This paper is devoted to investigate the effect of burning by fire flame on the behavior and load carrying capacity of rectangular reinforced concrete rigid beams. Reduced scale beam models (which are believed to resemble as much as possible field conditions) were suggested. Five end restrained beam specimens were cast and tested. The specimens were subjected to fire flame temperatures ranging from (25-750) ºC at age of 60 days, two temperature levels of 400ºC and 750ºC were chosen with exposure duration of 1.5 hour. The cast rectangular reinforced concretebeam (2250×375×375 mm) (length× width× height respectively) were subjected to fire. Results indicate remarkable reduction in the ultrasonic pulse velocity and rebound number of

         The world's population growth and the increasing demand for new infrastructure facilities and buildings , present us with the vision of a higher resources consumption, specially in the form of more durable concrete such as High Performance Concrete (HPC) . Moreover , the growth of the world pollution by plastic waste has been tremendous. The aim of this research is to investigate the change in mechanical properties of HPC with added waste plastics in concrete. For this purpose 2.5%, 5% and 7.5% in volume of natural fine aggregate in the HPC mixes were replaced by an equal volume of Polyethylene Terephthalate (PET) waste , got by shredded PET bottles. The mechanical propert

Experimental research was carried out to investigate the performance of CFRP wrapping jackets used for retrofitting twelve square reinforced concrete (CR) column specimens damaged by exposure to fire flame, at different temperatures of  300, 500 and 700ºC, except for two specimens that were not burned. The specimens were then loaded axially till failure after gradual or sudden cooling. The specimens were divided into two groups containing two main reinforcement ratios, ρ= 0.0314 and ρ= 0.0542. This was followed by the retrofitting procedure that included wrapping all the specimens with two layers of CFRP fabric sheets. The test results of the retrofitted specimens showed that the fire damaged RC

In this research work, a new type of concrete based on sulfur-melamine modification was introduced, and its various properties were studied. This new type of concrete was prepared based on the sulfur-melamine modification and various ingredients. The new sulfur-melamine modifier was fabricated, and its fabrication was confirmed by IR spectroscopy and TG analysis. The surface morphology resulted from this modifier was studied by SEM and EDS analysis. The components ratios in concrete, chemical and physical characteristics resulted from sulfur-melamine modifier, chemical and corrosion resistance of concrete, stability of concrete against water adsorption, stability of concrete against freezing, physical and mechanical properties and durabi

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

     The open hole well log data (Resistivity, Sonic, and Gamma Ray) of well X in Euphrates subzone within the Mesopotamian basin are applied to detect the total organic carbon (TOC) of Zubair Formation in the south part of Iraq. The mathematical interpretation of the logs parameters helped in detecting the TOC and source rock productivity. As well, the quantitative interpretation of the logs data leads to assigning to the organic content and source rock intervals identification. The reactions of logs in relation to the increasing of TOC can be detected through logs parameters. By this way, the TOC can be predicted with an increase in gamma-ray, sonic, neutron, and resistivity, as well as a decrease in the density log

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al