Enhanced Optimization Of Mass Transfer For Carbon Capture And Wastewater Remediation In Algal Systems Through Algorithmic And Bioprocessing Techniques, Peter Ofuje Obidi

Doctoral Dissertations

The scalability and industrial deployment of algal cultivation systems are limited by suboptimal mass transfer, constraining their effectiveness in carbon capture and wastewater remediation. This research investigated these challenges through integrated optimization methodologies that combine algorithmic frameworks with enhanced bioprocessing techniques to enhance efficiency, economy, and scalability. A System-of-Systems (SoS) meta-architecture was developed using genetic algorithms and fuzzy assessor functions to demonstrate a pathway toward cost reduction. Rigorous mechanical and chemical characterizations were quantitatively analyzed to reveal existing optimization strategies and further evaluated the best strategies to use in enhancing mass transfer for improved biomass yield. The work also integrates …

Investigation Of Arm Stiffness Modulation During Overground Physical Human-Human Interaction, Henry Tien

Masters Theses

The vision of advancing robots capable of direct physical engagement with humans begins with an understanding of how humans interact with each other. Even rudimentary interactive tasks, such as shaking hands, provides tremendous challenges for modern robotics and current research into the biomechanics of such interactions is limited. Thus, further analysis of physical Human-Human Interaction (pHHI) will bolster efforts to enhance collaborative robot capabilities. To this end, a custom Force Perturbation Handle (FPH) was developed, including the requisite mechanical, electrical, and software systems, to investigate the unique role of arm stiffness modulation in haptic communication between humans. The novel device …

Aerodynamic Design Workflow Optimization For Fsae: Advanced Cfd And Hpc Automation, Kyle Maynor

Masters Theses

This research identifies and resolves inefficiencies in the Computational Fluid Dynamics (CFD) workflow of the Missouri S&T Racing Formula SAE Team’s aerodynamic development. Key bottlenecks were found in simulation runtime, laborious simulation preparation, an overly manual simulation submission process, and unchecked mesh quality. A fully reimagined workflow was implemented with simulation parameters to adjust vehicle attitudes. From this, an automated design sweep could be executed to generate aero maps of the developing vehicle using the Design Manager Project. A Python-based submission app handles the terminal interfacing and macro editing that significantly slowed the job submission process before. Using a university …

Impacts Of A Multi-Layered Acousto-Elastic Bottom On Sound Propagation In A Seamount Environment, Haley H. Green

Open Access Master's Theses

The New England Seamounts Acoustics (NEMSA) experiment is a comprehensive oceanographic field study aimed at investigating underwater acoustic propagation and scattering effects within a complex marine environment. The primary objective of this research is to assess the influence of seafloor and sub-bottom geoacoustic properties on acoustic propagation, signal reflections, and transmission loss at Atlantis II Seamount. Two acoustic models, BOUNCE and BELLHOP, were employed to incorporate elastic wave effects within the sub-bottom layers and facilitate the analysis of range-dependent bathymetric features. Two model scenarios were analyzed and compared, one with a layered elastic bottom and another with a fluid bottom …

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft transforms future transportation systems by alleviating transportation congestion on the ground. This eVTOL technique possesses unique features, including reduced noise, low pollutant emissions, efficient operating costs, and flexible maneuverability. Meanwhile, battery consumption poses critical challenges to flight task duration. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimization, however, iteratively evaluates high fidelity simulation models, making the design process computationally intensive. In this work, we implement a machine learning-enabled inverse mapping optimization concept, i .e., directly predicting optimal design based on design requirements (including …

Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Design problems in aerospace engineering often require numerous evaluations of expensive to-evaluate high-fidelity models, resulting in prohibitive computational costs. One way to address the computational cost is through building surrogates, such as deep neural networks (DNNs). However, DNNs may only be an effective surrogate when sufficient evaluations of the high-fidelity model are required such that the up-front training cost is amortized, or in situations that require real-time responses (such as interactive visualizations). Typically, the data requirements for adequately accurate training of DNNs are often impractical for engineering applications. To alleviate this issue, the proposed work utilizes output dimensionality reduction along …

Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu

Chemistry Faculty Research & Creative Works

Bone tissue engineering (BTE) aims to repair bone defects using biocompatible materials with tailored geometries and pore structures, providing appropriate mechanical support and control over biodegradation kinetics to promote bone growth. In this study, we utilized digital light processing (DLP) 3D printing to fabricate scaffolds with varying pore sizes using polymer–ceramic slurries composed of polylactic acid (PLA) as the main polymer matrix, incorporated with hydroxyapatite (HA) and bioactive borate glass (BBG) at various ratios. We studied the effect of composition on rheological behavior, printability, mechanical properties, bioactivity, degradation rate, and biocompatibility. While HA increased viscosity and reduced printing accuracy, it …

Few-Shot Learning-Enhanced Tiered Path Planning For Mars Rover Navigation, Ziyi Wang, Di Yu, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Path planning for Mars rovers presents significant challenges due to the diverse terrain, ranging from easily navigable areas to hazardous zones. Traditional methods typically classify terrain simply as passable or impassable, failing to account for the nuances of more moderately challenging areas. In this paper, we introduce a tiered terrain-aware path planning strategy, employing few-shot learning to classify and segment Martian terrain into levels of difficulty. The few-shot learning model, trained on Earth, is sent to the rover, enabling real-time processing of images from satellites or helicopters. The flexibility of few-shot learning, which requires minimal data and training time, enables …

Advancing Cislunar Space Domain Awareness Through Robust Optimization Framework For Optical Sensors-Based Autonomous Satellite Systems, Smriti Nandan Paul, Siwei Fan, Igor Panfil

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The number of cislunar resident space objects is expected to proliferate rapidly because of strategic interests targeting long-term presence on the Moon and exploration of other planets (e.g., Artemis Accords) and liberalization of space through the entry of private space players (e.g., Intuitive Machines). It necessitates expanding current near-Earth space domain awareness (SDA) operation systems and knowledge to the relatively unexplored cislunar region. Besides the traditional complexities, xGEO orbits (orbits beyond the geosynchronous Earth orbit (GEO) region) face additional challenges because of highly non-linear and non-Keplerian dynamics, which results in inaccuracies in uncertainty propagation and state estimation. Further challenges include …

Safety And Sustainability In The Domestic Ferry Sector : A Pci Framework For Esg-Aligned Maritime Governance, Mirza Zeeshan Baig

World Maritime University Ph.D. Dissertations

The domestic ferry sector is a significant component of maritime transportation. It strengthens social ties, supports economic growth and connects communities. Despites its importance, this industry faces ongoing challenges. These include fragmented governance, operational adequacies, safety risks and environmental concerns. The study deals with these issues by combining a systems-based approach with governance and change management theories. It examines the interplay between human, technical and organizational aspects. The study integrates the rule-based and rights-based maritime governance along with the Lewin’s three stage change management model (Unfreeze, Change, and Refreeze).

At the core of the study is the development of a …

Reactive Model-Free Control For Underactuated Vehicles Operating In Resource-Constrained Environments, Austin Lane Sponaugle

Graduate Theses, Dissertations, and Problem Reports (ETD)

Buoyancy-driven, underactuated vehicles offer a compelling solution for long-duration autonomous operations in constrained environments. By leveraging buoyancy to generate lift, these vehicles can remain aloft for extended periods with minimal power requirements, making them well-suited for applications in atmospheric monitoring, planetary exploration, and communications. However, their limited actuation authority, strong coupling with environmental forces, and operating domains introduce significant control challenges, including nonlinearity, sensitivity to external disturbances, and limited observability.

This work investigates the design and implementation of lightweight, reactive model-free control strategies that enable robust autonomy in such constrained settings. A digital Extremum Seeking Controller (ESC) is first implemented …

Dynamic Force Feedback Controller Improves Metrics Of Stepping In A Biomimetic Robot Leg, Isabella Mae Kudyba

Graduate Theses, Dissertations, and Problem Reports (ETD)

Force feedback is a type of robotic control where forces are measured, fed back into the control system, and actuation is adjusted to compensate for environmental forces, with the goal of quick and precise limb positioning in walking. Robots of today use single force sensors (e.g. pressure sensitive pads, load cells) per leg which are often bulky, expensive, and susceptible to crosstalk. Walking robots often employ model predictive controllers or policy controllers trained through reinforcement learning (RL) to actuate their limbs, but these methods are time and energy consuming. Biomimetic robots offer an alternative approach, investigating biological theories with the …

A Novel Intelligent Thermal Feedback Framework For Electric Motor Protection In Embedded Robotic Systems, Mohamed Shili, Salah Hammedi, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

As robotic systems advance in autonomy and sophistication while being used in uncertain environments, the challenge of building reliable and robust electric motors that are embedded into robotic systems has never been a more important engineering problem. Thermal distress caused by extended operation or excessive loading can negatively affect a motor’s performance and efficiency and lead to catastrophic hardware failure. This paper proposes a novel intelligent control framework that includes real-time thermal feedback for hybrid electric motors that are embedded into robotic systems. The framework relies on adaptive control techniques and lightweight machine learning techniques to estimate internal motor temperatures …

Advances In Battery Modeling And Management Systems: A Comprehensive Review Of Techniques, Challenges, And Future Perspectives, Seyed Saeed Madani, Yasmin Shabeer, Ananthu Shibu Nair, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, Shi Xue Dou, Khay See, Saad Mekhilef, Françios Allard

Electrical & Computer Engineering Faculty Publications

Energy storage systems (ESSs) and electric vehicle (EV) batteries depend on battery management systems (BMSs) for their longevity, safety, and effectiveness. Battery modeling is crucial to the operation of BMSs, as it enhances temperature control, fault detection, and state estimation, thereby maximizing efficiency and preventing malfunctions. This paper thoroughly examines the most recent advancements in battery and BMS modeling, including data-driven, thermal, and electrochemical methods. Advanced modeling approaches are explored, including physics-based models that incorporate mechanical stress and aging effects, as well as artificial intelligence (AI)-driven state estimation. New technologies that facilitate data-driven decision-making, real-time monitoring, and simplified systems include …

Design Of A Spacecraft Power System Experiment, Jay Bakulkumar Kamdar

Masters Theses

This research delves into the design, implementation, and analysis of a controlled experimental framework for photovoltaic cell characterization and its application in spacecraft power systems. Such a system was simulated and validated by benchmarking characteristics of a photovoltaic module and implementing them in a system design simulation yielding performance data for comparative analysis. A hardware setup was developed to perform IV characterization tests under steady state thermal conditions. Experiments conducted across various thermal regulation profiles helped quantify the effects of temperature on the photovoltaic performance parameters. Active cooling reduced the steady state cell temperature by 17.9% and improved the cell …

Mechanical And Thermal Characterization Of Additively Manufactured Carbon/Nylon 12 And Carbon/Peek Composites, Matik Heskin, Bradley Deuser, Thomas P. Schuman, K. Chandrashekhara, John Bayldon, Jeff Degrange, Steven Patterson, Neiko Levenhagen

Chemistry Faculty Research & Creative Works

This study explores additive manufacturing of carbon fiber-reinforced thermoplastic composites using the Composite-Based Additive Manufacturing (CBAM) process. Carbon/Nylon 12 and Carbon/PEEK composites were fabricated and evaluated through mechanical (compression, tensile, flexural, and impact) and thermal (DSC and TGA) tests. Carbon/PEEK exhibited superior mechanical performance, with 97.5% higher tensile strength, 79.8% higher elastic modulus, and 59.6% higher flexural strength compared to Carbon/Nylon 12. Thermal testing showed that Carbon/PEEK had higher thermal stability, beginning degradation at 350 °C versus 298 °C for Carbon/Nylon. These results indicate that CBAM-fabricated Carbon/PEEK composites are suitable for applications requiring high strength and temperature resistance.

Numerical Investigation Of Pressurized Oxy-Combustion, Lei Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pressurized oxy-combustion (POC) is emerging as a promising and transformative technology for carbon capture, utilization, and storage, offering advantages of low cost, low emissions, and high efficiency. POC operates by burning pulverized coal at elevated pressures in a recycled flue gas environment, typically rich in O₂ and CO₂. This study presents a comprehensive numerical investigation into the fundamental behaviors of lab-scale POC reactors, using both two-dimensional (2D) Reynolds-Averaged Navier-Stokes (RANS) simulations and three-dimensional (3D) Large-Eddy Simulations (LES) with the commercial computational fluidized dynamics (CFD) software package ANSYS Fluent.

The primary focus of this work is to understand flame stabilization and …

Assessing And Predicting The Impact Of A Retrofitted Methane Mitigator On Non-Road Large Natural Gas Engines Using Artificial Neural Networks, Augustine Thomas Ojo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract

ASSESSING AND PREDICTING THE IMPACT OF A RETROFITTED METHANE MITIGATOR ON NON-ROAD LARGE NATURAL GAS ENGINES USING ARTIFICIAL NEURAL NETWORKS

Augustine Thomas Ojo

Methane emissions from the oil and gas sector present a pressing environmental and economic challenge, given methane’s high global warming potential and the considerable volumes of unutilized gas lost from industrial processes. This study investigates the impact of a retrofitted methane mitigation system, the Methane Mitigator (M²), on fuel consumption and engine-out emissions in non-road, four-stroke natural gas-powered, lean-burn engines and develops predictive Artificial Neural Network (ANN) models to estimate the resulting engine-out emissions and fuel …

Fundamental And Applied Investigation Of Ammonia Combustion: Characteristics And Emissions At Relevant Ic Engine Conditions, Luis Fernando Alvarez Correa

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ammonia (NH3) is regarded as a promising fuel for future carbon-free power and propulsion systems due to its high hydrogen content, ease of storage, and existing infrastructure. Despite these advantages, NH3 exhibits inherently poor combustion characteristics, including low laminar burning velocity, high ignition energy, narrow flammability limits, and sluggish chemical kinetics. These limitations were solved in prior research by blending NH3 with hydrogen (H2) or hydrocarbons, which improved reactivity but introduced trade-offs such as increased complexity, safety concerns, or carbon emissions. Consequently, there remains a significant lack of fundamental and applied research on neat NH3 combustion, particularly under engine-relevant conditions …

Effects Of The Upwind Spanwise Heterogeneous Terrain On The Wind Resource Distribution, Haosen H.A. Xu, Tianxiang Yu, Raúl Bayoán Cal, Xiaowei Zhu

Mechanical and Materials Engineering Faculty Publications and Presentations

Wind energy has become increasingly crucial among renewable energy resources, and as the prerequisite for effective wind energy utilization, accurate wind resource assessments are hence prominent. Topography significantly affects near-surface wind fields and is thus an essential factor to be considered for wind resource assessment. However, few studies have addressed the wind resource distribution downwind of spanwise-heterogeneous terrains, which are frequently encountered in both natural and urban environments. To fill this gap, large eddy simulations were performed to investigate wind distributions over a uniform terrain downwind of terrains featuring spanwise-alternating strips of low and high surface roughness, and the high …

Comparison Of Cnn And Lstm Networks On Human Intention Prediction In Physical Human-Robot Interactions, Khosro Ghorbani Zadeh, Niloofar Zendehdel, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Ming-Chuan Leu, Yun Seong Song

Psychological Science Faculty Research & Creative Works

Advancements in robotics and AI have increased the demand for interactive robots in healthcare and assistive applications. However, ensuring safe and effective physical human-robot interactions (pHRIs) remains challenging due to the sophistication of human motor communication and intent recognition. Traditional physics-based models struggle to capture the dynamic nature of human force interactions, limiting robot adaptability. To address these limitations, neural networks (NNs) have been explored for force-movement intention prediction. While multi-layer perceptron (MLP) networks show potential, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks effectively model sequential dependencies, while Convolutional Neural Networks (CNNs) enhance spatial feature …

A Generalized Coherence Framework For Quantifying Input Contributions In Multi-Input Systems With Correlated Or Uncorrelated Inputs, Nolan H. Howes, Matthew S. Allen, Dario Farina, Steven Knight Charles

Faculty Publications

In multi-input systems, it is often necessary to quantify the contribution of each input to an output. Such contribution analysis is frequently performed using coherence. However, when correlation is present between inputs, existing coherence measures do not accurately quantify the contribution of individual inputs, except in special cases. Here we propose an expanded coherence framework that enables contribution analysis in any multi-input system, regardless of input correlation. We bridged the gap by defining three new coherence measures: component, excluded, and isolated coherence. Component coherence is an intermediate measure that decomposes measured output power into components attributable to inputs directly vs …

Effect Of Alkyd And Polyester Resin Compositions On Corrosion Resistance, Blistering, And Adhesion In Utilization Of Oily Sludge As Anti-Rust Coating Material, Gerets Land Kakalang, Yohanes David Kristianto, Johny Wahyuadi Mudaryoto

Journal of Materials Exploration and Findings

Oil sludge is a waste derived from upstream and downstream activities of the oil and gas industry which is estimated at 10,000 tonnes generated from all PERTAMINA downstream activities spread across various fields, processing units and depots throughout Indonesia. Oil sludge has the same characteristics as asphalt, where asphalt in previous studies can be used as an anti-rust coating, so that the handling of oily sludge can be topped up by reusing and having its own added value. The purpose of this research is to utilise waste oily sludge as an alternative anti-rust coating material and compare alkyd resin and …

A Comparative Study Of Conventional And Statistically Active Corrosion Methods For Corrosion Growth Assessment Of A 24-Inch Gas Pipeline, Rudi Rinaldi, Jaka Fajar Fatriansyah

Journal of Materials Exploration and Findings

Component failures in oil and gas pipelines can have fatal consequences, leading to operational downtimes and environmental damage. Knowledge of the corrosion growth rate is fundamental to pipeline integrity management, as it is essential for risk assessment and decisions related to asset management. This article aimed to compare two approaches for the corrosion growth estimation of the 24-inch offshore gas pipeline: the conventional method versus the Statistically Active Corrosion (SAC) method. This article is based on the in-line inspection (ILI) results of two consecutive assessments from 2020 to 2023 of the entire 73 km of the pipeline. The results show …

Developing A Roadmap For Green Port In Timor-Leste, Emanuel Da Silva Maia

World Maritime University Dissertations

No abstract provided.

Assessing Potential Energy Sustainability Of Micro-Hydropower System Through A Sustainable Indicator Approach, Icmi Alif Safitri, Muhammad Sulaiman, Rachmawan Budiarto

Journal of Environmental Science and Sustainable Development

The development of micro-scale renewable energy power generation systems, such as micro-hydropower (MHP), often needs more consideration for sustainability during the planning stages. Many small-scale renewable energy systems have shorter-than-expected lifespans, jeopardizing Indonesia's Net Zero Emission Target for 2060 or earlier. Despite this, only some studies have examined the long-term viability of installed renewable energy generation projects, particularly MHP plants not managed by state-owned companies or PLN (Pembangkit Listrik Negara). The primary objectives of this research are to evaluate the feasibility of retrofitting and assess the potential sustainability of a decommissioned MHP in Banjarnegara, Central Java. A cash flow analysis …

Nano-Second Pulsed Laser Ablation Of Inconel 718 And Mmpcd For Simultaneous Optimal Ablation Rate And Surface Quality, Ahmed Elkaseer, Islam Abdelgaliel, Jon Lambarri, Iban Quintana, Steffen Scholz, Mohamed Aly

Mechanical Engineering

This study investigates the ablation performance of Inconel 718, a nickel-based superalloy, and metalmatrix polycrystalline diamond (MMPCD), a super composite, using a nano-second (ns) pulsed laseracross a range of ablation conditions. Single trenches varying in energy fluence and scanning speedswere created, analyzing the experimental responses in terms of ablation rate and surface roughness.Using regression techniques, models were developed to understand these relationships. Four multi-objective optimization algorithms, weighted value grey wolf optimizer (WVGWO), multi-objectivePareto search (MOPS), multi-objective genetic algorithm (MOGA), and multi-objective sunfloweroptimization (MOSFO), were employed to optimize these models. Key findings include MMPCDachieving the highest ablation rates at maximum fluence …

Energy-Efficient Technologies For Drying Mulberry Silkworm Cocoons Using Infrared Radiation, Doston Ishmukhammat Ugli Samandarov

Technical science and innovation

The article presents the results of theoretical and experimental studies on drying of mulberry silkworm cocoons. Based on the analysis of drying efficiency and silk quality, the use of infrared radiation (IR) at a temperature of 70 °C was found to be optimal. The experimental data were tested on six mathematical models, among which the Midilli model most accurately described the drying process. The effective moisture diffusion coefficient was found to vary in the range of 1.847×10^-⁹-4.339×10^-⁹ m²/s, and the drying rate was found to be 0.32-0.79 kg of water/hour. IR radiation promotes accelerated evaporation of …

Energy Saving Technology For Drying Garlic (Allium Sativum), Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Sultanova, А M. Mirkomilov

Technical science and innovation

Food drying is a widely used preservation method aimed at reducing water content to extend shelf life, decrease weight, and enhance storage efficiency. This process, particularly in garlic, involves rapid initial moisture loss followed by a slower phase due to the increasing difficulty of extracting residual water. Drying methods include natural solar drying and advanced mechanical techniques such as hot air and vacuum drying, each influencing product quality, drying efficiency, and economic feasibility. Dehydrated garlic exhibits specific sensory, physico-chemical, and microbiological characteristics, making it suitable for various applications, including powder production. Advanced drying equipment optimizes air volume, temperature, and material …