Risks are confronting the foundations of buildings and structures when exposed to earthquakes which leads to high displacements that may cause the failure of the structures. This research elaborates numerically the effect of the earthquake on the vertical and lateral displacement of footing resting on the soil. The thickness of the footing and depth of soil layer below the footing was taken as (0.5, 1.0, and 2.0 m) and (10, 20 and 40m), respectively. The stiffness ratio of soil to footing was also elaborated at 0.68, 0.8, 1.0, and 1.7. The results showed an increase in the verticle displacement of footing as the duration of the earthquake increases. The increase of soil layer thickness below the footing leads to a reduction in the vertical

The field of structural optimization (optimal design) has grown rapidly over the past decades with many different optimization methods that could be used to produce a structure of minimum weight. This research deals with two aspects, in the first, a general numerical technique based on the finite element analysis and it suggests to investigate the preliminary behavior of metal stiffened plate under action of static load environment. The technique was included a finite element model of the structures using high- order isoparimetric plate elements to be used to create a certain models to obtain their optimum design. The models are characterized such that, each model is builded using different types of stiffener configuration. The second as

The studies on unbonded post-tensioned concrete members strengthened with Carbon Fiber Reinforced Polymers (CFRPs) are limited and the effect of strengthening on the strain of unbonded pre-stressed steel is not well characterized. Estimating the flexural capacity of unbound post-tensioned members using the design methodology specified in the design guidelines for FRP strengthening techniques of bonded post-tensioned members does not provide a reliable evaluation. This study investigates the behavior of unbonded post-tensioned concrete members with partial strand damage (14.3% and 28.6% damage) and strengthened with CFRP laminates using a near-surface mounted technique with and without U-wrap anchorages. The experimental results show

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

The geophysical testing is increasingly being employed in many geotechnical applications. It is preferred in monitoring the mechanical characteristics of the ground because of its economy, not time consuming and non-destructive nature. Seismic wave test is one of the geophysical methods which showed a potential in observing the general behaviour of the reinforced soil with stone columns. Findings in most cases showed that the seismic wave measurements was integrated with or compared to the conventional tests such as standard penetration test or cone penetration test. There was a noticeable success in identifying the enhancement achieved to the ground upon the strengthening with the column, specifically when the associated surveys can produc

In the present work experiments were conducted to study  the effect of solid loading (1,5 and 9 vol.%) on the enhancement of carbon dioxide absorption in bubble column at various volumetric gas flow rate (0.75, 1 and 1.5 m³/h) and absorbent concentration (caustic soda)( 0.1,0.5 and 1 M  ). Activated carbon and alumina oxide (Al₂O₃) are used as solid particles. The Danckwerts method was used to calculate interfacial area and individual mass transfer coefficients during absorption of carbon dioxide in a bubble column. The results show that the absorption rate was increased with increasing volumetric gas flow rate, caustic soda concentration and solid loading. Mass transfer coefficient and interfac

This study deals with the aircraft wing analysis (numerical and experimental) which subjected to fatigue loading in order to analyze the aircraft wing numerically by using ANSYS 15.0 software and experimentally by using loading programs which effect on fatigue test specimens at laboratory to estimate life of used metal (aluminum alloy 7075-T651) the wing metal and compare between numerical and experimental work, as well as to formulate an experimental mathematical model which may find safe estimate for metals and most common alloys that are used to build aircraft wing at certain conditions. In experimental work, a (34) specimen of (aluminum alloy 7075-T651) were tested using alternating bending fatigue machine rig. The t

Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o