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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This study examines the causes of time delays and cost overruns in a selection of thirty post-disaster reconstruction projects in Iraq. Although delay factors have been studied in many countries and contexts, little data exists from countries under the conditions characterizing Iraq during the last 10-15 years. A case study approach was used, with thirty construction projects of different types and sizes selected from the Baghdad region. Project data was gathered from a survey which was used to build statistical relationships between time and cost delay ratios and delay factors in post disaster projects. The most important delay factors identified were contractor failure, redesigning of designs/plans and change orders, security is
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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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Background :Infectious disorders in general have high morbidity and mortality.. CNS infections include many disorders like bacterial meningitis, tuberculous and other subacute and chronic meningitis, viral meningitis, cerebral abscess, spinal cord infections, and others.
Objective: To assess our locality about prevalence of CNS infections , to have more awareness regarding CNS infections, and to try to find the proper way to reduce their prevalence and to treat them in appropriate way.
Method :We revised the records of all the cases of CNS infections excluding cases of spinal cord infections who were admitted in the wards of neuroscience hospital over the previous two years ( from July/2010 to June 2012 ),those were 132 cases.Seaso
Case Report.
To present a case of a previous complicated mandibular orthognathic surgery that aimed to setback the mandible in a female cleft lip and palate (CLP) patient, which led to bone necrosis on one side with subsequent severe mandibular deviation and facial asymmetry. We additionally reviewed the previous reports of similar complications, the pathophysiology and the factors that could lead to this dreadful result.
A 27-year-old female patient presented with a severe dentofacial deformity secondary to a complicated bilateral sagittal spli
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