One of the most important parameters determining structural members' durability and strength is the fire flame's influence and hazard. Some engineers have advocated using advanced analytical models to predict fire spread impact within a compartment and considering finite element models of structural components to estimate the temperatures within a component using heat transfer analysis. This paper presented a numerical simulation for a reinforced concrete beam’s structural response in a case containing Water Absorbing Polymer Spheres (WAPS) subjected to fire flame effect. The commercial finite element package ABAQUS was considered. The relevant geometrical and material parameters of the reinforced concrete beam model at elevated temperature are first suggested as a numerical model. After that, the suggested numerical model was validated against the experimental tests conducted in this study. The validated numerical model was used to conduct a parametric study to investigate the effects of two important parameters on the structural behavior after being exposed to fire flame. The effect of burning temperatures (500, 600, and 700) oC, as well as the influence of fire duration (1 and 2) hours, were included. The experimental program validation requirement comprised four self-compacted reinforced concrete beams each of the same geometric layout (150x200x1500) mm, reinforcing details, and compressive strength (fc'=50 MPa). Four percentages of (WAPS) were considered (0, 1, 2, and 3)%. The specimens were exposed to a fire flame with a steady-state temperature (500°C), a rising rate compatible with ASTM-E119, a one-hour duration, and a sudden cooling procedure. A static (two-point) load was applied to the burned beams. Through the assessed numerical model, the numerical analysis offered by the WAPS ratio effect was carried out for the reinforced concrete beam under the effect of static load. The findings revealed that the WAPS ratio substantially impacted structural behavior. The numerical model's results were in reasonable agreement with the experimental results. Concerning the fire exposure duration (two hours) at 500 oC, the specimens containing a ratio (3%) of WAPS improved the ultimate load and the ultimate deflection by about (46.63 and 72.24)%, respectively. The highest percentage variation of the absorbed energy at failure load was also detected in the ratio (3%) to be (139.43) %. As for the hardening concrete properties (compressive strength, splitting tensile strength, and modulus of elasticity), the residual strength was (61.06, 48.87, and 32.00)%, respectively. Regarding the steady-state burning temperature (500, 600, and 700)oC for a one-hour duration, the specimens with a ratio of (3%) WAPS improved the ultimate load by about (40.70, 62.00, and 40.76)%, respectively, corresponding to zero percentage of WAPS. The residual compressive strength, splitting tensile strength, and modulus of elasticity were (72.40, 56.12, and 43.78)%, (74.36, 56.50, and 44.79)%, and (45.23, 36.57, and 28.94)%, respectively.
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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In this study, Staphylococcus aureus was found to be the causative agent of furunculosis in 64 (27.5%) out of 233 Iraqi patients presented with furunculosis. 16SrRNA gene was located in all isolates. Nevertheless, mecA and lukS-lukF genes were located in 60% and 4% of S. aureus isolates, respectively. Interestingly, the lukS-lukF carrying S. aureus isolates were mecA positive as well.
In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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Visualization of subsurface geology is mainly considered as the framework of the required structure to provide distribution of petrophysical properties. The geological model helps to understand the behavior of the fluid flow in the porous media that is affected by heterogeneity of the reservoir and helps in calculating the initial oil in place as well as selecting accurate new well location. In this study, a geological model is built for Qaiyarah field, tertiary reservoir, relying on well data from 48 wells, including the location of wells, formation tops and contour map. The structural model is constructed for the tertiary reservoir, which is an asymmetrical anticline consisting of two domes separated by a saddle. It is found that
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The search included a comparison between two etchands for etch CR-39 nuclear track detector, by the calculation of bulk etch rate (Vb) which is one of the track etching parameters, by two measuring methods (thichness and change mass). The first type, is the solution prepared from solving NaOH in Ethanol (NaOH/Ethanol) by varied normalities under temperature(55˚C)and etching time (30 min) then comparated with the second type the solution prepared from solving NaOH in water (NaOH/Water) by varied normalities with (70˚C) and etching time (60 min) . All detectors were irradiated with (5.48 Mev) α-Particles from an 241Am source in during (10 min). The results that Vb would increase with the increase of
... Show MoreBackground : Coronary artery disease is theunderlying cause in approximately two thirds of
patients with systolic heart failure ;
Coronary artery angiogriphy may be useful to
define the presence ,
Anatomical characteristics ,and functional
significance of Coronary artery disease in
selected heart failure patients with or without signs
and aymptoms of Coronary artery disease.
Objectives: to verify the clinical usefulness of
coronary angiography (CA) in congestive heart
failure (CHF) patients with no history of ischemic
heart disease and to identify predictive factors for
performing coronary angiography to patients with
congestive heart failure with no obvious ischemia.
Methods :this is a cross-ses