This study deals with the serviceability of reinforced concrete solid and perforated rafters with openings of different shapes and sizes based on an experimental study that includes 12 post-fire non-prismatic reinforced concrete beams (solid and perforated). Three groups were formed based on heating temperature (room temperature, 400 °C, and 700 °C), each group consisting of four rafters (solid, rafters with 6 and 8 trapezoidal openings, and rafter with eight circular openings) under static loading. A developed unified calculation technique for deflection and crack widths under static loading at the service stage has been provided, which comprises non-prismatic beams with or without opening exposed to flexure concentra

This study focuses on studying the effect of reinforced steel in detail, and steel reinforcement (tensile ratio, compression ratio, size, and joint angle shape) on the strength of reinforced concrete (compressive strength) Fc' and searching for the most accurate details of concrete divisions, their behavior, and corner resistance of reinforced concrete joint. The comparison of this paper with previous studies, especially in the studied properties. The conclusions of the chapter are summarized that these effects had a clear effect and a specific effect on the behavior and resistance of the reinforced concrete corner joints under the negative moments and under their influence and the resulting stress conditions. The types of defects that can

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

The rheological and fusion behavior of polyvinyl chloride (PVC) compounds plays a dominant role in
the processing operations and in the development of physical properties in the processed material. A
comprehensive study was made in this work to evaluate the effect of shear and thermal history on stability, mechanical and rheological properties of rigid PVC compounds. Different samples of Rigid Poly vinyl chloride including dry blend powder, granules, and bottles molded from both were examined. A study was also made on recycled RPVC where 25% of reclaimed material was continuously blended with fresh dry blend and processed for 15 cycles. Results showed that compaction of the PVC material took place in the brabender plastograph at co

The aim of the research is the knowing of the academic Scientific Journals of the colleges of University of Baghdad , through searching in the University of Baghdad website and the websites of colleges and thus studying the presentation of these journals in those website , and this is done by surfing the main pages of the websites for the colleges included in the research , and by analyzing the research made a menu for all the academic Scientific Journals for all institutes of the University of Baghdad , which simplifies the way for the researchers to publish these researches in the specific journals for their specialties .

Bearing capacity of a concrete pile in fine grained cohesive soils is affected by the degree of saturation of the surrounding soil through the contribution of the matric suction. In addition, the embedded depth and the roughness of the concrete pile surface (expressed as British Pendulum Number BPN) also have their contribution to the shear strength of the concrete pile, consequently its bearing capacity. Herein, relationships among degree of saturation, pile depth, and surface roughness, were proposed as a mathematical model expressed as an equation where the shear strength of a pile can be predicted in terms of degree of saturation, depth, and BPN. Rel

The main objectives of this study were investigating the effects of the maximum size of coarse Attapulgite aggregate and micro steel fiber content on fresh and some mechanical properties of steel fibers reinforced lightweight self-compacting concrete (SFLWSCC). Two series of mixes were used depending on maximum aggregate size (12.5 and 19) mm, for each series three different steel fibers content were used (0.5 %, 1%, and 1.5%). To evaluate the fresh properties, tests of slump flow, T500 mm, V funnel time, and J ring were carried out. Tests of compressive strength, splitting tensile strength, flexural tensile strength, and calculated equilibrium density were done to evaluate mechanical properties. For reference mixes, the