Engineering Commons^™

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori

Theses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Utilizing Date Fruit Pomace As A Corrosion Green Inhibitor For Non Ferrous Alloys, Sardor Rustam Odilov

Theses

This thesis explores a novel green corrosion inhibitor derived from date fruit pomace extract (DFPE) for the protection of aluminum alloy 3003 in highly corrosive environments, specifically hydrochloric acid (HCl) and natural seawater. The central aim is to promote the sustainable reuse of agro-waste as an effective and eco-friendly alternative to conventional toxic inhibitors, aligning with environmental and industrial safety goals.

A comprehensive methodology was employed, including Soxhlet extraction (using both non-polar n-hexane and polar methanol-water solvents), rotary evaporation, and FTIR analysis to identify the active functional groups responsible for inhibition. Corrosion behavior was systematically evaluated using both mechanical (weight …

Interaction Of Liquid Phase Diisopropyl Methyl Phosphonate (Dimp) With Material Surrogates For Components Of Soil And Combustion Products Of Metal Fuels, Khushi Sunil Patel

Theses

Combustion products of three different Al-based materials, Al-CaCO₃, Al-SiO₂, and Al-Fe₂O₃ , have been produced to understand their interaction with liquid diisopropyl methyl phosphonate (DIMP), a surrogate for chemical weapon agents. The purpose of this is to see which materials were more effective at DIMP adsorption and decomposition at different temperatures. Prepared materials were characterized using electron microscopy, x-ray powder diffraction, and nitrogen adsorption. Prepared powders were submerged in DIMP and heated in a thermal analyzer, tracking the mass changes as a function of temperature. Surfaces of the recovered materials were studied using …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

A Study Of The Impact Of Balancing, Geometric Transformation, Generative Networks, And Roi Techniques In Eye Diseases Classification, Sghaira Hareb Alnuaimi

Theses

Automatic detection of ocular diseases helps medical professionals efficiently identify eye disorders, reduce diagnostic errors, and accelerate diagnoses to prevent blindness. Deep learning has been successfully utilized in various fields, including medical image classification. However, in spite of these advancements, challenges remain in ocular disease classification.

The objective of this work is to address these challenges using data processing, data augmentation in combination with Region of Interest (ROI) techniques. Medical datasets often suffer from scarcity, imbalance, and low-quality images, leading to inaccurate classification. To mitigate these issues, we utilize the ODIR dataset, which contains 7,000 labelled training images for both …

Wide Lock-In Energy Harvesting From Vortexinduced Vibrations Of A Deformable Cylinder, Ahmed Raafat Mostafa

Theses

Energy harvesting from ambient sources has gained attention due to increasing energy demands. Despite VIV-based harvesters showing significant potential, their lock-in region, where significant power is generated, is narrow. Given the continuously varying ambient conditions of fluid currents, harvesters can easily fall into de-synchronization, yielding low energy output. Existing solutions like tunable masses or multiple degrees of freedom systems increase complexity and weight, limiting practical applications. This work introduces a novel variable diameter cylinder mechanism—a practical technique that actively tunes the cylinder’s geometry in real time to enhance energy harvesting efficiency from VIV. The mechanism employs an expanding pulley system …

Identifying Barriers, Challenges And Opportunities Of Implementing Retrofitting Strategies In Existing Buildings In The Uae, Ahmad Ghalib Masri

Theses

The built environment of the UAE faces sustainability challenges because of its high energy usage and greenhouse gas emissions which require successful retrofitting methods to enhance aging buildings' performance and efficiency. This research investigates the barriers and challenges and opportunities of retrofitting strategy implementation in the UAE to provide direction for policymakers and stakeholders regarding sustainable practices. The research employed a mixed-methods approach through literature reviews and stakeholder surveys and interviews. The study shows that high upfront costs (68% of respondents) and building owner awareness limitations (54%) and fragmented regulations with inconsistent thermal insulation standards across emirates represent major barriers. …

Groundwater Storage Dynamics In Abu Dhabi Emirate Using In-Situ And Grace Data, Tala Jalal Maksoud

Theses

Water scarcity presents a significant challenge to the sustainable development; especially in arid regions like Abu Dhabi Emirate. Addressing concerns over nonrenewable aquifer depletion, caused by agricultural expansion and lifestyle advancements, has, therefore, become crucial in such regions. This thesis investigates Groundwater Storage (GWS) dynamics in Abu Dhabi Emirate by integrating satellite data from the Gravity Recovery and Climate Experiment (GRACE) with in-situ data from 257 wells over two decades (2002-2022), employing GIS and RS technologies. The main aim of this study is to provide a comprehensive approach to evaluate GWS dynamics considering multiple perspectives including: dealing with missing datasets, …

Smart Traffic Intersections: Leveraging Isac And Millimeter-Waves For Advanced Vehicle Platooning, Mohammed Risal Thadathil

Theses

The rapid advancement of self-driving cars is reshaping the transportation industry and accelerating the development of smart cities. Vehicle platooning, a key capability of autonomous vehicles, has the potential to enhance traffic efficiency, reduce congestion, and improve safety at intersections. However, maintaining platoon cohesion, minimizing latency, and optimizing traffic signal interactions remain significant challenges. This study addresses these issues by leveraging Integrated Sensing and Communication (ISAC) technology with millimeter-Waves (mmWaves) signals to optimize platooning performance at traffic signal intersections.

The research identifies gaps in existing Vehicle-to-Everything (V2X) communication frameworks, particularly in managing platoon movements in urban traffic intersections. To bridge …

Design And Evaluation Of Geopolymer Composite As A Potential Sorbent Of Heavy Metals From Water, Ebtesam Mohammed Alghafri

Theses

Reducing the levels of heavy metals in water is crucial, given their severe environmental and health impacts. Various methods exist for heavy metals removal. Yet, they mostly come with multiple drawbacks, such as costly treatments and limited efficiency. Previous studies have found geopolymer to be a promising sorbent because it is synthesized using by-product materials, making it an eco-friendly and economically sustainable alternative. Limited studies explored the sorption potential of fly ash-slag blended geopolymers; none examined the effect of mix design factors synergically on sorption, mechanical properties, and durability, and few considered solution characteristics and operating conditions simultaneously. Therefore, this …

A Bayesian Belief Networks Approach To Prioritize Road Safety Mitigation Measures For Eco-Mobility Modes, Fatmah Mohamed Alyammahi

Theses

This study presents an innovative decision-making approach that enables the prioritization of road safety measures for eco-mobility users—pedestrians, cyclists and light-electric micromobility riders—in Abu Dhabi. The analysis uses 2032 eco-mobility crash records (1016 pedestrian, 567 bicycle, 449 e-scooter) from 2020-2023 supplied by Abu Dhabi Police and the Department of Municipalities and Transport. A supervised Bayesian Belief Network (BBN) was constructed around six empirically estimated variables: visibility, predictability, road curvature, obstructions, lighting and speed limit. Maximum-likelihood conditional-probability tables were derived from the cleaned dataset; Beta priors were applied only where cell counts were sparse. Ten conventional machine-learning models—including Random Forest, Gradient …

Performance Comparison Of Iot-Powered Indoor Hydroponic Systems And Outdoor Traditional Environment, Saleha Alharthi

Theses

Traditional agriculture faces challenges, including high water consumption, greenhouse gas emissions, and fluctuations in environmental conditions. The research aims to develop alternative sustainable solutions to address issues related to traditional farming. Hydroponics provides opportunities to grow different types of vegetables indoors, where conventional agriculture is challenging. This thesis presents a comparative study of soil-based and hydroponic arugula cultivation using the nutrient film technique (NFT). The proposed methodology focuses on maintaining high similarity in the implementation of components across systems to ensure fair comparison. This thesis utilized distinct approaches. The first approach compared an outdoor soil-based system with an indoor hydroponic …

Hybrid Treatment Method Of Biofiltration Preceded With Advanced Oxidation Process For The Removal Of Emerging Contaminants From The Wastewater Treatment Plant Effluent, Anjali Mohan Payathuparambil

Theses

The global demand for potable quality water has been on a continuous rise. Consequently, water reuse is now considered as an alternative to significantly expand supplies of freshwater in communities facing water shortages. Most of the conventional wastewater treatment plants (WWTP) are not efficient in the removal of emerging contaminants from the water, which will cause serious issues to the environment, human and animal life. This research investigated the possibilities of treating wastewater for reuse. First, the feasibility of utilizing a biofiltration system without pre-treatment for removing emerging contaminants from the WWTP effluent was investigated. Two types of biofilter media- …

Investigation Of Innovative Heat Pipes / Fins System For Diesel Engine Cooling, Mohammad Shafiq Anees

Theses

Engine cooling is considered one of the most important factors that affect their efficiency and therefore their performance, so a new cooling method is proposed using both heat pipes and fins to improve the cooling efficiency of internal combustion engines and shall be examined theoretically and experimentally. A test rig has been designed and built using a specimen material with similar properties to the real engine materials with similar dimensions as the engine cylinder head / liner thickness. The experiment employed a specially designed testing apparatus that included a gas burner for consistent heating, a modifiable support structure, and an …

Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz

Theses

This thesis addresses a operational challenge in modern industrial operations: the increasing complexity of systems and the consequent cognitive burden on operators. As industrial technologies advance, the human-computer interface has become the primary conduit for information flow, playing a pivotal role in operational decision-making. However, the proliferation of data often leads to information overload, potentially compromising rather than enhancing operator performance. This research explores an approach to this pressing issue through the application of Bayesian networks as decision support systems in safety- critical scenarios. Our study employs a multi-faceted approach, combining theoretical modeling with empirical testing. Through collaboration with industry …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Exploration Of The Iterative Design Process: Integrating A Requirements Matrix And Hazard Analysis Toolsexploration Of The Iterative Design Process: Integrating A Requirements Matrix And Hazard Analysis Tools, Blaine Edlefsen

Theses

The iterative design process is applied to multiple industry sectors from software development to product manufacturing. The cyclical approach integrates the steps of design, prototyping, and testing toward the realization of a user's specified needs. The use of a requirements traceability matrix and hazard analysis documentation that supports the definition of the iterative design process is explored. These design project management tools are applied to a case study involving workholding design for a Wire Electrical Discharge Machining (Wire-EDM) manufacturing process. This industry-relevant case study is conducted in collaboration with New Jersey Precision Technologies, Incorporated (NJPT). The design requirements involve both …

Kinetics, Thermodynamics, And Biological Characterizations Of Hydrolysates Enzymatically Produced From Proteins Extracted From Microalgae, Hebah Al-Amodi

Theses

This thesis aims to explore the use of Zeolitic Imidazolate Framework-L (ZIF-L) as a support for immobilizing alcalase and its potency in producing protein hydrolysates. ZIF-L was synthesized at room temperature using an aqueous solution, and alcalase was immobilized through adsorption batch experiment. The successful immobilization of alcalase on ZIF-L was confirmed through Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). The maximum adsorption capacity of alcalase on ZIF-L was determined to be 672.1 ± 5.5 mg g^-1 at 40°C using an initial protein concentration of 5 mg mL-1. Adsorption equilibrium data …

Analysis, Design, And Experimental Validation Of The Thermal Subsystem Of Alainsat-1 Cubesat, Ameereh Seyedzadeh

Theses

This thesis investigates the thermal management techniques of AlAinSat-1 during extremely harsh space conditions. It presents a comprehensive analysis of its thermal behavior using numerical techniques and validates the CubeSat's survivability in space via experimental testing. AlAinSat-1 is a nanocube-shaped satellite carrying Earth observation payloads, including RITA (Remote sensing and Interference detector with radiome-Try and vegetation Analysis) and Locana. Understanding how the CubeSat behaves in harsh space conditions and maintains thermal stability during its mission is critical to its success. The main aim of this study is to employ finite element analysis (FEA) techniques to simulate the thermal behavior of …

Utility Of New Remote Sensing Data In Evaluating The Hydrological Response To Land Use And Land Cover Changes, Chithrika Jayamini Alawathugoda

Theses

Land use and land-cover (LULC) changes have profound impacts on hydrological responses, influencing runoff dynamics and flood risks. This study focused on two contrasting watersheds undergoing rapid LULC transformations: the arid Wadi Ham watershed in the UAE and the tropical Imphal watershed in India. The research emphasized the critical role of accurate LULC data for hydrological modeling in climate-sensitive regions, where land-use changes are accelerating. Using high-resolution PlanetScope and Sentinel-2 satellite imagery, LULC maps were developed and classified using Maximum Likelihood (ML) and Random Forest (RF) algorithms. PlanetScope imagery paired with the RF classifier achieved the highest overall accuracy, with …

Design And Implementation Of Attitude Control System For Gnssas 6u Cubesat, Anoud Nasser Alkatheeri

Theses

This thesis presents the design and simulation of the Attitude Control System (ACS) for the GNSSaS 6U CubeSat, developed by the National Space Science and Technology Center (NSSTC) at UAE University. The CubeSat's mission is to enhance GNSS signal accuracy, which requires precise attitude control to achieve this objective. The ACS utilizes magnetorquers and reaction wheels for actuation. The primary objective of this thesis is to design an ACS that fulfills the mission’s performance requirements, including maintaining pointing accuracy in both fine and medium pointing modes. To achieve this, a comprehensive disturbance analysis was conducted, leading to the selection of …

Heat Sink With Fins And Phase Change Material For Cooling Of High-Power Electronic Devices, Farooq Fakher Mahmoud

Theses

Electronics are integral to modern life, present in everything from household appliances to advanced computers. The performance and reliability of these devices are closely tied to their operating temperatures. High-power operations can lead to significant heating, necessitating effective thermal management to enhance functionality and prevent failure. This requirement drives the demand for efficient heat sinks, which dissipate the heat generated by these devices. Phase change material (PCM)-based heat sinks have become a popular passive cooling solution, increasingly replacing traditional heat sinks.

This research investigates finned PCM-based heat sinks using numerical simulations validated by existing literature and experimental data. Gallium is …

The Impact Of Outdoor Thermal Comfort On Users’ Walkability: Study Case In Al Ain Square, Al Ain City, Uae, Alyazia Saeed Alnehayan

Theses

Living in a hot dry arid climate limits the walkability of its inhabitants. The excessive heat and dryness of the weather undoubtedly make walking a less tempting, encouraging, and pleasant choice for getting around the city. For that reason, this master thesis analyzes the various strategies used to enhance outdoor thermal comfort. Outdoor thermal comfort is controlled by numerous factors, including street and building orientation, vegetation, shading devices, and water bodies. The purpose of this study is to examine the relationship between walkability and UTCI values (universal thermal comfort index) in the context of Al Ain Square, a neighborhood in …

Performance Analysis Of Underground-To-Aboveground Communication In Agricultural Iot Networks, Irfana Ilyas Manzil

Theses

This thesis investigates the potential of LoRa, a low-power, wide-area networking technology, for establishing reliable communication between underground sensors and aboveground infrastructure. We comprehensively analyze LoRa's performance in both single-hop and multi-hop configurations, considering the impact of diverse environmental factors such as soil composition, moisture content, underground transmission distance, and path loss on signal propagation. We delve into the crucial role of the spreading factor (SF) within the LoRa communication system, analyzing its influence on network performance. Furthermore, we develop a comprehensive mathematical model for bit error rate (BER) under various channel conditions, including additive white Gaussian noise (AWGN) and …

Neural Operator For Accelerating Coronal Magnetic Field Computations In Bifrost Mhd Model, Yutao Du

Theses

The application of the Tensorized Fourier Neural Operator (TFNO) to significantly enhance the computational efficiency of coronal magnetic field calculations within the Bifrost Magnetohydrodynamics (MHD) model is introduced in this study. Leveraging simulated data from the European Sunrise Science Data Center, the TFNO? an extension of the Fourier Neural Operator (FNO) that incorporates tensor decomposition for improved handling of high-dimensional data?is employed to solve time-varying partial differential equations (PDEs) over a 3D domain. The performance of the TFNO is compared with traditional machine learning methods, including Vision Transformer and CNN-RNN (encoder-decoder) architectures, to demonstrate its accuracy, computational efficiency, and scalability. …

Marking Estimation In Petri Nets Using Dynamic Mode Decomposition, Aditya Kale

Theses

Petri Nets (PNs) are a well-established framework for modeling and analyzing complex systems with interacting, concurrent processes. This thesis extends traditional Petri Net methodologies by integrating Dynamic Mode Decomposition (DMD), a technique originally developed for fluid dynamics, to analyze Continuous Petri Nets (CPNs). By applying DMD to CPN marking evolution, this research constructs a reduced-order model that captures its dynamics through dynamic modes and eigenvalues, enabling prediction of future markings without detailed knowledge of transition firings or underlying deterministic models. The principal contribution of this research is extending the kit of tools available for analysis of CPN dynamics, providing insights …

Effects Of Exoskeletal-Assisted Walking Rehabilitation On Gait Of Patients Post Stroke, Archisha Kanchan

Theses

Stroke can have detrimental effects on one's body. Its symptoms can range from lightheadedness to blurred vision to body paralysis. One of the more common effects of stroke is difficulty walking where many of the patients who have suffered from stroke are unable to ambulate fully. To mitigate gait difficulties, patients typically follow through with various kinds of physical therapy to help with their gait movements. Recently, robotic exoskeleton (RE) walking therapy has been used as a more innovative approach to gait rehabilitation, in conjunction with other physical therapy session techniques. However, studies involving RE therapy within the stroke population …

The Next Strike: Pioneering Forward-Thinking Attack Techniques With Rowhammer In Dram Technologies, Nakul Kochar

Theses

In the realm of DRAM technologies this study investigates RowHammer vulnerabilities in DDR4 DRAM memory across various manufacturers, employing advanced multi-sided fault injection techniques to impose attack strategies directly on physical memory rows. Our novel approach, diverging from traditional victim-focused methods, involves strategically allocating virtual memory rows to their physical counterparts for more potent attacks. These attacks, exploiting the inherent weaknesses in DRAM design, are capable of inducing bit flips in a controlled manner to undermine system integrity. We employed a strategy that compromised system integrity through a nuanced approach of targeting rows situated at a distance of two rows …

Targeted Drug Delivery: Investigating Protein Corona Behavior, Atharva Markale

Theses

Due to high specificity and less toxicity, nanoparticles have become promising for targeted drug delivery against cancer, although they face challenges when they enter the bloodstream, making their behavior unpredictable. The deposition of proteins on nanoparticles, the protein corona, changes their biosignature, affecting their circulation, drug release potency, targeting ability, and immunogenicity. The continuous exchange of protein layers on a nanoscale is complex to analyze.

Nanoparticle tracking analysis (NTA) is a method to characterize nanoparticles in blood plasma by combining principles of light scattering microscopy and Brownian motion. In this work, time-dependent experiments with plasma were conducted to analyze the …

Electrochemical Nitrate Reduction To Ammonia On Cu Based Nanoparticles Using Quantum Mechanical Simulations, Kathan Bhavin Shukla

Theses

Nitrate reduction to ammonia (NRA) is critical for environmental remediation and energy conservation, as it can remove harmful nitrate (NO₃^-) from water sources while producing usable ammonia (NH₃). Cu represents one of the most promising non-noble-metal NRA electrocatalysts. However, the intrinsic catalytic activity of Cu facets and their influence under different pH conditions remain unclear, particularly in the presence of ions commonly found in wastewater such as Cl^-, Na⁺, Mg²⁺, and Ca²⁺. Using density functional theory (DFT) calculations, we evaluated the nitrate reduction to ammonia (NRA) pathways …