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Feasibility Study of a Combined Electric Power and Water Desalination Plant in Jordan
No full textThe rapid growth in Jordan’s electrical and water needs cannot be addressed by the current and planned supply sources. A combined electric power and water desalination plant is proposed and studied in detail. The plant is designed to cover all of Jordan’s electrical and part of its water needs up to the year 2020. Sensitivity analysis of the plant’s profitability under several financing and fuel price scenarios was performed. The results show that such a plant represents a good investment opportunity under a wide range of conditions
Feasibility Study of a Municipality Solid Waste Incineration Plant in Jordan
No full textThe rapid growth in Jordan’s population coupled with an increasing standard of life, has resulted in a large increase of household and commercial waste. Environmental and health concerns as well as the high cost of establishing and maintaining adequate new landfills, has prompted serious thoughts of alternative methods for dealing with the increasing amount of waste. This paper focuses on the prospect of building a waste incineration plant that can be used to generate electricity and recycle material in Jordan. Sensitivity analyses of the plant profitability under several financing scenarios were performed. The results show that such a plant is economically feasible in Jordan
Convection heat transfer from a laminar flow over a 2-D backward facing step with asymmetric and orthotropic porous floor segments
No full textThe fluid and energy equations for the incompressible laminar reattaching flow over a 2-D backward facing step with a porous floor segment were solved numerically using the finite element method. The focus of this study was the change in die forced convection heat transfer characteristics of the flow field due to the addition of a porous floor segment. Several porous flow segment configurations with different lengths and depths were studied. The effect of orthotropicity of the porous segments was also studied. The porosity of the segments was varied over a wide range by changing the value of the pressure loss coefficients in either or both of the x and y directions. The changes in the local and overall Nusselt numbers were reported and discussed. Depending on the configuration, the overall Nusselt number increased or decreased relative to the case of a solid floor. For all configurations, the maximum local Nusselt number increased
Enhanced Solar Still Efficiency Using Water Film Cooling of the Glass
No full textThe effect of water film cooling of the glass cover on the efficiency of a single basin still is theoretically investigated. The effectiveness of film cooling under different operating conditions is reported. Part of the cooling water is recycled as makeup water to the still to further enhance its efficiency. The results of this investigation indicate that proper use of film cooling parameters can increase the still efficiency by as much as 6 percent, but poor combinations of film cooling parameters can lead to significant reductions in still efficiency. The presence of the cooling film neutralized the effect of wind speed on the still efficiency. The actual gain in still efficiency due to the use of a cooling film is further amplified when the practical considerations of where and how such a still is used are taken into account
Structure of a reattaching supersonic shear layer
No full textA Mach 1.83 fully developed turbulent boundary layer with boundary layer thickness, free stream velocity, and Reynolds number of 7.5 mm, 476 m/s, and 6.2 x 10 to the 7th/m, respectively, was separated at a 25.4-mm backward step and formed a shear layer. Fast-response pressure transducers, schlieren photography, and LDV were used to study the structure of this reattaching shear flow. The preliminary results show that large-scale relatively organized structures with limited spanwise extent form in the free shear layer. Some of these structures appear to survive the recompression and reattachment processes, while others break down into smaller scales and the flow becomes increasingly three-dimensional. The survived large-scale structures lose their organization through recompression/reattachment, but regain it after reattachment. The structures after reattachment form a 40-45-degree angle relative to the free stream and deteriorate gradually as they move downstream
Performance of Laser Doppler Velocimeter with Polydisperse Seed Particles in High-Speed Flows
No full textThe flowfield behind an oblique shock wave, where the LDV measured velocities are seed-particle-size dependent, was used to investigate the effects of LDV system parameters on the range of detectable polydisperse seed particles. The parameters included frequency shifting, laser power, scattered signal amplification level, and number of required fringe crossings. The results showed that with polydisperse seed particles ranging from 0.1 to 4.0 microns available in the flow, the average diameter of the detected particles could change from 0.2 to 3.0 microns by changing different LDV system parameters. The effects of this shift in the range of detectable particles on the frequency response of LDV are discussed
Comparing Digital and Traditional Reading for Pleasure: Effects on 11th Graders' Comprehension
No full textThis study investigates the impact of the Reading for Pleasure (RfP) program on 11th-grade students' reading comprehension in private schools in Ajman, UAE, comparing digital and printed reading mediums. It explores how students’ preferences for these formats influence their reading engagement and comprehension. Grounded in theories of reading comprehension and second language acquisition (SLA), the research uses a mixed-methods approach, incorporating quantitative assessments from a quasi-experiment and qualitative insights from a survey and a focus group interview. Findings show that while both digital and printed formats positively affect comprehension, printed texts consistently foster deeper cognitive engagement, particularly with complex reading tasks. Students expressed a preference for printed materials for their ability to minimize distractions and enhance focus, whereas digital formats were favored for accessibility and ease of use in shorter tasks. The study recommends a balanced integration of both mediums, supporting student choice and improving digital literacy skills. By blending the strengths of digital and printed texts, educators can better cater to diverse learning preferences. The research contributes to theoretical frameworks on cognitive engagement in reading and SLA, while offering practical recommendations for curriculum designers and educators in ESL contexts. Additionally, the study highlights the need for future research on the long-term effects of medium preferences and gender differences in reading outcomes
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
No full textThe rise of the Internet has led to the widespread adoption of digital learning platforms, revolutionising the creation, access, and delivery of digital educational resources. These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. By analysing the data generated from these learning platforms with ML techniques, we can uncover detailed insights into student performance. Accurately predicting student performance can help educators tailor teaching methods and interventions to individual needs. This study focuses on predicting and interpreting student performance in a blended learning environment using ML in a Jordanian school context. The primary aim of this research is to employ machine learning models and SHAP (SHapley Additive exPlanations) to predict and understand student performance. A dataset generated by a digital learning platform used by a private school in Jordan is utilised. Various ML algorithms, such as Support Vector Machines, Logistic Regression, K-Nearest Neighbors, Naïve Bayes, Decision Trees, Random Forest, AdaBoost, Bagging, and Artificial Neural Networks are applied to predict student performance. SHAP values are used to interpret these predictions, offering insights into the factors most impacting student outcomes. Key findings indicate that ensemble methods like Random Forest and Bagging outperform other models in predicting student performance, achieving higher accuracy at 95.90% and 95.48%, respectively, as well as balanced precision and recall, which are crucial for accurately identifying both high- and low-performing students. The findings suggest that using these ensemble methods allows for more reliable predictions and better-informed educational strategies. The analysis reveals that individual features, such as engagement with learning materials and worksheets, significantly influence student performance. By understanding these specific factors and their impacts, educators can tailor interventions more effectively to individual needs, thereby enhancing the educational outcomes and supporting personalised learning. The findings underscore the potential of data-driven strategies to enhance educational outcomes and support personalised learning