This paper presents a numerical analysis using ANSYS finite element program to simulate the reinforced concrete slabs with spherical voids. Six full-scale one way bubbled slabs of (3000mm) length with rectangular cross-sectional area of (460mm) width and (150mm) depth are tested as simply supported under two-concentrated load. The results of the finite element model are presented and compared with the experimental data of the tested slabs. Material nonlinearities due to cracking and crushing of concrete and yielding of reinforcement are considered. The general behavior of the finite element models represented by the load-deflection curves at midspan, crack pattern, ultimate load, load-concrete strain curves and failure m

The finite element method has been used in this paper to investigate the behavior of precast reinforced concrete dapped-ends beams (DEBs) numerically. A parametric investigation was performed on an experimental specimen tested by a previous researcher to show the effect of numerous parameters on the strength and behavior of RC dapped-end beams. Reinforcement details and steel arrangement, the influence of concrete compressive strength, the effect of inclined load, and the effect of support settlement on the strength of dapped-ends beams are examples of such parameters. The results revealed that the dapped-end reinforcement arrangement greatly affects the behavior of dapped end beam. The failure load decreases by 25% when

In this research, experimental and numerical studies were carried out to investigate the performance of encased glass-fiber-reinforced polymer (GFRP) beams under fire. The test specimens were divided into two peer groups to be tested under the effect of ambient and elevated temperatures. The first group was statically tested to investigate the monotonic behavior of the specimens. The second group was exposed to fire loading first and then statically tested to explore the residual behavior of the burned specimens. Adding shear connectors and web stiffeners to the GFRP beam was the main parameter in this investigation. Moreover, service loads were applied to the tested beams during the fire. Utilizing shear connectors, web stiffeners,

In this research, experimental and numerical studies were carried out to investigate the performance of encased glass-fiber-reinforced polymer (GFRP) beams under fire. The test specimens were divided into two peer groups to be tested under the effect of ambient and elevated temperatures. The first group was statically tested to investigate the monotonic behavior of the specimens. The second group was exposed to fire loading first and then statically tested to explore the residual behavior of the burned specimens. Adding shear connectors and web stiffeners to the GFRP beam was the main parameter in this investigation. Moreover, service loads were applied to the tested beams during the fire. Utilizing shear connectors, web stiffeners,

To enhance the structural performance of concrete-filled steel tube (CFST) columns, various strengthening techniques have been proposed, including the use of internal steel stiffeners, external wrapping with carbon fiber-reinforced polymer (CFRP) sheets, and embedded steel elements. However, the behavior of concrete-filled stainless-steel tube (CFSST) columns remains insufficiently explored. This study numerically investigates the axial performance of square CFSST columns internally strengthened with embedded I-section steel profiles under biaxial eccentric loading. Finite element (FE) simulations were conducted using ABAQUS v. 6.2, and the developed models were validated against experimental results from the literature. A comprehen

Strengthening of composite beams is highly needed to upgrade the capacities of existing beams. The strengthening methods can be classified as active or passive techniques. Therefore, the main purpose of this study is to provide detailed FE simulations for strengthened and unstrengthened steel–concrete composite beams at the sagging and hogging moment regions with and without profiled steel sheeting. The developed models were verified against experimental results from the literature. The verified models were used to present comparisons between the effect of using external post-tensioning and CFRP laminates as strengthening techniques. Applying external post-tensioning at the sagging moment regions is more effective because of the e

The main objective of this study is to characterize the main factors which may affect the behavior of segmental prestressed concrete beams comprised of multi segments. The 3-D finite element program ABAQUS was utilized. The experimental work was conducted on twelve simply supported segmental prestressed concrete beams divided into three groups depending on the precast segments number. They all had an identical total length of 3150mm, but each had different segment numbers (9, 7, and 5 segments), in other words, different segment lengths. To simulate the genuine fire disasters, nine beams were exposed to high-temperature flame for one hour, the selected temperatures were 300°C (572°F), 500°C (932°F) and 700°C (1292°F) as recomm

Introduction: Candida spp. has become increasingly resistant to antifungal drugs, with elevated MIC levels causing a negative medical impact and increasing the number of patients at risk of candidiasis. According to the CDC, about 7% of Candida blood samples show reduced susceptibility to fluconazole. Monitoring the antifungal resistance profile of Candida spp. is vital, as non-Albicans species may limit treatment options. Objective: Evaluate the antifungal effectiveness against clinical Candida spp. isolates of six antifungals: amphotericin B, fluconazole, voriconazole, itraconazole, caspofungin, and 5-fluorocytosine. Methods: 100 samples were collected from various clinical samples at the National Centre of Teaching Laboratories

     Deep 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

This research aims to introduce a new technique-off-site and self-form segmental concrete masonry arches fabrication, without the need of construction formwork or centering. The innovative construction method in the current study encompasses two construction materials forms the self-form masonry arches, wedge-shape plain concrete voussoirs, and carbon fiber-reinforced polymer (CFRP) composites. The employment of CFRP fabrics was for two main reasons: bonding the voussoirs and forming the masonry arches. In addition, CFRP proved to be efficient for strengthening the extrados of the arch rings under service loadings. An experimental test was conducted on four sophisticated masonry arch specimens. The research parameters were the Keystone thic