Mechanical Engineering Commons^™

Online Parameter Adaptation Of Lqr Controllers Via Rls For Prosthetic Joint Control: Experimental Validation On A Quanser Qube-Servo 2 Platform, Cynthia Lopez-Jordan

Theses and Dissertations

This thesis develops and experimentally validates an online adaptive Linear Quadratic Regulator (LQR) control method for prosthetic joint systems using Recursive Least Squares (RLS)-based real-time parameter estimation on the Quanser QUBE-Servo 2 platform. Traditional LQR controllers assume a fxed system model, which limits adaptability and results in reduced tracking accuracy, poor robustness, and loss of optimal performance when applied to dynamically changing prosthetic joints, infuenced by load variations, user gait changes, and mechanical wear. Limited experimental validation exists for combining RLS with online LQR adaptation in prosthetic-like systems.

To address these limitations, an RLS-driven Adaptive LQR framework was implemented to …

Digital Twins For Flexible Manufacturing, Drew Brandon Sander

Theses and Dissertations

With the establishment of Digital Twins as an enabling technology for Industry 4.0, it is time to transition from the previous foundations to works that implement and highlight the capabilities Digital Twins present. The Industry 4.0 paradigm has recentered the focus on customizability, leading to reemerging goals of flexibility within manufacturing. Empowered through new cyber-physical systems, new enabling technologies are driving the revolution. To identify how Digital Twins as an enabling technology contribute to flexibility within manufacturing, a comprehensive investigation is conducted along with a detailed case study. A systematic literature review is conducted to analyze quality Digital Twin implementations …

Novel Redox Oxygen Active Materials For Solid Oxide Cells And Thermochemical Hydrogen Production, Jiaxin Lu

Theses and Dissertations

This dissertation investigates novel materials designed to significantly enhance the performance and durability of oxygen electrodes for solid oxide cells and redox active materials for thermochemical hydrogen production. The first part of this work evaluates Ta-doped BaCoO₃₋δ (BCT) and its structural analog SrCoO₃₋δ (SCT), focusing on their catalytic performance in oxygen reduction and evolution reactions. Among BCT compositions (x = 0.1, 0.3, 0.5), the BCT10 (x = 0.1) composition exhibited the highest oxygen vacancy concentration, electronic conductivity, and lowest polarization resistance. However, SCT10 surpassed BCT10 in these critical performance parameters and also demonstrated greater stability over extended operational periods. Notably, …

Advanced Air Preheater Sealing Systems For Enhanced Efficiency And Reliability In Thermal Power Plants, Pavan Kumar Ravulaparthy

Theses and Dissertations

Global electricity generation still relies heavily on thermal power plants, which consume vast amounts of fuel and emit significant amounts of carbon dioxide. A major but often overlooked source of inefficiency in these plants lies within the rotary regenerative air preheater (RAPH), a critical heat-exchange component where air leakage can exceed 20% in aging units. This leakage increases fuel consumption, parasitic fan power, and CO₂ emissions, while degrading boiler reliability.

This research introduces advanced adaptive sealing systems designed to mitigate these losses by dynamically compensating for rotor eccentricity, thermal distortion, and wear under harsh operating conditions. Brush seals, composed of …

Implementation Of Quantized Artificial Neural Networks With Spintronic Stochastic Computing, Saadi Sabyasachi Mr.

Theses and Dissertations

Artificial intelligence or machine learning is going through a rapid expansion. It also incurs significant costs for power and device footprints. Various approaches are being explored to design energy and hardware efficient machine learning models. Stochastic computing has been proposed for efficient machine learning implementation. It requires a source of random number generation which poses some practical challenges. So spintronic solutions such as magnetic tunnel junction has been used for random number generation. Again, spintronic random number generation to implement high precision circuit is prone to device-to-device variations. Hence we designed quantized artificial neural network with spintronic stochastic computing which …

End-To-End Autonomous Quadcopter Using Reinforcement Learning, Mohamed Marwan Chawa

Theses and Dissertations

This thesis investigates the potential of Reinforcement Learning (RL) for achieving robust and adaptable quadcopter control, focusing on trajectory and attitude stabilization. We compare state-of-the-art RL algorithms, specifically Proximal Policy Optimization (PPO), against traditional Proportional-Integral-Derivative (PID) controllers across three tasks: hovering, slow trajectory following, and fast trajectory following. To enhance realism, we employ a modified PyFlyt simulation environment with a high-fidelity Crazyflie 2.x model, accounting for motor dynamics, noise, wind disturbances, and aerodynamic drag.

The challenge of operating a quadcopter can be divided into two distinct parts: planning a flight path and actually following that path. Our focus is on …

Crystal Plasticity Modeling To Capture Microstructural Variations In Cold-Sprayed Materials, Aulora Gail Williams

Theses and Dissertations

The high-velocity impact of powder particles in cold-spray additively manufactured (CSAM) parts creates intersplat boundaries with regions of high dislocation densities and sub-grain structures. Upon microstructure and mechanical characterization, CSAM Aluminum 6061 showed non-uniformity, with spatial variation in the microstructure and mechanical properties affecting the overall response of the additively manufactured parts. Post-processing treatments are conducted in as-printed samples to improve particle bonding, relieve residual stresses, and improve mechanical properties. In this work, we attempt to implement the effects of grain size and distribution of smaller grains along the intersplat boundaries using the grain size distribution function and powder size …

Experimental And Numerical Investigation Of Phase Change Material Melting Cycle In Microgravity, Ethan Michael Schuetzle

Theses and Dissertations

Efficient thermal management of spacecraft systems is crucial to overcome the extreme thermal conditions in space. Phase change materials (PCMs) offer significant advantages in thermal energy storage (TES) systems due to their high latent heat of fusion, the amount of energy stored or released during phase transitions. However, PCMs face limitations due to low thermal conductivity, especially in microgravity where heat transfer is primarily through conduction. This research addresses this issue by incorporating a 3D-printed aluminum lattice structure to enhance heat transfer to PCMs. Experimental data from sub-orbital flight tests and ground-based experiments, coupled with numerical simulations, are used to …

Effect Of Laser Textured Surface With Different Patterns On Tribological Characteristics Of Bearing Material, Paul Joshua S

Theses and Dissertations

This research work determines the wear rate and friction characteristics of bearing material under different laser textured surface conditions. Chrome steels are used in bearings since they possess high strength and wear resistance. However, when those parts are in service, failure happens due to sliding friction before the lifetime. To improve the durability of the American Iron and Steel Institute (AISI) 52100 chromium steel, in this work, the effect of laser surface texturing (LST) was analysed.

With the different pattern of circle, ellipse, groove and grid were produced on the sample surface, the wear behavior was investigated using the pin …

Primary And Secondary Resonances Of Fringe Effect Electrostatically Actuated Mems Cantilever Resonators, Miguel Armando Martinez

Theses and Dissertations

The nonlinear dynamics of micro-electromechanical system (MEMS) cantilever resonators actuated by the fringe field at parametric and primary resonances are studied. Three models are used based on different descriptions of the system capacitance. In the fringe and capacitance models, the electrostatic force due to the parallel-plate capacitance is neglected due to a hole in the ground plate (removes overlapping area). The SolidWorks model is based on numerical capacitance simulations performed on SolidWorks using EMS. All three models that approximate the fringe field capacitance are compared with one another. The Method of Multiple Scales (MMS) and Reduced Order Model (ROM) up …

Resonances Of Electrostatically Actuated Non-Uniform Mems Cantilever Resonator Of Constant Width And Linearly Varying Thickness, Rigoberto Flores

Theses and Dissertations

In this investigation the behavior of an electrostatically actuated non-uniform microelectromechanical (MEMS) cantilever resonator of constant width and linearly varying thickness is investigated. The cantilever resonator vibrates using soft AC voltage at near half the first natural frequency of the cantilever and near the first natural frequency of the cantilever, known as primary and parametric resonances, respectively. Bifurcation diagrams for the amplitude-frequency and amplitude-voltage response are obtained for both resonances. Two methods are used in this investigation, namely the Method of Multiple Scales (MMS) and Reduced Order Model (ROM) using up to 6 modes of vibration.

These methods are used …

End-To-End Learning For A Low-Cost Robotics Arm, Abhishek Chothani

Theses and Dissertations

Robotic manipulation is a cornerstone of automation, with the ultimate goal of developing versatile systems capable of executing a wide range of real-world tasks autonomously. Traditional robotics approaches, while reliable and widely adopted in industrial settings, often struggle with adaptability, perception, and dynamic task execution. This thesis explores the evolution from classical robotics techniques to modern learning-based approaches, leveraging advancements in artificial intelligence to overcome these limitations.

Initially, the thesis presents a pick-and-place pipeline built using the Drake robotics framework and the KUKA iiwa robotic arm. This system employs a pseudoinverse controller for inverse kinematics to perform structured tasks like …

Fabrication And Performance Of Scalable Bio-Engineered Porous Layers For Efficient Co2 Capture, Mary Sharon Rose Bondugula

Theses and Dissertations

This dissertation addresses the critical challenge of mitigating climate change by advancing CO2 capture technologies. As global CO2 emissions continue to rise, effective methods for capturing and separating CO2 from industrial processes are essential to combat climate change. Existing CO2 capture systems, such as Pressure Swing Adsorption (PSA) and Temperature Swing Adsorption (TSA), often rely on packed bed designs that face limitations, including poor heat and mass transfer, slow gas diffusion, and low thermal conductivity, reducing their efficiency. To overcome these challenges, this dissertation explores innovative solutions by developing advanced adsorbent coatings and scalable bed configurations.

This research begins by …

Fabrication And Charcaterization Of Pullulan-Collagen Nanofibers Via Forcespinning, Valeria Leon Leal

Theses and Dissertations

Extensive research on collagen has spurred advancements in tissue engineering and biomaterial development, given collagen´s pivotal role in regulating various tissue structures across diverse organisms. This study delves into fabricating nanocomposites utilizing collagen, along with silver nanoparticles, chondroitin sulfate and pullulan, for potential applications in antibacterial medical devices, and cell regeneration. Collagen, abundant in the extracellular matrix, provides essential structural support, while silver nanoparticles and chondroitin confer antimicrobial properties, crucial for combating infections. Pullulan, a polysaccharide polymer, serves as a biocompatible carrier for silver nanoparticles whilst being the starting nanofiber forming material. Utilizing Forcespinning® technology, composite nanofibers were successfully synthesized. …

Improving Robustness Of Learning-Based Approaches In Autonomous Systems And Engineering Education, Godwyll Aikins

Theses and Dissertations

This dissertation advances the development of robust learning-based approaches across two complementary domains: engineering education and autonomous systems. Through four studies, this research addresses critical challenges in preparing data-proficient engineers and developing reliable autonomous systems that can operate under uncertainty and incomplete information. The engineering education study examines how mechanical and aerospace engineering undergraduates conceptualize and develop data proficiency skills essential for modern engineering practice. Through interviews with 27 students, the research employs the How People Learn framework to analyze student perspectives on information literacy, data interpretation, and computational thinking. The findings inform pedagogical strategies for developing data proficiency in …

Identifying Challenges Faced By Small And Medium Enterprises (Smes) In The Middle East And North Africa (Mena) Region Through Total Quality Management, Mohamad Atef

Theses and Dissertations

Recently, Small and Medium Enterprises (SMEs) have become recognized as an important driver of global economic growth and innovation. This phenomenon is particularly evident in the MENA region, where small and medium-sized enterprises (SMEs) make a significant contribution to the businesses. SMEs offer significant benefits in terms of job creation, revenue generation, and fostering economic diversity. Although SMEs have a vital contribution in the economy of the MENA region, SMEs face many challenges that hinder their development and long-term viability. Focusing on these challenges is very important for fostering a vibrant and resilient economic environment. The objective of this thesis …

Heterogeneous Collaborative Robotics: Multi-Robot Navigation In Dynamic Environments, Tyler Nicholas Raettig

Theses and Dissertations

Abstract: The challenges of multi-robot navigation in dynamic environments, focusing on uncertainties in obstacle complexities, partial observation, and the transition of policies from simulations to the real world. The proposed approach utilizes a deep reinforcement learning (DRL) framework enabling a Light Detection and Ranging (LiDAR)-equipped robot to communicate with a camera-equipped robot to achieve optimal paths despite their different sensors. The key contributions include the development of a cooperative architecture for information exchange between robots, a DRL-based framework for learning navigation policies, and a training mechanism based on dynamic randomization for enhanced real-world adaptability. Experimental validation using Gazebo simulations demonstrates …

Investigating Electrochemical Performance And Interfacial Stability Of Solid-State Lithium Metal Batteries: A Study Of Hybrid Polymer-Ceramic Electrolyte Systems, Ziba Rahmati

Theses and Dissertations

Solid-state batteries (SSBs) are emerging as a promising energy storage technology, surpassing traditional liquid electrolyte (LE) counterparts in performance and safety. A critical component in SSBs is the solid-state electrolyte (SSE), which plays a pivotal role in safety, efficiency and stability. SSEs, including sulfides, halides, oxides, and polymers, present distinct advantages and challenges compared to LEs. Among these, oxide-based SSEs are particularly attractive for their balance in ionic conductivity and chemical stability.

This study addresses key challenges related to interfacial stability and electrochemical performance in SSBs by focusing on hybrid polymer-ceramic electrolyte systems. A major challenge to such a SSB …

Autonomous Real-Time Model Updating Within Digital Twin Frameworks For Thermal Systems, Braden Robert Priddy

Theses and Dissertations

As engineering systems increase in scale and complexity in the era of the Fourth Industrial Revolution, data-driven solutions will become essential in enabling the next generation of these systems. One of the trending tools that can aid in this transition is digital twins. As physical systems degrade throughout their life cycles, their behavior also changes. Digital twins use data assimilation to continuously update virtual models to represent the current state of their physical counterparts. A reliable digital twin can be leveraged by a system operator to perform diagnostics, optimize, and tests without ever needing the physical system. However, implementing effective …

A Process Planning Software For Modeling Parameter Behavior In Automated Fiber Placement, Benjamin Jeffrey Francis

Theses and Dissertations

The manufacturing of large-scale, geometrically complex composite structures is often accomplished today using the Automated Fiber Placement (AFP) process. AFP utilizes a fiber placement end effector and a gantry or robotic kinematic system to lay up groups of composite tows, iteratively building the complete structure. The reduced width of each tow allows the deployment of AFP for builds with significant curvature, unlike other automated methods such as automated tape laying. Despite its proven track record and widespread use, the current AFP process contains inefficiencies and suffers from workflow bottlenecks that significantly increase cycle time, material wastage, and overall cost. A …

Advancement Of The Zinc Ion Battery: Polymer Electrolyte And Electrode Development For Aqueous Zinc-Ion Batteries, Roya Rajabi

Theses and Dissertations

Rechargeable aqueous zinc-ion batteries (ZIBs) have garnered significant attention in recent years as a promising candidate for stationary large-scale energy storage due to their distinct safety features and cost-effectiveness compared to conventional lithium-ion batteries. Despite their great potential, ZIBs are currently facing critical challenges for commercialization, including poor cycle stability at low discharge rates, lower energy density (Wh/kg) and higher self-discharge rate. These issues must be addressed for them to become a viable energy storage solution. The above challenges are fundamentally rooted in the bulk properties of electrolytes and interactions with electrodes, such as; 1) formation of insulating layered double …

Augmented Reality (Ar) And Virtual Reality (Vr)-Based Data Visualization Frameworks For The Manufacturing Industry, Nitol Saha

Theses and Dissertations

Industry 4.0 is transforming the manufacturing industry by integrating digital technologies throughout the production lifecycle, leading to the development of smart factories. The integration of Augmented Reality (AR) and Virtual Reality (VR) alongside smart manufacturing is transforming traditional industry practices by establishing a robust cyber-physical infrastructure, enhanced data visualization, and improved task execution. This thesis aims to develop AR and VR-based data visualization frameworks for the manufacturing industry, focusing on detailed implementation strategies, initial results, and key findings of these frameworks. One major focus of these frameworks is the generalization of the technological assets so that these frameworks can be …

Augmented Reality Based Maintenance Operations And Training, Victor Scott Gadow

Theses and Dissertations

Augmented Reality (AR) is the process of superimposing virtual information on top of objects or other structures in the real-world environment. It is considered one of many paradigms included in the idea of smart manufacturing and can enable a mixture of the other technologies involved. A large increase in research on AR has been seen in the past decade as technologies have begun to evolve to become more robust and reliable. It has been implemented into several key areas of manufacturing such as maintenance, assembly, training, and quality control. The rise of industry 4.0 is changing how data is used …

Data-Driven Discovery Of Extreme Thermal Materials By High-Throughput Computation And Machine Learning, Joshua Ojih

Theses and Dissertations

The quest for materials with extraordinary properties has been a longstanding endeavor in material science and engineering, driving future technological advancement. However, the discovery of such materials is non-trivial. Recent advancements in computational methods, particularly the integration of machine learning (ML) techniques with density functional theory (DFT), have opened new avenues for accelerating the discovery of materials with exceptional and extreme properties. This dissertation focuses on developing a synergistic approach and workflow combining ML and DFT to identify materials with properties that are pushed beyond current limits, using lattice thermal conductivity (LTC) as a case study of the workflow.

We …

Integrating Digital Twin Technology For Real Time Blockage Detection In Water Cooled Electronics, Richard Scott Hainey Jr.

Theses and Dissertations

This paper presents a culmination of research into integrating Digital Twin (DT) technology in water-cooled electronic systems to improve system reliability by detecting faults in the cooling system that maintains the proper operation of heat-producing electronic components and systems. A DT is a virtual representation of a physical twin (PT). This PT can represent real-world systems, individual components, or processes. Using the DT, operators can gain insight into the behavior and characteristics of the PT, thereby facilitating informed decisions to improve its health and optimize processes. The DT system is designed to detect obstructions forming in the waste heat-producing components …

Interpretation Of Surface Roughness Of Stainless Steel 316l In Laser Powder Bed Fusion Additive Manufacturing, Tianyu Zhang

Theses and Dissertations

Laser Powder Bed Fusion (L-PBF), a widely used metal additive manufacturing (AM) method, is emerging as a key technology in the modern manufacturing industry. Its applications span across aerospace, transportation, energy, and biomedical industries, aiming to maximize product functionality, quality, and manufacturing efficiency.

Surface roughness, an important measure of product quality, impacts geometrical tolerances and plays a critical role in mechanical and functional properties. Although post-process techniques such as machining, shot peening, and chemical processing can be used to refine surfaces, internal surfaces in complex geometries remain difficult to treat, limiting part performance due to undesired surface features. The …

Investigation And Comparative Analysis Of Onset Of Nucleate Boiling (Onb) In A Narrow Rectangular Channel In Microgravity And Earth Gravity Environments, Fahim Foysal

Theses and Dissertations

Understanding the onset of nucleate boiling (ONB) in different gravitational environments is crucial for a wide variety of industrial and space applications of flow boiling systems for thermal management. This thesis provides a comparative analysis of ONB in both microgravity (µg) and Earth gravity (1g) environments, with the aim of identifying the key differences. NASA’s experimental facility called Flow Boiling and Condensation Experiment (FBCE) equipped with Flow Boiling Module (FBM) was used for both the experiment onboard the International Space Station (ISS) and on Earth. The experiment was conducted in a rectangular channel of 5mm (depth) ×2.5 mm (width) ×114.6 …

Leveraging The Usage Of Blockchain Towards Trust-Dominated Manufacturing Systems, Philip Joseph Samaha

Theses and Dissertations

Smart Manufacturing has elevated manufacturing processes, transitioning from automated systems to autonomous ones. This evolution has heightened the significance of data within manufacturing facilities. The role of data has evolved from solely monitoring processes to both monitoring and extracting insights from these processes, facilitating precise control. In this context, the data infrastructure plays a critical role, encompassing both internal data circulating within the facility—such as information exchanged between controllers and actuators—and external data transmitted to and from outside entities. When the factory's cyber infrastructure is connected to the internet, security concerns escalate significantly, amplifying associated risks. Therefore, the integration of …

Mechanics Based Characterization Of Elastic Metamaterials, Mamdudur Rahman

Theses and Dissertations

In bandgap engineering there is a shortage of systematic design approach which enables one to select design variables to achieve bandgap in desired frequency range. Tools that can address this can open new areas of interest, especially since phononic crystals with low frequency bandgaps have multitude of applications in attenuation of structural vibration. Furthermore, mechanics-based characterization of phononic crystals had not seen much progress in the recent years while a lot of applied research had been conducted on phononic materials with material phase periodicity and other factors taken into consideration. This work aims to propose a systematic characterization approach of …

Redefining Gas Turbine Engine Development: A Digital Twin Framework Informed By Operational Dynamics And Numerical Analysis, Sowmya Raghu

Theses and Dissertations

Gas Turbine Engines (GTEs) serve as primary propulsion systems in aviation and are key for power generation units in various industrial applications. The conventional Gas Turbine Engine Development and Monitoring Lifecycle (EDML) typically encompasses six stages: preliminary design, numerical analysis, prototyping and testing, manufacturing, systems integration, and subsequent systematic monitoring processes. This dissertation redefines the gas turbine engine design and development process by synergistically integrating design capabilities, real-time operational data, and predictive maintenance through the implementation of digital twins. The primary objective is to establish a comprehensive framework for gas turbine engine design by utilizing thermodynamic and aerodynamic modeling, supported …