Engineering Commons^™

Investigation Of Mechanical Performance And Metallurgical Characteristics Of Titanium Grade 2 Tube-To-Tubesheet Joints, Ahmad Hussein Al Tamimi

Thesis/ Dissertation Defenses

Tube-to-tubesheet joints, an integral component of shell and tube heat exchangers, are known for their vulnerability to leakage problems at the joint region due to mechanical and chemical factors coupled with fabrication techniques involved in creating these joints. An ideal condition of manufacturing process parameters and geometrical variables required to produce tube-to-tubesheet joints is highly desired. One of the most promising candidate materials to fabricate tube-to-tubesheet joints is titanium or titanium alloys due to their excellent strength and resistance to corrosion. The present study investigates the structural integrity of three categories of Titanium Grade 2 based tube-to-tubesheet joints comprising of …

Thermo-Chemical Recycling Of Waste Plastics Containing Halogenated Polymers (Br−, Cl−, F−) Using Potential Additives, Mohamed Shafi

Thesis/ Dissertation Defenses

Plastic waste handling is a daunting task due to the presence of halogenated polymers, specifically those cluttered with bromine (Br), chlorine (Cl), and fluorine (F). Halogenated plastics can be mixed with other polymers in the general plastic waste, particularly in the recycling stream. Brominated flame retardants (BFRs) are mainly present in e-waste and from the use of flame retardants in household items, textiles, and furniture. Plastics from discarded electronics often contain significant levels of bromine and chlorine, predominantly from flame retardants and plasticizers. Being the most deployed thermoplastic worldwide, waste polyvinyl chloride (PVC) generation is expected to increase by about …

Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …

Synthesis Of Sustainable Self-Foaming Glass Ceramics Using Waste Glass And Aluminium Dross, Abba Musa Hassan

Student Works (2020-2029)

The growing global demand for sustainable materials has driven extensive research into lightweight insulating materials, such as self-foaming glass ceramics (SFGCs), which align closely with the principles of a circular economy. While the alkali activation of aluminosilicates offers an environmentally friendly alternative to conventional, energy-intensive industrial methods for producing glass-based foams, current approaches often depend on synthetic foaming agents, high-speed agitation, and elevated sintering temperatures. These factors adversely affect slurry rheology, resulting in suboptimal microstructures, reduced mechanical strength, increased production costs, and negative environmental impacts. This study contributes to the advancement of the field by developing eco-friendly SFGCs using soda-lime …

Potential Use Of Waste-Derived Products In Producing Geopolymer Sorbents, Mariam Mohammed Al Nuaimi

Thesis/ Dissertation Defenses

Environmental sustainability and the circular economy are central to addressing global challenges in waste management and water pollution. This study investigates the synthesis and performance of geopolymers derived from industrial wastes, including fly ash, waste glass, silt deposits, and carbide lime, as adsorbents for methylene blue (MB) dye removal from water. Geopolymers were engineered under varying particle sizes, NaOH addition methods, and curing temperatures. Their physicochemical and microstructural properties were thoroughly characterized via scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray fluorescence (XRF), Fourier Transform Infrared Spectroscopy (FTIR), andparticle size analysis (PSA). Among the tested formulations, the sodium silicate–sodium hydroxide …

Evolving Towards Efficient Technologies In Power Systems: The Paradigm Of Energy Internet Survey, Dina Emad, Omar Abdel-Rahim, Tanemasa Asano, Sobhy M. Abdelkader

Mansoura Engineering Journal

The Energy Internet represents a significant advancement in the modernization and automation of electricity systems, offering a framework for future smart grids where all electrical devices are interconnected through energy routers. This system integrates advanced power electronics, information technology, and smart control technologies, enabling the accommodation of diverse energy sources and storage devices. With its bidirectional energy flow and sharing capabilities, the Energy Internet holds great promise for the future. However, several challenges must be addressed to fully realize this potential. This review provides an overview of the Energy Internet framework and explores key challenges, particularly those related to energy …

A Low-Cost Fault-Ride-Through Strategy For Electric Vehicle Inverters Using Four-Switch Topology, Ehab Bayoumi

Mechanical Engineering

This paper presents a fault-tolerant control strategy that dynamically reconfigures the proposed system, and the inverter leg with a fault is isolated through a MOSFET-based clamping branch. With the use of a modified Vector Control (VC) and Pulse-Width Modulation (PWM) technique, the remaining two phases can continue operating. MATLAB/Simulink is used to create a thorough simulation model that examines various fault scenarios and evaluates how well the control process adjusts to each one. The obtained findings demonstrate that, in the event of a fault, the system can maintain accurate speed regulation, maintain a tolerable current balance, and deliver steady torque. …

Flash Effect Is Diminished By Daily Fractionation Of Electron Rt In Mouse Skin, Aleksandra Ilina, William S. Thomas, Xu Cao, Matthew S. Reed, Kendall Jarvis, Albert Van Der Kogel, Nathaniel Van Asselt, Wesley S. Culberson, Brian W. Pogue

Dartmouth Scholarship

Objective. While FLASH radiotherapy is known to reduce skin damage in vivo from ultra-high dose rate (UHDR) irradiation relative to conventional dose rates (CDR), it is not clear whether this sparing is preserved when delivered as fractionated. This study was designed to directly assess whether three daily fractions would maintain the sparing effects in murine leg models and preserve the murine skin sparing with single fraction treatments. Approach. C57Bl/6j female mice were irradiated with 9 MeV UHDR and CDR beams from a FLASH-capable Mobetron system, in a dose escalation study with doses ranging from single dose 22–30 Gy in a …

Blockchain In Smart Cities, Shamma Alnuaimi

Thesis/ Dissertation Defenses

This thesis explores the integration of blockchain technology with smart cities to enhance efficiency, transparency, and reliability. The basic principles of blockchain, its layered architecture, consensus protocols, and decentralized security are first reviewed. The thesis then highlights how blockchain features can be integrated with urban and energy systems. The research focuses on how token economy can be used with smart cities to promote individuals to engage in desired behaviors by employing blockchain-based incentive mechanisms that can encourage responsible energy consumption.

The FairChain test system was developed and tested using blockchain technology and the Internet of Things (IoT) to demonstrate the …

A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani

Turkish Journal of Electrical Engineering and Computer Sciences

Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …

Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed

Turkish Journal of Electrical Engineering and Computer Sciences

Spoken digit recognition (SDR), a type of supervised automatic speech recognition, is essential for various human-machine interaction applications, including banking operations, dialing systems, price extraction, and airline reservation systems. However, designing an effective SDR system presents several challenges, such as developing labeled audio data, selecting appropriate feature extraction methods, and creating high-performance models. To overcome these challenges, a novel approach for robust spoken digit recognition using an integrated log spectrogram convolutional neural network (ILS-CNN) has been proposed. The proposed work presents an efficient SDR method by taking advantage of a log spectrogram layer directly within the neural network to enhance …

Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev

Turkish Journal of Electrical Engineering and Computer Sciences

Monitoring the condition of engineering objects is one of the urgent tasks of industry, construction, and transport infrastructure. This article describes a system for condition monitoring and diagnostics of rail tracks in real time. Compared with other similar studies, the proposed system has the advantages of compactness, usability, scalability and versatility of application. The proposed monitoring system is based on an Nvidia Jetson Nano embedded computing board and also includes inertial sensor modules, a microphone, a geolocation module, communication modules, an SSD storage device, and a battery. The prototype of the diagnostic module is a portable device that can be …

Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings, Onur Özel, Ali̇ Rifat Boynueğri̇, Hayri̇ Yi̇ği̇t, Burak Tekgün

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both …

Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power …

Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len

Turkish Journal of Electrical Engineering and Computer Sciences

A modernist technique, reconfigurable intelligent surface (RIS) provides outstanding signal reflection and amplification, making it highly valuable for upcoming communication systems. Besides, a major contributor is index modulation (IM), attaining superior spectral and energy efficiency, and achieving hardware sufficiency. The primary and novel contribution of this work is the derivation of a highly accurate, closed-form approximate expression for the average bit error rate (ABER) of an orthogonal frequency division multiplexing (OFDM)-IM system operating in the complex and challenging environment characterized by joint transmitter/receiver (Tx/Rx) in-phase and quadrature phase imbalance (IQI) and Weibull fading. This essential analytical achievement is facilitated by …

Towards A Generalized And Optimized Apriori Approach, Artem Abdikov

Master's Theses

Apriori is a machine learning algorithm developed in 1994 by R. Agrawal and R. Srikant for association rule mining purposes. This family of algorithms takes transactional data and analyzes relationships between variables in large datasets. The typical output of such algorithms is a prediction that if users choose item X, it is highly likely that they will also choose item Y. Apriori is known to be a robust algorithm and is used by many large companies in order to analyze user tendencies and even make recommendations. Although Apriori is a powerful algorithm, its original implementation is known to have limitations, …

Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …

Exploring The Link Between Emotional States And Coding Task Quality: A Pilot Study, Aquib Reshad, Valentina Nino, Maria Valero, Adriane Randolph, Yang Shi

Faculty Articles

Emotions play a crucial role in shaping cognitive performance, yet their influence on programing remains understudied. This pilot study investigates the relationship between emotional states and coding task quality. Ten participants completed a programing task while their brain activity was recorded using electroencephalography (EEG), with frontal alpha asymmetry (FAI) applied as a neural marker of emotional valence. Emotional self-reports were collected using the Scale of Positive and Negative Experience (SPANE), and coding quality was evaluated through a structured rubric. Preliminary findings indicate a potential association between FAI and coding performance, whereas self-reported affect showed weaker or inconsistent patterns. Given the …

Predicting Simulation Times For Multiphase Thermal-Hydraulic Models, Andrew Yule, Andrew Taylor

SMU Data Science Review

Addressing the challenge of computationally intensive OLGA

simulations in the oil and gas industry, a machine learning framework is

developed for accurate runtime prediction. A specialized feature extraction

pipeline identifies key parameters—such as simulation time, time step,

number of branches, and section count—from OLGA input files that serve as

high-impact predictors. Multiple predictive models, including regression,

tree-based ensembles, and neural networks, are implemented to validate

accuracy and robustness. Results reveal that prioritizing simulations based on

predicted runtimes optimizes licensing resources and reduces operational

costs, making real-time scheduling more efficient. This research demonstrates

the effectiveness of data-driven runtime prediction in enhancing …

Ai-Driven Optimization Of Wind Energy Distribution In Texas Using Multi-Agent Reinforcement Learning, Waleed Amer, Owolabi Oluwadamilola, Bassey Ogbonnaya

SMU Data Science Review

Abstract. The integration of large-scale wind power into modern electrical grids presents persistent challenges due to variability, curtailment, and compliance with operational constraints. This study proposes a multi-agent reinforcement learning (MARL) framework for optimizing wind energy distribution within the Texas power grid. The system employs three specialized agents—managing wind curtailment, storage utilization, and load adjustments—to collaboratively balance supply and demand under dynamic grid conditions. Using historical operational data from the Electric Reliability Council of Texas (ERCOT), the framework was trained and evaluated on a range of scenarios encompassing both typical and extreme operating conditions. Results demonstrate substantial performance improvements compared …

Development Of Composite Membranes And Nanofluid Absorbents Incorporating Surface-Functionalized Nanoparticles For Enhanced Co₂ Absorption In Gas–Liquid Membrane Contactors, Riya Ahammed Labeeb

Thesis/ Dissertation Defenses

Natural gas sweetening demands the efficient removal of CO₂ to enhance heating value and prevent equipment corrosion. Gas–liquid membrane contactors (GLMCs) have garnered attention as promising solutions to traditional separation methods due to their modularity, high interfacial area, and energy efficiency. Nonetheless, they suffer from some serious challenges such as membrane wetting, while absorbents either exhibit low absorption capacity or high energy demands and corrosion. This work addresses these limitations through two complementary strategies. In the first, ZnO nanoparticles were hydrophobically functionalised and incorporated into polymer matrices to fabricate composite membranes with superior hydrophobicity and reduced pore wetting. In the …

Bio-Corrosion Studies On Novel Zr‑Co‑Ti Based Metallic Glass Alloys For Biomedical Implant Applications, Shubhra Shitole

Thesis/ Dissertation Defenses

The relentless pursuit of advanced biomaterials that synergistically combine high mechanical strength, exceptional corrosion resistance, and inherent biocompatibility is critical for next-generation medical implants. This research addresses this challenge through the development and multi-faceted evaluation of a novel library of Zr-Co-Ti-based metallic glasses (MGs); Zr₆₀Co₃₀Ti₁₀, Zr₅₅Co₃₅Ti₁₀, and Zr₅₀Co₄₀Ti₁₀, fabricated via melt-spinning. The alloys were confirmed to be fully amorphous by X-ray diffraction (XRD), a structure underpinned by exceptional thermal stability, with the Zr60 composition exhibiting a larger supercooled liquid region (Δ𝑇𝑥) of …

Durability Of Basalt Fiber-Reinforced Polymer Bars In Moist Concrete Under Sustained Load, Osama Ahmed

Thesis/ Dissertation Defenses

This thesis is concerned with the long-term durability of basalt fiber-reinforced polymer (BFRP) bars embedded in moist concrete. The study focuses on the combined effects of exposure duration, elevated temperature, and sustained tensile stress, which together influence the mechanical and chemical stability of BFRP reinforcement in aggressive environments. The main objective is to evaluate the degradation mechanisms of BFRP bars subjected to coupled hygrothermal and mechanical conditions and to develop a predictive durability model capable of estimating service life under realistic climate scenarios. Concrete-encased BFRP bars were conditioned at three temperatures (20, 40, and 60°C), three durations (3, 6, and …

Diffog: Differentiable Policy Trajectory Optimization With Generalizability, Zhengtong Xu, Zichen Miao, Qiang Qiu, Zhe Zhang, Yu She

School of Industrial Engineering Faculty Publications

Imitation-learning-based visuomotor policies excel at manipulation tasks but often produce suboptimal action trajectories compared to model-based methods. Directly mapping camera data to actions via neural networks can result in jerky motions and difficulties in meeting critical constraints, compromising safety and robustness in real-world deployment. For tasks that require high robustness or strict adherence to constraints, ensuring trajectory quality is crucial. However, the lack of interpretability in neural networks makes it challenging to generate constraint-compliant actions in a controlled manner. This article introduces differentiable policy trajectory optimization with generalizability (DiffOG), a learning-based trajectory optimization framework designed to enhance visuomotor policies. By …

Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud

Faculty Articles

Hybrid energy storage systems (HESS) integrating batteries and supercapacitors offer a promising solution to overcome the limitations of battery-only architectures in electric vehicles (EVs). By leveraging the high energy density of batteries and the high power density of supercapacitors, HESS can enhance power delivery, improve energy efficiency, and extend battery lifespan. The effectiveness of HESS, however, is largely determined by the energy management system (EMS) that coordinates power flow under dynamic driving conditions. Unlike existing reviews, this work addresses common gaps in the literature, including the lack of industrial energy storage component examples, limited coverage of recently developed EMS strategies, …

Assessment Of Traffic Related Air Pollution Effects On Indoor Air Quality In Educational Buildings, Ahmed Gouda Mohamed, Mohamed Sherif Dr., Fahad Alqahtani Dr., Yousif Deeb Eng.

Civil Engineering

This study assesses the impact of traffic-related air pollution (TRAP) on indoor air quality (IAQ) within a Riyadh school. The main objectives are to pinpoint factors influencing IAQ and to evaluate the effectiveness of existing ventilation and filtration systems. Air quality Egg sensors monitored nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter (PM1.0, PM2.5, PM10) levels both indoors and outdoors over 30 days. Findings revealed average indoor PM2.5 and PM10 concentrations of 14.09 µg/m3 and 18.15 µg/m3, respectively, while outdoor concentrations averaged 20.63 µg/m3 and 27.88 µg/m3. A strong positive correlation was observed between indoor and outdoor PM levels, …

Effect Of Pore Structure On Void Formation In Lotus Type Porous Cu/Solder Joints, Jin-Kwan Lee, Keun-Soo Kim, Jae-Ho Shin, Seung-Min Cho, Sung Yi, Sang-Wook Kim, Soong-Keun Hyun

Mechanical and Materials Engineering Faculty Publications and Presentations

Void formation in solder joints is a critical reliability challenge in high-power electronics, as it degrades thermal dissipation and mechanical integrity. This study investigates a novel structural approach to mitigate this issue. The influence of an uni-directional porous structure in lotus-type porous Cu (Louts Cu) on void formation in solder joints was investigated. All pores in lotus Cu were infiltrated with SAC305 (Sn–3.0Ag–0.5Cu) solder paste. Then reflow soldering was performed under three different atmospheric conditions: air, nitrogen, and vacuum. The microstructure and void fraction were characterized. The shear strength was evaluated. The shear strength of Louts Cu joint was slightly …

2025 - The Sixth Annual Fall Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Fall 2025 Symposium of Student Scholars, held in November 2025. Includes abstracts from the presentations and posters.

Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty

Electrical and Computer Engineering Faculty Publications and Presentations

There are several essential elements in project construction management to be studied appropriately, and priority to these elements, such as cost and duration, is predominantly interesting to be investigated. In this research, the duration of field canal improvement projects (DFCIP) was predicted using two relatively new machine learning (ML) models - the Multivariate Adaptive Regression Spline (MARS) and Extreme Learning Machine (ELM). The targeted DFCIP was calculated using other dependent parameters, such as the length of the pipe, years of construction, the geographical zone of the network, the supplied area with water, and finally the actual cost of the field …

Yolo-Based Marine Search And Rescue Using Uav Multi-Dataset In Challenging Weather Conditions, Aysha Alshebli

Thesis/ Dissertation Defenses

Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.

Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …