Mechanical Engineering Commons^™

Enhanced Nanomechanical, Tribological And Electrical Properties Of Ni-Cr Coatings Via Max Phase Reinforcement And Metallic Interlayers, Mohammad Ashikul Alam

Theses and Dissertations

Nickel-Chromium (Ni-Cr) coatings are widely used in industrial applications due to their resistance to oxidation, thermal stability, and adjustable electrical and mechanical properties. However, achieving improved multifunctional performance across various use cases ranging from extreme tribological environments to microscale device integration remains a significant challenge. This thesis explores two complementary strategies for enhancing the performance of Ni-Cr coatings in both thick and thin film configurations, aiming to address limitations in wear resistance, durability, adhesion, and electrical conductivity. For thick coatings, Ni-Cr was reinforced with Ti3SiC2 MAX phase particles and processed using selective laser sintering (SLS) with optimized parameters. The addition …

Joint Kinematics And Kinetics During Vertical Jump Landings With Progressively Increasing External Loads, Darcie L. Yount

Dissertations

This study examined sagittal and frontal plane kinematics and kinetics during countermovement jump (CMJ) landings performed with either a traditional barbell (BB) or a hexagonal bar (HEX) across increasing submaximal loads in recreationally active males. Generally, hip and knee flexion angles and joint mean angular velocities decreased as loads increased. Hip extension and knee flexion moments increased as load increased up to 20 kg, at which point these values decreased. Performing the CMJ with the HEX exhibited increased frontal plane stability compared with the BB group. Additionally, the BB group exhibited stiffer landing strategies, with decreased sagittal plane joint angles …

High-Heat Transfer Lithium-Ion Batteries: A New Era In Battery Thermal Management, Alfred J. Piggott, Jeffrey S. Allen, Ahmad A. Pesaran

Michigan Tech Publications

Despite advances in lithium-ion battery technology, critical challenges remain that must be addressed to accelerate electric vehicle (EV) adoption and global energy transformation. Significantly improved battery thermal management (BTM) is key to overcoming these challenges. BTM approaches focus on increasing heat transfer coefficients via air, liquid, or refrigerant cooling, but less attention is given to reducing the battery's thermal resistance, a major bottleneck for heat transfer. This work introduces a novel approach to reduce battery thermal resistance by integrating in-plane heat transfer with optimized cell geometry, minimized thermal resistances, and reduced interfacial resistances, representing a departure from previous methods. The …

Mae Enewsbrief Apr- June 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Analysis And Predictive Modeling Of Stall And Spin Accidents In General Aviation Fixed-Wing Aircraft, Mehedi Hasan

Graduate Theses and Dissertations

Stall and spin accidents represent a persistent safety concern in General Aviation, with approximately 41% resulting in fatalities despite their relatively low occurrence. This study analyzes 1,079 General Aviation stall and spin accidents from 2008 to 2023 using the National Transportation Safety Board accident database. Our analysis identified the top phases of flight, injury outcomes, and causal factors in stall/spin accidents. Findings indicate that over 93% of stall/spin events involved General Aviation aircraft, with most accidents occurring during initial climb, takeoff, or low-altitude maneuvering. Pilot-related control errors, especially poor airspeed and angle-of-attack management, were the most common causes. To assess …

Engineered Interfaces For Enhanced Transient Liquid Phase Bonding In Electronics Assembly, John Russell Harris

Graduate Theses and Dissertations

Growing applications in transportation make power density a key optimization target in the power electronics industry. More power in a shrinking environment leads to high heat flux and junction temperatures that damage silicon-based switching devices. Temperatures approaching 175℃ can result in false triggering of the device’s activated state, resulting in short circuits. Developing wide bandgap semi-conductors, such as gallium nitride and silicon carbide, are less susceptible to this complication as the energy from elevated temperature is a smaller fraction of what would be required to trigger the device. These devices are projected to function reliably in environments of up to …

Photochemical Fabrication And Tribological Evaluation Of Hexagonal Grooves With Corner Dimples On Cast Iron Surfaces, Steven Sonntag

Graduate Theses and Dissertations

The traditional honing process used to texture cylinder liners in internal combustion engines has long been recognized as suboptimal, as evidenced by the need for a break-in period before achieving peak performance. Although laser-based methods can produce micro-scale features with high precision, they are often cost-prohibitive and difficult to scale for large or complex components. This study explores photochemical machining (PCM) as a low-cost, scalable alternative for fabricating high-resolution surface textures—specifically, hexagonal grooves with corner dimples—on gray cast iron. The resulting textures exhibit uniform groove widths (~13 μm) and varied depths, demonstrating PCM’s capability to create high-resolution patterns with sub-micron …

High-Resolution Energy Efficient Selective Laser Sintering Of Copper Nanoparticles, Bo Shen

Graduate Theses and Dissertations

Copper (Cu) is widely utilized in electronics and photonics applications due to its outstanding electrical and thermal conductivity. With increasing demand for miniaturization and higher precision in modern manufacturing, traditional selective laser sintering (SLS) techniques designed primarily for high-throughput production are becoming insufficient. These conventional methods struggle to deliver the resolution required for micro-scale fabrication and often cause thermal damage to sensitive substrates. Therefore, there is a growing necessity to develop compact and high-resolution laser sintering systems capable of precise microfabrication with minimal thermal influence. This study addresses this challenge by investigating nanosecond pulsed laser sintering as a method to …

Computational Study Of Nonlinear Electrokinetic Phenomena In Shear-Thinning Fluids, Wai Yuen Leung

All Theses

Electrokinetic phenomena have been widely used for fluid pumping and particle manipulation in micro/nanofluidic systems. They refer to the motion of fluids or particles in response to an electric field because of the spontaneous formation of an electric double layer at the fluid-solid interface. Understanding electrokinetic phenomena in micro/nanochannels is critical for a wide range of applications across various engineering fields, such as disease diagnostics, contaminant treatment and cell analysis. To date, numerous studies have been reported on electrokinetic phenomena in Newtonian fluids, where the classical Helmholtz-Smoluchowski theory indicates a linear relationship between fluid electroosmosis/particle electrophoresis and electric field. However, …

Design, Modeling, Control, And Analysis Of A Modular Two-Wheeled Self-Balancing Robotic System, Mishek Jair Musa

Graduate Theses and Dissertations

Two-wheeled self-balancing robots have garnered substantial attention within the realms of research and innovation in academia and industrial settings. In particular, advances in control algorithms, machine learning, reinforcement learning, and sensor technologies have played a pivotal role in their development. Although primarily recognized for their utility in personal transportation in the commercial sector, these robots possess potential applications across various domains, including search and rescue, healthcare, material handling, logistics, etc., due to their active stabilization and exceptional maneuvering capabilities. A particular area of interest lies in the creation of modular self-balancing robots designed for seamless reconfiguration and enhanced human interaction. …

The Development And Application Of A Method To Simulate Commotio Cordis Inducing Impacts For The Evaluation Of Football Chest Protective Equipment, Bianca J. Henline

All Theses

As one of the most widely played and watched contact sports in the United States, football presents a significant risk of blunt chest trauma. Thus, effective chest protection is essential to prevent rare but fatal injuries like commotio cordis. Despite this, current test methods for certifying chest protective equipment fail to account for injury metrics relevant to commotio cordis events. Recent literature identifies rib deformation and viscous criterion as critical predictors of commotio cordis, yet these metrics are not adequately addressed in the existing testing standard. Furthermore, this standard exclusively assesses chest gear specific to baseball and lacrosse through projectile …

Integration And Testing Of A Quadruped Robot With Ros2, Jeremy S. West

Master's Theses

The Cal Poly Legged Robotics Group has been developing research and teaching platforms for agile legged robotics since 2020. These platforms are expected to provide students with opportunities to develop complete legged-robot systems from low-level control to advanced robotics tasks such as motion planning and decision making. However, the current prototyped quadruped robot lacked the software and sensing capabilities for high-level quadrupedal gaits and advanced robotic research.

To address these challenges, this project developed Switch, a robotic platform that builds upon the previous BRUCE platform with significant hardware and software upgrades. Switch features a modular design that allows individual software …

Machine Learning And Clinical Eeg Data For Multiple Sclerosis: A Systematic Review, Badr Mouazen, Ahmed Bendaouia, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Multiple Sclerosis (MS) is a chronic neuroinflammatory disease of the Central Nervous System (CNS) in which the body’s immune system attacks and destroys the myelin sheath that protects nerve fibers, leading to a wide range of debilitating symptoms and causing disruption of axonal signal transmission. Accurate prediction, diagnosis, monitoring and treatment (PDMT) of MS are essential to improve patient outcomes. Recent advances in neuroimaging technologies, particularly electroencephalography (EEG), combined with machine learning (ML) techniques — including Deep Learning (DL) models — offer promising avenues for enhancing MS management. This systematic review synthesizes existing research on the application of ML and …

Effect Of Moderate Decrease In Contractility On Epithelial Cell-Cell Contacts Under External Stretch, Saika Sharmin

Mechanical & Aerospace Engineering Theses & Dissertations

Epithelial tissues are characterized by extensive cell–cell contacts and often subject to stretch during normal function. Cell-cell contact adhesion strength maintains mechanical continuity from cell to cell. Mechanical forces exerted by cells via actomyosin contractility are known to strengthen cell-cell adhesions to a certain extent. While it is known that a large decrease in contractility causes cell-cell contact rupture due to weakened adhesions, it is unclear how a moderate reduction in contractility affects cell-cell junction stability. Here, we studied how a moderate inhibition of non-muscle myosin II (NMII) affects the integrity of epithelial cell-cell contacts, especially when subject to the …

Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch

All Theses

The integration of metals and composites in automotive structures improves manufacturability and overall structural performance. The proposed Ultrasonic Additive Manufacturing (UAM) joint provides a promising solution for joining aluminum and carbon fiber; however, modeling its behavior across an entire vehicle can be computationally expensive. To address this challenge, a homogenized material card is developed to efficiently capture the joint’s mechanical response while maintaining computational efficiency. A novel characterization method is implemented, employing implicit simulations and optimization techniques to determine the effective material properties of the UAM transition joint. This approach enables rapid iteration of material parameters, facilitating the efficient evaluation …

Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

More than 51 million surgeries are performed on patients annually in the United States. That number grows to 310 million surgeries performed globally each year. Most surgeons go through a minimum of five years of residency – where they train and hone their surgical skills. It is important during this time, and throughout their careers, that they get plenty of practice. Surgical training is time intensive, expensive, and frequently under-resourced. There are finite amounts of surgical training modules for students to share at their facilities. The problem of getting adequate surgical training time continues to exist after surgeons begin their …

A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …

Modification Of Tini Alloy By Fast Pulse Laser Heat Treatment, Yitao Chen, Mohammad Masud Parvez, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, the effects of local heat treatment with fast pulse laser on thin TiNi shape memory alloy strip materials were investigated. Various materials characterization methods including optical microscope, scanning electron microscope, atomic force microscope, X-ray diffraction, differential scanning calorimetry, and Vickers hardness were used to identify the differences of microstructure, mechanical properties, and functional properties between regions inside and outside the laser-scanned region. The tensile test was also conducted for both the non-laser-scanned specimen and the laser-scanned specimen. The area covered by laser scanning shows great differences by possessing a more homogeneous austenite phase without shear bands and …

Digital Twins, Ai, And Cybersecurity In Additive Manufacturing: A Comprehensive Review Of Current Trends And Challenges, Md Sazol Ahmmed, Laraib Khan, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The development of Industry 4.0 has accelerated the adoption of sophisticated technologies, including Digital Twins (DTs), Artificial Intelligence (AI), and cybersecurity, within Additive Manufacturing (AM). Enabling real-time monitoring, process optimization, predictive maintenance, and secure data management can redefine conventional manufacturing paradigms. Although their individual importance is increasing, a consistent understanding of how these technologies interact and collectively improve AM procedures is lacking. Focusing on the integration of digital twins (DTs), modular AI, and cybersecurity in AM, this review presents a comprehensive analysis of over 137 research publications from Scopus, Web of Science, Google Scholar, and ResearchGate. The publications are categorized …

Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw

Open Access Theses & Dissertations

The aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, …

Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez

Open Access Theses & Dissertations

This dissertation presents an in-depth look at the mechanical behavior, size changes, and process improvement of ceramic and polymer materials made with additive manufacturing (AM). The work consists of four separate but related studies, each tackling important challenges in fabrication, characterization, and predictive modeling. Chapter 1 examines the nano-mechanical property changes of 3D-printed zirconia made using digital light processing (DLP). By employing nanoindentation and scanning electron microscopy (SEM), the effects of print orientation and sintering on hardness, elastic modulus, and microstructure are revealed. The results indicate that 0°-oriented sintered samples have up to 140% higher hardness compared to preconditioned samples, …

Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan

All Dissertations

A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …

Experimental Evaluation And Comparison Of Football-Related Head Impacts Among Ovine, Human, And Hybrid Iii Headforms, Madysn D. Cardinal

All Dissertations

Concussions and traumatic brain injury (TBI) remains a significant public health concern, especially in American football, where repeated head impacts pose long-term risks to athlete health. While current helmet testing standards rely heavily on the Hybrid III surrogate headform to evaluate protective performance, these surrogate models lack anatomical accuracy and exclude the presence of a brain component, limiting their ability to capture the true mechanics of concussion. To address this limitation, this research developed and validated a novel inverted impact testing method that allows the impact testing of a Hybrid III headform and a cadaveric specimen. Additionally, this fixture preserves …

Enhanced Point Cloud Generation From A Novel 360° Underwater Lidar, Olagoke E. Daramola

Dissertations

This dissertation presents novel algorithms to improve the mapping capabilities of a 360-degree underwater Pulsed Laser Line Scanner LiDAR (PLLS-360°). Due to its 360° field-of-view (FOV), the PLLS-360° is a compact full-waveform omnidirectional imager suitable for seafloor mapping, underwater asset inspection, object detection, ice-sheet mapping, and construction progress monitoring. The proposed methodology includes an improved waveform fitting technique for saturated waveform recovery, detection array response correction, radiometric corrections, and fusion of LiDAR and sonar bathymetric datasets. The first part of this dissertation assesses the LiDAR’s performance and describes how the data for this unique 360° FOV architecture is processed. The …

Mass Effects On Energy Transfer Paths In Nonlinear Vibrating Systems, Manal Mustafa

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation examines the role of mass in nonlinear systems, uncovering its role in enabling passive energy redistribution and robust vibration control in both idealized and real-world structures. Focusing on a strongly nonlinear two-degree-of-freedom system, it investigates how changes in mass ratio influence the dynamics of energy transfer, nonlinear normal modes (NNMs), and dissipation behavior.

A number of significant contributions are introduced in this work beginning with the introduction of the frequency-energy-peaks (FE-pks) plot, a novel tool that visualizes how energy flows through the system, revealing transient resonance orbits, internal resonance effects, and effectively capturing the different nonlinear phenomena with …

The Advancement Of Automation In Beef Packaging Pack-Off Systems, Matthew Newman

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Marble Technologies has developed a new system for beef, pork, and lamb producers that improves quality and worker experience in the packing of products. This work explores the augmentation of this system with the introduction of robotic packing to further reduce labor, increasing worker availability for value-added tasks.

Experimentation conducted to date has explored handling delicate meat products in the standard Marble system and the proposed robotic systems. These mechanical subsystems are critical intermediaries in safely and reliably delivering products to robots and from robots to boxes. Two case studies are presented to walk through the process and challenges of …

Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee

Open Access Theses & Dissertations

Understanding the directional properties of porous media is essential for accurately predicting flow behavior, reactive transport, and fluid-solid interactions in systems ranging from geothermal reservoirs to energy storage devices and biological tissues. Directional variations in permeability - reflecting a medium's response to flow at different angular orientations - are particularly important for complex, inherently anisotropic geometries. In this study, we employ a Lattice Boltzmann (LBM) model to calculate directional permeabilities from porous media images subjected to varying flow inlet angles. Three classes of porous media were investigated: (1) synthetic media with circular grains, serving as isotropic baselines; (2) synthetic media …

Modeling And Characterization Of Additively Manufactured Barium Titanate Ceramic, Luz Irene Bugarin

Open Access Theses & Dissertations

This dissertation investigates the influence of geometric design on the mechanical properties of BTO structures fabricated via 3D printing. Using finite element modeling (FEM), we simulate mechanical stress responses across a range of architected designs. Results reveal that specific design strategies can significantly enhance performance by promoting favorable stress distributions. This work highlights the critical role of structural design in optimizing functional ceramics and provides a computational framework for the design of next-generation piezoelectric devices.

A Digital Engineering Framework For Ai-Driven Trade-Off Evaluation And Predictive Component Classification, Alejandro Silva Au

Open Access Theses & Dissertations

This thesis introduces a digital engineering tool designed to help engineers make smarter decisions when choosing actuators. At its core, the system brings together machine learning (specifically XGBoost) and a decision-making method called Multi-Utility Attribute Theory (MUAT). The goal is to support engineers in picking components based on what really matters for their designs, whether that's speed, cost, durability, or any other performance factor. What makes this tool stand out is its user-friendly interface that lets people interact with the system directly. It takes a set of actuator performance data, classifies each one into a relevant use category, and then …

Shape Memory Behavior In Medium To High Entropy Shape Memory Alloys: Design, Prediction, And Experimental Analysis, Hatim Raji

Theses and Dissertations

This dissertation provides a data-driven system integrating synthetic data generation and machine learning (ML) techniques to create multicomponent SMA compositions with specific transformation temperatures (TTs). Models were trained to represent the nonlinear dependencies influencing martensitic transformation behavior by using elemental, thermodynamic, and process-related aspects. The capacity of the ML models on medium entropy NiTiHfPd and high entropy NiTiHfZrCu systems accuracy was confirmed by experimental validation showing TTs closely matched with model outputs.