Engineering Commons^™

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), …

Directional Dependent Fracture Characteristics Of 3d Printed Mechanical Metamaterials, Thomas Draper

Dissertations, Master's Theses and Master's Reports

Structural metamaterials, such as lattice metamaterials, are engineered cellular structures designed to achieve properties not achievable by natural materials. They enable mechanical properties unattainable by homogeneous solid materials and offer optimal properties for these materials tunable for specific applications in industries such as automotive, medical, and aerospace. Recent findings have revealed unique tunable mechanical properties such as negative Poisson's ratio, high strength-to-weight ratio, anisotropic stiffness, and much more. While the elastic and wave propogation properties of many lattice metamaterials are well investigated, the fracture properties are not well explored. However, their low fracture toughness is a bottleneck for their use …

Stable Energy-Efficient Macro-Scale Partial Flow-Boiling Operations Using Microstructured Surfaces And Ultrasonics, Divya Kamlesh Pandya

Dissertations, Master's Theses and Master's Reports

Controlled but explosive growth in vaporization rates is made feasible by ultrasonic acoustothermal heating of the microlayers associated with micro-scale nucleating bubbles within the microstructured boiling surface/region of a millimeter-scale single-channel heat exchanger (HX) – part of a typically multi-channel heat-sink. The experiments illustrate the achievement of a remarkably high stable heat flux (10 – 80 W/cm²) for a partial flow-boiling-based cooling approach and exceptional efficiency through active/passive enhancement in the vaporization rates into the heterogeneously nucleated micro-bubbles (through acoustothermal heating of their microlayers) and their removal rates (typically within the passive microstructured region of boiling). A controlled …

Application Of Fusion Based Deep Learning Models To Improve Millimeter Wave Beamforming, Abishek Subramanian

Dissertations, Master's Theses and Master's Reports

This study addresses the challenge of selecting millimeter Wave (mmWave) beamforming pairs for vehicle-to-infrastructure (V2I) communication, to mitigate latency in highly dynamic vehicular environments. We investigate the use of out-of-band sensor data as side information to model mmWave ray tracing paths and predicting a subset of top-K optimal beamforming pairs for efficient and low-latency searches. Unimodal-Fusion Deep Learning (F-DL) networks was applied to enhance mmWave beamforming process. We started by first investigating the centralized architecture, and then explored a novel distributed architecture through federated learning to minimize resource and latency overheads. The distributed architecture incorporates two biased client selection strategies: …

Aluminum Critical Mineral Production Feasibility Via Landfill Mining: Preliminary Study Of Potential Project Locations And Co-Benefits, Anabel M. Needham

Dissertations, Master's Theses and Master's Reports

In 2022, aluminum was named a critical mineral by the United States Geological Survey (USGS) and the global demand for aluminum is projected to increase by 40% from 2020 to 2030 (Aleksić 2023). There are currently no large-scale bauxite mines in the United States to contribute to aluminum production, and this study aims to investigate the feasibility of aluminum landfill mining in the United States to produce secondary aluminum. The feasibility of landfill mining for the purpose of recovering materials and energy is a relatively new technology, and often co-benefits are required to make these projects economically viable. Publicly available …

Gravity Fed Hopper Flow Of Bulk Solids For Lunar Isru, Jason Bendixen Noe

Dissertations, Master's Theses and Master's Reports

With the return to the moon in the decade of the 2020s, there has been a renaissance of lunar technology development and innovation. This has been particularly true for the area of lunar ISRU (In-Situ Resource Utilization). One key area in ISRU that has been neglected is lunar regolith storage hopper research. Many lunar regolith ISRU researchers use storage hoppers in their work but do not document the properties when designing the hoppers or do not have the information at hand. Because of this, hopper design and documentation are poorly understood, and more research is needed. Hoppers are vital for …

Assessing Wave Dynamics Induced Coastal Flooding Along The Southern Shores Of Lake Superior, Saumik Mallik

Dissertations, Master's Theses and Master's Reports

This study provides a comprehensive assessment of coastal hazards along the southern shores of Lake Superior, encompassing the interplay of static water levels, surges, and the amplifying effects of wave dynamics. Employing 51 years of historical water level data from five gauge stations in the US portion of Lake Superior, the study conducts extreme value analysis to estimate return levels over various return periods (25, 50, 100, and 500 years) for static water levels and surges. In parallel, Significant Wave Heights (SWH) data generated from the Simulating Waves Nearshore (SWAN) model is calibrated through a multi-step procedure based on historical …

Transient Simulations Of Power Systems With Inverter Interfaced Resources, Gaurish Shreedhar Gokhale

Dissertations, Master's Theses and Master's Reports

Renewable energy sources are interfaced with the electrical grid using power electronic inverters. These inverter-interfaced resources have been deployed for nearly 20 years. Still, NERC only recently highlighted the vast gap between the actual behavior of these inverters during power system transients and those observed in simulations. Simulation models need significant improvements, mainly for developing accurate inverter current controls, phase-locked loops, and fault response during different power priority modes. Additionally, only time-domain electromagnetic transient simulation tools can fully represent the fault response of the inverter-interfaced resources.

The developed simulation model of the inverter-interfaced resource is based on the recommendations made …

The Integration Of Neuromorphic Computing In Autonomous Robotic Systems, Md Abu Bakr Siddique

Dissertations, Master's Theses and Master's Reports

Deep Neural Networks (DNNs) have come a long way in many cognitive tasks by training on large, labeled datasets. However, this method has problems in places with limited data and energy, like when planetary robots are used or when edge computing is used [1]. In contrast to this data-heavy approach, animals demonstrate an innate ability to learn by communicating with their environment and forming associative memories among events and entities, a process known as associative learning [2-4]. For instance, rats in a T-maze learn to associate different stimuli with outcomes through exploration without needing labeled data [5]. This learning paradigm …

Matrix Stiffness Sensing By Nascent Adhesions And The Role Of Riam In Adhesion Assembly, Nikhil Mittal

Dissertations, Master's Theses and Master's Reports

Mechanical stiffness of the extracellular matrix (ECM) impacts many cellular functions such as proliferation, migration, and differentiation. ECM stiffness is sensed by a cell via integrin-based focal adhesions (FAs) by changing conformation and biochemical activities of molecules within FAs by the exchange of the force between the ECM and filamentous actin (F-actin). Cells in turn respond to this stiffness by generating traction force that plays an important role in many biological events such as tissue morphogenesis, stem cell differentiation, wound healing, and cancer cell metastasis. The stiffness of the extracellular matrix induces differential tension within integrin-based adhesions. Understanding stiffness sensing …

Developing Robust Autonomous Vehicles With Ros, Dylan J. Kangas

Dissertations, Master's Theses and Master's Reports

The demand for autonomous vehicles (AVs) is rising across both military and civilian sectors. These unmanned systems offer numerous advantages, such as improved efficiency, safety, and adaptability. Addressing this demand requires the development of resilient and versatile autonomous vehicles crucial for the transport and reconnaissance markets.

The sensory perception of autonomous vehicles of any kind is paramount to their ability to navigate and localize in their environment. Factors such as sensor noise, erroneous readings, and deliberate attacks should all be considered when developing a robust autonomous system. This work aims to quantify the degradation of sensor data which causes mapping …

Anaerobic Reductive Bioleaching Of Manganese Ores, Neha Sharma

Dissertations, Master's Theses and Master's Reports

Manganese extraction by biological methods is a green and economical way to produce manganese from low as well as high grade manganese ores. This is especially important for US ores, which are primarily either small in extent, low-grade with a high iron content, or both. They are therefore not suitable for conventional mining, which is very capital-intensive and requires a large up-front investment and are therefore imported at high costs. The goal is therefore to develop a process that can be applied at small scales, with minimal startup costs, and low equipment and labor requirements. It is also critical to …

Wave Energy Converter Wave Force Prediction Using A Neural Network, Morgan Kline

Dissertations, Master's Theses and Master's Reports

Due to the unpredictable nature of large bodies of water, wave energy can be a difficult renewable resource to rely on. One way to make Wave Energy Converters (WECs) more efficient is to apply a control strategy. In many control solutions, it is assumed that the wave excitation force is known into the future. In many instances, especially with complex waveforms, this is simply not the case. Simulation studies have shown the promise of wave force prediction using neural networks. This study demonstrates this experimentally and aims to characterize the important factors when designing such a network. Several wave elevation …

Modeling Of Inverter-Based Resources For Hardware In The Loop Testing Of Protection And Control Schemes, Md Aamir Rahmani

Dissertations, Master's Theses and Master's Reports

High penetration of inverter-based resources (IBR) may cause the misoperation of protective relays due to the dynamic nature of fault currents fed by the IBR during short-circuit faults. Misoperation may cause damage to power system equipment and affect the reliability of the power system. This dissertation presents an in-depth investigation into the modeling of IBR in the context of transmission line fault scenarios to understand and analyze the characteristics of fault currents fed by the IBR. The research objectives encompass the development of reliable IBR models capable of accurately replicating fault current behaviors, designing IBR operation control schemes, and implementing …

Halide-Assisted Growth Of Transition Metal Dichalcogenides, Vinaayak Sivam Balasubramaniam

Dissertations, Master's Theses and Master's Reports

Monolayers of transition metal dichalcogenides (TMDCs) have attracted significant attention as the rare two-dimensional (2D) semiconducting materials with a direct energy band gap. Chemical vapour deposition (CVD) is one of the scalable techniques to grow atomically thin TMDC monolayers in high quality, but it requires high growth temperature. Herein we report the growth of MoS2, WS2 and MoSe2 by a one-step halide-assisted CVD method using NaCl and KCl as the catalysts. These halides could reduce the growth temperature of TMDCS by reacting with the precursors (TMDC powders) to form volatile intermediate compounds as the growth species. We use optical microscopy, …

Continuous, Platform Purification Of Viral Products Using Aqueous Two-Phase Extraction, Natalie M. Nold

Dissertations, Master's Theses and Master's Reports

Cell and gene therapies, a ground-breaking class of drugs that can heal genetic diseases and cure cancer, often have treatment costs over $1 million. Most cell and gene therapies are delivered using virus-based delivery vectors, which are incredibly expensive to manufacture. Liquid chromatography is the favored method of viral vector purification since it is easily scalable and can be functionalized to purify by biospecificity, charge, hydrophobicity, or size. However, chromatography-based purification processes are highly expensive and usually only recover 20-50% of the viral vectors. There is currently no platform purification strategy for viral vectors due to differences in their surface …

Optimizing Diabetes Diagnostics: Electrophoretic Separation And Detection Of Hemoglobin A1c With Boronate, Rixlie Fozilova

Dissertations, Master's Theses and Master's Reports

Diabetes affects 537 million people worldwide, while 136 million Americans have diabetes or prediabetes; roughly 22.6% of individuals are undiagnosed. Diabetes is the inability to regulate blood sugar levels. Hemoglobin A1c (HbA1c) is glycosylated hemoglobin and indicates average blood sugar levels over the past three months.

We adapted the selective boronic acid binding to the HbA1c sugar moieties from boronate affinity chromatography and translated it into a portable microchip paper-based electrophoresis platform. We explored a range of boronate concentrations at a steady voltage and sample volume to determine the optimal HbA1c binding and subsequent electrophoretic separation. A pH above 11 …

Multi-Functional Gelatin-Dithiolane Hydrogels For Tissue Engineering, Saad Asim

Dissertations, Master's Theses and Master's Reports

Biomaterials that integrate multiple functionalities, mimic the extracellular matrix (ECM) microenvironment to support cellular growth, and adhere robustly to damaged tissues are highly needed to advance tissue engineering. Protein-based biomaterials are promising due to their inherent biocompatibility, biomimicry, biodegradation, and cell-supportive properties. Herein, by leveraging the unique ability of dithiolanes to generate on-demand in-situ thiols, we developed a new class of dithiolane-modified, protein-based biomaterial that combines unique, seemingly opposing functions for tissue engineering. Dithiolane-modified gelatin, a model protein used herein, enabled photoinitiator-free photo-crosslinking to form multi-functional gelatin-dithiolane (GelDT) hydrogels, which displayed exceptional long-term stability in cell culture media (>28 …

Initial Solution Improvements To A Tethered Robotic Path Planner Using Random Geometric Graph Configurations And Biased Sampling, Austen J. Goddu

Dissertations, Master's Theses and Master's Reports

With NASA's ongoing efforts to establish a presence on the lunar surface to eventually move on to exploring mars, the development of intelligent robotic systems is more important than ever. The ability of robotics to explore hazardous and extreme terrain, coupled with long communication times from earth places an ever increasing need on more robust and efficient autonomy. Tethered robotics offer unique advantages to explore scientific targets both on the lunar and martian surfaces, capable of using their tether as a physical or metaphorical lifeline to allow the exploration of slopes, extreme dark regions, or areas in which wireless communication …

Design, Testing And Neural Network Modeling Of A Low-Friction Wave Energy Converter Testbed, Vasu Bhardwaj

Dissertations, Master's Theses and Master's Reports

Point absorber wave energy converters (WECs) transform water wave kinetic energy into other useful forms, typically electrical. While it’s possible to extract energy from passive WECs, more energy can be captured using active control where its power take-off (PTO) acts as both a generator and an actuator. Control strategies usually require accurate models often obtained during model-scale testing. Unfortunately, friction can dominate the dynamic response in small WEC models. A frictionless point absorber WEC testbed is described in this report which allows the researcher to focus on fundamental hydrodynamic behavior instead of friction. It uses air bearings for vertical motion …

Comprehensive Review And Development Of A High-Pressure Hydraulic Impedance Tube For Vibroacoustic Attenuator Characterization, Matthew D. Beals

Dissertations, Master's Theses and Master's Reports

This research establishes a versatile test bench for characterizing hydraulic vibroacoustic attenuators. The primary evaluation metric is the transfer matrix, determined experimentally, with an emphasis on key properties such as transmission loss. To ensure accuracy and broad applicability, the methodology is based on industry-standard techniques for determining the transfer matrix. A comprehensive literature review consolidates existing approaches for hydraulic attenuator characterization. The test bench features a hydraulic impedance tube equipped with eight dynamic pressure transducer (DPT) taps strategically positioned before and after the sample interface. This setup accommodates arbitrary samples terminated with standard hydraulic fittings. Using ASTM E2611, the transfer …

Analytical And Machine Learning Modeling Of Direct Carbonation Of Natural Silicate Minerals, William Hanson

Dissertations, Master's Theses and Master's Reports

The climate-altering effects of atmospheric CO₂ make it necessary to develop innovative technologies that can remove it from the atmosphere. Mineral carbonation is a scalable technology to sequestrate and store CO2 in a stable carbonate mineral form. The efficiency of the mineral carbonation process depends on both feed mineralogy and process parameters. Comprehensive modeling and prediction of mineral carbonation efficiency for different CO₂ – reactive rocks has not been achieved in the past. In this thesis work, analytical and machine learning models are developed to predict the carbonation efficiency of dunite reactions. It is found that random forest …

Enhancing Resilience Of Critical Infrastructural Systems Against Severe Weather Conditions, Miaomiao Li

Dissertations, Master's Theses and Master's Reports

As climate change intensifies natural hazards and extreme weather events, critical infrastructure systems like power networks and pavements are increasingly vulnerable to damage. While significant progress has been made in studying individual hazards for specific systems, there remains a need for comprehensive frameworks addressing parametrized fragility for key components in critical infrastructure and their application in system risk and resilience evaluation. This dissertation investigates the failure mechanisms and fragility of power systems and pavements under extreme conditions, including winter storms, hurricanes, heatwaves, and flooding. Using structural analysis, numerical modeling, and statistical methods, this work evaluates system vulnerabilities, develops fragility models, …

Enhancing Privacy While Revealing Vulnerabilities: Strategies For Adaptation, Optimization, And Model Extraction, Madhureeta Das

Dissertations, Master's Theses and Master's Reports

In the evolving landscape of machine learning and artificial intelligence, this dissertation presents a series of innovative contributions spanning several critical areas: embracing semi-supervised domain adaptation for secure knowledge transfer, enhancing the model performance of tiny models, and executing model stealing attacks via diversified prompts. The overarching goal is to enhance the performance, scalability, and security of AI models across various applications.

The first research focus is on semi-supervised domain adaptation within federated learning frameworks. By leveraging semi-supervised learning techniques, this work addresses the challenge of adapting models trained on a source domain to perform effectively on a target domain …

Investigating Chloride Ingression In Concrete And Chloride-Induced Rebar Corrosion, Peifeng Su

Dissertations, Master's Theses and Master's Reports

The durability of reinforced concrete (RC) structures in chloride-rich environments is compromised due to steel reinforcement corrosion. This dissertation investigates chloride-induced corrosion in concrete containing supplementary cementitious materials (SCMs) and corrosion inhibitors through experimental and numerical methods.

First, the correlations between commonly used parameters and the chloride penetration resistance of concrete were investigated using matrix scatterplot analysis. Concrete samples with various binder types are tested. Results indicate that bulk resistivity is most related to chloride penetration resistance. The effect of SCMs on chloride binding was then studied, and an improved chloride profile prediction model was developed. The binding isotherm of …

Fatigue Resistant Cast Steel Railcar Couplers Produced By Wire-Arc Additive Manufacturing (Waam), Samuel Vellequette

Dissertations, Master's Theses and Master's Reports

Every year, approximately 90,000 cast steel railcar coupler knuckles are replaced preemptively to avoid fatigue failure. The coupler geometry has been in service since the early 1930s, so geometry changes are restricted to maintain compatibility with the existing fleet. Defects from the casting process, decarburization during heat treatment, and in-service exposure to corrosive environments combine to promote fatigue crack nucleation in high-stress regions of the knuckle. Wire-arc additive manufacturing (WAAM), which uses traditional welding techniques to build material to near-net shapes, was employed to deposit higher-strength materials in critical regions. By replacing the cast steel in the high-stress region of …

Me-Em Enewsbrief, December 2023, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

The Influence Of Boron (B), Tin (Sn), Copper (Cu), And Manganese (Mn) On The Microstructure Of Spheroidal Graphite Irons, A. V. Bugten, P. Sanders, C. Hartung, R. Logan, M. Di Sabatino, L. Michels

Michigan Tech Publications

Most spheroidal graphite irons (SGIs) have a matrix consisting of ferrite, pearlite, or a mix of the two. To achieve the desired matrix composition, pearlite promoters such as Mn, Cu, or Sn, are added to the molten metal. Among these elements, Sn is the most potent pearlite promoter. However, each has a different impact on the solidification, graphite precipitation, eutectoid transformation, and ultimately the final structure of the material. Research has shown that B promotes ferrite in fully pearlitic grades where Cu and Mn were used to promote pearlite. The present work investigates the effect of B in SGI with …

Monitoring Time Domain Characteristics Of Parkinson's Disease Using 3d Memristive Neuromorphic System, Md Abu Bakr Siddique, Yan Zhang, Hongyu An

Michigan Tech Publications

INTRODUCTION: Parkinson's disease (PD) is a neurodegenerative disorder affecting millions of patients. Closed-Loop Deep Brain Stimulation (CL-DBS) is a therapy that can alleviate the symptoms of PD. The CL-DBS system consists of an electrode sending electrical stimulation signals to a specific region of the brain and a battery-powered stimulator implanted in the chest. The electrical stimuli in CL-DBS systems need to be adjusted in real-time in accordance with the state of PD symptoms. Therefore, fast and precise monitoring of PD symptoms is a critical function for CL-DBS systems. However, the current CL-DBS techniques suffer from high computational demands for real-time …

Finding Ideal Parameters For Recycled Material Fused Particle Fabrication-Based 3d Printing Using An Open Source Software Implementation Of Particle Swarm Optimization, Shane Oberloier, Nicholas G. Whisman, Joshua M. Pearce

Michigan Tech Publications

As additive manufacturing rapidly expands the number of materials including waste plastics and composites, there is an urgent need to reduce the experimental time needed to identify optimized printing parameters for novel materials. Computational intelligence (CI) in general and particle swarm optimization (PSO) algorithms in particular have been shown to accelerate finding optimal printing parameters. Unfortunately, the implementation of CI has been prohibitively complex for noncomputer scientists. To overcome these limitations, this article develops, tests, and validates PSO Experimenter, an easy-to-use open-source platform based around the PSO algorithm and applies it to optimizing recycled materials. Specifically, PSO Experimenter is used …