Digital Commons Network^™

Physics-Based Machine Learning Methods For Control And Sensing In Fish-Like Robots, Colin Rodwell

All Dissertations

Underwater robots are important for the construction and maintenance of underwater infrastructure, underwater resource extraction, and defense. However, they currently fall far behind biological swimmers such as fish in agility, efficiency, and sensing capabilities. As a result, mimicking the capabilities of biological swimmers has become an area of significant research interest. In this work, we focus specifically on improving the control and sensing capabilities of fish-like robots.

Our control work focuses on using the Chaplygin sleigh, a two-dimensional nonholonomic system which has been used to model fish-like swimming, as part of a curriculum to train a reinforcement learning agent to …

A Digital Triplet For Utilizing Offline Environments To Train Condition Monitoring Systems For Rolling Element Bearings, Ethan Wescoat

All Dissertations

Manufacturing competitiveness is related to making a quality product while incurring the lowest costs. Unexpected downtime caused by equipment failure negatively impacts manufacturing competitiveness due to the ensuing defects and delays caused by the downtime. Manufacturers have adopted condition monitoring (CM) techniques to reduce unexpected downtime to augment maintenance strategies. The CM adoption has transitioned maintenance from Breakdown Maintenance (BM) to Condition-Based Maintenance (CbM) to anticipate impending failures and provide maintenance actions before equipment failure. CbM is the umbrella term for maintenance strategies that use condition monitoring techniques such as Preventive Maintenance (PM) and Predictive Maintenance (PdM). Preventive Maintenance involves …

Deep Reinforcement Learning For The Design Of Structural Topologies, Nathan Brown

All Dissertations

Advances in machine learning algorithms and increased computational efficiencies have given engineers new capabilities and tools for engineering design. The presented work investigates using deep reinforcement learning (DRL), a subset of deep machine learning that teaches an agent to complete a task through accumulating experiences in an interactive environment, to design 2D structural topologies. Three unique structural topology design problems are investigated to validate DRL as a practical design automation tool to produce high-performing designs in structural topology domains.

The first design problem attempts to find a gradient-free alternative to solving the compliance minimization topology optimization problem. In the proposed …

Improving Sizing Resolution Of Particle Impactors In The Nanoparticle Range, Shivuday Kala

All Dissertations

The application of particle size measurement extends across many fields: air quality measurement, pharmaceutical studies, paint and coating production, and nanoparticle formulation to name a few. Therefore, accurate measurement of nanoparticles is critical to aerosol science. While devices currently exist that can size and count nanoparticles such as electrical mobility spectrometers, dynamic light scattering devices, and small angle X-ray scattering devices, their high costs, complex operation, and lack of outdoor usability, restrict their use in practical applications. Among the devices that can size aerosols down to the nanoscale, cascade impactors stand out because of their robustness, relatively simple design, low …

Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon

All Dissertations

The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …

Experimental Study On The Impact Of Low Thermal Inertia Thermal Barrier Coatings On Ppci-Diffusion Gci Combustion, Kunal Vedpathak

All Theses

The application of thermal barrier coatings (TBCs) has been studied in homogenous charge compression ignition (HCCI), conventional diesel combustion (CDC), and spark ignition (SI). Gasoline compression ignition (GCI) combines the low soot and NOx emissions of HCCI with combustion controllability through fuel stratification. GCI has become an interesting prospect due to the reduction in gasoline consumption due to the electrification and hybridization of the light-duty sector. It can be used as a preferred combustion mode in heavy-duty engines to reduce emissions with minimal modifications. GCI exhibits better combustion efficiency than HCCI. Advances in material technology have combined low thermal conductivity …

The Generation Of A Physics Informed Machine Learning Model To Predict Defect Evolution In Materials & On The Thermally Activated Regime Of Dislocation Motion: A Simulation Driven Study On The Mechanical Behavior Of Crystals, Liam Myhill

All Theses

Line defects in crystals, known as dislocations, govern the mechanisms of plastic deformation at the micro-meso scale. The study of dislocations has proliferated the field of materials science and engineering for since the 1950’s, and modern studies show increasing utilization of computational methods to model the evolution of line defects in material systems. In keeping with modern research practice, the studies herewith demonstrate the use of advanced computing to generate models which can be used to better understand the behaviors of dislocations within crystal matrices. An advanced high-throughput model for a physically informed machine learning graph neural network (PIML-GNN) is …

Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng

All Theses

Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …

Temperature Gradient Effect On Solid-Liqid Interface Properties Of Al-Cu Alloy: A Molecular Dynamics Study, Prashant Kumar Jha

All Theses

Aluminum-copper (Al-Cu) alloys are widely used in the aerospace industry due to their favorable strength-to-weight ratio, good fatigue resistance, and corrosion resistance. These properties make Al-Cu alloys an excellent choice for aircraft structural components that require high strength and low weight. Additive manufacturing (AM), also known as 3D printing, has emerged as a promising processing method for Al-Cu alloys in aerospace manufacturing. AM enables the production of lightweight optimized geometries difficult to manufacture through conventional subtractive methods. AM also reduces material waste by only depositing material where needed in the part geometry. The rapid solidification conditions in AM processes motivate …

Model Of Surface Waves On A Viscoelastic Material In A Cylindrical Container With Edge Constraints, Phillip Wilson

All Theses

A theoretical model is developed for the resonant frequencies and mode shapes of pinned edge surface waves on a viscoelastic fluid contained in a finite depth cylindrical container. A boundary integral approach is used to map the governing equations to the domain boundary. The surface waves obey an eigenvalue operator equation that depends on four dimensionless parameters: the cylinder aspect ratio, the Bond number, the Ohnesorge number, and the elastocapillary number. A solution is constructed using a Rayleigh-Ritz variational procedure over a constrained function space, which is able to effectively incorporate the pinned edge boundary condition. Mode shapes are defined …

Improving Hexapod Platform Pose Accuracy - A Photogrammetry-Based Approach, Sourabh Karmakar

All Dissertations

The aim of this research is to make a newly constructed Stewart-Gough Platform-based test frame Tiger 66.1 operational by developing control software and estimating the error in its pose accuracy. The accuracy of the platform is affected by one source or multiple sources. The typical error sources are kinematic and structural, some of them originate from manufacturing imperfections, assembly deviations, elastic deformations, thermal deformations, and joint clearances which change the expected kinematic behavior of the manipulator. Also, some non-mechanical errors like transmission error, sensor accuracy, algorithm error, and truncation error in calculation contribute significantly in some cases. Using pose deviations …

Impacts Of Connected And Automated Vehicles On Energy And Traffic Flow: Optimal Control Design And Verification Through Field Testing, Tyler Ard

All Dissertations

This dissertation assesses eco-driving effectiveness in several key traffic scenarios that include passenger vehicle transportation in highway driving and urban driving that also includes interactions with traffic signals, as well as heavy-duty line-haul truck transportation in highway driving with significant road grade. These studies are accomplished through both traffic microsimulation that propagates individual vehicle interactions to synthesize large-scale traffic patterns that emerge from the eco-driving strategies, and through experimentation in which real prototyped connected and automated vehicles (CAVs) are utilized to directly measure energy benefits from the designed eco-driving control strategies. In particular, vehicle-in-the-loop is leveraged for the CAVs driven …

Cfrp Delamination Density Propagation Analysis By Magnetostriction Theory, Brandon Eugene Williams

All Dissertations

While Carbon Fiber Reinforced Polymers (CFRPs) have exceptional mechanical properties concerning their overall weight, their failure profile in demanding high-stress environments raises reliability concerns in structural applications. Two crucial limiting factors in CFRP reliability are low-strain material degradation and low fracture toughness. Due to CFRP’s low strain degradation characteristics, a wide variety of interlaminar damage can be sustained without any appreciable change to the physical structure itself. This damage suffered by the energy transfer from high- stress levels appears in the form of microporosity, crazes, microcracks, and delamination in the matrix material before any severe laminate damage is observed. This …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Vibration-Based Fault Diagnostics In Wind Turbine Gearboxes Using Machine Learning, Abdelrahman Amin

All Dissertations

A significantly increased production of wind energy offers a path to achieve the goals of green energy policies in the United States and other countries. However, failures in wind turbines and specifically their gearboxes are higher due to their operation in unpredictable wind conditions that result in downtime and losses. Early detection of faults in wind turbines will greatly increase their reliability and commercial feasibility. Recently, data-driven fault diagnosis techniques based on deep learning have gained significant attention due to their powerful feature learning capabilities. Nonetheless, diagnosing faults in wind turbines operating under varying conditions poses a major challenge. Signal …

Extensional Flows Of Polymer Solutions In Planar Microchannels, Mahmud Kamal Raihan

All Dissertations

Non-Newtonian fluids such as polymer solutions often flow under microscale extensional conditions in many natural and engineering flow fields such as in microfluidic chips, porous rocks, biological membranes and filters, printheads in additive manufacturing, etc. The changing cross sectional areas of the internal flow passages therein exert additional extension on the flow along with the shearing. Numerous studies have been dedicated to understanding the extensional flows of polymer solutions over the years. However, most of these studies only focused on flexible polymers exhibiting elasticity in their macroscopic rheology, whereas rigid polymers that portray shear-thinning but often elude elasticity in the …

Multiscale Modeling And Gaussian Process Regression For Applications In Composite Materials, Joshua Arp

All Dissertations

An ongoing challenge in advanced materials design is the development of accurate multiscale models that consider uncertainty while establishing a link between knowledge or information about constituent materials to overall composite properties. Successful models can accurately predict composite properties, reducing the high financial and labor costs associated with experimental determination and accelerating material innovation. Whereas early pioneers in micromechanics developed simplistic theoretical models to map these relationships, modern advances in computer technology have enabled detailed simulators capable of accurately predicting complex and multiscale phenomena.

This work advances domain knowledge via two means: firstly, through the development of high-fidelity, physics-based finite …

Applications Of Large Eddy Simulations To Novel Internal Combustion Concepts, Patrick O'Donnell

All Dissertations

Computational fluid dynamics (CFD) simulations of internal combustion engines (ICEs) are becoming an increasingly popular tool in the automotive industry to either explain experimentally observed trends or perform lower cost design iterations. The convenience of commercially available CFD software and advancements made in computing hardware have been the impetus behind this growing popularity. However, obtaining accurate results using these software packages is not a trivial process and requires an in-depth understanding of the underlying numerical methodology and sub models for various physical phenomena. Specific to the ICEs, CFD simulation often entails the use of models for detailed chemistry and combustion, …

Vibration Fatigue Of Leaded Solder Joint Interconnects For Pcb Electronics, John Crowder

All Theses

With the increasing prevalence of electronic equipment worldwide, there is also a decrease in the size of the components on their printed circuit boards (PCBs), leading to an increase in the density of these components. A significant amount of failure in electronic equipment is vibration fatigue of solder joints and their attachments. However, the complexity of these PCBs and their components has made finite element modeling (FEM) more complex, adding considerable time to create and analyze a model.

This paper aims to provide a literature review for the vibration fatigue of leaded solder components, create a test setup, and validate …

Characterization Of Mechanically Recycled Polylactic Acid (Pla) Filament For 3d-Printing By Evaluating Mechanical, Thermal, And Chemical Properties And Process Performance, Mahsa Shabani Samghabady

All Theses

Polylactic acid (PLA) is a biopolymer made from renewable resources such as sugar and corn. PLA filament is a popular material used in Fused Deposition Modeling (FDM) 3D-printing. While this material has many advantages, all the failed parts, support structures, rafts, nozzle tests, and the many prototype iterations during the 3D-printing process contribute to the plastic pollution and release of greenhouse gases. Although PLA is biodegradable, it can take years to degrade in landfills. Instead of throwing away PLA waste and buying new filaments, PLA can be recycled. Amongst the different recycling technologies, mechanical recycling is the most environmentally friendly. …

The Effect Of Deployment And Optimal Dispatch Of Shared Electric Shuttles On The Energy Efficiency Of Campus Transit, Robert Smith

All Theses

A problem facing most public transit systems is low energy efficiency and the continued cycling of large transport vehicles such as buses at low occupancy when low demand for transport exists, wasting energy to no benefit. To remedy this issue, we propose a hybrid system consisting of existing diesel buses and automated electric shuttles to augment the system during off-peak hours. Due to their smaller size, higher occupancy, and more efficient powertrains, these shuttles could reduce the system energy used per passenger-mile-traveled. Automation removes the labor cost of drivers and, thus, eliminates the need to employ more drivers for the …

The Influence Of Diversity Dimensions On Student’S Collaboration Success: What It Means For Workforce Development In Manufacturing, Oyinkansola Adeite

All Theses

Manufacturing productivity is measured by labor productivity which is the hourly output of the manufacturing economy. The recent reduction in productivity numbers by the United States Bureau of Labor Statistics emphasizes the need for workforce development. With globalization and technological advancements, diversity has emerged as a critical aspect for the workplace. By encompassing dimensions such as education, race, and age, diversity creates a tapestry of unique perspectives and experiences. This study’s aim is to figure out the effect of a diversity dimension on team performance using intelligent systems, and in addition, if extra dimensions of diversity further impact team performance. …

Life Cycle Energy Assesment Of Advanced Fiber Reinforced Composite Design And Manufacturing Methodologies, Urjit Lad

All Theses

Automotive industry at large is focused on vehicle light-weighting since a 6%-8% increase in fuel efficiency can be achieved with a 10% reduction in vehicle weight [1]. With the growing demand for cost-effective and sustainable light weighting of automobile structures, interest has increased in the application of fiber reinforced plastic (FRP) composites for use in the Body-in-White (BiW), which can account for up to 40% of the total vehicle weight. Traditional FRP composite manufacturing processes like vacuum assisted resin transfer molding, autoclave consolidation or use of automated fiber placement have been successfully used for marine and aerospace applications. However, these …

Influence Of Swirl And Turbulence In The Particle Removal Using Fog In A Pipe Flow, Nisarg T. Patel

All Theses

Fog-and-tube scrubbers are employed to remove harmful ultrafine aerosols, such as Diesel particulate matter (DPM), from an airflow. The underlying principle of this removal process involves enlarging the aerosol particles by coagulating them with fog drops, which are subsequently eliminated through inertial impaction onto the tube wall. Previous research conducted by Tabor et al. (2021) demonstrated an increase in scavenging of ultrafine DPM particles, ranging from 11.5 nm to 154 nm, by as large as 45% over the no fog case. This finding is crucial in addressing the challenges associated with conventional filtration methods for capturing ultrafine particles.

The present …

Dynamics And Steering Of A Vibration-Driven Bristle Bot In A Pipe System, Ian Stewart

All Theses

Soft vibrational robots are robots that incorporate compliant structures into their design and are driven by oscillating actuators. A recent, popular version of a soft vibrational robot is the bristle bot, which uses flexible bristles and a vibration motor to propel itself across surfaces and through pipes. This motion is primarily driven by stick-slip dynamics resulting from asymmetric frictional forces applied at the bristle tips. Depending on the frequency of vibration of the motor, the robot experiences various resonance regions allowing it to maneuver in different directions. Attaching bristles to all sides of the robot and placing it in a …

Investigation Of Fatigue Response With Analytical And Machine Learning Models And Hygroscopic Analysis Of Asymmetric Bistable Cfrp Composites, Shoab Ahmed Chowdhury

All Dissertations

Asymmetric bistable carbon fibre reinforced plastic (CFRP) composites enable a broad range of applications as they can sustain multiple stable configurations and have small snap-through load requirements. These unique features, coupled with their light strength-to-weight and stiffness-to-weight ratios, have made them preferred options for multifunctional systems. This study investigates the fatigue and hygroscopic response of 2-ply, [0/90] bistable CFRP laminates and proposes predictive modeling approaches for improved performance.

While previous studies widely researched and documented the fatigue of general composites in axial loading, fatigue analysis of asymmetric bistable composites in the out-of-plane snap-through direction is inadequate. This study performs fatigue …

Exploration Of Collaborative Design Spaces: Engineering Interactions And Workflows In Product Development, Frederick Rowell

Honors College Theses

Product Lifecycle Management (PLM) initiatives can improve an enterprise’s efficiency by increasing collaborative design opportunities within its business structure. PLM solutions provide digital mediums to collaborate on all aspects of a company’s workflow, including engineering, testing, manufacturing, marketing, business, and field support services. This paper examines the major PLM tools and software used to establish a collaborative engineering design space; computer-aided design (CAD), computer-aided engineering (CAE), computer-aided manufacturing (CAM), and product data management (PDM). The interactions between these PLM tools and a design team’s organizational structure are analyzed to determine some of the most effective PLM integration strategies to improve …

Understanding The Effect Of Nanointerfaces On Nanostructure And Mechanical Properties Of Semicrystalline Polymers Using Coarse-Grained Molecular Dynamic Simulations, Nayoung Kim

Honors College Theses

Polymer crystallization is a classical problem of polymer research. Many synthetic and natural polymers take the semi-crystalline form. Crystallization of polymers is a complex process associated with the partial alignment of their molecular chains. The final physical properties of semicrystalline polymers are determined by the degree of crystallinity and the size and orientation of the crystallites (nano- to micro-sized crystalline regions). Although it has been studied for many years, we still lack a fundamental understanding of the types of factors that influence the semicrystalline structure and how the structure affects the final properties. It is difficult because crystalline polymers are …

Mesoscale Modeling And Machine Learning Studies Of Grain Boundary Segregation In Metallic Alloys, Malek Alkayyali

All Dissertations

Nearly all structural and functional materials are polycrystalline alloys; they are composed of differently oriented crystalline grains that are joined at internal interfaces termed grain boundaries (GBs). It is well accepted that GB dynamics play a critical role in many phenomena during materials processing or under operating environments. Of particular interest are GB migration and grain growth processes, as they influence many crystal-size dependent properties, such as mechanical strength and electrical conductivity.

In metallic alloys, GBs offer a plethora of preferential atomic sites for alloying elements to occupy. Indeed, recent experimental studies employing in-situ microscopy revealed strong GB solute segregation …

Classification Of Electrical Current Used In Electroplastic Forming, Tyler Grimm

All Dissertations

Electrically assisted manufacturing (EAM) is the direct application of an electric current to a workpiece during manufacturing. This advanced manufacturing process has been shown to produce anomalous effects which extend beyond the current state of modeling of thermal influences. These purported non-thermal effects have collectively been termed electroplastic effects (EPEs).

While there is a distinct difference in results between steady-state (ideal DC) testing and pulsed current testing, the very definition of these two EAM methods has not been well established. A "long" pulse may be considered DC current; a "short" pulse may produce electroplastic effects; and even "steady-state" current shapes …