In this work, the possibility of utilizing osmosis phenomenon to produce energy as a type of the renewable energy using Thin Film Composite Ultra Low Pressure membrane TFC-ULP was studied. Where by forward osmosis water passes through the membrane toward the concentrated brine solution, this will lead to raise the head of the high brine solution. This developed static head may be used to produce energy. The aim of the present work is to study the static head developed and the flux on the high brine water solution side when using forward and reverse osmosis membranes for an initial concentration range from 35-300 g/l for each type of membrane used at room temperature and pressure conditions, and finally calculating the maximum possible po

The application of ultrafiltration (UF) and nanofiltration (NF) processes in the handling of raw produced water have been investigated in the present study. Experiments of both ultrafiltration and nanofiltration processes are performed in a laboratory unit, which is operated in a cross-flow pattern. Various types of hollow fiber membranes were utilized in this study such as poly vinyl chloride (PVC) UF membrane, two different polyether sulfone (PES) NF membranes, and poly phenyl sulfone PPSU NF membrane. It was found that the turbidity of the treated water is higher than 95 % by using UF and NF membranes. The chemical oxygen demand COD (160 mg/l) and Oil content (26.8 mg/l) were found after treatment according to the allowable limits set

The integration of nanomaterials in asphalt modification has emerged as a promising approach to enhance the performance of asphalt pavements, particularly under high-temperature conditions. Nanomaterials, due to their unique properties such as high surface area, exceptional mechanical strength, and thermal stability, offer significant improvements in the rheological properties, durability, and resistance to deformation of asphalt binders. This research reviewed the application of various nanomaterials, including nano silica, nano alumina, nano titanium, nano zinc, and carbon nanotubes in asphalt modification. The incorporation of these nanomaterials into asphalt mixtures has shown potential to increase the stiffness and high-tempera

This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6^th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

As a result of industrial development, many types of waste are generated, some of which are discharged into water, causing water pollution and having a negative impact on life. The electro-Fenton process (EF) has verified high efficiency in treating pollutants with low cost, ease of handling and operation, and this technology is one of the more efficient advanced oxidation technologies. The main objective of this present work is to explore the efficiency of a three-dimensional Electro-Fenton system (3DEF) in removing eosin, methylene blue, and methylene violet from simulated wastewater using graphite as anode, nickel foam as the cathode, and alum sludge as the third particle and as the source of catalyst. The study investigated the effect o

This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,