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.
Background: The incidence of maternal mortality in
placenta previa accrete is 7%,and its preoperative
diagnosis is of a great value.
Objective: to evaluate the efficacy of transabdominal
color Doppler ultrasound in diagnosing placenta
previa accreta and inccreta. Color Doppler imaging
criteria used in: includes diffuse parenchymal
placental lacunar flow, focal intra parenchymal
placental lacunar flow and bladder uterine serosa
interphase hyper-vascularity.
Design: Prospective study on patients from
January2007 to January 2008.
Patients and method: 48patients with one caesarean
section or more and with persistent anterior placenta
previa diagnosed by transabdominal ultrasound were
examined by c
Accurate calculation of transient overvoltages and dielectric stresses from fast-front excitations is required to obtain an optimal dielectric design of power components subjected to these conditions, which are commonly due to switching and lightning, as well as utilization of power-electronic devices. Toroidal transformers are generally used at the low voltage level. However, recent investigations and developments have explored their use at the medium voltage level. This paper analyzes the model-based improvement of the insulation design of medium voltage toroidal transformers. Lumped and distributed parameter models are used and compared to predict the transient response and dielectric stress along the transformer winding. The parameters
... Show MoreThe air flow pattern in a co-current pilot plant spray dryer fitted with a rotary disk atomizer was determined experimentally and modelled numerically using Computational Fluid Dynamics (CFD) (ANSYS Fluent ) software. The CFD simulation used a three dimensions system, Reynolds-Average Navier-Stokes equations (RANS), closed via the RNG k −ε turbulence model. Measurements were carried out at a rotation of the atomizer (3000 rpm) and when there is no rotation using a drying air at 25 oC and air velocity at the inlet of 5 m/s without swirl. The air flow pattern was predicted experimentally using cotton tufts and digital anemometer. The CFD simulation predicted a downward central flowing air core surrounded by a slow
... Show MoreIn 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
... Show MoreDuring 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
... Show MoreIncorporating the LiDAR sensor in the most recent Apple devices represents a substantial development in 3D mapping technology. Meanwhile, Apple's Lidar is still a new sensor. Therefore, this article reviews the potential uses of the Apple Lidar sensor in various fields, including engineering and construction, focusing on indoor and outdoor as-built 3D mapping and cultural heritage conservation. The affordable cost and shorter observation times compared to traditional surveying and other remote sensing techniques make the Apple Lidar an attractive choice among scholars and professionals. This article highlights the need for continued research on the Apple LiDAR sensor technology while discussing its specifications and limitations. A
... Show MoreThe present study addresses adopting the organic and nutritious materials in dairy wastewater as media for cultivation of microalgae, which represent an important source of renewable energy. This study was carried out through cultivation of three types of microalgae; Chlorella sp., Synechococcus, and Anabaena. The results shows the success the cultivation of the Synechococcus and Chlorella Sp, while the Anabaena microalgae were in low-growth level. The highest growth was in the Synechococcus farm, followed by Chlorella and Anabaena. However, the growth of Synechococcus required 10 days to achieve this increase that re
... Show MoreProtection of the oil pipelineswhich extracted from the wells was found to shut the well and prevent the leakage of oil when broken using safety valve. This valve is automatically activated by loss of pressure between the well and pipelines, which take the pressure, signal from hydraulic pressure sensor through pressure control valve which has constant or variable value but it is regulated manually. The manual regulatory process requires the presence of monitoring workers continuously near the wells which are always found in remote areas. In this paper, a smart system has been proposed that work with proportional pressure control valve and also electronic pressure sensor through Arduino controller, which is programmed in a way that satisfie
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