Journal of Engineering

Thrust blocks and restraint joints are the two most popular methods of counteracting the thrust force that generated at pipe fittings (bends, Tee, wye, reducers, dead ends, etc…). Both systems perform the same function, which is to prevent the joints from separating from the pipes. The aim of the study is to review previous studies and scientific theories related to the study and design of thrust blocks and restraint joints to study the behavior of both systems under thrust force and to study the factors and variables that affect the behavior of these systems. The behavior of both systems must be studied because they cannot be abandoned, as each system has conditions whose use is more feasible, scientific, and economical. The use of thrust blocks is usually more economical. Still, in many cases, its use is not appropriate, as it is required to wait for the result of the compressive strength test of the concrete. It is required to close the pipe trench as soon as possible; thus, this affects the safety of workers. Or there are future excavation works that may harm the stability of the block, and when the pipe diameter is large, we need a large amount of concrete which affects the economic aspect of the work. For this, the alternative system (restraint joint) must be studied. The main result of the research is that each system provides the opposite force against thrust force with a different mechanism from the other depending on the properties of the soil

The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be quite effective; the results were validated by the experimental agreement with those acquired from laboratory tests. Specifically, the correlation coefficient, R = 0.9944

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slung load.

Collapsible soil has a metastable structure that experiences a large reduction in volume or collapse when wetting. The characteristics of collapsible soil contribute to different problems for infrastructures constructed on it, such as cracks and excessive settlement found in buildings, railways, channels, bridges, and roads. This paper aims to provide an art review on collapse soil behavior all over the world, type of collapse soil, identification of collapse potential, and factors that affect collapsibility soil. As urban areas grow in several parts of the world, the collapsible soil will have more exposure to water. As a result, there will be an increase in the number of wetting collapse problems, so it's very important to comprehend these soils' collapse mechanisms under different conditions such as reduction in capillary rise force upon wetting, the concentration of the soluble salts, deficiency of clays, and under compaction that attributed the collapse potential to the nature of the porous fabric of loess soil

The paper investigates the performance of various machine learning models for intrusion detection systems (IDS). Using Python's Scikit-Learn library, models such as KNN, Support Vector Machine, Naïve Bayes, Decision Tree, Random Forest, Stochastic Gradient Descent, Gradient Boosting, and Ada Boosting classifiers were designed and evaluated. Performance analysis was conducted using the Confusion Matrix metric, and comparisons between the classifiers were made. The Random Forest classifier achieved the best performance with an accuracy of 99.96% and an error margin of 0.038%. The study also explored feature selection techniques like Information Gain, Pearson, and F-test, showing significant performance improvements with reduced feature sets.

A theoretical and experimental investigation was carried out to study the behavior of a two-phase closed thermosyphon loop (TPCTL) during steady-state operation using different working fluids. Three working fluids were investigated, i.e., distilled water, methanol, and ethanol. The TPCTL was constructed from an evaporator, condenser, and two pipelines (riser and downcomer). The driving force is the difference in pressure between the evaporator and condenser sections and the fluid returns to the heating section by gravity. In this study, the significant parameters used in the experiments were filling ratios (FR%) of 50%, 75%, and 100% and heat-input range at the evaporator section of 215-860.2 W. When the loop reached steady-state, the wall-temperature was recorded at various positions along the thermosyphon loop. Results showed that the thermal performance with water was better than methanol and ethanol under the same conditions. The experimental values of the heat transfer coefficient at the evaporator section were measured for the three working fluids. The results were estimated with the nucleate boiling correlation using the engineering equation solver (ESS) program. Additionally, a comparison between the experimental and theoretical values of the heat transfer coefficient in the evaporator section showed good agreement with a maximum difference of 16%.