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Abstract  

In some engineering applications soil stiffness only could not be a reliable parameter in accordance with specific standardizations especially, when

dealing with dynamic loading. In other words, foundation soil should be altered regarding its ductility in order to prevent sudden damage due to brittleness. Plenty of researchers have studied the effect of multifilament polypropylene fibers on soil reinforcement. Besides, the alkaline activation method has been adapted to alter the strength properties of soft soil. Furthermore, in a cutting edge method, alkaline activation of soft soil, using fly ash and Potassium hydroxide, coupled with soil reinforcement was adapted to change the post-peak behavior of soft soil. The goal of this novel technique is to increase the ultimate strength and to enhance the failure mode. In this research work alkali activated kaolin soil and alkali-activated reinforced kaolin soil were cured for 28 and 90 days respectively. Compressive stress tests were conducted on both mixtures, namely, SF40 ( Soil +40% fly ash) and SFR0.75 ( Soil+ 39.7% fly ash + 0.75% PP fibers) samples. Results drawn from the tests revealed a drastic increase in Compressive strength for SF40 samples cured for 28 and 90 days, namely, 3680 kPa and 18500 kPa, respectively. Whereas, the strength recorded by the control sample was only 190 kPa. Though a sharp drop was seen when approaching failure. The addition of reinforcing Polypropylene fibers brought about a drastic enhancement in failure mode for both of curing regimes.

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Abstract:

Wells that cannot produce liquids to the surface under their own pressure requires lift technologies to enable production. Some liquid wells need lift assistance from the beginning and almost all require it sooner or later. One of the most popular artificial lift methods applied in the oil industry, in order to increase productivity, is the gas lift method. Its main principal is the injection of gas in the well to reduce the average density of the fluids produced from the reservoir, hence the weight of the fluid column. As a result, the declined reservoir pressure is sufficient to lift the fluids up to the surface. In this project three wells, (N-36, N-18 and N-53), located in Amal field are selected for the study. The production for all wells is dropping due to increasing water production. Therefore, the main task in this study is to design a gas lift system for these wells by using Prosper software. The procedure of designing an optimized gas lift system in PROSPER is thoroughly described in this study. In the design performed by Prosper, the main points obtained and determined are number of gas lift valves needed to lift the wells up, also the depth of these valves distributed through the tubing and space between valves. In addition to this, the amount of gas injected daily through these valves from casing to tubing. Finally, Inflow performance relationship versus vertical lift performance curves for these wells are determined before and after gas lift design as indication of increasing productivity. 

Engineering education has a crucial role in the economic and social development of society; this paper aims to investigate the most significant factors that contributing in improving the quality of the engineering education. Furthermore, identify the factors affecting the students’ academic performance. The study was conducted by using statistical Design of Experiments (DOE) approach to investigate the main effects of lecture delivery, assessment, engagement, communication, and interaction with instructors. Minitab software is implemented to perform statistical analysis to identify the significance of each factor, and degree by which each factor influences the students’ academic achievement. Results showed that the students’ academic performance is affected by the availability of course materials, and communications with instructors.

This paper addresses a bi-criteria optimization problem to minimize total flow time and makespan simultaneously for a cellular flowshop with Sequence Dependent Setup Times (FMCSP with SDSTs); A multi-objective Particle Swarm Optimization (MPSO) and a Multi-objective Simulated Annealing (MOSA) Algorithm are proposed to solve the proposed problem. furthermore, an improved algorithm (named as IMPSO-TA), where MPSO is combined with Threshold Acceptance (TA) algorithm to improve the convergence of the obtained Pareto Fronts. The proposed algorithms are evaluated using several Quality Indicators (QI) measures for multi-objective optimization problems. Results showed that proposed algorithms can generate approximated Pareto Fronts in a reasonable CPU time. Furthermore, quality of Pareto fronts generated by IMPSO-TA is better than Pareto fronts found by MPSO and MOSA based on the test problems that are used in this research at the cost of CPU time. Further, the proposed IMPSO-TA performs as best available algorithms in the literature for small and medium test problems with a very minor deviation for best results for large test problems.