The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa). To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the second method, sudden, water splash was used to reduce the temperature. Eight of the tested beams were divided in to four groups, each were burned to one of the adopted temperature for about half an hour and cooled by the adopted cooling methods (one by sudden cooling and the other by graduated cooling). After burning and cooling the beams were tested under the effect of repeated load (loading – unloading) for five cycle and then up to failure. As a compared with the non- burned beam, the results indicated that the ultimate load capacity of the tested beams were reduced by (16, 23, 54 and 71)% after being burned to (200, 300, 400 and 500) oC , respectively, for a case of sudden cooling and by (8, 14, 36 and 64)% , respectively, for a case of graduated cooling. It was also found that the effect of sudden cooling was greater than that in a case of graduated cooling. Regarding the failure mode, there was a different between the non-burred beam and the other ones even that all of them had the same geometric layout, compressive strength and reinforcement details. The failure mode for all burned beams was combined shear- flexure failure which was belong to the reduction in the compressive strength of the concrete due to the effect of the temperature rising , while the failure mode of the non-burned beam was flexure failure which was compatible with the preliminary design. It was also detected that the residual deflection proportion directly with the temperature, as the temperature increase to (200, 300, 400 and 500) oC the residual deflection compared with the non-burned beam increased by (32, 48, 326 and 358)% for a case of sudden cooling and by (13, 29, 303 and 332)% for a case of graduated cooling. Another effect was appear represented by the method of cooling, the results showed that the sudden cooling had more effect on the residual deflection than the graduated cooling by (15-6)% approximately. To vanish the residual deflection, numbers of cycle (loading-unloading) were required. It was found that this number increase as the temperature of burning increased and it’s also larger in a case of sudden cooling.
The aim of the present work, was measuring of uranium concentrations in 25 soil samples from five locations of Al-Kut city. The samples taken from different depths ranged from soil surface to 60cm step 15 cm, for this measurement of uranium concentrations .The most widely used technique SSNTDs was chosen to be the measurement technique. Results showed that the higher concentrations were in Hai Al- Kafaat which recorded 1.49 ± 0.054 ppm . The uranium content in soil samples were less than permissible limit of UNSCEAR(11.7ppm).
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The ground state properties including the density distributions of the neutrons, protons and matter as well as the corresponding root mean square (rms) radii of proton-rich halo candidates 8B, 12N, 23Al and 27P have been studied by the single particle Bear– Hodgson (BH) wave functions with the two-body model of (core+p). It is found that the rms radii of these proton-rich nuclei are reproduced well by this model and the radial wave functions describe the long tail of the proton and matter density distributions. These results indicate that this model achieves a suitable description of the possible halo structure. The plane wave Born approximation (PWBA) has been used to compute the elastic charge form factors.
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In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as the Bayes method. The comparison was made using the mean error squares (MSE), where the best estimator is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).
لمقدمة
الحمد لله رب العالمين والصلاة والسلام على سيد الأنبياء والمرسلين نبينا محمد صلى الله عليه وسلم وعلى واصحابه أجمعين ومن تبعهم وأهتدى بهداهم الى يوم الدين اما بعد :
فوظيفة القضاء وظيفة سامية يراد منها اقامة العدل ولا يستقيم حالهم الا به دفعاّ للظلم ، ولقد اولى النبي صلى الله عليه وآله وسلم ومن بعده الخلفاء الراشدون
... Show MoreAn atomic force microscope (AFM) technique is utilized to investigate the polystyrene (PS) impact upon the morphological properties of the outer as well as inner surface of poly vinyl chloride (PVC) porous fibers. Noticeable a new shape of the nodules at the outer and inner surfaces, namely "Crater nodules", has been observed. The fibers surface images have seen to be regular nodular texture at the skin of the inner and outer surfaces at low PS content. At PS content of 6 wt.%, the nodules structure was varied from Crater shape to stripe. While with increasing of PS content, the pore density reduces as a result of increasing the size of the pore at the fiber surface. Moreover, the test of 3D-AFM images shows that the roughness of both su
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In this work, a novel design for the NiO/TiO2 heterojunction solar cells is presented. Highly-pure nanopowders prepared by dc reactive magnetron sputtering technique were used to form the heterojunctions. The electrical characteristics of the proposed design were compared to those of a conventional thin film heterojunction design prepared by the same technique. A higher efficiency of 300% was achieved by the proposed design. This attempt can be considered as the first to fabricate solar cells from highly-pure nanopowders of two different semiconductors.
The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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