² value of 0.996 and a maximum error of less than 4.31%. It was concluded that the inclusion of inclined skirts has a positive effect on bearing capacity, increasing it by up to approximately 2.97 times compared to non-inclined configurations, while significantly reducing settlement. In addition to numerical simulations, an empirical formula for bearing capacity and settlement was developed using multiple regression based on geometric and inclination parameters. The model demonstrated a good fit (R² = 0.993). Furthermore, an Artificial Neural Network (ANN) model with a 4-10-10-1 architecture was proposed to predict bearing capacity using normalized input parameters, including skirt depth, inclination angle, stress, and settlement ratio. During training, validation, and testing, R² values greater than 0.998 were achieved, indicating a high level of accuracy with low prediction error. These findings highlight the importance of skirt inclination in enhancing foundation design, providing an efficient and cost-effective approach to increase the safety factor of foundations constructed on weak soils without the need for additional structural elements such as panels or strips.
Compound 4-(((6-amino-7H-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazin-3-yl)methoxy)methyl)- 2,6-dimethoxyphenol (6) was synthesized by multi steps. The corresponding acetonitrile thioalkyl (7) was cyclized by refluxing with acetic acid to afford 4-(((6-amino-7H-[1,2,4]triazolo[3,4- b][1,3,4]thiadiazin-3-yl)methoxy)methyl)-2,6-dimethoxyphenol (8). Two new series of 4-(((6-(3- (4-aryl)thioureido)-7H-[1,2,4]triazolo[3,4-b][1,3,4] thiadiazin-3-yl)methoxy)methyl)-2,6- dimethoxyphenol (9a-c) and of 4-(((6-(substitutedbenzamido)7H-[1,2,4]triazolo[3,4- b][1,3,4]thiadiazin-3-yl)methoxy)methyl)-2,6-dimethoxyphenol (10a-c) were synthesized as new derivatives for fused 1,2,4-trizaole-thiadiazine(8). The antioxidants of newly compounds were evaluated by DPPH
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This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.
The comparison was done by simulation using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood with sample size (n = 30) is the best to represent the maternal mortality data after it has been reliance value param
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreSome experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.
Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,
... Show MoreGlass- fiber-reinforced polymer (GFRP) offers a significant alternative to steel in reinforced concrete, with superior corrosion and fire resistance. Though less ductile and more brittle in stress–strain behavior than steel, it is very helpful to combine GFRP with steel reinforcement that improves the structural behavior. This research investigates the flexural characteristics of a one-way slab reinforced by a combination of GFRP and steel reinforcement. Three identical concrete slabs ((1500 × 550 × 120) mm and 43 MPa) were tested under static load with GFRP replacement ratios of (0, 20, and 40)%. The experimental data were utilized to verify a numerical model. The experimen
Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem
... Show MoreAn experimental and numerical investigation of the effect of using two types of nanofluids with suspending of (Al2O3 and CuO) nanoparticles in deionized water with a volume fraction of (0.1% vol.), in addition to use three types of fin plate configurations of (smooth, perforated, and dimple plate) to study the heat transfer enhancement characteristics of commercial fin plate heat sink for cooling computer processing unit. All experimental tests under simulated conditions by using heat flux heater element with input power range of (5, 16, 35, 70, and 100 W). The experimental parameters calculated are such as water and nanofluid as coolant with Reynolds number of (7000, 8000, 9400 and 11300); the air
... Show MoreThe purpose of this paper is to gain a good understanding about wake region behind the car body due to the aerodynamic effect when the air flows over the road vehicle during its movement. The main goal of this study is to discuss the effect of the geometry on the wake region and the aerodynamic drag coefficient. Results will be achieved by using two different shapes, which are the fastback and the notchback. The study will be implemented by the Computational Fluid Dynamic (CFD) by using STAR-CCM+® software for the simulation. This study investigates the steady turbulent flow using k-epsilon turbulence model. The results obtained from the simulation show that the region of the air separation behind the vehicle
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