Effects Of Processing Parameters On Kerf Cutting Quality Following Abrasive Waterjet Slotting Of Ti-6al-4v/Cfrp/Al7075 Stacks, Abeer Eisa, Abdulaziz Elshinawi, Mohamed Fattouh

Journal of Engineering Research

Abrasive water jet machining (AWJM) presents a viable substitute to traditional machining methods for cutting straight kerfs in Ti-6Al-4V/CFRP/Al7075 composite stacks. This study investigated the influences of various process settings, namely the hydraulic pressure (P), traverse speed (V), and stand-off distance (SOD) on kerf characteristics, including the kerf geometry (W_k), taper angle (θ_K), roughness (R_a), and the material removal (MRR). The metal plates, including Ti-6Al-4V and Al7075, exhibited a positive taper angle, whereas the CFRP composite plate revealed a negative taper angle across …

A Computational Fluid Dynamics Approach To Analyze The Virtual Impactor In Pneumatic Aerosol Jet Printing, Akashita Sareen

Theses, Dissertations and Capstones

Aerosol jet printing (AJP) is a 3D printing, advanced manufacturing process that generates an aerosol mist appropriate for fine printing small, low-volume electronic parts. The pneumatic aerosol jet printing technology’s virtual impactor is the focus of this study. In this technology, high velocity nitrogen gas aerosolizes various inks in the atomizer. The aerosolized stream of ink is then transported to a virtual impactor (VI) to become dense and concentrated as it begins to enter the deposition head for high precision electronics printing. AJP faces challenges in large-scale adoption due to challenges related to overspray, instability, ink clogging etc. There is …

Improving The Reliability Of Parts Produced Via Laser Powder Bed Fusion Through A Data-Driven Geometry Optimization Methodology, Federico Venturi

Mechanical and Aerospace Engineering Dissertations - Archive

This research aims to qualify the effect of design geometry on quality metrics of additively manufactured (AM) components that define reliability. Through the use of a novel methodology to characterize these quality metrics, AM components are inspected for the presence of defects such as surface roughness notches and porosity. These directly hinder the high-cycle fatigue characteristics demonstrated through the Kitagawa-Takahashi diagram and the El-Haddad model. By demonstrating the effect of geometry through a designed experiment and the adoption of the Murakami square root area parameter and Arola-Ramulu model, the improvement to fatigue life can be quantified. Incorporating this data into …

Experimental And Numerical Modelling-Based Optimization Of Additive Manufacturing Processes, Vishnu V. Ganesan

Mechanical and Aerospace Engineering Dissertations - Archive

ABSTRACT

Experimental and Numerical Modeling-Based Optimization of Additive Manufacturing Processes

Vishnu V Ganesan, Ph.D.

The University of Texas at Arlington, 2025

Supervising Professor: Dr. Ankur Jain

Experimental and numerical modeling play a pivotal role in advancing additive manufacturing technologies by enabling a deeper understanding of complex, multi-physics processes that govern part quality, performance, and reliability. These manufacturing techniques—ranging from Powder Bed Fusion (PBF) and Material Extrusion (MEX) to Automated Fiber Placement (AFP)—involve tightly coupled thermal, mechanical, and material phenomena that are challenging to capture through empirical observation alone. Experimental methods offer critical validation and insights into real-world behavior, while numerical …

Multi-Objective Design Optimization Of Hypoid Geared Rotor Systems, Xinqi Wei

Mechanical and Aerospace Engineering Dissertations - Archive

Hypoid gears represent one of the most generalized and complex forms of gearing, widely used for power transmission of skew shafts in vehicles, aviation, and marine transmission applications. Optimizing their performance remains challenging due to the complex tooth surface and contact behavior. Specifically, the design parameters of the tooth surface are multi-scale, interdependent, and subject to strong constraints, leading to strong nonlinearity and an ill-conditioned Jacobian matrix in the parameter identification model. Moreover, feasible and insensitive contact conditions are difficult to constrain due to the inherent complexity of local conjugate contact between the meshing surfaces. These challenges significantly increase optimization …

Enhancing The Mechanical Properties Of Sla 3d-Printed Bio-Resin From Linseed Oil Using Cellulose And Lignin Biopolymers, Chukwunonso A. Ikedionu

College of Graduate Studies: Theses & Dissertations

Abstract

This research explores the development of bio resin from linseed oil by the process of epoxidation and acrylation to produce acrylated epoxidized linseed oil (AELO). Lignin and cellulose biopolymers were added as reinforcement at varying weight fractions of 1 wt.%, 2.5 wt.%, and 5 wt.%, and their mechanical performance was compared against pure AELO. The formulations were printed using an Elegoo SLA 3D printer to create standardized test specimens like tensile bars, compression cylinders, and hardness blocks, which were all prepared according to the ASTM testing standard.

The results indicate that reinforcement effects depend on both filler type and …

Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu

Chemistry Faculty Research & Creative Works

Bone tissue engineering (BTE) aims to repair bone defects using biocompatible materials with tailored geometries and pore structures, providing appropriate mechanical support and control over biodegradation kinetics to promote bone growth. In this study, we utilized digital light processing (DLP) 3D printing to fabricate scaffolds with varying pore sizes using polymer–ceramic slurries composed of polylactic acid (PLA) as the main polymer matrix, incorporated with hydroxyapatite (HA) and bioactive borate glass (BBG) at various ratios. We studied the effect of composition on rheological behavior, printability, mechanical properties, bioactivity, degradation rate, and biocompatibility. While HA increased viscosity and reduced printing accuracy, it …

Study On Field Emission Characteristics Of Carbon Nanotube Arrays Patterned Via Laser Welding Of Dissimilar Materials, Hung Yin Tsai, Yi Hung Chen, Kuan Ching Wang, Paul W. Leu, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper describes a new method of growing carbon nanotube (CNT) arrays using laser welding of a catalyst metal onto the surface of a quartz substrate, followed by CNT growth through the chemical vapor deposition (CVD) process. A major advantage of this method is its ability to pattern the catalyst before growing the CNTs, thus allowing for the formation of CNTs at specific locations. The laser pre-treatment method minimized structural damage to CNTs in comparison to the laser post-processing method, achieving a lower ID/IG value of 0.72 in Raman spectroscopy analysis. Using hexagonally patterned CNT arrays on quartz, we achieve …

Effect Of Alloying Additions On Austenite Refinement In Nickel-Alloyed Ductile Cast Irons, Adnan Adib Aahamed

College of Graduate Studies: Theses & Dissertations

The benefits associated with the application of ductile irons are significantly attributed to the control of microstructures, with refinement of austenitic matrix during solidification playing a significant role. Nickel alloyed ductile irons are attractive due to their potential for high ductility and suitability for potential high-temperature applications with stable austenitic microstructure. Refinement of austenite grain structure is thus important to enhance the mechanical properties of the alloyed ductile iron. This research investigates the impact of in-mold additions of different alloying elements on the austenite morphology and grain refinement of nickel-alloyed ductile iron along with the associated mechanical properties. A hypoeutectic …

Molecular Dynamics-Based Two-Dimensional Simulation Of Powder Bed Additive Manufacturing Process For Unimodal And Bimodal Systems, Yeasir Mohammad Akib, Ehsan Marzbanrad, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

The trend of adapting powder bed fusion (PBF) for product manufacturing continues to grow as this process is highly capable of producing functional 3D components with micro-scale precision. The powder bed’s properties (e.g., powder packing, material properties, flowability, etc.) and thermal energy deposition heavily influence the build quality in the PBF process. The packing density in the powder bed dictates the bulk powder behavior and in-process performance and, therefore, significantly impacts the mechanical and physical properties of the printed components. Numerical modeling of the powder bed process helps to understand the powder spreading process and predict experimental outcomes. A two-dimensional …

Influence Of Alloy Composition On The Process Robustness Of Steels Consolidated Via Laser-Directed Energy Deposition, Jonathan Kelley

Masters Theses

"To ensure consistent quality of additively manufactured parts, it is advantageous to identify alloys which can meet performance criteria while being robust to process variations. Toward this end, this work investigated the effect of alloy composition on the robustness of steels consolidated via laser-directed energy deposition (L-DED). Ultra-high-strength low-alloy steel (UHSLA) and pure iron powders were mixed in-situ to produce 10 compositions containing 10-100% UHSLA by mass. JMatPro material simulations roughly predicted phases and mechanical properties. Two sets of experiments were used to evaluate the sensitivity of as-built hardness (all 10 compositions) and tensile properties (5 select compositions) to process …

Transient Thermal Finite Element Simulation For Process Modeling In Wire Arc Additive Manufacturing, Satya Sai Kumar Pilli

Dissertations, Master's Theses and Master's Reports

This thesis presents the development of a transient thermal framework for Wire Arc Additive Manufacturing (WAAM) created using ANSYS Workbench. This study aims to understand the inherent properties and thermal behavior of WAAM by using the Finite Element (FE) simulation technique to reduce the need for experiments. Specifically, the transient thermal WAAM simulation framework uses the heat source Goldak model to understand the thermal behavior for a given voltage, initial temperature, and travel speed during the process to predict process temperature. The outcomes of this thesis aim to significantly decrease material waste and repetitive experiments and accelerate production process design …

Ai-Powered Image-Based Assessment Of Pressure Injuries Using You Only Look Once (Yolo) Version 8 Models, Mehedi Hasan Tusar, Fateme Fayyazbakhsh, Niloofar Zendehdel, Eduard Mochalin, Igor Melnychuk, Lisa Gould, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Objective: The primary objective of this study is to enhance the detection and staging of pressure injuries using machine learning capabilities for precise image analysis. This study explores the application of the You Only Look Once version 8 (YOLOv8) deep learning model for pressure injury staging. Approach: We prepared a high-quality, publicly available dataset to evaluate different variants of YOLOv8 (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and five optimizers (Adam, AdamW, NAdam, RAdam, and stochastic gradient descent) to determine the most effective configuration. We followed a simulation-based research approach, which is an extension of the Consolidated Standards of Reporting Trials …

Hands-Free Uav Control: Real-Time Eye Movement Detection Using Eog And Lstm Networks, Niloofar Zendehdel, Khosro Ghorbani Zadeh, Haodong Chen, Yun Seong Song, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Industry 4.0 has created a growing need for effective human-robot collaboration (HRC). As robots and humans work more closely together, efficient communication becomes essential for coordinating their actions seamlessly. While speech may seem like the obvious choice for communication, noisy factory environments can render it impractical. Additionally, workers often have their hands occupied with assembly tasks, making hand-controlled interfaces less practical for controlling robots. To address these challenges, this paper presents a novel, hands-free method for robot control using electrooculography (EOG) signals–specifically, eye movements and blinks–with unmanned aerial vehicles (UAVs) used as the demonstration platform. We developed a real-time system …

Solid Loading Effects On The Assembly Of Alumina Particles In Aqueous Suspensions Due To The Dielectrophoretic Forces, Sivakumar Chithamallu, Rohan Kiran Parai, Dipankar Ghosh

Mechanical & Aerospace Engineering Faculty Publications

Current work in situ investigated the mechanisms of the interparticle interactions that evolve in dilute aqueous alumina suspensions subjected to alternating current (AC) electric field and the effects of solid loading of suspensions. The interactions were investigated for alumina suspension compositions in the 0.005‒0.04 vol.% solid loading range. Field‐induced interactions evolved via particle motion and dynamic assembly, chain formation parallel to the direction of the applied field and chain growth, chain cross‐linking, and chain thickening. The evolution time of each of those events was rapidly accelerated with solid loading. While chain cross‐linking was negligible in low solid loading suspensions, a …

In-Situ Characterization Of Damage Mechanisms In Ceramic Matrix Composites, Cle' E. Sanchez

Theses and Dissertations--Mechanical and Aerospace Engineering

Ceramic Matrix Composites have many advantages, attracting the nuclear, aerospace, and automotive industries with their high heat stability, strength, and oxidation resistance. However, challenges are presented when machining these materials due to the brittle properties and complicated microstructure. The objective of this project was to identify damage mechanisms that occur when a CMC is orthogonally machined and the cutting mechanics are observed in-situ, followed by post-cut characterization of the as-machined surface morphology. In this analysis, the main variable is the feed rate, which can influence the damage mechanisms, such as matrix failure (matrix cracking) or fiber failure (pullout). Through this …

In-Situ Informed Modeling And Characterization Of Friction And Built-Up Edge In Machining Of Aerospace Alloys, Avery Hartley

Theses and Dissertations--Mechanical and Aerospace Engineering

Machining is by no means a new manufacturing process. However, it is separated from other traditional deformation processes by its extreme temperatures and strain rates. The function and life of a multitude of products and mechanical components are dependent on the material properties induced by changing the surface through machining. Furthermore, the tools used within machining are often expensive and material reserves are sparse. The understanding the mechanics of the machining process, especially related to the friction of the tool and workpiece, helps to further the life of tools and parts to minimize economic and environmental impact.

Current friction modeling …

Machining-Induced Residual Stress Modeling Using Physics-Informed Neural Networks, Md Mehedi Hasan

Theses and Dissertations--Mechanical and Aerospace Engineering

Process-induced residual stress (RS) plays a critical role in determining the structural integrity, fatigue life, corrosion resistance, and dimensional stability of manufactured components. Tensile residual stress can be harmful to the machined workpiece by lowering fatigue strength, while compressive residual stress helps to prevent such issues. Therefore, accurate prediction and control of machining-induced residual stresses are essential for optimizing manufacturing processes and enhancing component performance. However, existing modeling approaches—empirical, analytical, and numerical—often have limited predictive accuracy, demand extensive calibration, or involve high computational costs. Traditional finite element analysis (FEA) provides modeling insights but is constrained by its high computational cost …

Integrated Compliant Structure For A Hand Exoskeleton, Tristan R. Koopman

Honors Undergraduate Theses

This thesis presents the design and prototyping of a wearable hand exoskeleton that integrates a flexible structural framework to assist with hand movement while maintaining comfort and anatomical conformity. The goal was to create a device that supports tendon-driven actuation through a compliant structure, combining elements of rigidity and flexibility to match the natural geometry and motion of the human hand. Traditional hand exoskeletons often trade off motion for structure or vice versa. This project aims to bridge that gap with a hybrid compliant design that balances flexibility and support. The design process followed an iterative approach involving rapid prototyping …

Comparison Of Cnn And Lstm Networks On Human Intention Prediction In Physical Human-Robot Interactions, Khosro Ghorbani Zadeh, Niloofar Zendehdel, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Ming-Chuan Leu, Yun Seong Song

Psychological Science Faculty Research & Creative Works

Advancements in robotics and AI have increased the demand for interactive robots in healthcare and assistive applications. However, ensuring safe and effective physical human-robot interactions (pHRIs) remains challenging due to the sophistication of human motor communication and intent recognition. Traditional physics-based models struggle to capture the dynamic nature of human force interactions, limiting robot adaptability. To address these limitations, neural networks (NNs) have been explored for force-movement intention prediction. While multi-layer perceptron (MLP) networks show potential, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks effectively model sequential dependencies, while Convolutional Neural Networks (CNNs) enhance spatial feature …