Digital Commons Network^™

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 …

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 …

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 …

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 …

Multi-Objective Optimization Of The Fast Neutron Source By Machine Learning, John L. Pevey

Doctoral Dissertations

The design and optimization of nuclear systems can be a difficult task, often with prohibitively large design spaces, as well as both competing and complex objectives and constraints. When faced with such an optimization, the task of designing an algorithm for this optimization falls to engineers who must apply engineering knowledge and experience to reduce the scope of the optimization to a manageable size. When sufficient computational resources are available, unsupervised optimization can be used.

The optimization of the Fast Neutron Source (FNS) at the University of Tennessee is presented as an example for the methodologies developed in this work. …

Power Market Cybersecurity And Profit-Targeting Cyberattacks, Qiwei Zhang

Doctoral Dissertations

The COVID-19 pandemic has forced many companies and business to operate through remote platforms, which has made everyday life and everyone more digitally connected than ever before. The cybersecurity has become a bigger priority in all aspects of life. A few real-world cases have demonstrated the current capability of cyberattacks as in [1], [2], and [3]. These cases invalidate the traditional belief that cyberattacks are unable to penetrate real-world industrial systems. Beyond the physical damage, some attackers target financial arbitrage advantages brought by false data injection attacks (FDIAs) [4]. Malicious breaches into power market operations could induce catastrophic consequences on …

A Numerical Optimization Study Of A Novel Electrospray Emitter Design, Joshua H. Howell

Masters Theses

The low thrust and high specific impulse of electric propulsion has been brought to the forefront for CubeSat and small spacecraft applications. Electrospray thrusters, which operate via electrostatic principles, have seen much research, development, and application in recent years. The small sizes of the spacecraft that utilize electrospray thrusters has focused development into the miniaturization of this technology to the micro-scale. Miniaturization introduces design challenges that must be addressed, including power supply mass and footprint requirements. This consequence requires investigation into the effects of design choices on the thruster onset voltage, defined as the voltage at which ion emission begins. …

Optimal Communication Structures For Concurrent Computing, Andrii Berdnikov

Doctoral Dissertations

This research focuses on communicative solvers that run concurrently and exchange information to improve performance. This “team of solvers” enables individual algorithms to communicate information regarding their progress and intermediate solutions, and allows them to synchronize memory structures with more “successful” counterparts. The result is that fewer nodes spend computational resources on “struggling” processes. The research is focused on optimization of communication structures that maximize algorithmic efficiency using the theoretical framework of Markov chains. Existing research addressing communication between the cooperative solvers on parallel systems lacks generality: Most studies consider a limited number of communication topologies and strategies, while the …

Costs Of Protected Areas In The United States, Diane Le Bouille

Doctoral Dissertations

Protected areas, or land owned in fee by agencies and non-profits to further conservation goals, have traditionally been the go-to choice for conservation interests. The UN Environment World Conservation Monitoring Centre estimates that, currently, close to 15% of all terrestrial and inland water areas are protected. This figure falls short of the Aichi Biodiversity Target of 17% in 2020, that was added to the Convention on Biological Diversity by its 196 signatories in 2010. But as the Convention prepares to set new post-2020 targets, this percentage is expected to keep increasing. Although acquiring a parcel of land is only one …

Benchmarks And Controls For Optimization With Quantum Annealing, Erica Kelley Grant

Doctoral Dissertations

Quantum annealing (QA) is a metaheuristic specialized for solving optimization problems which uses principles of adiabatic quantum computing, namely the adiabatic theorem. Some devices implement QA using quantum mechanical phenomena. These QA devices do not perfectly adhere to the adiabatic theorem because they are subject to thermal and magnetic noise. Thus, QA devices return statistical solutions with some probability of success where this probability is affected by the level of noise of the system. As these devices improve, it is believed that they will become less noisy and more accurate. However, some tuning strategies may further improve that probability of …

Coffee Supply Chain Planning Under Climate Change, Rui Zhou

Masters Theses

Coffee is a valuable crop for many tropical countries and provides an export value estimated at US$30.1 billion in 2019 worldwide. Coffee trees are climate sensitive. Published studies show that climate change is projected to have a negative impact on suitable growing areas for coffee beans, so the coffee bean production is facing a rising risk. At the same time, the consumption of coffee is increasing in recent years, especially in Asian countries. Therefore, the sustainability of the coffee industry has become a concern shared by all participants along the coffee supply chains. Decision making in arabica coffee bean cultivation, …

Modeling And Optimization Algorithm For Sic-Based Three-Phase Motor Drive System, Ren Ren

Doctoral Dissertations

More electric aircraft (MEA) and electrified aircraft propulsion (EAP) becomes the important topics in the area of transportation electrifications, expecting remarkable environmental and economic benefits. However, they bring the urgent challenges for the power electronics design since the new power architecture in the electrified aircraft requires many benchmark designs and comparisons. Also, a large number of power electronics converter designs with different specifications and system-level configurations need to be conducted in MEA and EAP, which demands huge design efforts and costs. Moreover, the long debugging and testing process increases the time to market because of gaps between the paper design …

Zone-Based Manufacturing, Abhay Rajendra Bajpai

Masters Theses

The biggest improvement possible with productivity and profit in a manufacturing environment is to decrease the production time or cycle time and increase the takt time without any significant or no loss to product quality. But this could come at a cost of unequal work distribution if it is a people-based manufacturing process. This paper provides the best possible schedule by using a heuristic model that gives an optimal schedule. Based on jobs precedence the schedule is made to have the least possible makespan for the process at any given station in an assembly line. Furthermore, the objective is to …

Efficient Elevator Algorithm, Sean M. Toll, Owen Barbour, Carl Edwards, Daniel Nichols, Austin Day

Chancellor’s Honors Program Projects

No abstract provided.

Deep Reinforcement Learning For Real-Time Residential Hvac Control, Evan Mckee

Masters Theses

The model-free Deep Reinforcement Learning (DRL) environment developed for this work attempts to minimize energy cost during residential heating, ventilation, and air conditioning (HVAC) operation. The HVAC load associated with heating and cooling is an ideal candidate for price optimization through automation for two reasons: Its power footprint in a typical home is sizeable, and the required level of participation from an inhabitant is passive. HVAC is difficult to accurately model and unique for every home, so online machine learning is used to allow for real-time readjustment in performance. Energy cost for the cooling unit shown in this work is …

Autonomous Multi-Chemistry Secondary-Use Battery Energy Storage, Mitchell Smith

Doctoral Dissertations

Battery energy storage is poised to play an increasingly important role in the modern electric grid. Not only does it provide the ability to change the time-of-day and magnitude of energy produced by renewable resources like wind and solar, it can also provide a host of other 3ancillary grid-stabilizing services. Cost remains a limiting factor in deploying energy storage systems large enough to provide these services on the scale required by an electric utility provider. Secondary-use electric vehicle batteries are a source of inexpensive energy storage materials that are not yet ready for the landfill but cannot operate in vehicles …

Optimizing The Implementation Of Green Technologies Under Climate Change Uncertainty, Mohammad Ramshani

Doctoral Dissertations

In this study, we aim to investigate the application of the green technologies (i.e., green roofs (GRs), Photovoltaic (PV) panels, and battery integrated PV systems) under climate change-related uncertainty through three separate, but inherently related studies, and utilize optimization methods to provide new solutions or improve the currently available methodsFirst, we develop a model to evaluate and optimize the joint placement of PV panels and GRs under climate change uncertainty. We consider the efficiency drop of PV panels due to heat, savings from GRs, and the interaction between them. We develop a two-stage stochastic programming model to optimally place PV …

Essays In Network Theory Applications For Transportation Planning, Jeremy David Auerbach

Doctoral Dissertations

Throughout the dissertation, network methods are developed to address pressing issues in transportation science and geography. These methods are applied to case studies to highlight their use for urban planners and social scientists working in transportation, mobility, housing, and health. The first chapter introduces novel network robustness measures for multi-line networks. This work will provide transportation planners a new tool for evaluating the resilience of transportation systems with multiple lines to failures. The second chapter explores optimizing network connectivity to maximize the number of nodes within a given distance to a focal node while minimizing the number and length of …

Data Analytics For Privacy In Smart Grids, Albraa Bahour

Masters Theses

The emergence of smart grids has allowed for integrating new technologies in the power grid, with information flowing across the system allowing for more efficient power delivery and event response. Demand response is a new technology enabled by smart grids, which is a program aiming to reduce or shift peak demand by varying the price of electricity or offering incentives for changing consumption habits.Despite demand response benefits, privacy advocates have raised concerns with information leakages allowed by the type of high-resolution data collected by smart meters, as it can reveal customer usage patterns and different parties can take advantage of …

Supply Chain Optimization And Economic Analysis Of Using Industrial Spent Microbial Biomass (Smb) In Agriculture, Lixia He Lambert

Masters Theses

This thesis uses a mixed integer program to minimize the transport and storage cost of delivering spent microbial biomass (SMB), a bio-coproduct resulting from the production of 1,3-propanediol, to farm fields as a soil amendment and fertilizer substitute. The case study examines focuses on a bioprocessing facility and corn production in East Tennessee. The results indicate on-farm storage of SMB minimizes transport and storage costs of the material. A one percent decrease in the moisture content of SMB results in less than five percent decrease in the total transport and storage costs. Future research should investigate farmers' willingness to adopt …

An Efficient Partial-Order Characterization Of Admissible Actions For Real-Time Scheduling Of Sporadic Tasks, Saajid Al Haque

Masters Theses

In many scheduling problems involving tasks with multiple deadlines, there is typically a large degree of flexibility in determining which tasks to serve at each time step. Given a cost function it is often possible to cast a scheduling problem as an optimization problem to obtain the most suitable schedule. However, in several applications, especially when the schedule has to be computed in-line or periodically adjusted, the cost function may not be completely known a priori but only partially. For example, in some applications only the cost of the current allocation of resources to the tasks could be available. Under …

An Inquiry Into Supply Chain Strategy Implications Of The Sharing Economy For Last Mile Logistics, Vincent Emanuel Castillo

Doctoral Dissertations

As the prevalence of e-commerce and subsequent importance of effective and efficient omnichannel logistics strategies continues to rise, retail firms are exploring the viability of sourcing logistics capabilities from the sharing economy. Questions arise such as, “how can crowdbased logistics solutions such as crowdsourced logistics (CSL), crowdshipping, and pickup point networks (PPN) be leveraged to increase performance?” In this dissertation, empirical and analytical research is conducted that increases understanding of how firms can leverage the sharing economy to increase logistics and supply chain performance. Essay 1 explores crowdsourced logistics (CSL) by employing a stochastic discrete event simulation set in New …

Flight Risk Management And Crew Reserve Optimization, Ying Zhang

Doctoral Dissertations

There are two key concerns in the development process of aviation. One is safety, and the other is cost. An airline running with high safety and low cost must be the most competitive one in the market. This work investigates two research efforts respectively relevant to these two concerns.

When building support of a real time Flight Risk Assessment and Mitigation System (FRAMS), a sequential multi-stage approach is developed. The whole risk management process is considered in order to improve the safety of each flight by integrating AHP and FTA technique to describe the framework of all levels of risks …

Electric Power System Operations With A Variable Series Reactor, Xiaohu Zhang

Doctoral Dissertations

Series FACTS devices, such as a Variable Series Reactor (VSR), have the ability to continuously regulate the transmission line reactance so as to control power ow. This research work evaluates the benefits brought by VSRs in different aspects of power system and develops efficient planning models and algorithms to provide optimal investment plan for the VSRs.

First, an optimization approach capable of finding both optimal locations and settings of VSRs under a specific operating condition is developed. The tool implements a full ac model as well as detailed models for different power system components.

Second, an optimization tool which can …

Algorithms And Methods For Optimizing The Spent Nuclear Fuel Allocation Strategy, Gordon Matthew Petersen

Doctoral Dissertations

Commercial nuclear power plants produce long-lasting nuclear waste, primarily in the form of spent nuclear fuel (SNF) assemblies. Spent fuel pools (SFP) and canisters or casks that sit at an independent spent fuel storage installation (ISFSI) at the reactor site store the fuel assemblies that are removed from operating reactors. The federal government has developed a plan to move the SNF from reactor sites to a Consolidated Interim Storage Facility (CISF) or a geological repository. In order to develop a predictable pick-up schedule and give utilities notice of an impending pickup from a reactor site, the federal government developed a …

Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan

Doctoral Dissertations

With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.

First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience …

Improving Ventricular Catheter Design Through Computational Fluid Dynamics, Sofy Hefets Weisenberg

Masters Theses

Cerebrospinal fluid (CSF) shunts are fully implantable medical devices that are used to treat patients suffering from conditions characterized by elevated intracranial pressure, such as hydrocephalus. In cases of shunt failure or malfunction, patients are often required to endure one or more revision surgeries to replace all or part of the shunt. One of the primary causes of CSF shunt failure is obstruction of the ventricular catheter, a component of the shunt system implanted directly into the brain's ventricular system. This work aims to improve the design of ventricular catheters in order to reduce the incidence of catheter obstruction and …

Joint Optimization Of Allocation And Release Policy Decisions For Surgical Block Time Under Uncertainty, Mina Loghavi

Doctoral Dissertations

The research presented in this dissertation contributes to the growing literature on applications of operations research methodology to healthcare problems through the development and analysis of mathematical models and simulation techniques to find practical solutions to fundamental problems facing nearly all hospitals.

In practice, surgical block schedule allocation is usually determined regardless of the stochastic nature of case demand and duration. Once allocated, associated block time release policies, if utilized, are often simple rules that may be far from optimal. Although previous research has examined these decisions individually, our model considers them jointly. A multi-objective model that characterizes financial, temporal, …

Developing An Optimal Model For Infant Home Visitation, Isaac Atuahene

Doctoral Dissertations

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) …

Assessment Of Reactivity Equivalence For Enhanced Accident Tolerant Fuels In Light Water Reactors, Nathan Michael George

Doctoral Dissertations

The neutronic behavior of accident tolerant fuel (ATF) concepts was simulated in light water reactors (LWRs) to establish design parameters to match reactivity lifetime requirements of standard UO₂ [uranium dioxide]/Zircaloy fuel. The two concepts discussed in this dissertation are fully ceramic micro-encapsulated (FCM) fuel and alternate cladding concepts. To compare the required fuel alterations against standard UO₂/Zircaloy fuel, a 2D lattice-physics based reactivity equivalence method was established to estimate excess reactivity at the completion of each weighted batch cycle.

In the case of FCM fuel, the uranium-based tristructural isotropic (TRISO) kernel and the surrounding particle layers/matrix material …