AUS Repository (American University of Sharjah)
Not a member yet
2669 research outputs found
Sort by
Enhancing the Shear Capacity of RC Beams with Web Openings in Shear Zones Using Pre-Stressed Fe-SMA Bars: Numerical Study
No full textOpenings in the shear span can significantly affect the structural behavior of reinforced concrete (RC) beams, particularly in terms of shear capacity and crack propagation. This paper aims to investigate the feasibility of strengthening the web opening in the shear zone of RC beams by using iron-based shape memory alloy (Fe-SMA) bars, providing valuable insights for structural engineers and researchers. Numerical analysis with ABAQUS/CAE 2020 software was employed in the current study. The research was divided into six groups of beams with web openings of different lengths (150, 300, and 450 mm), prestressing levels (0%, 30%, and 60%), and reinforcement diameters (14, 18, and 22 mm) of Fe-SMA bars. The results show that the presence of web openings can cause a significant reduction in the cracking and ultimate loads of the beams, with reductions ranging from 11% to 50% and 36% to 48%, respectively. However, by adding pre-stressed Fe-SMA bars around small web openings (100 × 150 mm), the shear capacity of the beam is restored, and the beam exhibits behavior similar to solid beams. Additionally, activating the Fe-SMA bars by 30% and 60% resulted in almost similar cracking loads but improved load-carrying capacity of the beam with small openings by 12% and 9%, respectively, compared to the solid beam. The technique proposed for enhancing shear strength is most effective for beams with small (100 × 150 mm) and medium (100 × 300 mm) web openings as it can restore both the beam’s shear strength and stiffness. However, for beams with larger web openings (100 × 450 mm), the use of activated Fe-SMA beams can recover almost 90% of the solid beam’s shear capacity. Furthermore, reinforcing small openings with Fe-SMA bars of different diameters enhances beam shear capacity and stiffness, while for larger openings, higher Fe-SMA reinforcement ratios could potentially restore the beam’s full strength and stiffness. This study emphasizes the importance of strengthening web openings in RC beams, particularly in shear zones, and provides significant insights into how to strengthen beams with web openings, thereby contributing to developing safer structures. However, further laboratory experiments are recommended to validate, complement and extend the findings of this numerical study.American University of Sharja
Nested ensemble selection: An effective hybrid feature selection method
No full textIt has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. To address this issue, we propose a highly effective approach, called Nested Ensemble Selection (NES), that is based on a combination of filter and wrapper methods. The proposed feature selection algorithm differs from the existing filter-wrapper hybrid methods in its simplicity and efficiency as well as precision. The new algorithm is able to separate the relevant variables from the irrelevant as well as the redundant and correlated features. Furthermore, we provide a robust heuristic for identifying the optimal number of selected features which remains one of the greatest challenges in feature selection. Numerical experiments on synthetic and real-life data demonstrate the effectiveness of the proposed method. The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. The proposed method is compared against several popular algorithms including mRMR, Boruta, genetic, recursive feature elimination, Lasso, and Elastic Net. The results show that NES significantly outperforms the benchmarks algorithms especially on multi-class datasets.American University of Sharja
A comprehensive review on the use of natural fibers in cement/geopolymer concrete: A step towards sustainability
No full textThe construction industry is shifting towards environmentally friendly products due to the rising demand for non-renewable raw materials, their high energy consumption, and, most importantly, their detrimental environmental effects. High levels of solid waste produced by raw materials release dangerous gases like nitrous and Sulphur oxides, which are very harmful to the environment. In recent years, the usage of fibers has tremendously increased to make significantly robust structures. For sustainable, waste-free development, manufactured fibers can be replaced with natural fibers without compromising on the requirements. This study considers various natural fibers like basalt, coconut/coir, banana, sugarcane bagasse, hemp, kenaf, bamboo, jute, sisal, abaca, and cotton, and their effects on fresh and hardened concrete have been discussed. This article also reviews the composition, preparation, and processing procedures of various natural fibers, and their potential applications in building materials are highlighted. Future research avenues are identified, and possible negative impacts and limitations are discussed. Our findings confirm the feasibility of standard concrete using natural fibers in cement or geopolymer concrete. Lastly, this review compiles insights from numerous sources to aid academia and the construction industry in developing eco-friendly materials.Riad Sadek Endowed Chair in Civil Engineering of the American University of SharjahAmerican University of Sharja
Influence of synthesized nanomaterials in the strength and durability of cementitious composites
No full textThe development of high-performance materials has been prompted by a constantly expanding infrastructure with complex technical constraints. Performance modification of cement composites using nanoparticles has been thoroughly researched to address demands in the construction industry. This cutting-edge review examines the various parameters of cement composites, such as fresh properties, mechanical properties, and durability characteristics that can be improved using synthesized nanomaterials such as nano-SiO2, nano-Al2O3, graphene oxide, and carbon nanotubes, as well as their inherent limitations. Based on the detailed review, the ideal replacement levels of nano-SiO2 (1–4 wt%), nano-Al2O3 (1–3 wt%), graphene oxide (0.05–0.1 wt%), and carbon nanotubes (0.1–0.5 wt%) can be recommended for the practical applications. It has been noted that the addition of synthesized nanomaterials tends to lower the workability of cement composites. However, nanoalumina, graphene oxide, nano-silica, and carbon nanotubes improve mechanical qualities such as compressive strength, flexural strength, and resistance to abrasion of the blended cementitious system at an optimum replacement level. Similarly, resistance against chemical attacks was imporved with the addition nano-silica, while the addition of graphene oxide in cement is more effective against chloride migration and fire exposure. The overall effect of synthesized nanomaterials is also compared in the study.Riad Sadek Endowed Chair in Civil Engineering at the American University of SharjahOpen Access Program (OAP) at the American University of Sharja
Performance of Membrane Biological Reactor for Tobacco Wastewater Treatment
No full textA Master of Science thesis in Chemical Engineering by Abdallah Hazim Abdallah Alhajar entitled, “Performance of Membrane Biological Reactor for Tobacco Wastewater Treatment”, submitted in April 2023. Thesis advisor is Dr. Sameer Al-Asheh and thesis co-advisor is Dr. Ahmed Aidan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).As technologies develop and populations grow, the demand for water sources increases. To keep up with such demand, the need for innovative methods for water regeneration becomes necessary. Amongst these methods is the utilization of Membrane Biological Reactors (MBRs) for wastewater treatment. This work discusses MBR technology for tobacco wastewater treatment and the factors that affect its performance. Currently, tobacco wastewater treatment methods reveal high time requirement, complexity, and cost. The study revealed that MBRs can effectively remove 80-90% of Chemical Oxygen Demand (COD), 88-94% of Biological Oxygen Demand (BOD5), and 88-91% of total organic carbon (TOC) content from wastewater produced by the tobacco industry while operating at a pH of 6 – 8 with a hydraulic retention time (HRT) of 1 day. The process was favorable in treating tobacco wastewater at temperatures ranging between 20 to 40 oC. Additionally, the study revealed that the design is able to treat wastewater with a COD concentration of 2000 ppm given that the HRT is to be increased. Moreover, the design was successful in decreasing the turbidity by 97% and TDS by over 85% even though it incorporates microfiltration. Furthermore, the results showed better membrane performance with a low fouling propensity, which indicates the suitability of ceramic membranes for installment within the system. Finally, the study compared the effect of membrane pore size by observing the difference in performance between 0.1 and 0.3 μm nominal pore sizes. This change in nominal pore size had minimal effect on the performance of the MBR. Overall, the system showed great potential and applicability to be adapted for the treatment of tobacco wastewater.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE
Gas Metal Arc Welding (GMAW) Process Optimization Using Machine Learning Models
No full textA Master of Science thesis in Engineering Systems Management by Ahmed Sharaf entitled, “Gas Metal Arc Welding (GMAW) Process Optimization Using Machine Learning Models”, submitted in November 2023. Thesis advisor is Dr. Noha Hussein. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
Static Video Summarization Using Video Coding Features with Frame-level Temporal Sub-Sampling and Deep Learning
No full textThere is an abundance of digital video content due to the cloud’s phenomenal growth and security footage, it is therefore essential to summarize these videos in data centers. This paper offers innovative approaches to the problem of key-frame extraction for the purpose of video summarization. Our approach includes feature variables extracted from the bit streams of coded videos, followed by optional stepwise regression for dimensionality reduction. Once the features are extracted and reduced in dimensionality, we apply innovate frame-level temporal sub-sampling techniques followed by training and testing using deep learning architectures. The frame-level temporal subsampling techniques are based on cosine similarity and PCA projections of feature vectors. We create three different learning architectures by utilizing LSTM networks, 1D-CNN networks, and Random Forests. The four most popular video summarization datasets, namely, TVSum, SumMe, OVP, and VSUMM are used to evaluate the accuracy of the proposed solutions. This includes the Precision, Recall, F-score measures, and computational time. It is shown that the proposed solutions when trained and tested on all subjective user summaries, achieved F-scores of 0.79, 0.74, 0.88, and 0.81, respectively, for the aforementioned datasets, showing clear improvements over prior studies.American University of Sharja
Cost and Sustainability Optimization of Desalinated Water Supply Chains
No full textA Master of Science thesis in Engineering Systems Management by Sami Taher Freihat entitled, “Cost and Sustainability Optimization of Desalinated Water Supply Chains”, submitted in November 2023. Thesis advisor is Dr. Moncer Hariga and thesis co-advisor Dr. Rami Afif As’ad. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The increasing demand for freshwater along with the diminishing conventional water resources are the major reasons why the demand for desalinated water has been escalating. Given that the desalinated Water Supply Chain (WSC) involves elevated levels of greenhouse gases emissions along with disposal of brine, it is imperative to develop a plan that safeguards the rights of future generations of sustainable production of freshwater. This thesis presents a mathematical model that minimizes the total cost and environmental impact associated with a set of strategic and tactical decisions taken over the planning horizon within the desalinated WSC. In order to validate the model, a case study was conducted in the Emirate of Sharjah, where forecasted water demand, operational data, and costs associated with WSC related decisions were collected from Sharjah Electricity and Water Authority (SEWA) and literature. The mathematical model was coded using GAMS and solved using CPLEX. Results collectively provided the optimal values of strategic and operational decisions over the entire planning horizon. These decisions include replacement of retiring units, installation of new desalination plants, utilized desalination technology, as well as location and expansion of new plants, pipelines, and storage facilities. Moreover, the results included the yearly production level in each plant, allocation of water to the different demand zones, and water levels in storage tanks. The minimum total cost of the model was found to be AED17.637 billion, and it was concluded that operational cost components of desalination, transportation pipelines, and storage facilities are more significant than their capital cost components. In addition, all replaced and new units employed Reverse Osmosis (RO) technology, which is in line with the trend worldwide. Finally, the effect of increasing the capacity of new units and varying the carbon emissions tax on the relevant decisions as well as the overall cost was studied as part of the sensitivity analysis.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
A Review on Membrane Fouling Prediction Using Artificial Neural Networks (ANNs)
No full textMembrane fouling is a major hurdle to effective pressure-driven membrane processes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO). Fouling refers to the accumulation of particles, organic and inorganic matter, and microbial cells on the membrane’s external and internal surface, which reduces the permeate flux and increases the needed transmembrane pressure. Various factors affect membrane fouling, including feed water quality, membrane characteristics, operating conditions, and cleaning protocols. Several models have been developed to predict membrane fouling in pressure-driven processes. These models can be divided into traditional empirical, mechanistic, and artificial intelligence (AI)-based models. Artificial neural networks (ANNs) are powerful tools for nonlinear mapping and prediction, and they can capture complex relationships between input and output variables. In membrane fouling prediction, ANNs can be trained using historical data to predict the fouling rate or other fouling-related parameters based on the process parameters. This review addresses the pertinent literature about using ANNs for membrane fouling prediction. Specifically, complementing other existing reviews that focus on mathematical models or broad AI-based simulations, the present review focuses on the use of AI-based fouling prediction models, namely, artificial neural networks (ANNs) and their derivatives, to provide deeper insights into the strengths, weaknesses, potential, and areas of improvement associated with such models for membrane fouling prediction.Dana Gas Endowed Chair for Chemical EngineeringAmerican University of Sharja
Assessing the Relationship Between Motivation and Foreign Language Anxiety: The Role of Variance
No full textA Master of Arts thesis in Teaching English to Speakers of Other Languages (TESOL) by Mary Boktor entitled, “Assessing the Relationship Between Motivation and Foreign Language Anxiety: The Role of Variance”, submitted in November 2023. Thesis advisor is Dr. Phillip McCarthy and thesis co-advisor is Dr. Paul Almonte. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The interaction between motivation and foreign language anxiety exhibits a complex nature in shaping learning experiences. The current study explores the varying levels of motivation and foreign language anxiety experienced by the learners and identifies whether a significant correlation exists between the two variables. Two contrasting hypotheses were developed in this study. The first hypothesis is that with higher anxiety levels, learners’ motivation levels diminish. The second hypothesis is for, a positive correlation between learners’ motivation levels and anxiety; thus, where higher motivation levels are associated with higher anxiety levels. A cross-validation method was adopted to address these hypotheses. The University Achievement Bridge Program at the American University of Sharjah serves as the chosen context for this study.The study employed two adapted questionnaires, the Motivation Questionnaire by Gardner in 2004, and the Foreign Language Anxiety Scale by Horwitz et al. in 1986. Both questionnaires used a 6-point Likert scale to measure the levels of motivation and anxiety in the context of language learning. A total of 50 participants were initially included; however, the study ultimately included 33 participants because of common issues of withdrawals and incomplete surveys. Participants were randomly categorized into two groups, and each group received the questionnaires in a distinct sequence of elements. Correlation was measured between motivation and anxiety within each group. Results demonstrated a positive correlation between motivation and anxiety, initially indicating higher motivation levels are associated with increased anxiety levels, affirming their interdependence. Participant evaluation mostly centered around responses 3 and 4, reinforcing the importance of considering the role of variance in correlation analysis and understanding the intricate link between the two variables.College of Arts and SciencesDepartment of EnglishMaster of Arts in Teaching English to Speakers of Other Languages (MA TESOL