For the design of a deep foundation, piles are presumed to transfer the axial and lateral loads into the ground. However, the effects of the combined loads are generally ignored in engineering practice since there are uncertainties to the precise definition of soil–pile interactions. Hence, for technical discussions of the soil–pile interactions due to dynamic loads, a three-dimensional finite element model was developed to evaluate the soil pile performance based on the 1 g shaking table test. The static loads consisted of 50% of the allowable vertical pile capacity and 50% of the allowable lateral pile capacity. The dynamic loads were taken from the recorded data of the Kobe earthquake. The current numerical model takes into account the material non-linearity and the non-linearity of pile-to-surrounded soil contact surfaces. A lateral ground acceleration was adapted to simulate the seismic effects. This research emphasizes modeling the 1 g model by adapting MIDAS GTS NX software. This will, in turn, present the main findings from a single pile model under a combined static and dynamic load. Consequently, the main results were first validated and then used for further deep investigations. The numerical results predicted a slightly higher displacement in the horizontal and vertical directions than the 1 g shaking table. The shear stress–shear strain relationship was predicted. Positive frictional resistance for the closed-ended pile was captured during the first 5 s when low values of acceleration were applied and, consequently, the pile resistance decreased and became negative. Internal and external frictional resistance was captured for the open-ended pipe pile. Overall, frictional resistance values were decreased with time until they reached the last time step with a minimum value. As a result, the evaluation of the current study can be used as a guide for analysis and preliminary design in engineering practice.
This article presents the results of numerical simulations performed using ABAQUS/CAE version 2019. The study aims to evaluate the structural integrity of reinforced concrete (RC) T-beams strengthened with externally bonded carbon fiber reinforcements polymer composite materials (EB) (CFRP), especially their response to bending and shear forces. The numerical model was validated by comparing the numerical and experimental results of eight RC T-beams. The numerical analysis was then extended to include various factors, including the impact of the tilt angle of the U-CFRP shell on the shear strength. The goal of this numerical extension is to implement a numerical model capable of simulating the nonlinear behavior of these beams accur
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The removal of SO2 from simulated gas stream (SO2 + air) in a fixed bed reactor using Modified Activated Carbon (MAC) catalysts was investigated. All the experiments were conducted at atmospheric pressure, initial SO2 concentration of 2500 ppm and bed temperature of 90oC. MAC was prepared by loading a series of nickel and copper oxides 1, 3, 5, 7, and 10 w
... Show MoreThe present article includes an experimental study of the behavior of dry and saturated dense sandy soil under the action of a single impulsive load. Dry and saturated dense sand models were tested under impact loads. Different falling masses from different heights were conducted using the falling weight deflectometer (FWD) to provide the single pulse energy. The responses of dense soils were evaluated at surface of soil under impact load. These responses include; displacements, velocities, and accelerations that are developed due to the impact acting at top and the displacement at different depths within the soil using the falling weight deflectometer (FWD) and accelerometers (ARH-500A waterproof, and low capacity acceleration tran
... Show MoreIs in this research review of the way minimum absolute deviations values based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.
The aim of this paper is to introduce the concept of N and Nβ -closed sets in terms of neutrosophic topological spaces. Some of its properties are also discussed.
The present study involves experimental analysis of the modified Closed Wet Cooling Tower (CWCT) based on first and second law of thermodynamics, to gain a deeper knowledge in this important field of engineering in Iraq. For this purpose, a prototype of CWCT optimized by added packing under a heat exchanger was designed, manufactured and tested for cooling capacity of 9 kW. Experiments are conducted to explore the effects of various operational and conformational parameters on the towers thermal performance. In the test section, spray water temperature and both dry bulb temperature and relative humidity of air measured at intermediate points of the heat exchanger and packing. Exergy of water and air were calculated by applying the exergy
... Show MoreAbstract Throughout this paper R represents commutative ring with identity and M is a unitary left R-module, the purpose of this paper is to study a new concept, (up to our knowledge), named St-closed submodules. It is stronger than the concept of closed submodules, where a submodule N of an R-module M is called St-closed (briefly N ≤Stc M) in M, if it has no proper semi-essential extensions in M, i.e if there exists a submodule K of M such that N is a semi-essential submodule of K then N = K. An ideal I of R is called St-closed if I is an St-closed R-submodule. Various properties of St-closed submodules are considered.
In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
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