Engineering Commons^™

Improving Cast Steel Rail Coupler Fatigue Resistance Through Local Wire-Arc Additive Manufacturing, Andrew M. Bunge

Dissertations, Master's Theses and Master's Reports

Every year, thousands of cast-steel railcar couplers suffer from corrosion-initiated fatigue cracking in similar areas of the coupler’s knuckle; between 2015 and 2018 about 90,000 knuckles were replaced, otherwise these couplers would have been at risk for unexpected failures. These types of couplers have been common in industrial use as early as 1932, hence it is desirable for a countermeasure to the fatigue cracking that does not involve significantly altering the geometry or casting process. Wire arc additive manufacturing (WAM) is a developing technology which boasts the ability to produce complex near-net-shape components; however, less attention has been paid to …

Nickel Superalloy Composition And Process Optimization For Weldability, Cost, And Strength, Sophie A. Mehl

Dissertations, Master's Theses and Master's Reports

To advance sustainability efforts, electric power plants have reduced specific carbon dioxide emissions by increasing operating temperatures and pressures to improve power generation efficiency. The latest improvements are utilized in advanced ultra-supercritical power generation. To meet these operating conditions, nickel superalloys are used in the highest temperature components; however, they are expensive and present weldability challenges. This project aims to experimentally optimize a nickel superalloy to improve material weldability and decrease cost without compromising strength. Three optimized compositions were developed, and their microstructures and mechanical properties were compared to Nimonic 263, a common nickel superalloy in electric power plants. The …

Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa

Dissertations, Master's Theses and Master's Reports

Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …

Collagen V Promotes Fibroblast Contractility, And Adhesion Formation, And Stability, Shaina P. Royer-Weeden

Dissertations, Master's Theses and Master's Reports

Ehlers-Danlos syndrome, classical type, (cEDS) is a hereditary connective tissue disorder causing excessive elasticity and fragility of the connective tissue and problems with wound healing. Most cases of cEDS are caused by haploinsufficiency for collagen V. Collagen V regulates collagen fibril diameter. In cEDS fibroblast migration is impaired and integrin expression is altered.

The effects of collagen V on collagen gel ultrastructure and how it alters its mechanical properties were measured using scanning electron microscopy (SEM) and rheology respectively. Fibroblast contractility and adhesion dynamics were investigated to better understand the role of fibroblast disfunction in wound healing in cEDS. To …

Memory Optimizations For High-Throughput Computer Systems, Zhiyuan Lu

Dissertations, Master's Theses and Master's Reports

The emergence of new non-volatile memory (NVM) technology and deep neural network (DNN) inferences bring challenges related to off-chip memory access. Ensuring crash consistency leads to additional memory operations and exposes memory update operations on the critical execution path. DNN inference execution on some accelerators suffers from intensive off-chip memory access. The focus of this dissertation is to tackle the issues related to off-chip memory in these high performance computing systems.

The logging operations, required by the crash consistency, impose a significant performance overhead due to the extra memory access. To mitigate the persistence time of log requests, we introduce …

Benchmarking Model Predictive Control And Reinforcement Learning For Legged Robot Locomotion, Shivayogi Akki

Dissertations, Master's Theses and Master's Reports

This research delves into the realm of quadrupedal robotics, focusing on the comparative analysis of Model Predictive Control (MPC) and Reinforcement Learning (RL) as predominant control strategies. Through the comprehensive dataset compiled and the insights derived from this analysis, this research aims to serve as a valuable resource for the legged robotics community, guiding researchers and practitioners in the selection and implementation of control strategies. The ultimate goal is to contribute to the advancement of legged robot capabilities and facilitate their successful deployment in real-world applications.

In this study, we employ the Unitree Go1 quadrupedal robot as a testbed, subjecting …

Direct Recycling Of Lithium-Ion Battery Materials Using Physical Separation Methods., Tinuade Ololade Folayan

Dissertations, Master's Theses and Master's Reports

The increased demand for Lithium-ion batteries for Electric vehicles has influenced worldwide interest in the research and development of methods for recycling end-of-life Lithium-ion batteries. Direct recycling method has gained more attention in recent times as a method that is low-cost with the ability to recover all Lithium-ion battery materials without changing the chemical and structural properties of the recycled materials.

A lithium-ion battery contains a complex mixture of materials with significantly different physical properties. This work develops physical separation techniques as Direct recycling methods to recycle individual battery components without damaging the functional integrity of the recycled materials. In …

Alternative Method For Low Frequency Impact Sound Measurement For Building Field Tests, Sunit Girdhar

Dissertations, Master's Theses and Master's Reports

What do high heels, dog nails, and dragging furniture have in common? They are all frequent sources of noise pollution and annoyance in multi-story buildings. Building codes exist to control and mitigate such noise, but these codes are outdated and fail to protect the residents against noise annoyance. Footstep noise is still the number one cause of complaints among the residents. The impact performance of floor-ceiling assemblies is characterized using a single-number rating called the Impact Sound Rating (ISR). A standard tapping machine is used in pre-defined locations on the floor and the radiated Sound Pressure Level (SPL) is measured …

Evaluating Geomechanical Uncertainty In Open Pit Mine Planning, Evan Ricchio-Hitchcock

Dissertations, Master's Theses and Master's Reports

Open pit mine planning encompasses a variety of uncertainties. Uncertainty due to geomechanics is most critical for a safe operation in an open pit mine. Without sufficient knowledge of the geomechanical properties of the subsurface, a reliability analysis of the slope stability could be challenging. Slope stability is a crucial step in pit optimization since the cash flow analysis of a mine is constrained by a stable slope angle. However, obtaining a stable slope angle with certainty is difficult to achieve as geomechanical parameters are modeled using a very limited number of samples. This thesis proposes a method to integrate …

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Molecular Dynamics Modeling Of Polymers For Aerospace Composites, Swapnil Sambhaji Bamane

Dissertations, Master's Theses and Master's Reports

Polymer matrix composite materials are widely used as structural materials in aerospace and aeronautical vehicles. Resin/reinforcement wetting and the effect of polymerization on the thermo-mechanical properties of the resin are key parameters in the manufacturing of aerospace composite materials. Determining the contact angle between combinations of liquid resin and reinforcement surfaces is a common method for quantifying wettability. It is challenging to determine contact angle values experimentally of high-performance resins on CNT materials such as CNT, graphene, bundles or yarns, and BNNT surfaces. It is also experimentally difficult to determine the effect of polymerization reaction on material properties of a …

Predicting The Reactivities And Reaction Mechanisms Of Photochemically Produced Reactive Intermediates, Benjamin Barrios Cerda

Dissertations, Master's Theses and Master's Reports

Photochemically produced reactive intermediates (PPRIs) such as the hydroxyl radical, carbonate radical (CO₃^•-) singlet oxygen (¹O₂) and triplet state of chromophoric dissolved organic matter (³CDOM^*) are formed in sunlit natural waters upon photoexcitation of chromophoric dissolved organic matter (CDOM). PPRIs react with the organic compounds involved in key environmental processes, resulting in transformation products of smaller molecular weight than their parent compounds. Photochemical transformation of these key water constituents due to their reactions with PPRIs may pose potential effects on human and aquatic ecosystems. Consequently, there is a need …

Effect Of Sc On Recrystallization Resistance Of Aa7050, Keaton Schmidt

Dissertations, Master's Theses and Master's Reports

The extrusion process involves high temperatures and strains that can result in undesirable microstructures, especially along the surface. Extruded alloys tend to exhibit surface recrystallization during heat treating at regions of higher strains, which can lead to reduced fatigue strength and corrosion resistance. By adding Sc to AA7050, nano-sized dispersoids are formed with Sc cores and Zr shells that restrict recrystallization more than the base alloy that only utilizes Zr. Billets with varying Sc content and a control with only Zr were cast, and extrusions were made in order to compare surface microstructures at varying strains in the as-extruded and …

Quantifying The Impact Of Wide Base Tires On Pavement Performance In Michigan, Lei Yin

Dissertations, Master's Theses and Master's Reports

This study aimed to investigate the use of wide base tires (WBT) in Michigan to quantify the effect of different percentages of WBT loads on flexible and rigid pavements. Surveys and field investigations were conducted to quantify the WBT usage in Michigan. The JULEA (for flexible pavements) and Illislab (for JPCP) software programs were used to calculate the mechanical response between dual tire (DT) and WBT loads, while the Mechanical-Empirical (ME) pavement design process was utilized for damage accumulation and pavement distress analysis. Investigation results rationalized the assumption of WBT proportion for design purposes as 10% currently and up to …

Stability Of Linicoal-Oxide Electrode Material Under High-Temperature Ceramic Fuel Cell Conditions, Wei Zhang

Dissertations, Master's Theses and Master's Reports

LiNi0.8Co0.15Al0.05O2 (LNCA) is an important cathode material for room-temperature operation of lithium-ion batteries (LIBs). As an emerging research area, LNCA was recently applied as electrodes (both cathode and anode) for high-temperature ceramic fuel cells (CFCs) with impressive performances. However, the stability of LNCA electrode material under CFC operating conditions (i.e., reactive atmospheres and high temperatures) remains unknown. In this dissertation: (1) The stability of LNCA in air and H2 atmospheres was systematically evaluated at elevated temperatures (i.e., the operating electrode environments of H2-fueled CFCs). It was found that LNCA exhibited excellent stability in air within a wide temperature range from …

Joint Probability Analysis Of Extreme Precipitation And Water Level For Chicago, Illinois, Anna Li Holey

Dissertations, Master's Theses and Master's Reports

A compound flooding event occurs when there is a combination of two or more extreme factors that happen simultaneously or in quick succession and can lead to flooding. In the Great Lakes region, it is common for a compound flooding event to occur with a high lake water level and heavy rainfall. With the potential of increasing water levels and an increase in precipitation under climate change, the Great Lakes coastal regions could be at risk for more frequent and severe flooding. The City of Chicago which is located on Lake Michigan has a high population and dense infrastructure and …

Quantifying The Evolution Of Strengthening Mechanisms For Commercially Produced Niobium And Titanium Hsla Steel Sheet, Isabella M.W. Jaszczak

Dissertations, Master's Theses and Master's Reports

Strength uniformity along the coil length of commercially produced high-strength, low-alloy (HSLA) steel hot-rolled sheet is crucial to avoid the downgrading of product that does not meet strength specifications. In addition to contributing to precipitation strengthening through the growth of niobium-titanium carbides ((Nb,Ti)-C), niobium hinders austenite recrystallization and refines ferrite grain size. The potency of these strengthening mechanisms relies heavily on the austenite to ferrite transformation kinetics of the hot-rolling process. While niobium’s effect on precipitation strengthening, Hall-Petch strengthening, dislocation strengthening, and solute strengthening have all been studied in literature independently, the interactions of these mechanisms with each other and …

Optimizing The Extrudability Of 6082 Aluminum By Varying The Magnesium And Silicon Concentration, Eli A. Harma

Dissertations, Master's Theses and Master's Reports

Alloy 6082 aluminum is used for high-volume manufacturing in the automotive industry due to its high strength, impact performance, and corrosion resistance. However, given these improved properties, the alloy has decreased formability compared to other 6xxx series alloys, especially in the extrusion process. Controlling the dynamic recovery and recrystallization properties by changing the additions of Mg and Si can improve the hot deformation properties. Five alloys of varying Mg and Si concentrations between 0.6 to 1.2wt% Mg and 0.7 to 1.3wt% Si were made with constant concentrations of Cr, Fe, and Mn and the same homogenization heat treatment. The proposed …

Treating Contaminated Water: Predicting Reactivities Of Aqueous Organic Contaminants With Hydrated Electrons, And Development Of A Biogarden To Manage Greywater Discharge In Monteverde, Costa Rica, Rose C. Daily

Dissertations, Master's Theses and Master's Reports

Advanced reduction processes (ARPs) that generate highly reactive solvated electrons (e^-_aq) are a promising method for the destruction of conventional and emerging aqueous organic contaminants. While there is a large database of contaminant reactivity with e^-_aq in the literature, there is little information on the detailed elementary mechanisms for reduction of multifunctional group compounds and the impact of those functional groups on reactivity. As it is difficult to determine specific mechanisms through experiments and time consuming to measure reactivity, the development of computational approaches to elucidate mechanisms and predict reactivity is becoming increasingly important. In …

Study Of Nanocomposite Materials Using Molecular Dynamics, Prashik Sunil Gaikwad

Dissertations, Master's Theses and Master's Reports

There is an increase in demand for new lightweight structural materials in the aerospace industry for more efficient and affordable human space travel. Polymer matrix composites (PMCs) with reinforcement material as carbon nanotubes (CNTs) have shown exceptional increase in the mechanical properties. Flattened carbon nanotubes (flCNTs) are a primary component of many carbon nanotube (CNT) yarn and sheet materials, which are promising reinforcements for the next generation of ultra-strong composites for aerospace applications. These flCNT/polymer materials are subjected to extreme pressure and temperature during curing process. Therefore there is a need to investigate the evolution of properties during the curing …

Capturing Microstructural Heterogeneity And Predicting Local Transport Phenomena In Pemfc Catalyst Layers: A Comprehensive Network Modeling Approach, Shahriar Alam

Dissertations, Master's Theses and Master's Reports

A unique network architecture that captures the microstructural heterogeneity and predicts the local transport properties of PEMFC catalyst layers is proposed. Separate networks containing numerous cylindrical elements and nodes are generated that represent the solid and pore phase of the catalyst layer. Transport resistances are assigned to the elements while the nodes are volumeless. The networks are interlinked through nodes where local properties are stored. The generated computational grid's macroscopic behaviors (percolation behavior, gas diffusivity, and ion conductivity) will be matched against the experimental data for validation. Diffusion-like transport equations are applied to the networks that provide local water balance, …

On The Gaussian-Core Vortex Lattice Model For The Analysis Of Wind Farm Flow Dynamics, Apurva Baruah

Dissertations, Master's Theses and Master's Reports

Wind power science has seen tremendous development and growth over the last 40 years. Advancements in design, manufacturing, installation, and operation of wind turbines have enabled the commercial deployment of wind power generation systems. These have been due, in a large part, to the expertise in the simulation and modeling of individual wind turbines. The new generation of wind energy systems calls for a need to accurately predict and model the entire wind farm, and not just individual turbines. The commercial deployment of these wind farms depends on model's ability to accurately capture the different physics involved, each at its …

An Active Voice Coil Negative Stiffness Vibration Isolator With Application To Mobile 3d Printing, Lucas M. Schloemp

Dissertations, Master's Theses and Master's Reports

Equipment whose performance degrades when exposed to base vibration is often deployed in vibration-rich environments. Using 3D printers in mobile applications, such as vehicles and ships, are typical examples where the extruder and bedplate are easily excited by base vibration. A versatile active vibration isolator is considered in this thesis constructed using a voice coil actuator and a laser displacement feedback sensor to achieve a wide range of dynamic response characteristics, including negative stiffness. This approach permits transmissibility shaping to meet band-limited base isolation requirements without active damping vibration control. A combination of simulation and hardware validation is used to …

Programming The Bistable Dynamic Vibration Absorbers Of A 1d-Metastructure For Adaptive Broadband Vibration Absorption, Shantanu H. Chavan

Dissertations, Master's Theses and Master's Reports

This research addresses a critical challenge in structural engineering—achieving comprehensive vibration control and energy dissipation in meta-structures. Departing from the limitations of passive structures with fixed bandgaps, we propose an innovative approach utilizing active meta-structures capable of dynamically tuning their bandgaps. The primary goal is to introduce an efficient method for programming meta-structures with multiple variable bandgaps, thereby enabling effective vibration attenuation across a broad frequency spectrum.

The methodology involves transforming passive resonators into bistable adaptable Dynamic Vibration Regulators (DVRs) through a sophisticated switching mechanism. This adaptation sets the stage for numerous unique combinations by independently switching each resonator. A …

Bioaccumulation Of Polychlorinated Biphenyl Compounds And Mercury In A Mining Impacted Aquatic Ecosystem, Michelle Bollini

Dissertations, Master's Theses and Master's Reports

The Keweenaw area continues to be influenced by the century of copper mining that ended nearly 50 years ago. This project is focused on Torch Lake, an aquatic ecosystem that has been heavily impacted by mining waste disposal. The watershed has been impaired by mine discharge and tailings, smelter and smokestack plumes, and poor waste disposal practices. The lake is listed as a Great Lakes Area of Concern with beneficial use impairments of restrictions on fish consumption and a degraded benthic community. Polychlorinated biphenyl compounds (PCBs) and methylmercury (MeHg) are persistent, bioaccumulative, and toxic substances (PBTs). These contaminants pose threats …

Dynamic Mode Decomposition Approach For Estimating The Shape Of A Cable, Yash Manik Chavan

Dissertations, Master's Theses and Master's Reports

This study investigates the dynamic behavior of a flexible cable with heterogeneous stiffness using a data-driven approach. The study aims to develop accurate models describing intricate structures with rigid or flexible components. To achieve this, reflective markers were attached to the cable at equal spacing, and the motion was manually excited and captured using an 8-camera setup and OptiTrack's Motive software.

The cable displacement data at the marker locations were used as initial conditions for various Dynamic Mode Decomposition (DMD) models. The performance of the data- driven cable model is compared against the performance of the DMD modeling approach, fitting …

Microscopic And Laboratory Scale Characterization Methods To Evaluate Biomass Deconstruction, Meenaa Chandrasekar

Dissertations, Master's Theses and Master's Reports

Renewable fuels from lignocellulosic biomass are an appealing option because they can seamlessly integrate into the existing fuel distribution infrastructure. Lignocellulosic biomass constitutes nonedible plant material obtained from plant cell walls. The natural recalcitrance of lignocellulosic biomass poses a challenge in accessing the cell wall carbohydrates during biochemical conversion. Despite various approaches, enzymatic hydrolysis of lignocellulosic biomass remains economically impractical due to incomplete knowledge about biomass recalcitrance and the influence of environmental factors on biomass quality.

The first goal of this dissertation was to construct a microfluidic imaging reactor to better understand the tissue-specific deconstruction of plant materials. Confocal laser …

Exploring Ph Gradient Phenomena In Non-Linear Electrokinetic Microfluidic Devices, Azade Tahmasebi

Dissertations, Master's Theses and Master's Reports

Electrokinetic microfluidics is a versatile technology utilized within lab on a chip (LOC) devices for diagnostic and analytical applications; advantages include reduced resource demands, flexibility, and simplicity of use. Dielectrophoresis (DEP) is a precision nonlinear electrokinetic tool utilized within microfluidic microdevices to induce polarization and control bioparticle motions for applications that range from hemoglobin separations to cancer cell isolation and detection. Despite promising results, undesired side phenomena can occur in electrokinetic systems which impede reproducibility and accuracy. These unfavorable phenomena have not been comprehensively explored in the literature. Prior preliminary research suggests the fundamental phenomena originate from microelectrodes utilized in …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Developing A Regional Scale Landslide Early Warning System In A Data-Sparse Region Using Remote Sensing, Geostatistics, And Google Earth Engine, Vishnu Chakrapani Lekha

Dissertations, Master's Theses and Master's Reports

The Landslide Early Warning System (LEWS) is a non-structural approach to mitigate landslide risk by alerting vulnerable communities at an early stage. This study aimed to develop a regional LEWS for rain-induced shallow landslides in Idukki, a mountainous district in India with sparse rainfall data. The landslide model consists of a rainfall component and a slope stability component. Satellite precipitation data can be used in data-sparse regions, but they must be calibrated because they tend to underestimate rainfall. To improve the accuracy of satellite data, this study used a geostatistics-based multi-criteria approach to identify optimal locations to install new rain …