Journal of University of Babylon

Adhering to the project timeline without delays is a major challenge that demonstrates the ‎efficiency of construction projects. Delays can be controlled if their real causes have been ‎evaluated properly. Delay in submitting/ approving engineering shop drawings is more often ‎encountered in projects. Therefore, it is important to investigate the reasons of the shop drawings ‎delay. This study aims to identify and evaluate the factors causing delays in the process of ‎implementing engineering shop drawings in the Iraqi construction market. To achieve this aim, a ‎comprehensive review of previous literatures was conducted to identify the reasons of project ‎delays, analyze its findings, and highlight its relevance to this study. Based on the literature ‎review findings, twenty specific causes of work delays related to project schedule, cost, and ‎stakeholder performance were identified and investigated through a structured survey conducted ‎by 49 Iraqi engineers. This research is quantitative relies on the statistical approach to analyze the ‎data. The results were presented and analyzed using a Pareto chart. The calculations were ‎performed sequentially as follows: calculating the importance index (IMP.I) for each item, ‎sorting them in descending order to obtain the cumulative frequency percentage, and then ‎importing the results into a Pareto chart. Based on the chart's output, the 20 factors have the ‎same degree of influence on the preparation of working shop drawings and should receive the ‎same degree of attention while trying to minimize their impact on project performance. Therefore, ‎the project team will need to overcome the impact of the first 10 causes to solve 52% of the ‎delay problem, the first 15 factors to solve the 77%, and so on until 100% is solved. The findings ‎from this study can be used to develop strategic plans for preventing and eliminating delay ‎factors. However, the project's budget and site conditions primarily determine the priority of ‎these methods and techniques‎

The performance of two types of reverse osmosis membranes, namely the Carbon Nano-‎Tube Filtration Membrane and the Ceramic Filtration Membrane, was evaluated in this study by ‎comparing the removal efficiency of the conventional plant in the refinery and the reverse ‎osmosis removal efficiency, after tracing the treated wastewater streamline in the Al-Qayyarah ‎refinery treatment plant. In both membranes, the treated water has pH is 6.4, 6.2, lead (Pb) is ‎‎0.0449, 0.0016, cadmium (Cd) is 0.00443, 0.00255, copper (Cu) is 0.00443, 0.00255, cobalt (Co) ‎is 0.0031, 0.00041, Total E-coli is 39, 27, conductivity less than 97, 83 μS/cm, (SO4) less than ‎‎9.15, 4.416 ppm, chemical oxygen demand less than 9.346, 7.861 ppm, calcium carbonate ‎‎(CaCO3) less than (4.3, 1.1 mg/L), Sodium (Na+) is 2.1, 2.61ppm, and total nitrogen (TNO3 or ‎NO3) less than 0.34, 0.06 ppm, Orthophosphate (PO4) is 0.081, 0.002, Sulfate (SO4) is 9.15, ‎‎4.416 , for Carbon Nano-Tube Filtration Membrane and the Ceramic Filtration Membrane,‎‏ ‏respectively. It concluded that the Carbon Nano-Tube Filtration Membrane is more efficient in ‎terms of treatment, and the Ceramic Filtration Membrane has a stronger texture and longer ‎working life. The proposed treatment strategy is expected to make a significant reduction in the ‎amount of water in refinery primary water withdrawal possible as a result of its reuse in the ‎cooling system. ‎

This research attempts to review most of the studies of groundwater contamination near ‎landfills, mainly arising from un-engineered landfills or open dumps overseas, and its influence on ‎human health. Leachate water from landfills contains various types of municipal toxic wastes as ‎well as heavy metals, which eventually seep into the ground and infiltrate the groundwater table. ‎Consumption of such water causes severe health risks and can occasionally be lethal if consumed ‎over lengthy periods of time. Several investigations have demonstrated indications of significant ‎quantities of heavy metals in both leachate water and surrounding groundwater sources. In addition, ‎the environmental impacts of leachate on groundwater quality are critically analyzed, focusing on ‎the Leachate Pollution Index (LPI) and the Canadian Water Quality Index (CCME WQI) as tools for ‎assessing contamination levels. Finally, It is recommended that all open waste dumps be removed ‎and engineered waste dumps be established in accordance with approved environmental ‎specifications. Furthermore, the generated leachate should be collected by constructing wells from ‎which the leachate should be diverted to a basin (with a suitable lining system) for treatment.‎

The mechanical performance of fiber-reinforced concrete (FRC), especially its flexural ‎strength and toughness measured by the load-deflection response, depends strongly on fiber ‎characteristics such as volume fraction, length, tensile strength, shape, and type. While extensive ‎research has explored these factors, much of it relies on idealized laboratory data, limiting ‎practical applicability. This study addresses this gap by using real-world FRC data to develop ‎predictive machine learning (ML) models that capture the combined influence of fiber and ‎concrete properties on toughness. A comprehensive dataset of 146 FRC samples compiled from ‎prior studies was analyzed. Four regression models—Random Forest (RF), Gradient Boosting ‎‎(GB), Linear Regression, and Support Vector Regression—were trained and evaluated to predict ‎the area under the load-deflection curve, a key indicator of toughness. The GB model achieved ‎the best performance, with a coefficient of determination (R²) of 0.83 and a mean absolute error ‎‎(MAE) of approximately 39, followed closely by RF (R² = 0.79). Feature importance analysis ‎identified fiber volume fraction, fiber type and shape, and flexural strength as the most ‎influential factors in enhancing toughness. This research provides a robust, data-driven predictive ‎tool for estimating FRC toughness based on key physical and mechanical properties, offering ‎valuable insights for engineers to optimize fiber-reinforced composite designs in practical ‎structural applications.‎

The growing problem of plastic waste piling up around the world, along with the large ‎environmental impact of traditional building materials, means that new ways of building that are ‎good for the environment are needed. This thorough study offers an in-depth comparative ‎analysis of environmentally friendly bricks made from recycled plastic waste, employing two ‎different filler materials: sand and clay. The study methodically analyzes two production ‎methods: a compression-heating technique for plastic-sand bricks and a firing process for plastic-‎clay bricks. Brick samples were made with different plastic-to-filler ratios (10:90, 20:80, and ‎‎30:70 by weight) to test how well they worked in terms of compressive strength, fire resistance, ‎water absorption, thermal insulation, durability, production costs, and environmental impact. The ‎results consistently show that plastic-sand bricks made by compression-heating are much better ‎than plastic-clay bricks on most performance measures. Plastic-sand bricks had a compressive ‎strength of 23.7 MPa, very little water absorption (2.5%), and better thermal insulation properties ‎‎(0.48 W/m•K) when the ratio was 30:70. Plastic-clay bricks were more fire-resistant because they ‎had a ceramic matrix, but they cost about 15% more to make because firing them takes a lot of ‎energy. The in-depth study finds that plastic-sand bricks are a better option for sustainable ‎construction because they offer the best combination of mechanical strength, durability, cost-‎effectiveness, and environmental benefits. They are best for light structural and non-load-bearing ‎uses.‎

This paper presents the results of the experimental investigation on the shear performance ‎of beams strengthened with different types of grids (i) GFRP (Glass Fiber Reinforced Polymers) ‎mesh; (ii) geogrid; and (iii) steel mesh. The experimental program reports the test results of twelve ‎reinforced-concrete (RC) beams strengthened internally with dimensions of 1200 mm in length, ‎‎150 mm in width, and 200 mm in depth that were constructed and tested up to failure using a ‎four-point load configuration. One beam is considered as a control beam, and the other beams are ‎divided into three groups; each group is strengthened with different material mesh. Various ‎parameters were considered in this study, including the number of mesh layers, the type of ‎reinforcement material mesh, and the strengthening configurations. The test results indicated that ‎beams strengthened with steel meshes achieved a peak shear load of 174 kN with an increase of ‎‎66% compared with the control beam. While the development in the ultimate load for ‎strengthened beams using GFRP ranged from 1% to 18% compared to the control beam. ‎Insufficient improvement in the ultimate load for beams strengthened using geogrid is obtained ‎from the experimental results.‎

Servo motors have been adopted in various industry applications, as a result of which there ‎has been a trend toward improving their speed accuracy. DC servomotors with feedback ‎encoders established themselves as participants for various motion control applications in ‎industrial automation and consumer electronics. This article presents speed control of DC ‎servomotors with different control methods (traditional PID, fuzzy logic, and hybrid PID–fuzzy ‎logic controller). Although of simplicity, there are constraints to the PID controllers for ‎nonlinearities and uncertainties; hence, a significant step has been made toward intelligent and ‎hybrid control strategies. In MATLAB Simulink the control performance of these controllers is ‎simulated, and it is noted that the hybrid PID–fuzzy logic controller has less settling time, very ‎little overshoot, and near-zero steady-state error. This hybrid approach offers the accuracy of the ‎PID control system and the flexibility of the fuzzy logic controller and introduces a robust and ‎effective method to enhance the motor speed response for the servo motor application. ‎applications,‎

Hazardous organic pollutants are a common environmental problem, as they do not ‎readily decompose in the environment, leading to their accumulation and a negative impact on ‎ecosystems and human health. Therefore, finding effective and sustainable ways to dispose of ‎them is crucial for preserving the environment and mitigating the health risks associated with ‎them. Consequently, this work demonstrated a cost-effective, environmentally friendly, and ‎straightforward technique for creating a zinc oxide nanocomposite using potato peels (PP).This ‎nanocomposite, known as ZnO-PP,was synthesized and then combined with metakaolin yo from ‎a composite with the prepared material to form a composite designed to facilitate an advanced ‎oxidation process (AOP) for the removal of basic fuchsin (BF) from aqueous ‎media.Comprehensive characterization of the synthesized composites was performed using ‎several analytical instruments, including Fourier Transform Infrared Spectroscopy (FTIR), X-ray ‎Diffraction (XRD), Field-Emission Scanning Electron Microscopy (FESEM),and Brunauer–‎Emmett–Teller (BET) surface area analysis. The BET results indicated specific surface areas of ‎‎2.95 m²/g for raw potato peels (PP), 15.985 m²/g for ZnO-PP, 28.251 m²/g for ZnO-MK ‎composite. Under optimal conditions, namely a ZnO-MK dosage of 0.15 g per 100 mL solution, ‎an initial BF concentration of 10 mg/L, a contact time of 120 minutes, and pH 7 the composite ‎achieved a maximum dye removal efficiency of 96%. Kinetic evaluation revealed that the ‎degradation of BF conformed to a pseudo-first-order rate model, with a coefficient of ‎determination (R²) of 0.9526.‎

This study is examined the combined effects of using recycled ceramic powder ‎as cement substitute and the accumulation of polyethylene glycol 4000 (PEG-4000) as ‎a self-internal curing agent on the mechanical features of concrete. Compressive ‎strength, tensile splitting strength, unit weight and Flexural strength were studied as ‎well as fresh property such as slump. By using less quantities of cement, the primary ‎goal is to enhance sustainability and lower CO2 effluents. PEG-4000's was added at ‎‎0%, 0.5%, 1%, 1.5%, and 2% as a percentage of total weight of cement, while recycled ‎ceramic was employed at replacement percentage of 0%, 10%, 15%, 20%, and 25%. ‎Results illustrate that for mixtures that use ceramic powder as a partial cement ‎substitute, a PEG-4000 dosage of about 1% would be the best way to retain a workable ‎consistency. Generally, using ceramic powder as cement replacement along with PEG-‎‎4000 lowers the self-curing concrete's unit weight. The optimal compressive strength is ‎found to be at 10% cement replacement with 0.5% curing agent. Generally, the ‎obtained split tensile strength designate that the splitting tensile strength of concrete is ‎significantly impacted when recycled ceramic powder is added as a partial cement ‎substitute. 10% ceramic replacement with 1.0–1.5% PEG 4000 is the ideal combination, ‎as the beneficial self-curing effect makes up for the lower cement concentration and ‎creates a more durable and finer microstructure. The complementary advantages of self-‎curing and pozzolanic reaction cause increased flexural strength at intermediate ceramic ‎replacement (10–20%) with combination of 1% PEG-4000. There was a growth in ‎flexural strength by (12%) as compared to the baseline mix with 15% ceramic and 1% ‎PEG.‎

Bot malware and botnet are two widely understood concepts in the cyber security ‎literature. Specifically, a botnet is a geographically dispersed network of infected bots (such as ‎any computing device, including an Internet of Things (IoT) device such as a smart TV, that is ‎compromised by bot malware), which is remotely controlled by a bot. The master is controlled. ‎Such botnets are commonly used to carry out a wide range of malicious cyber activities, from ‎sending spam to launching distributed denial of service (DDoS) attacks to spreading malicious ‎programs (malware) to distributing illegal material (such as child abuse material). In this research, ‎botnet detection systems were investigated and methods to optimize and increase their efficiency ‎in order to identify botnets developed. The chosen method for this work is the combination of ‎independent component analysis and the decision tree algorithm and the single decision tree 15 ‎method, which we discussed with the classification of the data used, i.e., UNSW-NB features, ‎and the 40 dataset contains 15 The chosen method for this work is the combination of ‎independent component analysis and decision tree algorithm and single decision tree 15method, ‎which we discussed with the classification of the data used i.e. UNSW-NB features and the 40‎‏ ‏dataset contains 15 ‎‏ ‏Since the UNSW.‎‏ ‏NB2018and CiCIDS features, we investigated the use of ‎the two approaches in 78 datasets has 2018CiCIDS terms of accuracy, correctness and error ‎criteria. The accuracy obtained for botnet detection according to the approach of combining ‎independent component analysis percent 99.994data set is equal to 15and decision tree algorithm ‎on the UNSW-NB. Also, the amount of RMSE error 99.177 data set is equal to 2018 and on the ‎CiCIDS and on the 0.0076 data set is equal to a small value of 15obtained on the UNSW-NB ‎‎0.0076 data set equal to 2018CiCIDS This research focuses on studying and improving robot ‎network detection systems to enhance their identification efficiency. The proposed methodology ‎uses a hybrid approach combining Independent Component Analysis (ICA) and Decision Tree ‎‎(DT) algorithms, and compares its performance to an independent decision tree model.‎

Good insulation is one of the most important issues‏ ‏to make buildings more energy-‎efficient and friendly to the environment. There are many different insulation materials, making it ‎difficult to compare their efficiency, therefore this paper introduces a comparative study of some ‎thermal insulation materials which are employed to enhance the energy efficiency of residential ‎buildings in hot dry environments. Design Builder program is used to illustrate heat transfer, ‎energy demand, and comfort levels in different thermal insulation conditions. A group of ‎insulation materials is selected to examine their efficiency, such as expanded polystyrene (EPS), ‎polyurethane foam (PU), rock wool, and aerogel, depending on their thermal conductivity, ‎thickness, and impact on the annual energy required for cooling a space. The results of the ‎simulation point out that the selection of insulating material has a significant effect on energy ‎efficiency. Aerogel used the least energy and achieved the greatest reduction in cooling load. ‎Rock wool was the most cost-effective choice, but it was just average in terms of efficiency. The ‎results of the simulation give architects and engineers vital information on how to choose the best ‎insulation solutions for long-term energy management, and how to provide comfortable internal ‎environment with low energy consumption. ‎