Engineering Commons^™

Design Considerations For Self-Management Technologies For People Living With Dementia And Informal Carers - Perspectives Of Healthcare Professionals And Charity Workers, Dympna O'Sullivan, Julie Doyle, Orla Moran, Michael Wilson, Siobhan Oneill, Jonathan Turner, Suzanne Smith

Conference papers

Dementia is a neurodegenerative disorder that leads to decline in memory, language, reasoning, and the ability to perform daily activities. It is linked to poorer quality of life for the person with dementia and their informal (unpaid) carers. While early intervention and access to adequate care are critical in slowing dementia's progression and better managing associated symptoms, dementia is frequently only diagnosed at an advanced stage and care is often fragmented. To better understand how to meet the complex needs of persons living with dementia and their informal carers, 10 healthcare professionals and 10 charity workers from relevant community and …

Evaluating Llm Generative A.I. Responses To Engineering Design Questions, Dominik Steinhauer

AI Assignment Library

Students will utilize different Large Language Model Generative A.I. Software to ask an Engineering Design Question relevant to their Sr. Design Project. The students will then assess the A.I. responses on usability, relevance, & accuracy. Finally, the students will reflect on the results of the assessments and their thoughts on LLM Generative A.I. This is an In Class Discussion assignment intended to build off of previous lectures on Information/Digital Literacy, Assessment of Sources, Large Language Model Generative A.I., and Prompt Engineering.

Electrochemical Investigation Of Moisture Byproducts In Molten Calcium Chloride, Rankin Shum, Marah Gragun, Tyler Williams, Devin Rappleye

Faculty Publications

Residual water in molten CaCl₂ reacts to form different byproducts, such as HCl, which can impact the corrosivity of the salt and efficiency of electrochemical operations, such as electrolytic oxide reduction and electrorefining. The ability to detect and quantify these byproducts electrochemically can provide feedback on the efficacy of vacuum drying and other purification methods, as well as the impact of these byproducts on process operations. An electrochemical signal’s association with the production of H₂ is verified and characterized using cyclic voltammetry (CV) and residual gas analysis. CV estimated a 2-electron exchange process associated with H2 production. CV …

A Review Of The Dry Methods Available For Coal Beneficiation, Nikki Hughes, Marco Le Roux, Quentin Peter Campbell, Fardis Nakhaei

Mining Engineering Faculty Research & Creative Works

Water is a precious global resource that is important in most currently employed coal beneficiation practices. These widely accepted processes deliver consistent and precise separation efficiencies at desired product yields and throughputs. Although favored, the water usage related to wet processing may be impractical and unsustainable in certain regions. Consequently, present-day practices used in coal processing may soon have to adapt, irrespective of any improved technical and economic feasibility offered. Therefore, the development of efficacious dry beneficiation methods has become an appealing research topic. This review assembles information pertaining to the principle and success of commercially available and experimental phase …

Text-To-Model Transformation: Natural Language-Based Model Generation Framework, Aditya Akundi, Joshua Ontiveros, Sergio Luna

Mechanical Engineering Faculty Publications

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model …

Multiple-Point Metamaterial-Inspired Microwave Sensors For Early-Stage Brain Tumor Diagnosis, Nantakan Wongkasem, Gabriel Cabrera

Electrical and Computer Engineering Faculty Publications

Simple, instantaneous, contactless, multiple-point metamaterial-inspired microwave sensors, composed of multi-band, low-profile metamaterial-inspired antennas, were developed to detect and identify meningioma tumors, the most common primary brain tumors. Based on a typical meningioma tumor size of 5-20 mm, a higher operating frequency, where the wavelength is similar or smaller than the tumor target, is crucial. The sensors, designed for the microwave Ku band range (12-18 GHz), where the electromagnetic property values of tumors are available, were implemented in this study. A seven-layered head phantom, including the meningioma tumors, was defined using actual electromagnetic parametric values in the frequency range of interest …

Neuro-Symbolic Ai For Deep Analysis Of Social Media Big Data, Vedant Khandelwal, Manas Gaur, Ugur Kursuncu, Valerie Shalin, Amit P. Sheth

Faculty Publications

This tutorial introduces a neuro-symbolic AI framework to analyze big data from social media platforms. Integrating human-curated knowledge through symbolic AI with the pattern recognition capabilities of neural networks enhances the adaptability and efficiency of traditional neural network approaches. Knowledge-guided zero-shot learning techniques enable swift adaption to new linguistic contexts and emerging events [6]. Participants will explore how to design, develop, and utilize these models in specific domains, such as public health surveillance, that require dynamic adaptation to new terminologies. This session The tutorial aims to equip attendees with practical skills and a deep understanding of how to apply neuro-symbolic …

Fine-Tuning Cesium Lead Chloride Perovskite Field-Effect Transistors For Sensing Applications: Bridging Numerical Modeling And Experimental Validation, Gehad Ali, Reem Mahmoud, Mohamed Wafeek, Motaz Yousef, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Advanced Transistor-Based Dynamic Equivalent Circuit Modeling Of Mesostructured-Based Solar Cells, Eman Farouk Sawires, Sameh O. Abdellatif

Electrical Engineering

This study introduces a pioneering transistor-based equivalent circuit model explicitly tailored for mesostructured-based solar cells, primarily focusing on dye-sensitized solar cells (DSSCs) and perovskite solar cells (PSCs). By incorporating the experimental data spanning various inorganic, organic, and hybrid solar cell technologies across different optical injection levels, the model aims to provide a comprehensive understanding of the electrical behavior of these advanced photovoltaic devices. In addition to the circuit schematic, a Verilog-A script was created to elucidate the behavior of the cells, facilitating the utilization of such a block by the research community in developing interfacing circuits and implementing dc–dc converters …

Implementing Reactivity In Molecular Dynamics Simulations With Harmonic Force Fields, Jordan J. Winetrout, Krishan Kanhaiya, Josh Kemppainen, Pieter J. In ‘T Veld, Geeta Sachdeva, Ravindra Pandey, Behzad Damirchi, Adri Van Duin, Gregory Odegard, Hendrik Heinz

Michigan Tech Publications

The simulation of chemical reactions and mechanical properties including failure from atoms to the micrometer scale remains a longstanding challenge in chemistry and materials science. Bottlenecks include computational feasibility, reliability, and cost. We introduce a method for reactive molecular dynamics simulations using a clean replacement of non-reactive classical harmonic bond potentials with reactive, energy-conserving Morse potentials, called the Reactive INTERFACE Force Field (IFF-R). IFF-R is compatible with force fields for organic and inorganic compounds such as IFF, CHARMM, PCFF, OPLS-AA, and AMBER. Bond dissociation is enabled by three interpretable Morse parameters per bond type and zero energy upon disconnect. Use …

Evolution Of Physical, Thermal, And Mechanical Properties Of Poly(Methyl Methacrylate)-Based Elium Thermoplastic Polymer During Polymerization, Swapnil S. Bamane, Prathamesh Deshpande, Sagar Patil, Marianna Maiaru, Gregory Odegard

Michigan Tech Publications

Elium-based thermoplastic composites are a key material for future use in the marine, wind energy, and automotive industries because of their recyclability and ease of manufacture. To optimize the processing of the Elium composites to yield optimal structural properties, computational process modeling can be used to relate processing parameters to residual stresses and material durability. The key ingredient for reliable and accurate process modeling is the evolution of physical, thermal, and mechanical properties during polymerization. The objective of this study is to use molecular dynamics to predict the mass density, bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, glass transition …

Flexible Load Conformance: A Work-In-Progress White Paper, Dana Paresa, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Utilities have used residential loads for providing grid services to utility customers for decades, particularly for demand response. However, the number of customers participating in such programs remains low. New Flexible Load Management strategies for providing grid services have the potential to accelerate customer participation. Efforts to improve customer participation and experience will result in increased load balancing capacity of demand response, which will benefit both customers and electric utilities. This white paper investigates whether current smart grid devices (specifically water heaters) can provide needed services while meeting ANSI/CTA-2045 standard requirements.

Big Geospatiotemporal Data Approaches To Monitoring And Mitigating Environmental Impacts In Agriculture, Olatunde D. Akanbi, Vibha S. Mandayam, Erika I. Barcelos, Arafath Nihar, Yinghui Wu, Jeffrey Yarus, Roger H. French

Student Scholarship

This research explores the application of geospatial techniques for global agricultural monitoring, integrating satellite imagery and soil data to assess crop health and soil conditions. Our approach provides actionable insights to improve agricultural productivity and sustainability, addressing food security challenges through advanced machine learning models.

Model Predictive Control Of A Grid-Scale Thermal Energy Storage System In Relap5-3d, Jaron Wallace, John Hedengren, Kody Powell, Matthew Memmott

Faculty Publications

This research delves into the integration and control of a Thermal Energy Storage (TES) system with a Small Modular Reactor (SMR), specifically the NuScale VOYGR SMR module in RELAP5-3D. The research methodology centered on modeling the NuScale VOYGR SMR, a light water pressurized water reactor (LWR) with a power output capacity of 77 MWe per module. The reactor and plant details were sourced from NuScale's final safety analysis report and supplemented by information from the NuScale website. The SMR plays a crucial role in energy generation, and to manage and dispatch the produced energy effectively, a robust storage system …

Introduction To Robotics Systems Assignment 2, Tarek Elderini

AI Assignment Library

An assignment was reformatted with respect to TILT using both Claude 3 and ChatGPT. One of the problems is that whatever pics in the file will not be added to the reformatted file. Also, I asked ChatGPT and Claude 3 to make a comparison between the two created assignments showing the pros and cons for each at the end. It was funny that both agreed that ChatGPT was more professional from the aspect of an engineering assignment. This document contains the original file, the 2 formatted assignments, and the comparison at the end.

Comparative Analysis Of Muskingum Routing: Traditional Vs. Ai-Assisted Methods, Vida Atashi

AI Assignment Library

In this assignment, students will apply traditional and AI-assisted Muskingum routing methods to real-world discharge data from the USGS over a 10-day period. The goal is to compare these approaches, enhancing skills in hydrological modeling and data analysis crucial for water resources engineering.

A Simulated Annealing Approach To The Scheduling Of Battery-Electric Bus Charging, Alexander Brown, Greg Droge

Electrical and Computer Engineering Faculty Publications

With an increasing adoption of battery-electric bus (BEB) fleets, developing a reliable charging schedule is vital to a successful migration from their fossil fuel counterparts. In this paper, a simulated annealing (SA) implementation is developed for a charge scheduling framework for a fixed-schedule fleet of BEBs that utilizes a proportional battery dynamics model, accounts for multiple charger types, allows partial charging, and further considers the total energy consumed by the schedule as well as peak power use. Two generation mechanisms are implemented for the SA algorithm, denoted as the "quick" and "heuristic" implementations, respectively. The model validity is demonstrated by …

Redwater Test Data, Paul Van Susante, Kris Zacny

Michigan Tech Research Data

The RedWater mission is to extract water from subterranean glaciers found on Mars. Honeybee robotics has contracted the PSTDL to conduct small scale tests in order to collect data on the power consumed by a high-density cartridge heater to melt through cryogenic clear ice at Martian atmospheric pressure.

High-Frequency-Based Transmission Line Percentage Differential Protection With Traveling Wave Alignment, Igor F. Prado, Flavio Costa, Kleber M. Silva, Rodrigo P. Medeiros, Bruce A. Mork

Michigan Tech Publications

This paper presents a wavelet-based differential protection algorithm for transmission lines. It uses restraint and operating components obtained with high-frequency components of a few kHz from instantaneous energy values of the real-time boundary stationary wavelet transform instead of low-frequency components from phasor estimation. It does not require capacitive current suppression as well. Therefore, the proposed method overcomes the limitations of conventional percentage differential protection. Furthermore, the proposed technique uses traveling wave theory to perform the current sample alignment at a few kHz, thereby, not requiring the global positioning system (GPS). The performance of the proposed method is evaluated through extensive …

All You Need Is Unary: End-To-End Bit-Stream Processing In Hyperdimensional Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi

Faculty Scholarship

Hyperdimensional Computing (HDC) is a brain-inspired computing paradigm introduced to achieve energy efficiency with a lightweight and single-pass training model. Hypervectors (HVs) at the heart of the HDC systems play a fundamental role in elevating the accuracy and obtaining the desired performance. Image-based HV encoding requires two types of HVs: Position and Level HVs. State-of-the-art approaches utilize pseudo-random methods for generating these HVs, which might degrade system performance and cause higher power consumption due to poor randomness in HV generation. These conventional methods require iteratively calculating orthogonal Positional HVs for acceptable accuracy. This work proposes a fast, ultra-lightweight, and high-quality …

Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen

Engineering Faculty Articles and Research

Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …

Cyberattack Detection And Handling For Neural Network-Approximated Economic Model Predictive Control, Jihan Abou Halloun, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks on control systems can create unprofitable and unsafe operating conditions. To enhance safety and attack resiliency of control systems, cyberattack detection strategies can be developed. Prior work in our group has sought to develop cyberattack detection strategies that are integrated with an advanced control formulation known as Lyapunov-based economic model predictive control (LEMPC), in the sense that the controller properties can be used to analyze closed-loop stability in the presence or absence of undetected attacks. In this work, we consider neural network-approximated control laws, concepts for mitigating cyberattacks on such control laws, and how these ideas elucidate concepts in …

Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate …

Study Of The Application Of Blender For Simulation Of A Closed-Loop Image-Based Greenhouse Supplemental Lighting Control, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Image-based control and sensing has been applied in a wide variety of next generation manufacturing fields. Utilizing methods of simulating closed-loop image-based control may be advantageous for improving control performance and design without the need for an experimental setup. One software capable of these simulations is the open-source 3D modeling software Blender, which has many capabilities aided by a Python API. This work explores the use of Blender as an image-based control test bed, where both the process and the controller are simulated, in the context of a greenhouse supplemental lighting control system.

Safety With Non-Deterministic Control Action Selection Using Quantum Devices, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent increasing interest in quantum computers has spurred research into practical engineering applications for quantum algorithms. One potential application is process control. The unique quantum phenomena involved with quantum computing brings up interesting considerations for control. This work focuses on non-determinism, first through a motivating simulation utilizing a continuous stirred-tank reactor. Following this, two methods of potentially ensuring system stability in the presence of non-determinism are discussed. The first involves including an additional gate to the modified Grover’s algorithm presented in our previous work, which is designed to prevent a qubit state corresponding to an undesired control input from being …

Profit Considerations For Nonlinear Control-Integrated Cyberattack Detection On Process Actuators, Keshav Kasturi Rangan, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Prior research from our group developed a control-integrated active actuator cyberattack detection strategy. This strategy continuously probed for cyberattacks by updating target steady-states at every sampling time and then moving the process state toward these over the subsequent sampling period. Attacks were fagged if a Lyapunov function around the target steady-state did not decrease over a sampling period. This strategy had the benefit of ensuring safety of the process until an attack was detected. However, the continuous probing for attacks could decrease profit from the process compared to not probing for the attacks, which could limit the attractiveness of the …

A Panel Data Regression Model For Defense Merger And Acquisition Activity, Corey D. Mack, Clay Koschnick, Michael Brown, Jonathan D. Ritschel, Brandon M. Lucas

Faculty Publications

Excerpt: This paper examines the relationship between a prime contractor's financial health and its mergers and acquisitions (M&A) spending in the defense industry. It aims to provide models that give the United States Department of Defense (DoD) indications of future M&A activity, informing decision-makers and contributing to ensuring competitive markets that benefit the consumer.

The results show a significant relationship between efficiency and M&A spending, indicating that companies with lower efficiency tend to spend more on M&As. However, there was no significant relationship between M&A spending and a company's profitability or solvency. These results were consistent with previous research and …

An International Consensus Panel On The Potential Value Of Digital Surgery, Jamie Erskine, Payam Abrishami, Jean Christophe Bernhard, Richard Charter, Richard Culbertson, Jo Carol Hiatt, Ataru Igarashi, Gretchen Purcell Jackson, Matthew Lien, Guy Maddern, Joseph Soon Yau Ng, Anita Patel, Koon Ho Rha, Prasanna Sooriakumaran, Scott Tackett, Giuseppe Turchetti, Anastasia Chalkidou

School of Public Health Faculty Publications

OBJECTIVES: The use of digital technology in surgery is increasing rapidly, with a wide array of new applications from presurgical planning to postsurgical performance assessment. Understanding the clinical and economic value of these technologies is vital for making appropriate health policy and purchasing decisions. We explore the potential value of digital technologies in surgery and produce expert consensus on how to assess this value. DESIGN: A modified Delphi and consensus conference approach was adopted. Delphi rounds were used to generate priority topics and consensus statements for discussion. SETTING AND PARTICIPANTS: An international panel of 14 experts was assembled, representing relevant …

Finite Element Analysis Of The Bearing Component Of Total Ankle Replacement Implants During The Stance Phase Of The Gait Cycle, S J. Hazelwood, Mohammad N. Noori, Naudereh B. Noori, Timothy S. Jain, Amanda Anderson, Joseph Rencis

Biomedical Engineering

Total ankle arthroplasty (TAA) is a motion-preserving treatment for end-stage ankle arthritis. An effective tool for analyzing these implants’ mechanical performance and longevity in silico is finite element analysis (FEA). An FEA in ABAQUS was used to statically analyze the mechanical behavior of the ultra-high-molecular-weight polyethylene (UHMWPE) bearing component at varying dorsiflexion/plantarflexion ankle angles and axial loading conditions during the stance phase of the gait cycle for a single cycle. The von Mises stress and contact pressure were examined on the articulating surface of the bearing component in two newly installed fixed-bearing TAA implants (Wright Medical INBONE II and Exactech …

Boosting Steam Tolerance And Electrochemical Performance Of An La0.6Sr0.4Co0.2,Fe0.8O3− Δ-Based Air Electrode For Protonic Ceramic Electrochemical Cells, Lei Wu, Jiqiang Sun, Huiyang Qi, Baofeng Tu, Chunyan Xiong, Fanglin Chen, Peng Qiu

Faculty Publications

La_0.6Sr_0.4Co_0.2Fe_0.8O_3−δ (LSCF) is the state-of-the-art air electrode material for solid oxide electrochemical cells using oxide-ion electrolytes, yet its application in proton ceramic electrochemical cells (PCCs) remains limited, mainly attributed to its instability under operating conditions of high temperature and high humidity. To address this issue, coating a PrCoO_3−δ (PCO) catalyst onto the LSCF scaffold has been evaluated in this study. The introduction of the PCO coating not only enhances the LSCF electrode's electrochemical performance but also significantly improves its steam tolerance by preventing direct contact between steam and …