Engineering Commons^™

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications, Part 2

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction-a measure of …

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish K. Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications, Part 2

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction—a measure of …

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), …

S-Net: A Multiple Cross Aggregation Convolutional Architecture For Automatic Segmentation Of Small/Thin Structures For Cardiovascular Applications, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

Michigan Tech Publications, Part 2

With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-level features are learned, and the receptive field size of the network increases, which results in unsatisfactory performance for detecting low-level small/thin structures such as atrial walls and small arteries. To address this issue, we propose to keep the different encoding layer features at their original sizes to constrain the receptive field from increasing as the network …

Evolution Of Glassy Carbon Derived From Pyrolysis Of Furan Resin, Josh Kemppainen, Ivan Gallegos, Aaron Krieg, Jacob R. Gissinger, Kristopher E. Wise, Margaret Kowalik, Julia A. King, S. Gowtham, Adri Van Duin, Gregory Odegard

Michigan Tech Publications, Part 2

Glassy carbon (GC) material derived from pyrolyzed furan resin was modeled by using reactive molecular dynamics (MD) simulations. The MD polymerization simulation protocols to cure the furan resin precursor material are validated via comparison of the predicted density and Young's modulus with experimental values. The MD pyrolysis simulations protocols to pyrolyze the furan resin precursor is validated by comparison of calculated density, Young's modulus, carbon content, sp carbon content, the in-plane crystallite size, out-of-plane crystallite stacking height, and interplanar crystallite spacing with experimental results from the literature for furan resin derived GC. The modeling methodology established in this work can …

Establishing Physical And Chemical Mechanisms Of Polymerization And Pyrolysis Of Phenolic Resins For Carbon-Carbon Composites, Ivan Gallegos, Josh Kemppainen, Jacob R. Gissinger, Malgorzata Kowalik, Adri Van Duin, Kristopher E. Wise, S. Gowtham, Gregory Odegard

Michigan Tech Publications, Part 2

The complex structural and chemical changes that occur during polymerization and pyrolysis critically affect material properties but are difficult to characterize in situ. This work presents a novel, experimentally validated methodology for modeling the complete polymerization and pyrolysis processes for phenolic resin using reactive molecular dynamics. The polymerization simulations produced polymerized structures with mass densities of 1.24 ± 0.01 g/cm3 and Young's moduli of 3.50 ± 0.64 GPa, which are in good agreement with experimental values. The structural properties of the subsequently pyrolyzed structures were also found to be in good agreement with experimental X-ray data for the phenolic-derived carbon …

Reconstructing 42 Years (1979–2020) Of Great Lakes Surface Temperature Through A Deep Learning Approach, Miraj Kayastha, Tao Liu, Daniel Titze, Timothy C. Havens, Chenfu Huang, Pengfei Xue

Michigan Tech Publications, Part 2

Accurate estimates for the lake surface temperature (LST) of the Great Lakes are critical to understanding the regional climate. Dedicated lake models of various complexity have been used to simulate LST but they suffer from noticeable biases and can be computationally expensive. Additionally, the available historical LST datasets are limited by either short temporal coverage (<30 >years) or lower spatial resolution (0.25° × 0.25°). Therefore, in this study, we employed a deep learning model based on Long Short-Term Memory (LSTM) neural networks to produce a daily LST dataset for the Great Lakes that spans an unparalleled 42 years (1979–2020) at …

Coordinating Tethered Autonomous Underwater Vehicles Towards Entanglement-Free Navigation, Abhishek Patil, Myoungkuk Park, Jungyun Bae

Michigan Tech Publications

This paper proposes an algorithm that provides operational strategies for multiple tethered autonomous underwater vehicle (T-AUV) systems for entanglement-free navigation. T-AUVs can perform underwater tasks under reliable communication and power supply, which is the most substantial benefit of their operation. Thus, if one can overcome the entanglement issues while utilizing multiple tethered vehicles, the potential applications of the system increase including ecosystem exploration, infrastructure inspection, maintenance, search and rescue, underwater construction, and surveillance. In this study, we focus on developing strategies for task allocation, path planning, and scheduling that ensure entanglement-free operations while considering workload balancing among the vehicles. We …

Neuroevolution Application To Collaborative And Heuristics-Based Connected And Autonomous Vehicle Cohort Simulation At Uncontrolled Intersection, Frederic Jacquelin, Jungyun Bae, Bo Chen, Darrell Robinette

Michigan Tech Publications, Part 2

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go …

Vision-Based Online Defect Detection Of Polymeric Film Via Structural Quality Metrics, Nathir Rawashdeh, Paniz Hazaveh, Safwan Altarazi

Michigan Tech Publications

Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be implemented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used …

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 …

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 …

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 …

Chemical Decomposition Of Flexible Polyurethane Foam To Generate A Media For Microbial Upcycling, Kaushik Baruah

Dissertations, Master's Theses and Master's Reports

Polyurethane waste is becoming a global concern as a large amount is being disposed of in landfills every year, and only a fraction is being recycled. Several polyurethane recycling techniques exist, of which ammonolysis and base-catalyzed hydrolysis is the least explored. Flexible polyurethane foam (FPUF) decomposition can generate amines that can act as a carbon source for the growth of microbial consortia. This study aims to generate a novel media capable of microbial upcycling via ammonolysis and base-catalyzed hydrolysis of flexible polyurethane foams (FPUFs) using ammonium hydroxide and subsequently determine the reaction conditions for maximum solubilization of polyurethane foam in …

Investigating Collaborative Explainable Ai (Cxai)/Social Forum As An Explainable Ai (Xai) Method In Autonomous Driving (Ad), Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

Explainable AI (XAI) systems primarily focus on algorithms, integrating additional information into AI decisions and classifications to enhance user or developer comprehension of the system's behavior. These systems often incorporate untested concepts of explainability, lacking grounding in the cognitive and educational psychology literature (S. T. Mueller et al., 2021). Consequently, their effectiveness may be limited, as they may address problems that real users don't encounter or provide information that users do not seek.

In contrast, an alternative approach called Collaborative XAI (CXAI), as proposed by S. Mueller et al (2021), emphasizes generating explanations without relying solely on algorithms. CXAI centers …

Water-Soluble Saponins Accumulate In Drought-Stressed Switchgrass And May Inhibit Yeast Growth During Bioethanol Production, Sarvada Hemant Chipkar, Katherine Smith, Elizabeth M. Whelan, Derek J. Debrauske, Annie Jen, Katherine A. Overmyer, Andrea Senyk, Larkin Hooker-Moericke, Marissa Gallmeyer, Joshua J. Coon, A. Daniel Jones, Trey K. Sato, Rebecca G. Ong

Michigan Tech Publications

Background: Developing economically viable pathways to produce renewable energy has become an important research theme in recent years. Lignocellulosic biomass is a promising feedstock that can be converted into second-generation biofuels and bioproducts. Global warming has adversely affected climate change causing many environmental changes that have impacted earth surface temperature and rainfall patterns. Recent research has shown that environmental growth conditions altered the composition of drought-stressed switchgrass and directly influenced the extent of biomass conversion to fuels by completely inhibiting yeast growth during fermentation. Our goal in this project was to find a way to overcome the microbial inhibition and …

A Smart Parallel Gripper Industrial Automation System For Measurement Of Gripped Work Piece Thickness, Erik Kocher, Chukwuemeka George Ochieze, Ahmat Oumar, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of the smart parallel gripper system to measure the width of components grasped with the gripper. In addition, details of the system’s components, operation, more advanced uses are discussed. On the automation line, this smart gripper can be used to measure the thickness of work pieces while handling them and classifying these as either acceptable, too large …

Gesture Controlled Collaborative Robot Arm And Lab Kit, Abel A. Reyes, Skylar Reinhardt, Tony Wise, Nathir Rawashdeh, Sidike Paheding

Michigan Tech Publications

In this paper, a mechatronics system was designed and implemented to include the subjects of artificial intelligence, control algorithms, robot servo motor control, and human-machine interface (HMI). The goal was to create an inexpensive, multi-functional robotics lab kit to promote students’ interest in STEM fields including computing and mechtronics. Industrial robotic systems have become vastly popular in manufacturing and other industries, and the demand for individuals with related skills is rapidly increasing. Robots can complete jobs that are dangerous, dull, or dirty for humans to perform. Recently, more and more collaborative robotic systems have been developed and implemented in the …

Operation Of A Controllable Force-Sensing Industrial Pneumatic Parallel Gripper System, Brian Piechocki, Chelsey Spitzner, Namratha Karanam, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project was performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and application of a force-programmable and sensing pneumatic parallel gripper system. Force sensing is a critical part of many systems in modern automation systems. Applications such as prosthetics, robotic surgery, or basic manufacturing systems may rely on the ability to properly read and control forces applied to an object. This work evaluates the basic operation of the pneumatic force-sensing gripper …

An Industrial Pneumatic And Servo Four-Axis Robotic Gripper System: Description And Unitronics Ladder Logic Programming, Zongguang Liu, Chrispin Johnston, Aleksi Leino, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project is performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and ladder programming of a four-axis robot enclosed in a cage with one side guarded by an optical fence. The robot has pneumatically actuated X-Y linear motion and a pneumatic gripper. Furthermore, the Z-axis motion and gripper wrist rotation are controlled by servo motors. A human machine interface (HMI) is also present, and it allows for easy manipulation and programming …

Mechatronics Bachelor Curriculum Development In Light Of Industry 4.0 Technology Needs: Contrasting Us And German University Curricula, Paniz Hazaveh, Aleksandr Sergeyev, Nathir Rawashdeh

Michigan Tech Publications

This study compares Mechatronics bachelor curricula at universities in the United States of America and German universities. Mechatronics education is relatively new in the United States, but has been common in Germany for over a decade. With the multidisciplinary nature of technologies required by the 4’th industrial revolution, a.k.a. Industry 4.0, composing an appropriate Mechatronics curriculum becomes a challenge and an opportunity. This paper studies how Mechatronics education can address the future needs of industry, while building on a specific university’s strengths and industry links. We have also analyzed the new undergraduate Mechatronics program at Michigan Technological University (MTU) and …

The Missing Link Between Standing-And Traveling-Wave Resonators, Qi Zhong, Haoqi Zhao, Liang Feng, Kurt Busch, Sahin K. Özdemir, Ramy El-Ganainy

Michigan Tech Publications

Optical resonators are structures that utilize wave interference and feedback to confine light in all three dimensions. Depending on the feedback mechanism, resonators can support either standing-or traveling-wave modes. Over the years, the distinction between these two different types of modes has become so prevalent that nowadays it is one of the main characteristics for classifying optical resonators. Here, we show that an intermediate link between these two rather different groups exists. In particular, we introduce a new class of photonic resonators that supports a hybrid optical mode, i.e. at one location along the resonator the electromagnetic fields associated with …

An Algorithm For Task Allocation And Planning For A Heterogeneous Multi-Robot System To Minimize The Last Task Completion Time, Abhishek Patil, Jungyun Bae, Myoungkuk Park

Michigan Tech Publications

This paper proposes an algorithm that provides operational strategies for multiple heterogeneous mobile robot systems utilized in many real-world applications, such as deliveries, surveillance, search and rescue, monitoring, and transportation. Specifically, the authors focus on developing an algorithm that solves a min-max multiple depot heterogeneous asymmetric traveling salesperson problem (MDHATSP). The algorithm is designed based on a primal-dual technique to operate given multiple heterogeneous robots located at distinctive depots by finding a tour for each robot such that all the given targets are visited by at least one robot while minimizing the last task completion time. Building on existing work, …

Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang

Michigan Tech Publications

The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …

Fidget Spinner Generator System For Mi-Star Unit 7.1, Douglas Oppliger

Mi-STAR

This simple system is an integral and important part of this unit. It allows students to see, feel, and experience how kinetic energy can be transformed to another kind of energy. It is an effective learning tool in the unit because it is reasonably easy to make, has just a few simple and visible components, and reliably transforms enough energy to light an LED (light emitting diode). The LED provides a satisfying light output which is easy to observe.

On-Ice Detection, Classification, Localization And Tracking Of Anthropogenic Acoustic Sources With Machine Learning, Steven J. Whitaker

Dissertations, Master's Theses and Master's Reports

Arctic acoustics have been of concern in recent years for the US navy. First-year ice is now the prevalent factor in ice coverage in the Arctic, which changes the previously understood acoustic properties. Due to the ice melting each year, anthropogenic sources in the Arctic region are more common: military exercises, shipping, and tourism. For the navy, it is of interest to detect, classify, localize, and track these sources to have situational awareness of these surroundings. Because the sources are on-water or on-ice, acoustic radiation propagates at a longer distance and so acoustics are the method by which the sources …

Design And Analysis Of Marangoni-Driven Robotic Surfers, Mitchel L. Timm

Dissertations, Master's Theses and Master's Reports

We designed and experimentally studied the dynamics of two robotic systems that surf along the water-air interface. The robots were self-propelled by means of creating and maintaining a surface tension gradient resulting from an asymmetric release of isopropyl alcohol (IPA). The imbalance in the distribution of surface tension surrounding the robots generates a propulsive force commonly referred to as Marangoni propulsion. First, we considered a single surfer, which was custom-made with novel control mechanisms that allow for both forward motion and steering to be remotely adjusted solely through the manipulation of local surface stresses. We analyzed the performance of this …

Collective Hydrodynamics Of Robotic Fish, Rohit S. Pandhare

Dissertations, Master's Theses and Master's Reports

Many animals in nature travel in groups either for protection, survival, or endurance. Among these, fish do so under the burden of hydrodynamic loads, which incites questions as to the significance of the multi-body fluid-mediated interactions that facilitate collective swimming. We study such interactions in the idealized setting of a rotational array of robotic fish whose tails undergo a prescribed flapping motion, but whose swimming speed is determined as a natural result of the hydrodynamic effects. Specifically, we examine how the measured collective speed of the swimmers varies with the imposed frequency and amplitude of their tail flapping, and with …