Engineering Commons^™

Techniques To Overcome Energy Storage Limitations In Electric Vehicles, Matthew J. Hansen

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles are becoming increasingly popular, battery limitations (cost, size, and weight) complicate electric vehicle adoption. While important research on battery development is ongoing, this dissertation discusses two main approaches to overcome those limitations within the existing battery technology paradigm. Those thrusts are: improving battery health through an optimal charging strategy and minimizing necessary battery size through dynamic wireless power transfer. In this dissertation, relevant literature is discussed, with opportunities for further development considered. Within the two thrusts, three objectives sharpen the focus of the research presented here. First, a planning tool is defined for a battery electric bus fleet. …

Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen

Data Science Undergraduate Honors Theses

This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …

Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback

Doctoral Dissertations and Master's Theses

College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …

Dig Limits Optimization Using Binary Integer Linear Programming Method In Open Pit Mines, Hussam Naif Altalhi

Masters Theses

"Dig limits optimization is the process for classifying different materials (e.g., ore, stockpile material, and waste) into appropriately sized contiguous zones for open pit mining. The efficient determination of dig-limits is crucial for profitable and sustainable resource extraction in mining. Previous research has focused on defining dig-limits manually or using optimization approaches, but these methods are limited to only handling two material destinations (ore and waste). Thus, there is a need for operations research methods that consider the selectivity of mining equipment and can optimize dig-limits for metal mining operations with more than two material destinations. Consequently, the objective of …

Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora

Computer Science and Engineering Theses

This thesis delves into the intricate symbiosis between machine learning (ML) methodologies and embedded hardware systems, with a primary focus on augmenting efficiency and real-time processing capabilities across diverse application domains. It confronts the formidable challenge of deploying sophisticated ML algorithms on resource-constrained embedded hardware, aiming not only to optimize performance but also to minimize energy consumption. Innovative strategies are explored to tailor ML models for streamlined execution on embedded platforms, with validation conducted across various real-world application domains. Notable contributions include the development of a deep-learning framework leveraging a variational autoencoder (VAE) for compressing physiological signals from wearables while …

Economy Of Scale Of Energy Intensity In Aquifer Storage And Recovery (Asr), Alyson Haley Rapp

Theses and Dissertations

More water utilities are adopting Aquifer Storage and Recovery (ASR) to balance long-term water supply and demand. Due to large implementation and operation costs, ASR projects need to be optimized, particularly for energy use, which is a major operating expense. This study examines the relationships among energy use, recharge, and recovery at two ASR projects in the western United States. The major finding is an economy of scale for recovery processes, but not for gravity-fed recharge processes. The economy of scale found is as follows: the energy intensity recovered decreases with volume. This suggests it is more energy-efficient to recover …

Imerys: Tube Mill Optimization Project, Ryan Waltman, Dalton Beasley, Dyson Beasley, Tristan Mcmichael

Senior Design Project For Engineers

The Tube Mill Optimization Project is in partnership with Imerys for Tube Mill 81 at their Marble Hill site in Georgia. Tube Mill 81 is a dry ball mill that operates 24/7 and makes an intermediary product for Plant 3. Tube Mill 81 needs quality improvement and a production rate increase to meet demand. Imerys’s quality specification is between a particle size of 12-18 microns and an acceptable production rate of 5 tons per hour. This project focuses on the development and implementation of three solutions: increase the amps on the separator to increase production, replace missing classifier blades in …

Optimization Of Hydraulic Cylinder Positioning For Wind Tower Hydraulic Erection System, Anbesh Rawal

Master's Theses

Wind produced electricity is a rapidly growing field with wind towers serving as critical components. Conventionally, special cranes are commonly used for wind tower erection. This study explores the use of hydraulic cylinders for small-scale wind tower erection. The thesis aims to find the optimal position of hydraulic cylinder connections in a hydraulic erection system for safe and energy-efficient tower erection and retraction and to enhance the performance and longevity of the system.

Structural analysis was conducted to investigate various hydraulic cylinder positioning configurations, ensuring minimal force exertion while maintaining structural integrity. The study included the selection of locally available …

Utilization Of Integer Programming For Scheduling Maintenance At Nuclear Power Plants, Timothy Gallacher

Doctoral Dissertations

This thesis develops a thought that naturally explores three specific motifs for solving the complexities of scheduling maintenance at Nuclear Power Plants (NPP). The first chapter of this paper will develop the initial thought around creating a schedule for a given work week, including all the various constraints inherent to this problem. Such constraints include but are not limited to personnel availability, allowable component out-of-service time, and the Plant Risk Assessment. The objective function being to minimize the total cost of worker’s compensation for that given week.

The second chapter addresses the question of whether this simple schedule can be …

Deep Reinforcement Learning For The Design Of Structural Topologies, Nathan Brown

All Dissertations

Advances in machine learning algorithms and increased computational efficiencies have given engineers new capabilities and tools for engineering design. The presented work investigates using deep reinforcement learning (DRL), a subset of deep machine learning that teaches an agent to complete a task through accumulating experiences in an interactive environment, to design 2D structural topologies. Three unique structural topology design problems are investigated to validate DRL as a practical design automation tool to produce high-performing designs in structural topology domains.

The first design problem attempts to find a gradient-free alternative to solving the compliance minimization topology optimization problem. In the proposed …

Parametric Optimization Of A Wing-Fuselage System Using A Vorticity-Based Panel Solver, Chino Cruz

Master's Theses

Aerodynamic topology optimization is a useful tool in the aerodynamic design pro-
cess, especially when looking for marginal gains within a design. One example is
a turboprop racer concept aircraft that is designed with the goal of breaking world
speed records. An optimization framework was developed with the intention of later
being applied to this design. In the early design stages, the optimization framework
must focus on quicker methods of drag estimation, such as a panel codes. The large
number of design variables in topology optimization can exponentially increase func-
tion evaluations and thus computational cost. A vorticity-based panel solver …

Cost Minimizing Energy Management Control Scheme For Microgrids Considering Dynamic Electricity Prices, Levi T. Miller

All Graduate Theses and Dissertations, Fall 2023 to Present

As countries develop and technology improves, the world is using more energy than ever before. This fact along with several other political, social, and economic factors has resulted in simultaneous energy and climate crises. A partial solution to both problems is bringing clean energy sources of electricity closer to the customers who use that energy. A microgrid is a smaller version of the national electric grid where smaller electricity generators are networked with local consumers and controlled independently of the main grid. Because control of electricity sources and loads are transferred to local controllers, the flexibility with which they can …

Extremum Seeking Control Algorithms For Extremely High Frequency Antenna System Pointing, Scott Shore

Mechanical Engineering ETDs

The research examines the application of extremum seeking control (ESC) algorithms to ground station antenna pointing for extremely high frequency (EHF) communication systems. ESC algorithms search for local maxima or minima by locating where an objective function gradient goes to zero. With wireless communication expanding into higher frequencies, the ground station pointing requirement is increasing. ESC presents a method which utilizes available equipment and information to perform ground station pointing. Additionally, ESC algorithms do not rely on assumptions or approximations needed for other techniques. The dissertation demonstrates ESC algorithm feasibility for the ground station pointing problem, benchmarks the ESC algorithms …

Surrogate-Assisted Simulation-Optimization Framework For Groundwater Management In A Multi-Aquifer System, Melika Mani

LSU Master's Theses

Uncontrolled groundwater exploitation can lead to aquifer depletion, land subsidence, and saltwater intrusion. Effective groundwater management is challenging due to the intricate nature of subsurface hydrogeology and spatiotemporally variable pumping, especially in a multi-aquifer system. To ensure sustainable withdrawal, multi-objective optimization is an effective tool for balancing management goals and drawdown effects. However, running simulation-optimization using detailed groundwater models is computationally expensive, pushing decision-makers to decide based on limited scenarios. In this study, a hydrogeological framework was constructed for the Capital Area, Louisiana, allowing for individual assessment of each unit to better understand each aquifer's condition. Moreover, a surrogate-assisted simulation-optimization …

Resource Allocation In Subsidy Welfare Programs: Managerial Insights For Nonprofits, Governments, And Service Providers, Wei Wei

Doctoral Dissertations

Subsidy welfare programs provide financial assistance to economically disadvantaged individuals and families to access essential and life-altering services (e.g., education, child care, and housing) that they might not otherwise have access to. Access to these services is considered critical to achieving a better and more sustainable future for all. As such, these high-quality services are directly related to several United Nations Sustainable Development Goals, which were adopted as a universal call to action to end poverty, save the planet and improve the lives and prospects of everyone, everywhere." In particular, the need for these affordable and high-quality services has been …

Reduced Bias User Preference Methods For Determining The Pareto-Optimal Solution Point, Dylan Thomas Johnson

Master's Theses (2009 -)

Engineering design is filled with tradeoffs between competing objectives such as performance, mass, cost, and schedule. A designer must navigate these complex multi-objective problems and deliver the right solution for their application. Multi-objective optimization techniques are powerful and widely used; however, a key drawback to these techniques is that they often output a set of equivalent solutions called the Pareto Front. The designer must perform an additional multi-objective down selection on the Pareto Front to determine a single Pareto-optimal solution point for their design. Existing Pareto Front processing techniques either use traditional infinitely adjustable weights, which can yield results that …

Water Quality Monitoring And Mapping Using Rapidly Deployable Sensor Nodes, Mohamed Abdelwahab

Theses and Dissertations

Efficient and continuous monitoring of water quality parameters plays a pivotal role in responding to pollution incidents and ensuring the safety of both human consumption and ecological resources. This research introduces an affordable and dependable in-situ water quality sensor package designed for seamless continuous monitoring, providing essential data to facilitate informed decision-making in water resource management. The sensor package enables comprehensive on-site assessment of key water characteristics, including pH, temperature, turbidity (measured in NTU), and total dissolved solids (TDS, measured in ppm). Spatial interpolation techniques, specifically Kriging, are employed to extrapolate variable values at unobserved locations based on nearby measurements. …

Developing A Smart And Sustainable Public Transportation System: A Case Study In Camden, New Jersey, Zahra Vafakhah

Theses and Dissertations

The transportation sector is a major contributor to air pollution and Greenhouse Gas (GHG) emissions. As a significant source of emissions, public transportation presents an opportunity for mitigation through electrification. However, transitioning to an electric bus fleet necessitates substantial investments in bus procurement and charging infrastructure. To address the associated costs, this study introduces a mixed-integer linear mathematical model developed to optimize the location of on-route fast charging stations within bus networks. The central objective of this optimization formulation is to minimize the overall cost of establishing the charging infrastructure. The study employs a real-world case study focusing on a …

Transforming Large-Scale Virtualized Networks: Advancements In Latency Reduction, Availability Enhancement, And Security Fortification, Ibrahim Tamim

Electronic Thesis and Dissertation Repository

In today’s digital age, the increasing demand for networks, driven by the proliferation of connected devices, data-intensive applications, and transformative technologies, necessitates robust and efficient network infrastructure. This thesis addresses the challenges posed by virtualization in 5G networking and focuses on enhancing next-generation Radio Access Networks (RANs), particularly Open-RAN (O-RAN). The objective is to transform virtualized networks into highly reliable, secure, and latency-aware systems. To achieve this, the thesis proposes novel strategies for virtual function placement, traffic steering, and virtual function security within O-RAN. These solutions utilize optimization techniques such as binary integer programming, mixed integer binary programming, column generation, …

Modeling And Solution Methodologies For Mixed-Model Sequencing In Automobile Industry, Ibrahim Ozan Yilmazlar

All Dissertations

The global competitive environment leads companies to consider how to produce high-quality products at a lower cost. Mixed-model assembly lines are often designed such that average station work satisfies the time allocated to each station, but some models with work-intensive options require more than the allocated time. Sequencing varying models in a mixed-model assembly line, mixed-model sequencing (MMS), is a short-term decision problem that has the objective of preventing line stoppage resulting from a station work overload. Accordingly, a good allocation of models is necessary to avoid work overload. The car sequencing problem (CSP) is a specific version of the …

Improving Mobility And Safety In Traditional And Intelligent Transportation Systems Using Computational And Mathematical Modeling, Shahrbanoo Rezaei

Doctoral Dissertations

In traditional transportation systems, park-and-ride (P&R) facilities have been introduced to mitigate the congestion problems and improve mobility. This study in the second chapter, develops a framework that integrates a demand model and an optimization model to study the optimal placement of P&R facilities. The results suggest that the optimal placement of P&R facilities has the potential to improve network performance, and reduce emission and vehicle kilometer traveled. In intelligent transportation systems, autonomous vehicles are expected to bring smart mobility to transportation systems, reduce traffic congestion, and improve safety of drivers and passengers by eliminating human errors. The safe operation …

Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton

Electrical and Computer Engineering ETDs

With the complexity of high-performance computing designs continuously increasing, the importance of evaluating with simulation also grows. One of the key design aspects is the network architecture; topology and bandwidth greatly influence the overall performance and should be optimized. This work uses simulations written to run in the Structural Simulation Toolkit software framework to evaluate a variety of architecture configurations, identify the optimal design point based on expected workload, and evaluate the changes with increased scale. The results show that advanced topologies outperform legacy architectures justifying the additional design complexity; and that after a certain point increasing the bandwidth provides …

A Systems Approach To Design And Plan Sustainable Antifragile Infrastructure Based On Aggregate Footprint And Satisfaction, Farboud Khatami

Theses and Dissertations

The concepts of robustness and sustainability in planning and design of water and energy infrastructures have been extensively explored in previous research, primarily focusing on system reliability, environmental considerations, and economic aspects. This study aims to broaden the understanding of these concepts by offering comprehensive frameworks that capture the essence of robustness and sustainability at two distinct levels.

The first level of investigation focuses on the performance of infrastructure networks during natural disasters. Traditionally, this has been addressed using reliability, resilience, and vulnerability metrics. However, these methods rely on static, deterministic, and non-stationary data, which is inadequate when dealing with …

Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young

Electronic Theses and Dissertations

While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …

Distributed Control Of Servicing Satellite Fleet Using Horizon Simulation Framework, Scott Plantenga

Master's Theses

On-orbit satellite servicing is critical to maximizing space utilization and sustainability and is of growing interest for commercial, civil, and defense applications. Reliance on astronauts or anchored robotic arms for the servicing of next-generation large, complex space structures operating beyond Low Earth Orbit is impractical. Substantial literature has investigated the mission design and analysis of robotic servicing missions that utilize a single servicing satellite to approach and service a single target satellite. This motivates the present research to investigate a fleet of servicing satellites performing several operations for a large, central space structure.

This research leverages a distributed control approach, …

An Analysis Of The Production Of Pharmaceutical-Grade Acetone Via The Dehydrogenation Of Isopropanol (Ipa), Jordan Desplas

Honors Theses

The production of 99.9 wt% acetone from isopropanol in Unit 1100 is designed to start up in 2025 and operate for 12 years after startup. The engineering team was tasked with designing the process, creating an economic model, and optimizing the net present value (NPV). The process was simulated in AVEVA PRO/II Simulation for the design process, and the economic analysis was estimated in Microsoft Excel. Parametric and topological optimization was performed linearly on the unit operations in the process. The NPV was improved by $14M from a base case of $122M to an optimized case of $136M. The project …

Exploiting Symmetry In Linear And Integer Linear Programming, Ethan Jedidiah Deakins

Doctoral Dissertations

This thesis explores two algorithmic approaches for exploiting symmetries in linear and integer linear programs. The first is orbital crossover, a novel method of crossover designed to exploit symmetry in linear programs. Symmetry has long been considered a curse in combinatorial optimization problems, but significant progress has been made. Up until recently, symmetry exploitation in linear programs was not worth the upfront cost of symmetry detection. However, recent results involving a generalization of symmetries, equitable partitions, has made the upfront cost much more manageable.

The motivation for orbital crossover is that many highly symmetric integer linear programs exist, and …

Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno

Open Access Theses & Dissertations

Natural disasters have been determined as the leading cause of power outages, causing not only huge economic losses, but also the interruption of crucial welfare activities and the arise of security concerns. Because of the later, decision-making considering grid modernization, power system economics, and system resiliency has been a crucial theme in power systemsâ?? research. The need to better withstand catastrophic events and reducing the dependency of bulky generating units has propelled the development and better management of behind-the-meter generation or distributed energy resources (DERs). DERs can assist in the grid in different manners, not only by meeting energy demand …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Chance Constrained Stochastic Optimal Control Of Discrete Time Linear Stochastic Systems With Applications In Multi-Satellite Operations, Shawn Priore

Electrical and Computer Engineering ETDs

Stochastic disturbances arise in a variety of engineering applications. For tractability, Gaussian disturbances are often assumed. However, this may not always be valid, such as when a disturbance exhibits heavy-tailed or skewed phenomena. As autonomous systems become more ubiquitous, non-Gaussian disturbances will become more common due to the compounding effects of sensing, actuation, and external forces. Despite this, little has been done to develop formal methods that are both computationally efficient and allow for analytical assurances with non-Gaussian disturbances. Addressing convex polytopic set acquisition and non-convex collision avoidance chance constraints with quantile and moment-based reformulations, this dissertation proposes novel stochastic …