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.
This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.
Moreover, the proposed controller i
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Background: Phosphodiesterase-5 (PDE-5) inhibitorsrestore nitric oxide (NO) signaling and may reducecirculating inflammatory markers, and improve metabolicparameters through a number of mechanisms. Dailyadministration of the PDE-5 inhibitor, tadalafil (TAD) mayattenuate inflammation; improve fasting plasma glucose andtriglyceride levels and body weight. This study aims toevaluate the efficacy of low dose PDE-5 inhibitor, tadalafil(TAD) in controlling dysglycemia and body weight in obesediabetic men.Methods: Forty obese men with type 2 diabetes aged 30-50years incorporated in this study, all with A1c of 7-8.5%,attending obesity unit in AL-Kindy college of medicine.Weight, height, BMI, FPG, A1c, cholesterol, TG, HDL andLDL measured for all
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
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This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio
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Because of the quick growth of electrical instruments used in noxious gas detection, the importance of gas sensors has increased. X-ray diffraction (XRD) can be used to examine the crystal phase structure of sensing materials, which affects the properties of gas sensing. This contributes to the study of the effect of electrochemical synthesis of titanium dioxide (TiO2) materials with various crystal phase shapes, such as rutile TiO2 (R-TiO2NTs) and anatase TiO2 (A-TiO2NTs). In this work, we have studied the effect of voltage on preparing TiO2 nanotube arrays via the anodization technique for gas sensor applications. The results acquired from XRD, energy dispersion spectro
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra
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