Engineering Commons^™

08.18.2025 Ored Connect, Liz Williamson

ORED Newsletter

ORED on-demand training, Tableau training, Research Reception 2025

Origin Of The World-Class Eagle, Eagle East, And Tamarack Ni-Cu-Pge Deposits, Robert Nowak, Chad Deering, Espree Essig

Michigan Tech Publications

The 1.1 Ga Mesoproterozoic Midcontinent rift hosts the Eagle, Eagle East, and Tamarack Ni-Cu-PGE deposits and Embayment Prospect. These deposits are hosted by ultramafic igneous rocks and have some of the highest Ni-Cu grades on Earth. We use new bulk-rock data and published datasets (bulk-rock, mineral chemistry, and isotopic analyses) to examine major, minor, and trace element trends of both Midcontinent rift-related alkaline and tholeiitic intrusions. In addition, we compare the geochemical data to local kimberlite-hosted lower-crustal xenoliths and local igneous (Archean) and sedimentary (Paleoproterozoic) country rocks. We found the peridotite magma compositions dominantly consist of primitive mantle compositions with …

Class A Biosolids Production Using Conventional And Low-Cost, Low-Tech Processes At Small Water Resource Recovery Facilities: A Multidimensional Sustainability Assessment, Janna Brown, Robert Handler, Eric Seagren, Jennifer Becker

Michigan Tech Publications

Producing Class A biosolids is a beneficial way to reuse wastewater treatment solids, but most conventional processes are energy-intensive and expensive. There is growing interest in the use of low-cost, low-tech (LCLT) Class A biosolids treatment processes, especially at small water resource recovery facilities (WRRFs). This study used a holistic sustainability assessment to examine the environmental, economic, and social sustainability of conventional and LCLT processes at small WRRFs. The technologies studied were Direct Heat Drying, Composting, Lagoon Storage, Air Drying, and Temperature-Phased Anaerobic Digestion (TPAD). Environmental impacts were determined by conducting life-cycle assessments for all technologies, which is described in …

Development Of Turbulence Models For Prediction Of Hypersonic Flows Using Compressibility Corrections And Uncertainty Quantification With Emphasis On The Wray-Agarwal Model, Aidan Robert Murphy

McKelvey School of Engineering Graduate Student Theses & Dissertations

Accurate prediction of high-speed compressible turbulent flows remains one of the most significant challenges in Computational Fluid Dynamics (CFD), especially in the realm of hypersonic vehicle design. These flow regimes involve significant aerodynamic heating and shock-wave boundary layer interactions (SBLI) which remain a significant challenge for the current CFD prediction capabilities. While Direct Numerical Simulation (DNS) and Large-Eddy Simulation (LES) provide high-fidelity solutions, their computational demands limit their usability, making the Reynolds-Averaged Navier-Stokes (RANS) equations an efficient alternative for many industrial aerodynamic applications. Traditional RANS techniques, while computationally efficient, often provide limited accuracy in high-speed flows due to the presence …

Development, Numerical Simulation, And Optimization Of Quiet Supersonic Transport Aircraft And Extension Of The Wray-Agarwal Algebraic Transition Model To Include Compressibility And Crossflow Effects, Dean Ryan-Simmons

McKelvey School of Engineering Graduate Student Theses & Dissertations

In the first part of this thesis, the goal of the research is to implement and extend multi fidelity methods for conceptual design and optimization of a commercial supersonic transport (SST). Most modern commercial aircraft operate at a cruise condition between Mach 0.7 and 0.9, as this is the optimal trade-off of flight efficiency, operational cost, and adherence of noise regulations for overland travel. Advancements in aviation propulsion fuel efficiency and design materials suggests a primary restraint on commercial supersonic transport is noise regulations. At speeds above Mach 1, the shock waves generated by the airframe are strong enough to …

A Control Theoretic Approach To The Stochastic Multi-Armed Bandit Problem With Applications In Hyperparameter Optimization, Jonathan Gornet

McKelvey School of Engineering Graduate Student Theses & Dissertations

Decision-making under uncertainty is a fundamental problem encountered frequently in many real-world applications. This challenge has been rigorously formulated as the Stochastic Multi-Armed Bandit (SMAB) problem, which consists of a learner interacting with an environment. For each interaction, the learner selects an action and then receives a reward from the environment based on the chosen action. The learner's objective is to maximize the accumulated reward over a set number of rounds. This thesis addresses the SMAB problem by leveraging the field of Control Theory and dynamical systems. We specifically focus on a SMAB environment where the rewards are the output …

Multi-Layer Support For Component-Based Cyber-Physical Systems Applications, Oren Bell

McKelvey School of Engineering Graduate Student Theses & Dissertations

Component-based design is a paradigm meant to aid in development of software applications by modularizing different functionalities of a system. This building-block approach is used extensively in cyber–physical and robotic systems. Common and established solutions to specific problems, such as perception nodes, state estimators, and motion planners, can be developed, verified, and reused as off-the-shelf modules. These modules may be integrated atop today’s heterogeneous hardware platforms, where an application can be distributed across GPUs, FPGAs, and CPU cores. When heterogeneous computational devices share the workload of a collection of components, the very act of integration may inject timing uncertainty. For …

Moment Ensemble Approaches For Estimation And Robust Quantum Control, Andre Luiz Paes De Lima

McKelvey School of Engineering Graduate Student Theses & Dissertations

Large-scale population dynamics governed by ensemble systems present significant challenges due to their inherently high dimensionality. Recent advances have demonstrated the effectiveness of moment-based methods (particularly those employing polynomial bases such as Legendre and Chebyshev polynomials) when integrated with optimization techniques for control design in ensemble systems. However, these methods have not been extensively explored for enhancing robustness against systematic noise, nor have they been widely applied to complex quantum systems involving multi-parameter configurations and entanglement phenomena. In this work, we extend the application of moment methods in ensemble systems through two projects. Initially by developing a Kalman filter analogue, …

Transition And Instability Characteristics Of The Separated Shear Layer Formed At Low Reynolds Number Over Three-Dimensional Irregular Rough Surface, Ganesh Kt Mr

Theses and Dissertations

The present experimental work investigates the effects of irregularly roughened surfaces and imposed streamwise pressure gradients on the topological, transitional, and instability characteristics of the laminar separated shear layer (SSL). Experiments are conducted in the low-speed wind tunnel for 𝑅𝑒𝑡=30000, based on the thickness of the airfoil model, t, and freestream turbulence intensity, fst = 0.8%. The airfoil model used in this study features a semicircular leading edge followed by a constant-thickness flat portion and a pitchable trailing-edge flap. Test conditions include two rough surfaces: sandblasted (SB) and sand-deposited (SD), and flap deflections: 𝛽=−30° and 𝛽=+30°, imposing adverse (APG) and …

A Contemporary Approach For Exploring The Influence Of Detoxification And Standardization Of Traditional Metallopharmaceutical Product Pharmacological And Toxicological Aspects, Malarvizhi K

Theses and Dissertations

Polyherbomineral formulation possess unique medicinal properties due to the presence of metals and minerals as integral part, as processed in addition to specific herbals. There is an increased interest in metallopharmaceuticals in clinical and research areas, because of their immense therapeutic efficiency towards multiple diseases and evidence for non-toxic claim. Sivanar Amirtham is one of the polyherbomineral Siddha medicine recommended for the treatment of various respiratory diseases and other ailments including antidote therapy for poisonous bites. The present research work attempted for standardization of Sivanar Amirtham preparation as per the traditional standard protocols (including the detoxification process of raw materials) …

Magnetic Molecularly Imprinted Polymers For Quercetin Adsorption: Fabrication, Characterization, And Application, Vinitha Ug

Theses and Dissertations

A highly selective Magnetic Molecularly Imprinted Polymer (MMIP) was developed for the detection and purification of Quercetin. The Density Functional Theory was utilized for the selection of suitable monomers based on binding energy interaction between quercetin and monomers (Acrylamide, Acrylonitrile, Methacrylic Acid). From computational studies, Acrylamide was selected as a suitable monomer for the synthesis of MMIP. Under ultrasound irradiation both quercetin and naringin imprinted materials MMIP-Q and MMIP-N were fabricated.

Compared to ultrasound-assisted synthesis, Microwave Synthesis provides uniform heat transfer throughout the reaction solution, which enables uniformity in the size of synthesised material, increases the yield of material and …

Design And Development Of Deep Learning Based Generic Platform For Promoting Precision Agriculture, Srilakshmi A

Theses and Dissertations

Precision agriculture also referred as precision farming or smart farming, is an innovative approach to agricultural management that leverages technology and data to optimize various aspects of the farming process. This approach aims to make farming more effective, sustainable, and profitable by affording farmers with the application tools and information they need to make more informed decisions.

Precision agriculture combines elements of agriculture, technology, and data science to enhance crop production, and resource utilization. Precision agriculture techniques can be highly effective in leaf disease detection within crop fields. Machine learning has been developed incredibly across multiple domains and shown it …

Facile Fabrication Of Protein-Polysaccharide Conjugate Multifilament Nerve Guidance Conduit For Peripheral Nerve Regeneration, Preethy Amruthavarshini R

Theses and Dissertations

Long segmental defects in peripheral nerves impair sensory and motor function by disrupting neural impulse transmission. End-to-end autologous grafting with proper fascicular complementation has demonstrated functional recovery per the Medical Research Council Classification (MRCC). However, obtaining donor nerve tissue exceeding 30 mm remains a significant challenge. Artificial hollow conduits serve as an alternative but are limited to defects smaller than 30 mm due to inadequate innervation across the lumen.

Multichannel nerve guidance conduits (mNGCs) have emerged as a promising solution by enhancing fascicular complementation similar to autografts. This study presents a two-step approach for fabricating nerve conduits with precise fascicular …

Structural Response Of Rc Columns Strengthened Using Bfrp Based Bfegc System – Under Fire And Cooling Regime, Ruba P

Theses and Dissertations

Retrofitting fire-damaged columns is essential for restoring structural integrity. This study evaluates the effectiveness of BFRP based Basalt fiber Engineered Geopolymer Composites (BFEGC). The performance of basalt fiber wrapping and BFEGC was tested for fire protection system and retrofitted system. An optimal BFEGC mix achieved a compressive strength of 55.34 MPa, with split tensile strength, flexural strength, and strain hardening behaviour of 15.5 MPa, 5.13 MPa, and 6% respectively.

Microstructural analysis was accessed for the optimum mix. Durability tests include water absorption, sorptivity, and RCPT which confirmed compliance with standards. Thermo gravimetry analysis (TGA) shows the minimal weight loss of …

Encountering And Mitigating Selfish Mining In Bitcoin Mining Pools, Jeyasheela Rakkini M J

Theses and Dissertations

Blockchain, an innovative decentralized distributed, disrupting programming paradigm embodies key principles such as decentralization, data provenance, immutability, and transparency. At its core blockchain begins with the genesis block and progresses with each subsequent block containing the hash of the previous block, Merkle root, timestamp, a coin base transaction address, and a nonce. Miners compete to discover a target hash value (hash value of the previous block and nonce) for the current block, that is less than or equal to the difficulty value set by the system, a process known as mining.

This work encounters selfish mining attacks in bitcoin mining …

Computational Studies On The Major Antioxidant Enzymes Of Wuchereria Bancrofti Towards The Development Of Anti Filarial Leads, Sureshan M

Theses and Dissertations

Lymphatic filariasis (LF), or elephantiasis, is a mosquito-borne parasitic disease affecting the lymphatic system, primarily in tropical and subtropical regions. It is the second leading cause of long-term disability and a neglected tropical disease. According to WHO, LF threatens 882 million people in 44 countries, with over 9 billion treatments administered. The disease is caused by three nematodes: Wuchereria bancrofti (90% of cases worldwide, including India), Brugia malayi (10% in Southeast and Eastern Asia), and Brugia timori (found in Timor and nearby islands). Lymphatic filariasis (LF) is an ancient disease that continues to challenge scientists and physicians. Current treatments include …

Impact Of Ionic Liquids On The Treatment Of Various Derivatives Of Prosopis Juliflora For Removing Toxic Pollutants From Wastewater, Karthikeyan A

Theses and Dissertations

Water resources are increasingly contaminated by toxic pollutants, particularly industrial effluents, posing significant environmental concerns. Addressing the toxicity of these pollutants, especially those released from textile industries, presents challenges due to their harmful effects on living organisms. Various treatment methods are employed to mitigate this issue, including coagulation, flocculation, membrane filtration, photocatalytic degradation, adsorption, anaerobic processes, and chemical oxidation. Among these, adsorption emerges as an effective and economical method due to its minimal secondary contamination, negligible sludge production, and the use of inexpensive agricultural and marine waste materials.

This study examines the ability of Prosopis juliflora treated with imidazolium-based ionic …

Artificial Intelligence-Based Adaptive Data-Driven Techniques For Disruption Prediction In Tokamak, Priyanka M

Theses and Dissertations

Tokamaks are nuclear fusion reactors designed to generate sustainable energy by confining plasma, yet plasma disruptions remain a major obstacle as they can damage reactor components and interrupt fusion reactions. Addressing this challenge requires reliable models that can classify plasma discharges and predict disruptions in advance. This thesis develops machine learning and deep learning approaches to improve both classification and forecasting.The first contribution is a semi-supervised active learning framework, Nearest Margin-Ranked Batch Mode Active Learning (NM-RBMAL), integrated with an ensemble model.

Unlike traditional classifiers that operate on static training data, this approach continuously adapts to new plasma conditions, reducing model …

Ai Based Early Detection Of Hormonal Imbalance And Poly-Cystic Ovary Syndrome In Young Women, Reka S

Theses and Dissertations

A hormonal disorder, Poly-Cystic Ovary Syndrome (PCOS) usually affects women during the reproductive age. It is characterised by imbalances in hormones, particularly a rise in the female body's androgen level (male hormone) and enlarged ovaries with small cysts. PCOS can cause ovarian cysts, weight gain, acne, excessive hair growth, insulin resistance, and irregular menstrual cycles along with other health problems. While the exact origin of PCOS is uncertain and its symptoms are unclear, diagnosing PCOS in real-world conditions is a difficult task. Therefore, prompt and precise PCOS diagnosis is essential for efficient treatment and for averting long-term issues.

Clinicians typically …

Bioprospecting Of Wheat Straw Pyrolysis Aqueous Phase To Combat Multi-Drug Resistant Pathogens, Srividhya K

Theses and Dissertations

Hospital-acquired infections (HAIs) significantly contribute to the emergence and spread of antimicrobial resistance (AMR), primarily through the contamination of high-touch surfaces. Current disinfectants have drawbacks like high environmental persistence, ecotoxicity, and resistance development, prompting the need for environmentally friendly alternatives.

One potential approach is pyrolysis, during which the biomass components are broken down into solid, liquid, and pyro-gas. The aqueous phase of the liquid fraction is usually discarded as waste, but it contains a variety of organic compounds that have the potential for antibacterial and antifungal activity. The present study assessed the anti-infective and anti-biofilm properties of wheat straw pyrolysis …

Fabrication Of Transparent Conducting Electrodes By Chemical Approaches & Their Application Towards Sensing And Energy Storage, Namuni Sneha

Theses and Dissertations

In the intelligent era, there is a growing demand for developing highly efficient and robust wearable electrodes through simple chemical approaches. We developed highperforming transparent electrodes using interconnected Au nanoparticle networks via a simple liquid-liquid interface approach that offers high conductivity, transparency (>85%), and mechanical durability. Additionally, the prepared electrodes exhibit tunable transmittance and sheet resistance, and the method was also adaptable to various substrates without harsh chemical or thermal treatments.

Furthermore, using Au 1L (1-layer) nanonetwork, a highly transparent breath sensor is fabricated with short response and recovery times (1.1 s and 1.3 s). The Au-1L sensor is …

Design And Investigation Of Deep Eutectic Solvent-Assisted Extractive Fermentation Of Biomolecules, Ramya M

Theses and Dissertations

The increasing demand for sustainable and efficient bioprocessing techniques has prompted the development of novel separation strategies integrating bioproduction with downstream processing. Extractive fermentation has emerged as a promising process intensification to overcome product inhibition and enhance productivity by constantly removing target biomolecules from the fermentation medium. Although the extractive fermentation of acids and alcohols has been extensively studied, less attention has been focused on green solvents and their compatibility, phase-forming abilities, and reactor configurations.

Therefore, advancing extractive fermentation technology necessitates comprehensive studies on solvent systems and the development of modified bioreactor configurations to aid future optimization. Initially, 22 DESs …

Exploring Longitudinal Stability Of Spatiotemporal Sequential Patterns By Means Of Autoencoder Schemes For Eeg Based Personal Identification, Muhammed E. Oztemel

LSU Doctoral Dissertations

Robust personal identification remains a critical and challenging task in the digital era. Electroencephalography (EEG) offers a unique biometric modality that captures individual brain dynamics through complex neural signals. This dissertation proposes autoencoder (AE) based feature extraction and subject identification through these features. EEG recordings are first transformed into topographic maps to represent spatial brain activity. Consecutive topomaps are then concatenated to capture temporal transitions across frames. Convolutional autoencoders (CAEs) are used to learn spatial and temporal patterns, while domain-adaptive AEs are designed to model evoked potential based responses. Additionally, self-attention mechanism is incorporated to enhance feature representation. To analyze …

Investigation Of Dependency Parsing Techniques For Digital Document Analysis Through Deep Learning Approach, Rekah D Ms

Theses and Dissertations

Digital document dependency parsing is a significant task in natural language processing. Dependency parsing supports verification of the grammatical correctness of a sentence besides enabling extraction of relevant documents. Inappropriate extraction of features may result in falsely parsing a document, leading to decreased accuracy. Machine learning methods have been employed to perform feature extraction. However, selecting pertinent features was never achieved which minimizes the time consumption and overhead.

Hence, novel machine learning and deep learning techniques have been designed in our work for accurate and computationally efficient digital document analytics through dependency parsing. Four different contributions have been proposed for …

Cyclone Intensity Prediction In The Bay Of Bengal Using Deep Learning Methods, Senthil Kumar J

Theses and Dissertations

The Bay of Bengal region's coastlines have been badly devastated by tropical cyclones, as the region experiences an average of five to six cyclones per year, with about two to three of these intensifying into tropical storms or severe cyclones. Thus it necessitates to study the accurate and efficient forecasting of their intensity to improve preparedness and response to natural disasters. The present study compares and examines three distinct approaches to cyclone intensity prediction using historical datasets from 1998 to 2020: hybrid optimisation, deep learning-based, and empirical approaches.The predicted accuracy, computational effectiveness, and feasibility for real-time scenarios of each model …

Development Of Powder Activator From Agro-Industrial Waste And Its Application In The Preparation Of One-Part Alkali Activated Concrete, Anoop Kn

Theses and Dissertations

The environmental concerns associated with the traditional ordinary Portland cement (OPC) such as CO2 emission and high energy demand along with resource depletion as binder has led to the development of alkali activated binders (AABs). Even with the reduction in environmental issues, the implementation of AAB in practice is hindered by the handling issues of liquid activators. Hence, it is required to develop AAB with powdered activators to address the handling issues and to further reduce the environmental issues related to the production of activators. This research investigates the development of one-part alkali-activated concrete (OAAC) system utilising wastederived materials as …

Design Of An Integrated Lightweight Cryptographic Algorithm For Device Level Security And Fraternal Cryptographic Algorithm For Communication Security In Medical Cyber Physical Systems, Vimala Devi P

Theses and Dissertations

Healthcare involves detecting symptoms, diagnosing conditions and giving treatment to patients. It is one of the fundamental human rights, and it might be difficult to provide healthcare to those with chronic illnesses, elderly people with disabilities and those under distant observation. The World Health Organisation (WHO) states that Cardio Vascular Disease (CVD) is the leading cause of death worldwide.

According to the prediction, CVD-related causes such as heart attacks and strokes, could result in 23.3 million deaths by 2030. In addition, the number of people with diabetes will reach 246 million; thereby, the prevalence of CVD patients and diabetics will …

Investigations Of Secure Memory For Vlsi Based Crypto System, Vijay Sai R Mr

Theses and Dissertations

Semiconductor technology is growing very rapidly in their architectural developments, involving the usage of processor and memory. Presence of memory, in general is a vital commodity in various devices which are almost embedded into human activity, from robust work stations to handy mobile phones. Security of data stored in memory is very important, and hence, observation must be made that these valuable data should not be thwarted by malicious means. Security in cache memory is a major issue in memory related applications such as smart cards and bio-metric implementations.

Cache, is a small and limited memory located between central processing …

Effects Of Eogo In Metakaolin-Based Geopolymer, Chaewon Lee, Hoyoung Lee, Jinwoo An, Boo Hyun Nam

Civil Engineering Faculty Publications

Geopolymer concrete uses a geopolymer binder instead of traditional Portland cement; thus, it reduces carbon emissions by a significant amount. In this study, Edge-Oxidized Graphene Oxide (EOGO), a carbon-based nanomaterial, was added into a metakaolin-based geopolymer, and its effect on the mechanical and rheological properties of the mixture was investigated. EOGO was added into the mixture at 0% (control), 0.1%, 0.5%, and 1% of the metakaolin mass. Several experiments were conducted to characterize the properties of the metakaolin–EOGO (MKGO) geopolymer, including its compressive strength, free–free resonance column (FFRC), void content, water absorption, setting time, flow, and rheology. It was found …

Performance Analysis Of Pem Fuel Cells Via Puma Optimizer With The Aid Of Practical Verifications, Hossamm Ashraf, Sameh O. Abdellatif, Mahmoud M. Elkholy \, Attia A. El-Fergany

Electrical Engineering

This manuscript presents a novel application of the recently developed Puma Optimizer (PO) for identifying the unknown parameters in Mann’s model, which is widely used for characterizing the behavior of Polymer Electrolyte Membrane Fuel Cells (PEMFCs). The proposed PO-based methodology is rigorously evaluated using three test cases. One test case involves experimental I–V measurements under various operating conditions from a commercial PEMFC stack, the Horizon H-100 (100 W), which was assembled and tested in the laboratory. The other two cases are established benchmark PEMFC systems, the Ballard Mark V 5 kW and BCS 500 W units. Comprehensive statistical analyses over …