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.
Human cystic echinococcosis caused by Echinococcus granulosus is one of most important and widespreadparasitic zoonoses in the world. The present study was aimed to identify the immunomodulatory activity ofaqueous extract of Cordia myxa fruit since this plant considers one of medically important plants, which is widely used for treatment of numerous diseases, that correlate with the effectiveness of immunized by hydatid cyst fluid antigen HCFAg. Forty Balb/c mice were divided into equal groups, first group was immunized with HCFAg, the second group was treated with aqueous extract of C. muxa fruit, the third group was immunized and treated, the fourth group was as a control. Delayed type hypersensitivity (DTH), Mitotic index (MI) and histop
... 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
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Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.
This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.
The Mishrif formation was
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In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.
This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.
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