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.
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Incorporating 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
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Throughout this paper, a generic iteration algorithm for a finite family of total asymptotically quasi-nonexpansive maps in uniformly convex Banach space is suggested. As well as weak / strong convergence theorems of this algorithm to a common fixed point are established. Finally, illustrative numerical example by using Matlab is presented.
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model. In addition, the efficiency of the PV panel is established by the genetic algorithm
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In this work, metal oxide nanostructures, mainly copper oxide (CuO), nickel oxide (NiO), titanium dioxide (TiO2), and multilayer structure, were synthesized by the DC reactive magnetron sputtering technique. The effect of deposition time on the spectroscopic characteristics, as well as on the nanoparticle size, was determined. A long deposition time allows more metal atoms sputtered from the target to bond to oxygen atoms and form CuO, NiO, or TiO2 molecules deposited as thin films on glass substrates. The structural characteristics of the final samples showed high structural purity as no other compounds than CuO, NiO, and TiO2 were found in the final samples. Also, the prepared multilayer structures did not show new compounds other than th
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This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl
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A comparative study was done on the adsorption of methyl orange dye (MO) using non-activated and activated corn leaves with hydrochloric acid as an adsorbent material. Scanning electron microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) were utilized to specify the properties of adsorbent material. The effect of several variables (pH, initial dye concentration, temperature, amount of adsorbent and contact time) on the removal efficiency was studied and the results indicated that the adsorption efficiency increases with the increase in the concentration of dye, adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature for both the treated and untreated corn leaves. The equi
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