AUS Repository (American University of Sharjah)
Not a member yet
2669 research outputs found
Sort by
IoT Based Smart City Bus Stops
No full textThe advent of smart sensors, single system-on-chip computing devices, Internet of Things (IoT), and cloud computing is facilitating the design and development of smart devices and services. These include smart meters, smart street lightings, smart gas stations, smart parking lots, and smart bus stops. Countries in the Gulf region have hot and humid weather around 6–7 months of the year, which might lead to uncomfortable conditions for public commuters. Transportation authorities have made some major enhancements to existing bus stops by installing air-conditioning units, but without any remote monitoring and control features. This paper proposes a smart IoT-based environmentally - friendly enhanced design for existing bus stop services in the United Arab Emirates. The objective of the proposed design was to optimize energy consumption through estimating bus stop occupancy, remotely monitor air conditioning and lights, automatically report utility breakdowns, and measure the air pollution around the area. In order to accomplish this, bus stops will be equipped with a WiFi-Based standalone microcontroller connected to sensors and actuators. The microcontroller transmits the sensor readings to a real-time database hosted in the cloud and incorporates a mobile app that notifies operators or maintenance personnel in the case of abnormal readings or breakdowns. The mobile app encompasses a map interface enabling operators to remotely monitor the conditions of bus stops such as the temperature, humidity, estimated occupancy, and air pollution levels. In addition to presenting the system’s architecture and detailed design, a system prototype is built to test and validate the proposed solution
Multi-Facility Inventory System Management for Repairable Items
No full textA Master of Science thesis in Engineering Systems Management by Muhammad Affan entitled, “Multi-Facility Inventory System Management for Repairable Items”, submitted in July 2019. Thesis advisor is Dr. Mojahid F. Saeed Osman. Soft and hard copy available.Multi-Facility inventory system for repairable items is used for the management of critical spare parts for durable equipment where a repair facility is considered along with several operating facilities. This inventory system is very useful in industries in which there is a constant and huge demand for repaired and new spare parts from multiple operating facilities. It is exceptionally vital for maintenance, repair and overhaul organizations to enhance the spare parts inventory management by modeling the on-hand inventory of new and repaired spare parts. Nowadays, simulation methods have become promising methods to investigate and optimize real-world processes. It is anticipated that the appropriate development of simulation models for managing repaired and new spare parts of durable equipment in industry can result in healthy stocks of repaired and new spare parts and cost savings. This research describes the development of promising simulation models for multi-facility inventory system of repairable items in a centralized inventory environment considering the probabilistic nature of the system, with emphasis on the applicability of the models to different industries where multiple operating facilities in a region undergo spare parts repair whereby they send their faulty spare parts to a repair facility. Such models allow investigating the inventory systems for repairable items in a flexible and risk-free manner to effectively design the processes of repairing faulty spare parts and procuring new spare parts considering different ordering policies, and, furthermore, achieving sufficient fill rate and service level of spare parts with minimum inventory investment. A case study along with its results, sensitivity analysis, and managerial insights are presented in this research to illustrate the applicability and suitability of the proposed simulation models. The key results are the valuable managerial insights provided by the proposed simulation models into the complex inventory system of repairable items. These managerial insights are extremely important for achieving a maintenance, repair and overhaul organization's objectives such as minimizing inventory costs and maximizing service levels.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
Transmit Beamforming Methods for the Frequency Diverse Array
No full textA Master of Science thesis in Electrical Engineering by Mobeen Mahmood entitled, “Transmit Beamforming Methods for the Frequency Diverse Array”, submitted in May 2019. Thesis advisor is Dr. Hasan Mir. Soft and hard copy available.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Production of Acidic Bio-Char from Food Waste
No full textA Master of Science thesis in Chemical Engineering by Fatemeh Hassan Pour entitled, “Production of Acidic Bio-Char from Food Waste”, submitted in December 2019. Thesis advisor is Dr. Yassir Makkawi. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Bio-char is a carbon-rich solid, produced by pyrolysis of biomass at a high temperature in absence of oxygen. The process also produces a hydrocarbon gas, which upon condensation, produces a liquid fraction and a permanent gas. When applied in sandy soil, the bio-char increases the water retention, enhances nitrification, and alters acidity, hence, enhancing the life and growth of plants. In this project, the aim is to use food waste, a feedstock available in UAE, for the production of acidic bio-char in an auger reactor. To assess the effect of the pyrolysis temperature on the quality of the products, the process was carried out at six different temperatures within the range of 350−580 °C. The highest bio-char yield (50.2 %) was obtained at 350 °C while the highest bio-oil yield (48.9 %) was obtained at 550 °C. The food waste was found to produce acidic bio-char with pH=6.73 at the pyrolysis temperature of 440 °C, which is lower than the pH for most bio-chars produced from conventional woody biomasses. The bio-char surface area, water retention capacity and electrical conductivity were found to increase with increased temperature. In terms of stability, the bio-char was found to be relatively stable as per their position in the Van Krevelen diagram. The quality of the bio-oil produced from the food waste was found to be exceptionally high with very low water content and high heating value. In conclusion, this study, provided valuable information for the potential of food waste as a source of bio-char and bio-oil, hence contributing to the diversity of sources for soil amendment material and clean energy in the UAE. For future work, it is recommended to explore wider operating conditions to enhance the bio-char acidity, among these is to consider pre-treatment of the biomass, use of CO2 as a sweeping gas and increasing the bio-char residence time.College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE
The Use of Artificial Intelligence and Big Data in the Continuous Improvement Process of Engineering Curricula
No full textA Master of Science thesis in Engineering Systems Management by Basel Obaid entitled, “The Use of Artificial Intelligence and Big Data in the Continuous Improvement Process of Engineering Curricula”, submitted in July 2019. Thesis advisor is Dr. Salwa Beheiry. Soft and hard copy available.Higher education institutions generate huge caches of data that can be pivotal in creating value for the next generation. The excellence of these institutions and the engineering programs they provide, their continuous improvement and, above all, the sustainability of engineering education can be ensured if big data, current and dynamic, heterogeneous and large in volume, is collected, analysed and evaluated accurately. Engineering Programs can satisfy the Accreditation Board for Engineering and Technology (ABET) criteria by leveraging the latest disruptive technologies, such as Artificial Intelligence and Big Data Mining, to achieve cost efficiency and to develop better processes for the continuous improvement of the accredited programs. Data analysis helps programs showcase their efforts and help ABET assess the institutions’ conformity to the set standards and provide feedback as well. Above all, the integration of AI in the ABET framework will help in reducing the human involvement and assess the student outcomes in relation to the course learning outcomes. Better decision-making, decision control, trend forecasting, and greater participation of the educational program constituents are some of the other advantages. The primary aim of this research was to develop a framework to integrate AI and Big Data techniques in the continuous improvement process. Subsequently, a metric entitled the Artificial Intelligence Engineering Curricula Index (AIECI) was developed to measure the adoption level of AI and Big Data in the ABET continuous improvement process. This thesis used the existing literature body to amalgamate different AI applications that can be solidly linked to the ABET continuous improvement process. Furthermore, experts from the educational sector were solicited to validate the importance of each AI tool and its link to the ABET continuous improvement process using the Relative Importance Index (RII). Finally, rank sum, reciprocal rank and rank exponent were used to specify weight for each tool based on the results obtained from RII. The results show that learning analytics and gap analysis can be referred to as the most important application for AI with RII of 0.92. Lastly, Performance Prediction was ranked last, with an RII of 0.640.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM
Estimating the Impact of Combined Horizontal and Vertical Curves on Drivers’ Perception
No full textA Master of Science thesis in Civil Engineering by Mohammad Essam Alozn entitled, “Estimating the Impact of Combined Horizontal and Vertical Curves on Drivers’ Perception”, submitted in November 2019. Thesis advisor is Dr. Akmal Abdelfatah. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Highway design focuses on providing safe facilities and smooth mobility on road networks. The increasing rate in highway accidents’ fatalities resulted in an increasing demand for evaluating and improving highway design methodologies. Dubai road safety is a major concern as per its Roads and Transport Authority’s (RTA) vision to have a safe and smooth transport for road users. Among the most critical highway segments that affect safety are the ones that include combined horizontal and vertical alignments. The driver’s perception is highly affected due to the existence of combined curves. This research aims at developing a procedure for the evaluation of the effect of combined horizontal and vertical curves on drivers’ perception. Several combined curves’ scenarios are developed to highlight the impact of curve combination on driver’s perception. The proposed three-dimensional curve scenarios were created through importing their horizontal and vertical alignments to a computer animation software to extract their driving perspective views. These views were presented to a sample population to record their perception. A hypothesis stating that all drivers perceive horizontal curve radius with the right perception, in the presence of combined horizontal and vertical curves, is tested to examine if the combined curves have an impact on the drivers’ perception. The collected data show no significant statistical difference among drivers’ groups regarding age, nationality, and combined curves type groups. Based on the collected data, a regression model was developed to predict the deviation from the right perception percentage of the horizontal curve radius when it is combined with a vertical curve. The statistical analysis performed with (α=5%) showed that several geometric parameters affect drivers’ perception of combined curves with different rates. The consistency model examines the drivers’ behavior on combined curves. The model was applied to road segments with combined alignments to evaluate them. Also, the developed methodology was compared with other consistency models developed in other countries. Finally, the developed model proves that there is a misperception of the horizontal radius while driving on a combined curve. The research provides some recommendations to avoid the negative effects of the drivers’ misperception of the road dimensions.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
Experimental and Numerical Study of RC Beams Strengthened in Flexure with Bolted/Bonded AA Plates
No full textA Master of Science thesis in Civil Engineering by Omar Raed Abuodeh entitled, “Experimental and Numerical Study of RC Beams Strengthened in Flexure with Bolted/Bonded AA Plates”, submitted in April 2019. Thesis advisor is Dr. Jamal Abdalla and thesis co-advisor is Dr. Rami Haweeleh. Soft and hard copy available.Reinforced Concrete (RC) members are susceptible to deterioration due to many factors. Externally bonded reinforcement (EBR) such as fiber-reinforced polymers (FRP), had emerged as one of the proven techniques for flexural strengthening and retrofitting of RC members. This is due to its practicality and structural effectiveness; however there are shortcomings that include premature de-bonding/de-lamination failure or brittle FRP rupture failures. The use of mechanically anchored Aluminum Alloy (AA) plates instead has the potential of overcoming these drawbacks by providing both strength and ductility while influencing the failure modes. In this project, 16 RC beams were prepared, one beam was left unstrengthened (CB), one was strengthened with AA plate using epoxy only (CBE), and 14 beams were strengthened with AA plates with different bolt sizes, spacing, bolt layout and epoxy. The specimens were tested to failure and all specimens with bolted AA plates exhibited approximately 30% increase in strength accompanied with drastic increase in ultimate ductility (56.5%) and failure ductility (84.1%) compared to the control beam with epoxy (CBE). It is concluded that the implementation of a hybrid anchorage system (i.e., bolts with epoxy) in retrofitting applications serves as a viable option for fixing AA plates to RC beams. Furthermore, nonlinear finite element (FE) models for all specimens were developed using validated constitutive laws for capturing the nonlinear properties of the materials. Contour plots and concrete cracking patterns were generated to monitor the stress and cracking propagation for each model. The FE predictions closely resemble that of the experimental results in terms of load-deflection, cracks patterns and failure modes. This validated the use of FE as a simulation tool for further investigating the behavior of RC beams strengthened with externally bonded and bolted AA plates.College of EngineeringDepartment of Civil EngineeringMaster of Science in Civil Engineering (MSCE
PIRATA: A Sustained Observing System for Tropical Atlantic Climate Research and Forecasting
No full textPrediction and Research Moored Array in the Tropical Atlantic (PIRATA) is a multinational program initiated in 1997 in the tropical Atlantic to improve our understanding and ability to predict ocean‐atmosphere variability. PIRATA consists of a network of moored buoys providing meteorological and oceanographic data transmitted in real time to address fundamental scientific questions as well as societal needs. The network is maintained through dedicated yearly cruises, which allow for extensive complementary shipboard measurements and provide platforms for deployment of other components of the Tropical Atlantic Observing System. This paper describes network enhancements, scientific accomplishments and successes obtained from the last 10 years of observations, and additional results enabled by cooperation with other national and international programs. Capacity building activities and the role of PIRATA in a future Tropical Atlantic Observing System that is presently being optimized are also described. Plain Language Summary Long data records are essential for improving our understanding of the weather and climate, their variability and predictability, and how the climate may change in the future in response to anthropogenic greenhouse gas emissions. Climate variability in the tropical Atlantic Ocean has strong impacts on the coastal climate in particular and, consequently, the economies of the surrounding regions. Since 1997, the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) program has maintained a network of moored buoys in the tropical Atlantic in order to provide instantaneous high‐quality data to research scientists and weather forecasters around the world. This paper describes PIRATA successes in terms of scientific discoveries and observing technology enhancements. Perspectives are also provided on PIRATA's role in the future Tropical Atlantic Observing System, currently under design, that will consist of a variety of coordinated measurements from satellites, ships, buoys, and other ocean technologies
Enhancing a Simple Water-Based Photovoltaic-Thermal (PVT) Solar Collector Using CFD Analysis
No full textA Master of Science thesis in Mechanical Engineering by Marwan Hicham Osman entitled, “Enhancing a Simple Water-Based Photovoltaic-Thermal (PVT) Solar Collector Using CFD Analysis”, submitted in July 2019. Thesis advisor is Dr. Mehmet Fatih Orhan and thesis co-advisor is Dr. Mohammad Omar Hamdan. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).Photovoltaics thermal collectors are gaining more attention due to their promising potential to pave the way for the penetration of solar energy in modern day power generation technologies. PVTs’ flexibility, manufacturability, high efficiency, and multi-output nature inspired many innovative designs and design improvements available in the literature. PVT solar collectors conventionally attach PV cell(s) to a solar thermal collector to simultaneously generate electrical and thermal energies from the same solar input. The advantages of PVTs are twofold. First, extraction of the generated heat from the PV cells to be utilized in end-user applications, most often space heating or direct hot water (DHW). Second, maintaining the PV cells at a reasonable operating temperature, which reflects on the cells’ conversion efficiency and longevity. This study aims to design a PVT system and optimize its operation to maximize overall efficiencies using a zero-dimensional model along with a detailed Computational Fluid Dynamics (CFD) analysis of the thermal collector. The PVT performance can be investigated by determining its thermal and electrical characteristics. The approach taken in this study to analyze the PVT collector is separated into two main sections, energy and exergy analyses in which the thermal, electrical and overall efficiencies are evaluated. The zero-dimensional model involves controlling heat convection of the PV to study the trade-off between high water outlet temperature and electrical conversion efficiency. A detailed CFD analysis is conducted to evaluate the performance of a workable design for the PVT hybrid system. Then, the CFD analysis is used to calculate the overall convection heat transfer for a PVT system. By applying the mathematical model, the effect of flow rate and the inlet temperature on the energy and exergy efficiency has been tested. It was observed that the overall efficiency and exergy of the PVT increase as the mass flow rate increased. This study demonstrated that, the optimum inlet water temperature to maximize the overall exergy generated by the system at any operating conditions can be achieved. Nevertheless, the performance of the PVT was tested at different thermal conductivity and collector geometries to see the effect on the overall exergy and energy efficiency.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME
Autonomous Vehicles Delivery Systems: Analyzing Vehicle Routing Problems with a Moving Depot
No full textA Master of Science thesis in Engineering Systems Management by Batool Mezar Madani entitled, “Autonomous Vehicles Delivery Systems: Analyzing Vehicle Routing Problems with a Moving Depot”, submitted in April 2019. Thesis advisor is Dr. Malick Ndiaye. Soft and hard copy available.The vast growth in the e-commerce market has increased the attention to resolving the problem of Last Mile Delivery that has significant challenges such as reducing operational cost or ecological impact and increasing supply chain performance. The inclusion of new technologies such as drones and robots help tackle these challenges by developing new distribution systems to improve from traditional deliveries methods. However, the use of these technologies brings new operational challenges. This research deals with the impact of using autonomous vehicles in logistics. We first present a technological review of the use autonomous vehicles in logistics and use it to introduce a classification of the delivery systems based on the parcel handover at the time of the last handling before delivery to customers. We describe three categories of handovers, namely, machine-to-person, machine-to-machine, and person-to-machine, and characterize for each of them the type of vehicle routing optimization that it implies. Moreover, we study a truck-drone system, where the truck serves as a depot from where we load the product to the drone for final delivery to customers. The depot is now moving unlike in a traditional Vehicle Routing Problem for which we always assume a fixed depot. Therefore, we present a new class of Vehicle Routing Problems with a moving depot for a truck-drone system and formulate six Integer Linear Programming formulations to minimize the total operational cost through sequencing the deliveries to different customers and optimizing the locations for the truck to release and collect the drones. The problem is NP-hard, thus developing heuristic solutions is more appropriate for large size instances. The proposed models are first solved using the General Algebraic Modeling System software to find the optimal solutions and study their characteristics. Furthermore, a Clarke and Wright Savings heuristic is developed using C++ language to solve large-size problems. The algorithm returned solutions that are within the known quality, 20%. The solutions provided 8% to 20% deviation from the optimal solutions. The algorithm returned solutions for 80 nodes within 1200 seconds. Different real-life applications can adopt the proposed models such as the UPS truck-drone and Amazon airborne fulfilment centre.College of EngineeringDepartment of Industrial EngineeringMaster of Science in Engineering Systems Management (MSESM