A Structural Evaluation And Design Optimization Of A Tow Bar For Disabled Snowmobiles, David M. Pevic

Masters Theses

Snowmobile tow bars are devices used to rigidly connect two snowmobiles, such that a disabled snowmobile can be recovered from a remote location with a working snowmobile. These devices, however, are not widely used or readily available. An existing tow bar design was evaluated and redesigned to improve its structural capacity and performance. This evaluation provided a baseline to quantify improvement and included Finite Element Analysis (FEA), Design Failure Mode and Effect Analysis (DFMEA), and Design for Assembly analysis (DFA). A review of existing snowmobile tow bar patents was also performed. An updated design was then fabricated and similarly evaluated. …

Investigating The Structure-Property Correlations Of Pyrolyzed Phenolic Resin As A Function Of Degree Of Carbonization, Ivan Gallegos, Vikas Varshney, Josh Kemppainen, Gregory Odegard

Michigan Tech Publications

Carbon-carbon (C/C) composites are attractive materials for high-speed flights and terrestrial atmospheric reentry applications due to their insulating thermal properties, thermal resistance, and high strength-to-weight ratio. It is important to understand the evolving structure-property correlations in these materials during pyrolysis, but the extreme laboratory conditions required to produce C/C composites make it difficult to quantify the properties in situ. This work presents an atomistic modeling methodology to pyrolyze a crosslinked phenolic resin network and track the evolving thermomechanical properties of the skeletal matrix during simulated pyrolysis. First, the crosslinked resin is pyrolyzed and the resulting char yield and mass density …

Processing, Testing, Failure Analysis, And Modeling Of Elementary Natural Fiber-Reinforced Composites, Shuo Sun

All ETDs from UAB

Natural fiber reinforced composites have garnered significant interest as potential substitutes for conventional materials because of their eco-friendly attributes and favorable physical and mechanical properties. Typically, natural fibers undergo chemical treatments to enhance their compatibility with the polymer matrix prior to composite production. However, these treatments primarily affect the surface of the fiber bundles and have a limited impact on the inner elementary fibers within the bundle. This research work introduced a mechanical treatment method for hemp fiber by using an elevated temperature aqueous condition and mechanical force, which broke down the technical fiber bundles into elementary fibers and created …

Lessons In Low-Tech: A Handbook For Sustainable Education, Ceri Almrott, Loann Astorino, Sébastien Bette, Benoit Delinchant, Philippe Fortemps, Ulysse Girard, Paul Hendrick, Sacha Hodencq, Fabian Lecron, Julie Lhuissier, Kévin Loesle, Luis Miguel Lopez Santiago, Santiago Perez Rodriguez, Gauthier Renard, Tatiana Reyes, Virginie Vandenbulcke, John Walsh

Other resources

LT4SUSTAIN, an Erasmus+ funded transnational project, is at the forefront of responding to the increasing awareness of environmental and climate challenges. This awareness, particularly among youth, has led to a demand for social justice. With the coordinated work among six institutions, ranging from higher education institutions to private companies and associations, LT4SUSTAIN aims to raise awareness of Lowtech across society.

LT4SUSTAIN is pioneering a unique approach to technology design. By developing “hackathons” and other “hands-on” events, we are engaging students and industry in a way that improves inclusiveness. Our objective is to equip individuals with the skills to embark on …

Feasibility Study Of A Smart Insole With Triboelectric Energy Harvesters For Early Flatfoot Detection, Mohammad Alghamaz

Mechanical Engineering Theses

This study introduces a self-powered smart insole system designed for real-time monitoring of foot health, with a specific focus on detecting flatfoot conditions. The insole integrates multiple triboelectric energy harvesters strategically positioned to capture electrical signals generated from ground reaction forces during daily activities such as walking, jogging, and running. Proof-of-concept testing was conducted on a single participant under two conditions: a healthy foot and a simulated flatfoot created by reducing the medial arch height by approximately 70\. In the healthy foot trials, the system demonstrated consistent and reliable performance, with negligible electrical output from the medial arch sensor, as …

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 …

A Systems-Based Framework For Product Circularity Assessment, Gisele Bortolaz Guedes, Junwon Ko, Fazleena Badurdeen, I. S. Jawahir, K. C. Morris, Vincenzo Ferrero

Mechanical Engineering Faculty Publications

One of the key aspects of Circular Economy (CE), particularly when focusing on the product level, lies in its emphasis on designing products to facilitate the circulation of resources and maximize value throughout their entire lifecycle. To effectively develop such products an understanding of the characteristics of circular products (CP) is needed. Adopting a systems perspective that considers the total lifecycle and stakeholders involved and recognizing interdependencies among them is essential for identifying factors that characterize CPs. Existing methods for assessing product circularity do not identify all factors that charac- terize CPs and have limitations in the measurement methods proposed, …

Foundational Robotics, Akshit Lunia, Ananya Nagabhushana Rao, Yue Wang

Robotics

This textbook is a product of Co-DREAM OER (Collaborative Development of Robotics, Mechatronics, and Advanced Manufacturing Open Educational Resources), a US Department of Education-funded initiative to develop Open Educational Resource textbooks on robotics, mechatronics, and advanced manufacturing processes. It has been created by a diverse team of scholars and graduate students from across the country and is intended for higher-level robotics courses offered by 4-year undergraduate programs.

Multiobjective Optimal Design Of Hierarchical Control Architectures For Quadcopter Systems: Linear And Hybrid Approaches, Xinhuang Wu

Theses, Dissertations and Capstones

This thesis investigates the design of many-objective optimal controllers for quadcopter unmanned aerial vehicles (UAVs), focusing on both linear and hybrid control structures. In Chapter 2, a multi-input–multi-output (MIMO) optimal control system is developed for a six-degree-of-freedom UAV actuated by four brushless DC motors. The UAV dynamics are first derived and linearized around an operating point, and then organized into a three-loop nested control structure. The outer loop computes the roll and pitch angles required to maneuver the vehicle in the global X and Y directions, the middle loop regulates attitude and altitude, and the inner loop controls the angular …

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 …

Stress Analysis Of Anisotropic Inclusion Problems Using Complex Variables, Liming Chen

Mechanical and Aerospace Engineering Dissertations - Archive

This research presents an analytical framework for determining stress fields in an elastic medium containing a circular anisotropic inclusion embedded in an infinitely extended isotropic matrix subjected to far-field uniform stresses. Stress distributions within both the inclusion and the matrix are described using classical stress functions, widely employed in two-dimensional elasticity theory.

To manage the complexity of the mathematical derivations, symbolic computation software (Mathematica) is used to streamline the analysis and obtain closed-form solutions. This approach overcomes traditional computational barriers that have limited the practical application of complex variable methods (CVM) in elasticity.

The methodology builds upon the foundational work …

Design Strategy For Hybrid Thrust Air Bearings: Comparative Analysis Of Rigid Vs. Foil Bearings Considering Optimum Taper Angle And Orifice Location With Experimental Validation, Ehiremen Ebewele

Mechanical and Aerospace Engineering Dissertations - Archive

Gas foil thrust bearings (GFTBs) are contactless bearings that offer advantages such as lightweight construction and the ability to accommodate misalignments and geometric irregularities. However, their load capacity is lower than rigid or magnetic bearings. The structure and geometry of the foil significantly influence GFTB performance. The taper-flat design is the most used configuration due to its effectiveness and ease of implementation. Key parameters in designing this geometry include taper ratio, taper height, orifice size, and orifice location. These parameters must be optimized alongside manufacturing constraints to produce an effective GFTB. This study presents a design optimization investigation of various …

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 …

Intelligent Microfluidic Systems For Precision Manipulation And Real-Time Recognition Via Dielectrophoresis And Deep Learning, Negar Danesh

Mechanical and Aerospace Engineering Dissertations - Archive

This dissertation introduces intelligent microfluidic platforms by combining advanced DEP-based manipulation with real-time visual feedback. A DEP device featuring circular corral traps and dual-plane electrodes enables precise submicron particle trapping, high-resolution particle separation, and cell-particle co-assembly. Simulations and experiments confirm enhanced electric field control and stable confinement. To enable adaptive operation in EWOD systems, a deep learning model (U-Net) was developed for real-time droplet meniscus segmentation. The model achieved 98% accuracy and remained robust under noisy, low-contrast conditions. A live video pipeline was implemented, enabling consistent frame-by-frame feedback for closed-loop control. Together, these innovations establish a foundation for autonomous, high-performance …

Nonlinear Bump Stiffness Model And Its Effect On Structural Stiffness And Nonlinear Rotordynamic Characteristic Of Foil Bearing, Woongeon Lee

Mechanical and Aerospace Engineering Dissertations - Archive

Bump foils are the most widely used in foil bearings, but the behaviors of bump foils are complicated, and their characteristics have been a focus of research for decades. Bump foils are usually modeled as stiffness and damping are accounted for through interactions with shaft eccentricity, loading, shaft speed and excitation frequency. These nonlinear characteristics of the bump foil of radial foil bearings can be observed during both manufacturing and operational processes because of their inherent structural properties such as bump geometry, forming process, age-hardening process and complicated contact behavior with bearing housing. These nonlinear characteristics are one of the …

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 …

Deep Neural Network Models For Heatsink Performance Prediction And Optimization In Single Phase Immersion Cooling: Framework For Future Design Tools And Digital Twin Integration, Braxton J. Smith

Mechanical and Aerospace Engineering Theses - Archive

The rapidly rising computational power of modern computing components combined with the advanced packaging techniques being implemented has resulted in exponentially increasing thermal design powers (TDP) from CPUs and GPUs. Traditional air-cooling methods are approaching their effective cooling limits for many of these components, requiring lower supply air temperatures, higher supply air flowrates, and much larger heatsinks to remain feasible. Transitioning from air-cooling to single-phase immersion cooling offers numerous benefits in thermal performance, data-center size reduction, and energy efficiency. To leverage the merits of immersion cooling, the performance of a given heatsink must be predicted and optimized for best performance …

An Improved Machining Temperature Prediction Model For Aerospace Alloys: Effect Of Cutting Edge Radius And Tool Wear, Jonathan Theraroz, Oguzhan Tuysuz, Julius Schoop

Mechanical Engineering Faculty Publications

Temperature rise during machining impacts the workpiece material properties, residual stresses, surface and sub-surface quality. Experimental, numerical, and analytical methods have been used to predict the temperature fields in the tool, workpiece and chip. Each approach has its limitations: experimental techniques are cumbersome with expensive equipment, and numerical modeling is computationally inefficient. Existing analytical models only consider the effect of wear while ignoring the edge radius, though the latter changes with the flank wear in practice. To address this limitation, this article proposes an improved analytical temperature prediction model for orthogonal machining by introducing discrete linear heat sources on the …

Study On Motion Prediction Analysis Of Large Vessels Entering Kaohsiung Port Second Harbor, Li-Heng Cheng, Hsing-Yu Wang

Journal of Marine Science and Technology–Taiwan

Pilotage is a primary service offered by ports, ensuring the safe passage of entering and exiting vessels. This study applied motion prediction analysis to large vessels navigating the constrained waterways of Kaohsiung Port’s second harbor. To address the needs of pilots and port operators, a simplified planar motion equation was developed that incorporated speed over ground and rate of turn (ROT) as primary variables. The model relied on inputs of limited navigational data, enabling pilots to predict changes in heading and position over time and determine the conditions for safe harbor entry. Vessel paths and turning angles were analyzed to …

Scratching Behavior Of Copper-Niobium Nanolaminates, Matthew C. Peterson

Graduate Research Theses & Dissertations

Metal nanolaminates are known in material science for their unique mechanical properties and high strength due to their interface behavior. Cu/Nb nanolaminates specifically are studied for their uses in electronics due to their good conductivity and superior tensile strength compared to copper conductors, as well as their radiation resistance in radioactive environments. Currently, most molecular dynamics (MD) simulations of Cu/Nb simulations are axially loaded. This work attempts to characterize the scratching behavior of Cu/Nb nanolaminates with varying indenter size, temperature, speed, and layer thickness. The coefficient of friction (CoF), friction force, normal force, and material removal were then compared. A …

Materials Reliability In Direct-To-Chip Cooling: A Systematic Study Of Aluminum Corrosion In Next-Generation Data Center Coolants, Fnu Harish Gangadhara

Mechanical and Aerospace Engineering Theses - Archive

Data centers are rapidly scaling to support artificial intelligence, cloud platforms, and other high-performance workloads, driving a sharp increase in chip and rack power densities that are now approaching, and in some cases surpassing, 50–100 kW per rack. In response, direct-to-chip liquid cooling has become a key enabling technology for managing these extreme thermal loads, yet the durability of materials in contact with the coolant remains a major reliability concern over system lifetimes. Copper has traditionally been used for cold plates and cooling-loop components, but its relatively high cost, mass, and supply-chain uncertainty are motivating a shift toward aluminum as …

Development Of A Design Tool For Tow-Steered Composite Structures With Machine Learning-Assisted Modeling, Bangde Liu

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Fiber-reinforced composites (FRCs) are widely used in aerospace, automotive, and other engineering applications due to their lightweight characteristics and superior mechanical properties. Traditional FRCs employ a fixed fiber orientation in each layer, and while different layup sequences can tailor performance, the mechanical properties remain spatially uniform. Tow-steered composites, which enable fibers to follow curvilinear paths, offer the potential for spatially varying stiffness and strength, improving structural performance.

This dissertation addresses key challenges in modeling and designing tow-steered composite structures, including the lack of commercial design tools, the high computational cost of design optimization, and the need to efficiently evaluate manufacturing …

Evaluation Of The Maneuverability Of An 85m Fishing Trawler (Focusing On Dynamic Stability), Chun-Ki Lee, Su-Hyung Kim

Journal of Marine Science and Technology–Taiwan

Most fishing vessels are less than 100 meters in length, so IMO maneuverability standards do not apply. As a result, studies on the maneuverability of fishing vessels are considerably fewer compared to those on merchant ships. However, with technological advancements, the size of fishing vessels continues to grow, and as more fishermen are on board, accidents could lead to fatal casualties. In response, the authors determined that research on the maneuverability of fishing vessels is urgently needed. Thus, the authors conducted a maneuverability evaluation on a fisheries training vessel with the hull shape of a fishing trawler, 85 meters in …

A Hybrid Image Filtering Approach For Improving Edge Detection Of Riverbed Particles With Complex Textures, Po-Wei Lin, Hsun-Chuan Chan

Journal of Marine Science and Technology–Taiwan

The distribution of particle size in gravel-bed rivers affects the flow condition, sediment transport, and river morphology. However, conventional particle size analysis is laborious and time-consuming. To enhance the efficiency of particle size analysis, image-based methods have been widely explored, but complex particle textures increase the difficulty in identifying particle edges during image analysis. This study develops a filtering approach based on the rolling guidance filter and leverages the differences in grayscale gradients between particle edges and textures to design a guidance image tailored for the rolling guidance filter. This design enables the filter to preserve particle edges while smoothing …

Comparison Of Canopy Materials To Improve The Performance Of Sea Anchors Used For Fishing Operations, Namgu Kim, Su-Hyung Kim, Yoo-Won Lee, Kyung-Jin Ryu

Journal of Marine Science and Technology–Taiwan

Sea anchors used for fishing operations help improve catch rates by stabilizing vessel drift speeds to match tidal or ocean currents. The underwater resistance experienced by a sea anchor's canopy significantly impacts its performance, yet there has been limited research on canopy materials. This study investigates how different canopy materials can enhance sea anchor performance. Specifically, we tested sea anchors made from three fabrics: the currently used polyamide (PA) material, PA material with increased yarn density in the weft direction, and polyester (PES). Using Korean national standards, we compared the yarn density, weight, water absorption capacity, drying rate, air permeability, …

Research On Ship Track Prediction Based On Ipso-Cnn, Xiangen Bai, Nuo Chen, Xiaofeng Xu

Journal of Marine Science and Technology–Taiwan

With the rapid development of the global economy, international imports and exports have become increasingly important. Timely and effective tracking and prediction of ship trajectories are important in the face of complex maritime traffic. Based on AIS data, this study establishes a ship trajectory prediction model combining improved particle swarm optimization (IPSO) and a convolutional neural network (CNN) that uses the ship's historical navigation trajectory data to predict the future navigation trajectory. The historical ship trajectory data of the Port of Ningbo-Zhoushan were selected for the experiment, and the IPSO-CNN model experiment results were compared with those of other models. …

Extended-Duration Satellite Testing Via Altitude-Controlled High-Altitude Balloon, Drew Early, Evan Champney, Nikki Allen, Riley Galatis, Lukas Hezel, Joseph Kloess, Andrew Donnell, Sam Whitlock, Kaden Queener

Von Braun Symposium Student Posters

Undergraduate runner-up, 2025 Von Braun Symposium Student Poster Contest

Fault Tree Analysis For Robust Design, Jonathan Degroff, Gene Jean-Win Hou

Mechanical & Aerospace Engineering Faculty Publications

The objective of this research is to incorporate system failure into a robust design formation and solution process. The system failure referred to here will be built using fault tree analysis (FTA), which will take all lower-level failure events into consideration. Two examples are investigated here. One will directly treat the probabilities of the basis events as design variables, The other will be formulated in five different models: deterministic design optimization, the reliability index-based, the “and” gate-based, the “or” gate-based and the “inhibit” gate-based robust design. Their corresponding optimization solutions will be compared with each other. The post-optimality analysis of …

Polarized Positrons At Ce⁺Baf, A. Ushakov, J. Benesch, M. Bruker, L. Cardman, J. Conway, S. Covrig Dusa, P. Degtiarenko, Y. Enomoto, S. Gessner, P. Ghoshal, S. Gopinath, J. Grames, C. Gulliford, S. Habet, G. Hays, C. Hernández-García, A. Hofler, R. Kazimi, M. Kostin, V. O. Kostroun, F. Lin, V. Lizárraga-Rubio, K. Mahler, Y. Morikawa, S. Nagaitsev, S. Ogur, G. Palacios-Serrano, N. Raut, B. Rimmer, Y. Roblin, A. Seryi, K. Smolenski, M. Stutzman, R. Suleiman, A. Sy, N. Taylor, D. Turner, A. Ushakov, C. Valerio-Lizarraga, E. Voutier, S. Wang, Y. Zhang

Mechanical & Aerospace Engineering Faculty Publications

A baseline concept for a continuous wave (CW) polarized positron injector was developed for the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab [1]. This concept is based on positron beam generation by a high current polarized electron beam (1 mA, 120 MeV, >85% polarization) irradiating a rotating water-cooled tungsten target or liquid metal target. The update on the development of the Ce⁺BAF injector concept including the polarized electron source, the development of high power targets, simulations of positron capture, the design of the transport line from the positron injector to the CEBAF North Linac and the planned experiment …

Deep Learning Approaches For Predicting Strain Energy In Heterogeneous Materials, Junesh Gautam

Electronic Theses and Dissertations

Finite Element Analysis (FEA) faces computational challenges when analyzing nonlinear and heterogeneous materials. Utilizing the Mechanical MNIST dataset, comprising 60,000 simulated samples of 28x28 pixel domains under large deformation, the study evaluates classical regression methods (Linear Regression, Random Forest, Gradient Boosting) and advanced deep learning architectures (Convolutional Neural Networks (CNN) and Residual Networks (ResNet)). CNN models achieved superior performance, with a Mean Squared Error (MSE) of 4.21 and an R2 value of approximately 0.982, outperforming classical regression models and slightly surpassing ResNet architectures. These deep learning methods automatically learn spatial relationships from pixel-based representations, eliminating the need for manual feature …