Mechanical Engineering Commons^™

On The Structure, Energy, And Segregation Behavior Of Grain Boundaries In Metallic Systems, Yasir Mahmood

All Dissertations

Nearly all structural metallic systems are multi-component polycrystalline aggregates; their microstructures are composed of crystalline grains that are internally joined at grain boundaries (GBs). This thesis focuses on GB structure, energy, and chemistry, as these greatly influence many material properties and processes, including boundary dynamics during processing treatments or under operating conditions.

Using atomistic simulations, we examine the impact of metastable GB structures on solute segregation. A wide range of GB geometries and metastable structures are used in our study. The Al-Mg alloy is used because it is of interest for light weighting. The atomistic simulation results are used to …

Linear And Nonlinear Topology Optimization With Morphing Beam Networks, Andrew S. Montalbano

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Topology optimization (TO) is an engineering design discipline dedicated to optimizing material distribution within a given domain. In traditional gradient-based topology optimization, the solid domain is discretized into small volumetric elements. Using finite element analysis (FEA) of the structure, the gradient of the objective function with respect to the design variables (the pseudo densities) is computed, and these design variables are updated iteratively until convergence is achieved. Although gradient-based TO methods are well-established, sensitivity analyses of objective functions and constraints can be both mathematically complex and computationally intensive. The nonconvex nature of most TO problems often complicates efficient convergence. Furthermore, …

Hybrid Physics-Infused Machine Learning Framework For Fault Diagnostics And Prognostics In Cyber-Physical System Of Diesel Engine, Shubhendu Kumar Singh

All Dissertations

Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result, the demand for new cognitive fault diagnosis algorithms is the need of the hour. Existing deep learning algorithms can detect, classify, and isolate faults. Still, most depend solely on data availability and do not incorporate the system's underlying physics into their prediction. Therefore, the results generated by these fault-detecting algorithms sometimes need to make more sense and deliver when tested in actual operating conditions.

Similar to diagnosis, the fault prognosis of diesel engines is paramount in numerous industries. …

Novel Vector Assignment Approach For Inherent Strain Modeling Of Laser Powder Bed Fusion Manufacturing, Lucas M. Morand

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The expansion of the design space due to additive manufacturing (AM) has been a large motivator for the success of this family of processes. Despite the complexity of the physics in metal laser powder bed fusion AM causing significant stresses and strains in finished parts, the design advantages and subsequent performance improvements continue to drive the expansion of AM. Because the trial-and-error approach to AM part development is cost prohibitive, simulation of prints has become crucial. However, full thermo-mechanical simulation is susceptible to the same pitfall of time and computational cost in order to attain part-scale results. The development of …

Multifunctional Surfaces By Ultrafast Laser Multiscale Surface Structuring, Kewei Li

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Surface structures are crucial for regulating surface functions, including self-cleaning, surface coloration, and anti-fouling, which are of significance in various applications such as prolonging the lifetime of the solar cells, anti-counterfeiting marking, and enhancing the vessel’s performance. Ultrafast laser technology emerges as a revolutionary approach for surface structuring, distinguished by its exceptional precision, high throughput, versatility across materials, and remarkable processing efficiency. Despite the intensive study in the ultrafast laser surface structuring area, the fundamental mechanisms accounting for the ultrafast laser-induced surface structures are still not well understood. The correlation among laser processing parameters, surface structures, and surface functions remains …

Numerical Simulation Of Laser Induced Elastic Waves In Response To Short And Ultrashort Laser Pulses., Alireza Zarei

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In an era of intensified market competition, the demand for cost-effective, high-quality, high-performance, and reliable products continues to rise. Meeting this demand necessitates the mass production of premium products through the integration of cutting-edge technologies and advanced materials while ensuring their integrity and safety. In this context, Nondestructive Testing (NDT) techniques emerge as indispensable tools for guaranteeing the integrity, reliability, and safety of products across diverse industries.

Various NDT techniques, including ultrasonic testing, computed tomography, thermography, and acoustic emissions, have long served as cornerstones for inspecting materials and structures. Among these, ultrasonic testing stands out as the most prevalent method, …

Quantifying Hurricane Effects On Housing: Evaluating Damage, Loss, And Shelter Demands Using Historical And Simulated Storm Tracks, Adish Deep Shakya

All Theses

This research introduces an advanced framework which employs parametric wind field models for peak wind speeds, and building fragility curves, loss functions, and demographic data to estimate for estimating housing damage and loss. The uninhabitable units immediate displaced households, short-term and long-term shelter need households are determined. with a particular focus on those eligible for FEMA assistance. The framework's validity is reinforced by a high correlation in the analysis of recent hurricane events between estimated numbers of displaced households and actual FEMA aid recipients, where FEMA aids about 20-60% of the predicted long-term displaced households. A novel application of the …

Digital Twin In Military Ground Vehicles: Design And Predictive Maintenance, Conner W. Eddy

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Digital twin technology builds upon virtual engineering models, computer simulation, and real-time field data streaming to enable next-generation designs and predictive maintenance. A digital twin is a computer-based high-fidelity collection of models that predicts the performance of dynamic systems per operating cycles, input feature parameters, and data communication from a physical plant. Product Lifecycle Management (PLM) is growing in importance and is central to virtual design processes where the digital twin toolset fits into this emerging architecture. The product design process can be advanced using digital twin resources by eliminating the need for, and cost from, continual physical prototyping, reliability …

Deep Reinforcement Learning Of Variable Impedance Control For Object-Picking Tasks, Akshit Lunia

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The increasing deployment of robots in industries with varying tasks has accelerated the development of various control frameworks, enabling robots to replace humans in repetitive, exhaustive, and hazardous jobs. One critical aspect is the robots' interaction with their environment, particularly in unknown object-picking tasks, which involve intricate object weight estimations and calculations when lifting objects. In this study, a unique control framework is proposed to modulate the force exerted by a manipulator for lifting an unknown object, eliminating the need for feedback from a force/torque sensor. The framework utilizes a variable impedance controller to generate the required force, and an …

Improved Ballistic Impact Resistance Of Nanofibrillar Cellulose Films With Discontinuous Fibrous Bouligand Architecture, Colby Caviness

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Natural protective materials offer unparalleled solutions for impact-resistant material designs that are simultaneously lightweight, strong, and tough. Particularly, the dactyl club of mantis shrimp features chitin nanofibrils organized in a Bouligand structure, which has been shown to effectively dissipate high-impact energy during powerful strikes. The mollusk shells also achieve excellent mechanical strength, toughness, and impact resistance with a staggered, layer-by-layer structure. Previous studies have shown that hybrid designs, by combining different bioinspired microstructures, can lead to enhanced mechanical strength and energy dissipation capabilities. Nevertheless, it remains unknown whether combining Bouligand and staggered structures in nanofibrillar cellulose (NFC) films, forming a …

The Effect Of Football Facemask Design Variability On Dynamic Impact Performance And Quasi-Static Stiffness, Adam W. Smith

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This research addresses the role of facemasks in helmet systems, focusing on their dynamic impact performance and material properties. A total of 150 facemasks from 30 types and five helmets were tested both quasi-statically and dynamically. The facemasks were grouped by style and helmet type for comparison. Dynamic testing involved three different locations and two speeds, with data collected for maximum angular velocity and linear acceleration. Quasi-static stiffness, performed at two locations, was compared with collected dynamic results to determine the strength of relationship. A concussion metric, HARM, was calculated from collected data and compared across style groups.

Significant differences …

Study Of Electrospun Nanocomposite Nanofiber Nonwoven Mats With Precursor Solutions Prepared By Ultrasonic Processing, Stephanie Tussey

All Dissertations

Understanding the complexity of changes in a polymer solution through the addition of nanoparticles and the process used to prepare the solutions is vitally important to obtain desirable characteristics of electrospun nanofibers such as degree of crystallinity, morphological, thermal and mechanical properties. Although there have been significant efforts in this research area, a more in-depth understanding on how nanoparticles can affect the formation of polymeric structures during electrospinning is still needed to ensure overall quality and performance of the nonwoven material. The present study aimed to specifically explore the relationship between solution processing method, nanoparticle volume fraction, and solution properties …

A Manufacturing-To-Response Pathway For Manufacturing Optimization Of Carbon Fiber Reinforced Polymer Composite Structures, Madhura Limaye

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Over the past decade, there has been an increased adoption of thermoplastic and thermoset based continuous carbon fiber reinforced polymer (CFRP) composites for structural applications in several industries. Among the different manufacturing methods, thermoforming process for thermoplastic based continuous CFRP’s offer a major advantage in reducing cycle times for large scale productions. Similarly, out-of-autoclave curing process for thermoset based continuous CFRP’s using heated tooling enables production of large composite structures. However, these manufacturing processes can have a significant impact on the structural performance of parts by inducing undesirable effects. These effects include inhomogeneous fiber orientations, thickness variations, and residual stresses …

Oscillations Of Capillary Surfaces With Volume And Edge Effects, Dingqian Ding

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Capillary surfaces are defined by an interface endowed with surface tension that is partially supported by a solid substrate and are susceptible to oscillations reflecting a balance between fluid inertia and the restorative force of surface tension. The wave dynamics strongly depend upon volume change within the domain and edge effects through the boundary conditions applied at the contact-line formed at the liquid-gas-solid interface, while the spatial wave structure conforms to the geometry of the capillary surface. This dissertation develops mathematical models to address these effects for several canonical capillary surfaces, which are organized into two parts that are focused …

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

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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 …

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 …

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

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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 …

Finite Element Analysis On Laser Sintering Of Ceramic Materials, Shardul Sharma

All Theses

Laser sintering of ceramics plays a vital role in advanced additive manufacturing due to its precise fabrication of complex ceramic structures, localized heating and microstructural control. It allows the production of complex and customized ceramic parts for applications such as the aerospace industry and biomedical devices. However, due to the high thermal gradients produced during the process, laser sintering technology faces fundamental challenges, such as thermal stresses and crack formation. Establishing a valid numerical model to guide the ceramic laser sintering process, which predicts the thermal and mechanical behavior of the component, is necessary.

In this work, the modified Skorohod-Olevsky …

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

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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 …

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 …

Trust-Based Variable Impedance Control And Passivity-Based Switched System Analysis For Human-Robot Cooperative Manipulation, Zhanrui Liao

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Human-robot cooperative manipulation (co-manipulation) is one of the most prominent human-robot collaboration (HRC) tasks, where humans and robots manipulate the same object. Trust in HRC is crucial in determining human acceptance of robots and, hence, robot utilization. A probabilistic dynamic Bayesian network (DBN) trust model that integrates a time-series trust model is presented in this thesis. The trust model is learned using a continuous and normalized Baum-Welch (BW) algorithm, devised to account for the continuous nature of trust evolution and the limitations of the classic parameter learning method. To ensure a good HRC in co-manipulation, a variable impedance control framework …

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

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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 …

Femtosecond Laser Shock Peening And The Dynamics Of Femtosecond Laser-Induced Shock Waves, Yuxin Li

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Laser shock peening (LSP) is an important material surface strengthening technique that uses laserinduced shock waves to cause severe plastic deformation near material surfaces. It can significantly improve material properties like hardness, strength, fatigue life, and corrosion resistance and is widely used in industrial sectors such as automotive, aerospace, nuclear, and medical areas. The conventional nanosecond laser shock peening (ns-LSP) has demonstrated effectiveness but faces challenges such as complex setup, low throughput, high energy consumption, and inflexibility for complex geometries. Femtosecond laser shock peening (fs-LSP) offers a promising alternative to overcome these issues, thanks to its ultra-high laser intensity and …

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 …

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

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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 …

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 …

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

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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

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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 …

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

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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 …

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

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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 …