Columns subjected to pure axial load rarely exist in practice. Reinforced concrete columns are usually subjected to combination of axial and lateral actions and deformations, caused by spatially‐complex loading patterns as during earthquakes causes lateral deflection that in turn affects the horizontal stiffness. In this study, a numerical model was developed in threedimensional nonlinear finite element and then validated against experimental results reported in the literatures,
to investigate the behavior of conventionally RC columns subjected to axial load and . lateral reversal cyclic loading. To achieve this goal, numerical analysis was conducted by using finite element program ABAQUS/Explicit. The variables considered in this study were axial load index, concrete compressive strength, column aspect ratio, longitudinal and transverse reinforcement ratios. According to numerical case studies, the results revealed that axial load index and longitudinal reinforcement ratio have the most impact on the column response. Also, increasing concrete compressive strength and reducing column aspect ratio resulted in increasing strength capacity of the column. Moreover, increasing lateral confinement by transverse reinforcement at the column ends increases the flexural strength of a flexure-controlled RC columns.
The sintering behavior of Alumina was investigated by adding TiO2. The addition of TiO2 lowered the sintering temperature of the Alumina compared with those of pure Alumina. The result suggests that TiO2 acts as an activator for sintering of Alumina. Water absorption, apparent porosity and density were examined for both pure and TiO2 added to Alumina samples. The variations of sintering behavior were discussed in terms of shrinkage, porosity, water absorption and density. Thermal shock resistance was also examined. In term of this work, the way of improving the thermal shock resistance in oxide- based materials by adding reactive Titania powder to the Alumina samples. The laboratory results showed an improvement in thermal shock resistance
... Show MoreIn the oil industry, the processing of vacuum residue has an important economic and environmental benefit. This work aims to produce industrial petroleum coke with light fuel fractions (gasoline, kerosene , gas oil) as the main product and de asphalted oil (DAO) as a side production from treatment secondary product matter of vacuum residue. Vacuum residue was produced from the bottom of vacuum distillation unit of the crude oil. Experimentally, the study investigated the effect of the thermal conversion process on (vacuum residue) as a raw material at temperature reaches to 500 °C, pressure 20 atm. and residence time for about 3 hours. The first step of this treatment is constructing a carbon steel batch re
... Show MoreThe correct and sincere process of socialization is working on appropriate social climate in
which this process is the provision, and the climate is achieved in the presence of a positive
environment free of negatives and contradictions, but when there is a socialization processes
inadequate and contradictory was not based on the principles of punishment and reward nor a
balance between methods soft and intensity of treatment and interaction with small and
adolescent does not require intensive social care formulas do not create the conditions
essential items required by the successful and effective socialization, the young and the young
people who are going through in such Altanisah and educational operations will be
The Invar effect in 3D transition metal such as Ni and Mn, were prepared on a series composition of binary Ni1-xMnx system with x=0.3, 0.5, 0.8 by using powder metallurgy technique. In this work, the characterization of structural and thermal properties have been investigated experimentally by X-ray diffraction, thermal expansion coefficient and vibrating sample magnetometer (VSM) techniques. The results show that anonymously negative thermal expansion coefficient are changeable in the structure. The results were explained due to the instability relation between magnetic spins with lattice distortion on some of ferromagnetic metals.
Light naphtha one of the products from distillation column in oil refineries used as feedstock for gasoline production. The major constituents of light naphtha are (Normal Paraffin, Isoparaffin, Naphthene, and Aromatic). In this paper, we used zeolite (5A) with uniform pores size (5Aº) to separate normal paraffin from light naphtha, due to suitable pore size for this process and compare the behavior of adsorption with activated carbon which has a wide range of pores size (micropores and mesopores) and high surface area. The process is done in a continuous system - Fixed bed reactor- at the vapor phase with the constant conditions of flow rate 5 ml/min, temperature 180oC, pressure 1.6 bar and 100-gram weight o
... Show MoreAbstract:
This study seeks to shed light on the important processes are linked to the impact of accounting information on the behavior of producer and user of information and are urging informational and informational use. That accounting as a system of accounting information and functions of the delivery of information to decision makers Under behavioral entrance to the formulation of accounting theory should be taken into account Othertlk accounting information in the behavior of the decision maker which requires an explanation of human behavior and predictable.
On the other hand that the accounting information that should be delivered to the decision maker will affect your beha
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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