Four simply supported reinforced concrete (RC) beams were test experimentaly and analyzed using the extended finite element method (XFEM). This method is used to treat the discontinuities resulting from the fracture process and crack propagation in that occur in concrete. The Meso-Scale Approach (MSA) used to model concrete as a heterogenous material consists of a three-phasic material (coarse aggregate, mortar, and air voids in the cement paste). The coarse aggregate that was used in the casting of these beams rounded and crashed aggregate shape with maximum size of 20 mm. The compressive strength used in these beams is equal to 17 MPa and 34 MPa, respectively. These RC beams are designed to fail due to flexure when subjected to lo

The -multiple mixing ratios of γ-transitions from levels of populated in the are calculated in the present work by using the a2-ratio methods. We used the experimental coefficient (a2) for two γ-transitions from the same initial state, the statistical tensor, which is related to the a2-coefficient would be the same for the two transitions. This method was used in a previous work for pure transitions or which can be considered pure. In these cases the multiple mixing ratios for the second transition ( ) equal zero, but in our work we applied this method for mixed γ-transitions and then the multiple mixing ratio ( ) is known for one transition. Then we calculate the ( ) value and versareversa. The weight average of the -values calcu

The present study illustrates observations, record accurate description and discussion about the behavior of twelve tested, simply supported, precast, prestressed, segmental, concrete beams with different segment numbers exposed to high fire temperatures of 300°C, 500°C, and 700°C. The test program included thermal tests by using a furnace manufactured for this purpose to expose to high burning temperature (fire flame) nine beams which were loaded with sustaining dead load throughout the burning process. The beams were divided into three groups depending on the precast segments number. All had an identical total length of 3150mm but each had different segment number (9, 7, and 5 segments), in other words, different segment length

Background: Restoration of the gingival margin of Class II cavities with composite resin continues to be problematic, especially where no enamel exists for bonding to the gingival margin. The aim of study is to evaluate the marginal leakage at enamel and cementum margin of class II MOD cavities using amalgam restoration and modern composite restorations Filtek™ P90, Filtek™ Z250 XT (Nano Hybrid Universal Restorative) and SDR bulk fill with different restoratives techniques. Materials and method: Eighty sound maxillary first premolar teeth were collected and divided into two main groups, enamel group and cementum group (40 teeth) for each group. The enamel group was prepared with standardized Class II MOD cavity with gingival margin (1 m

The main aim of this paper is studied the punching shear and behavior of reinforced concrete slabs exposed to fires, the possibility of punching shear failure occurred as a result of the fires and their inability to withstand the loads. Simulation by finite element analysis is made to predict the type of failure, distribution temperature through the thickness of the slabs, deformation and punching strength. Nonlinear finite element transient thermal-structural analysis at fire conditions are analyzed by ANSYS package. The validity of the modeling is performed for the mechanical and thermal properties of materials from earlier works from literature to decrea

Zinc Oxide (ZnO) is considered as one of the best materials already used as a window layer in solar cells due to its antireflective capability. The ZnO/MgF2 bilayer thin film is more efficient as antireflective coating. In this work, ZnO and ZnO/MgF2 thin films were deposited on glass substrate using pulsed laser deposition and thermal evaporation deposition methods. The optical measurements indicated that ZnO thin layer has an energy gap of (3.02 eV) while ZnO/MgF2 bilayer gives rise to an increase in the energy gap. ZnO/MgF2 bilayer shows a high energy gap (3.77 eV) with low reflectance (1.1-10 %) and refractive index (1.9) leading to high transmittance, this bilayer could be a good candidate optical material to improve the performance

This research explored the performance of steel fiber concrete-filled stainless-steel tube columns stiffened with embedded carbon steel T-sections with various steel fiber ratios under biaxial bending conditions. A numerical parametric analysis was adopted, using finite element modeling with Abaqus CAE/2021 to evaluate the effects of the fiber ratio (ranging from 0% to 1.5%) on the load-bearing capacity and deflection behavior of columns. In addition, the compressive strength of concrete ranged between 45 and 65 MPa. An increase in the fiber ratio led to a substantial improvement in the ultimate load-bearing capacity (up to 24%), a reduction in deflection (of approximately 49%), and an improvement in column ductility, which were obt

The present study aims to study the correlation between visfatin levels and metabolic syndrome in Iraqi obese adolescence (with and without metabolic syndrome) and its relation with other studied biochemical parameters. Sixty obese adolescences were depended in this study (with and without metabolic syndrome), compared with (30) non-obese children as control group. This study was done in the period from April 2020 until the end of December 2020, in the National Diabetes Centre/Mustansiriya University, Baghdad/Iraq. There were no significant differences in age, height, waist circumferences (WC), and diastolic blood pressure (DBP) in the patients' groups. In contrast, a significant increase differs (p<0.05) was recorded in the values of

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D