Engineering Commons^™

High Temperature Strength Reduces Soldering In Aluminum High Pressure Die Casting, Jacob A. Belke

Dissertations, Master's Theses and Master's Reports

Die soldering, an adhesion defect in high pressure die casting (HPDC), is a symptom of localized sticking where a localized portion of the cast material is adhered to the tooling surface causing build up over time. This requires the tooling to be serviced which incurs additional costs to the process that gets passed on to the parts. Historically, soldering has been mitigated using lubricants, coatings, and alloy chemistry modifications but solder persists.

The Tresca friction thermomechanical model suggests soldering occurs when the local interfacial shear stress between the casting and die surface exceeds the local shear strength of the casting. …

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 …

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 …

Machine Learning For Electronic Structure Prediction, Shashank Pathrudkar

Dissertations, Master's Theses and Master's Reports

Kohn-Sham density functional theory is the work horse of computational material science research. The core of Kohn-Sham density functional theory, the Kohn-Sham equations, output charge density, energy levels and wavefunctions. In principle, the electron density can be used to obtain several other properties of interest including total potential energy of the system, atomic forces, binding energies and electric constants. In this work we present machine learning models designed to bypass the Kohn-Sham equations by directly predicting electron density. Two distinct models were developed: one tailored to predict electron density for quasi one-dimensional materials under strain, while the other is applicable …

Investigation Of Operational Parameter Differences Between The Standard Ron Test Method And Knock-Limited Modern Spark-Ignition Engine Operation, Alexander Hoth

Dissertations, Master's Theses and Master's Reports

Octane numbers (ONs) are used worldwide to rate the knock propensity of gasoline-like fuels for spark-ignition engines, making ONs the leading indicator of fuel quality for commercial distribution. The ONs were established 90 years ago and have only received minor changes compared to significant advancements in modern engine operation and fuel composition. This has resulted in discrepancies between knock-limited modern engine operation and standard ON ratings. This dissertation used a standard CFR octane rating engine at Argonne National Laboratory that was instrumented with modern combustion research tools to investigate key differences between the Research Octane Number (RON) rating conditions and …

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 …

Valorization Of Spent Vetiver Roots For Biochar Generation, Sameer Neve, Dibyendu Sarkar, Manas Warke, Teresa Bandosz, Rupali Datta

Michigan Tech Publications, Part 2

Vetiver root is widely used to produce essential oils in the aromatherapy industry. After the extraction of oil, the roots are disposed of as waste. The central objective of this research was to explore the conversion of this waste into a resource using a circular economy framework. To generate biochar, vetiver roots were pyrolyzed at different temperatures (300, 500, and 700 °C) and residence times (30, 60, and 120 min). Analysis showed the root biochar generated at 500 °C and held for 60 min had the highest surface area of 308.15 m2/g and a yield of 53.76%, in addition to …

Heating Capacity And Biocompatibility Of Hybrid Nanoparticles For Magnetic Hyperthermia Treatment, Aline Alexandrina Gomes, Thalita Marcolan Valverde, Vagner De Oliveira Machado, Emanueli Do Nascimento Da Silva, Daniele Alves Fagundes, Fernanda De Paula Oliveira, Erico Freitas, José Domingos Ardisson, José Maria Da Fonte Ferreira, Junnia Alvarenga De Carvalho Oliveira, Eliza Rocha Gomes, Caio Fabrini Rodrigues, Alfredo Miranda De Goes, Rosana Zacarias Domingues, Ângela Leão Andrade

Michigan Tech Publications, Part 2

Cancer is one of the deadliest diseases worldwide and has been responsible for millions of deaths. However, developing a satisfactory smart multifunctional material combining different strategies to kill cancer cells poses a challenge. This work aims at filling this gap by developing a composite material for cancer treatment through hyperthermia and drug release. With this purpose, magnetic nanoparticles were coated with a polymer matrix consisting of poly (L-co-D,L lactic acid-co-trimethylene carbonate) and a poly(ethylene oxide)–poly(propylene oxide)–poly(ethylene oxide) triblock copolymer. High-resolution transmission electron microscopy and selected area electron diffraction confirmed magnetite to be the only iron oxide in the sample. Cytotoxicity …

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), …

A Physical Test Artifact For Evaluating Edge Cases Of Individual And Fused Automated Driving Perception Sensors, Colin Schaefer

Dissertations, Master's Theses and Master's Reports

With the advent of technologies to support autonomous vehicles (AVs), the number of different AV models from a variety of companies and organizations has proliferated. With this increase in options comes the need to physically evaluate their perception systems. However, there is a lack of standard methods to physically evaluate these perception systems. A set of test artifacts can be used to compare the performances of perception systems, but the artifacts must be usable with different types of perception sensors and various sensor fusion systems. This thesis presents the development of an artifact that injects edge case scenarios into the …

Engineering Self-Efficacy And Spatial Visualization: Connecting The Spatial Dots, Katrina L. Carlson

Dissertations, Master's Theses and Master's Reports

Questions exist as to why students in the ENG 1002: Introduction to Spatial Visualization (Spat Vis) course, an intervention course at Michigan Technological University (MTU), have historically attained higher average grades in their first year STEM courses, such as Engineering I and II, calculus I and II, computer science, and chemistry courses. Research shows the retention rate, especially of women, is higher for students who have taken Spatial Visualization. One possible explanation for these observed benefits may be related to the students’ confidence in their ability (self-efficacy) to gain the engineering graphics skills needed to become an engineer. No work …

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 …

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 …

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 …

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, Part 2

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, Part 2

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, Part 2

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 …

Modular Open-Source Design Of Pyrolysis Reactor Monitoring And Control Electronics, Finn K. Hafting, Daniel G. Kulas, Etienne Michels, Sarvada Chipkar, Stefan Wisniewski, David Shonnard, Joshua M. Pearce

Michigan Tech Publications, Part 2

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually; however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) is a framework that provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis …

Modification Strategies For Development Of 2d Material-Based Electrocatalysts For Alcohol Oxidation Reaction, Haichang Fu, Zhangxin Chen, Xiaohe Chen, Fan Jing, Hua Yu, Dan Chen, Binbin Yu, Yun Hang Hu, Yanxian Jin

Michigan Tech Publications, Part 2

2D materials, such as graphene, MXenes (metal carbides and nitrides), graphdiyne (GDY), layered double hydroxides, and black phosphorus, are widely used as electrocatalyst supports for alcohol oxidation reactions (AORs) owing to their large surface area and unique 2D charge transport channels. Furthermore, the development of highly efficient electrocatalysts for AORs via tuning the structure of 2D support materials has recently become a hot area. This article provides a critical review on modification strategies to develop 2D material-based electrocatalysts for AOR. First, the principles and influencing factors of electrocatalytic oxidation of alcohols (such as methanol and ethanol) are introduced. Second, surface …

Modification Strategies For Development Of 2d Material-Based Electrocatalysts For Alcohol Oxidation Reaction, Haichang Fu, Zhangxin Chen, Xiaohe Chen, Fan Jing, Hua Yu, Dan Chen, Binbin Yu, Yun Hang Hu, Yanxian Jin

Michigan Tech Publications, Part 2

2D materials, such as graphene, MXenes (metal carbides and nitrides), graphdiyne (GDY), layered double hydroxides, and black phosphorus, are widely used as electrocatalyst supports for alcohol oxidation reactions (AORs) owing to their large surface area and unique 2D charge transport channels. Furthermore, the development of highly efficient electrocatalysts for AORs via tuning the structure of 2D support materials has recently become a hot area. This article provides a critical review on modification strategies to develop 2D material-based electrocatalysts for AOR. First, the principles and influencing factors of electrocatalytic oxidation of alcohols (such as methanol and ethanol) are introduced. Second, surface …

Perfusability And Immunogenicity Of Implantable Pre-Vascularized Tissues Recapitulating Features Of Native Capillary Network, Dhavan Sharma, Archita Sharma, Linghao Hu, Te An Chen, Sarah Voon, Kayla J. Bayless, Jeremy Goldman, Alex J. Walsh, Feng Zhao

Michigan Tech Publications, Part 2

Vascularization is a key pre-requisite to engineered anatomical scale three dimensional (3-D) constructs to ensure their nutrient and oxygen supply upon implantation. Presently, engineered pre-vascularized 3-D tissues are limited to only micro-scale hydrogels, which meet neither the anatomical scale needs nor the complexity of natural extracellular matrix (ECM) environments. Anatomical scale perfusable constructs are critically needed for translational applications. To overcome this challenge, we previously developed pre-vascularized ECM sheets with long and oriented dense microvascular networks. The present study further evaluated the patency, perfusability and innate immune response toward these pre-vascularized constructs. Macrophage-co-cultured pre-vascularized constructs were evaluated in vitro to …

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, Part 2

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 …

Encoder–Decoder With Pyramid Region Attention For Pixel-Level Pavement Crack Recognition, Hui Yao, Yanhao Liu, Haotian Lv, Ju Huyan, Zhanping You, Yue Hou

Michigan Tech Publications, Part 2

Timely and accurate extraction of pavement crack information is crucial to maintain service conditions and structural safety for infrastructures and reduce further road maintenance costs. Currently, deep learning techniques for automated pavement crack detection are far superior to traditional manual approaches in both speed and accuracy. However, existing deep learning models may easily lose crack details when processing images containing complex background textures or other noises. Although many studies have alleviated this challenge by introducing attention mechanisms, especially the non-local (NL) block, which has the ability to efficiently capture long-range dependencies to facilitate crack pixel capture, the huge computational cost …

Rapid Saline Permafrost Thaw Below A Shallow Thermokarst Lake In Arctic Alaska, Benjamin M. Jones, Mikhail Z. Kanevskiy, Andrew D. Parsekian, Helena Bergstedt, Melissa K. Ward Jones, Rodrigo C. Rangel, Kenneth M Hinkel, Yuri Shur

Michigan Tech Publications, Part 2

Permafrost warming and degradation is well documented across the Arctic. However, observation- and model-based studies typically consider thaw to occur at 0°C, neglecting the widespread occurrence of saline permafrost in coastal plain regions. In this study, we document rapid saline permafrost thaw below a shallow arctic lake. Over the 15-year period, the lakebed subsided by 0.6 m as ice-rich, saline permafrost thawed. Repeat transient electromagnetic measurements show that near-surface bulk sediment electrical conductivity increased by 198% between 2016 and 2022. Analysis of wintertime Synthetic Aperture Radar satellite imagery indicates a transition from a bedfast to a floating ice lake with …

Efficient Navigation And Motion Control For Autonomous Forklifts In Smart Warehouses: Lspb Trajectory Planning And Mpc Implementation, Konchanok Vorasawad, Myoungkuk Park, Changwon Kim

Michigan Tech Publications, Part 2

The rise of smart factories and warehouses has ushered in an era of intelligent manufacturing, with autonomous robots playing a pivotal role. This study focuses on improving the navigation and control of autonomous forklifts in warehouse environments. It introduces an innovative approach that combines a modified Linear Segment with Parabolic Blends (LSPB) trajectory planning with Model Predictive Control (MPC) to ensure efficient and secure robot movement. To validate the performance of our proposed path-planning method, MATLAB-based simulations were conducted in various scenarios, including rectangular and warehouse-like environments, to demonstrate the feasibility and effectiveness of the proposed method. The results demonstrated …

Nr Sidelink Performance Evaluation For Enhanced 5g-V2x Services, Mehnaz Tabassum, Felipe Henrique Bastos, Aurenice M. Oliveira, Aldebaro Klautau

Michigan Tech Publications, Part 2

The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous …

Estimation Of Anthropogenic And Volcanic So2 Emissions From Satellite Data In The Presence Of Snow/Ice On The Ground, Vitali E. Fioletov, Chris A. Mclinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, Simon Carn

Michigan Tech Publications, Part 2

Early versions of satellite nadir-viewing UV SO2 data products did not explicitly account for the effects of snow/ice on retrievals. Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. This leads to increased uncertainties of satellite emission estimates and potential seasonal biases due to the lack of data in winter months for some high-latitudinal sources. In this study, we investigated how Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) satellite SO2 measurements over snow-covered surfaces can …

Differential Impact Of Blood Pressure Control Targets On Epicardial Coronary Flow After Transcatheter Aortic Valve Replacement, Brennan Vogl, Alejandra Chavez-Ponce, Adam Wentworth, Eric Erie, Pradeep Yadav, Vinod H. Thourani, Lakshmi Prasad Dasi, Brian Lindman, Mohamad Alkhouli, Hoda Hatoum

Michigan Tech Publications, Part 2

Background: The cause for the association between increased cardiovascular mortality rates and lower blood pressure (BP) after aortic valve replacement (AVR) is unclear. This study aims to assess how the epicardial coronary flow (ECF) after AVR varies as BP levels are changed in the presence of a right coronary lesion. Methods: The hemodynamics of a 3D printed aortic root model with a SAPIEN 3 26 deployed were evaluated in an in vitro left heart simulator under a range of varying systolic blood pressure (SBP) and diastolic blood pressure (DBP). ECF and the flow ratio index were calculated. Flow index value …

Compatibility Investigation Of Waste Plastics In Bitumen Via A Molecular Dynamics Method, Hui Yao, Xin Li, Hancheng Dan, Qingli Dai, Zhanping You

Michigan Tech Publications, Part 2

The compatibility between waste plastic polymers and bitumen is the most challenging issue hindering the improvement of modified bitumen performance. The current practice of recycled waste plastics includes the use of polyvinyl chloride (PVC), polypropylene (PP), polyethylene (PE), etc. This study was designed to investigate the compatibility of different waste plastic polymers with bitumen binders by conducting molecular dynamics (MD) simulations at different temperatures. The molecular models of these materials were constructed in this study for the compatibility analysis, and they include the base bitumen, polymers (PVC, PP, and PE), polymer- bitumen blending systems. Using the output and related calculations …

Synthetic Aperture Scatter Imaging, Qian Huang, Zhipeng Dong, Gregory Nero, Yuzuru Takashima, Timothy J. Schulz, David J. Brady

Michigan Tech Publications, Part 2

Diffraction limits the minimum resolvable feature on remotely observed targets to $\lambda R_{c}/A_{c}$, where $\lambda$ is the operating wavelength, $R_{c}$ is the range to the target and $A_{c}$ is the diameter of the observing aperture. Resolution is often further reduced by scatter or turbulence. Here we show that analysis of scattered coherent illumination can be used to achieve resolution proportional to $\lambda R_{s}/A_{s}$, where $R_{s}$ is the range between the scatterer and the target and $A_{s}$ is the diameter of the observed scatter. Theoretical analysis suggests that this approach can yield resolution up to 1000× better than the diffraction limit. …