Engineering Commons^™

Enabling Large-Scale Transportation Electrification For Shared And Connected Mobility Systems, Md Rakibul Alam

Graduate Thesis and Dissertation 2023-2024

Owing to advancements in technology, substantial investments within the automotive industry, and the formulation of supportive state policies, the future landscape of the transportation sector is poised to witness a shift from traditional internal combustion engine vehicles (ICEVs) to electric vehicles (EVs). While EVs have made inroads in the market, they still face significant hurdles in the form of range anxiety and prolonged charging durations, inhibiting their widespread adoption. To tackle these challenges, a comprehensive approach to smart transportation electrification is proposed, emphasizing the pivotal roles of infrastructure development, particularly in the allocation of charging stations, and strategic operational decisions, …

Development Of A Configurable Real-Time Event Detection Framework For Power Systems Using Swarm Intelligence Optimization, Umar Farooq

Dissertations and Theses

Modern power systems characterized by complex topologies require accurate situational awareness to maintain an adequate level of reliability. Since they are large and spread over wide geographical areas, occurrence of failures is inevitable in power systems. Various generation and transmission disturbances give rise to a mismatch between generation and demand, which manifest as frequency events. These events can take the form of negligible frequency deviations or more severe emergencies that can precipitate cascading outages, depending on the severity of the disturbance and efficacy of remedial action schema. The impacts of such events have become more critical with recent decline in …

Gradient-Based Wind Farm Layout Optimization, Jared Joseph Thomas

Theses and Dissertations

As wind energy technology continues to mature, farm sizes grow and wind farm layout design becomes more difficult, in part due to the number of design variables and constraints. Wind farm layout optimization is typically approached using gradient-free methods because of the highly multi-modal shape of the wind farm layout design space. Gradient-free method performance generally degrades with increasing problem size, making it difficult to find optimal layouts for larger wind farms. However, gradient-based optimization methods can effectively and efficiently solve large-scale problems with many variables and constraints. To pave the way for effective and efficient wind farm layout optimization …

Quantum Grover's Oracles With Symmetry Boolean Functions, Peng Gao

Dissertations and Theses

Quantum computing has become an important research field of computer science and engineering. Among many quantum algorithms, Grover's algorithm is one of the most famous ones. Designing an effective quantum oracle poses a challenging conundrum in circuit and system-level design for practical application realization of Grover's algorithm.

In this dissertation, we present a new method to build quantum oracles for Grover's algorithm to solve graph theory problems. We explore generalized Boolean symmetric functions with lattice diagrams to develop a low quantum cost and area efficient quantum oracle. We study two graph theory problems: cycle detection of undirected graphs and generalized …

Mathematical Optimization Algorithms For Model Compression And Adversarial Learning In Deep Neural Networks, Tianyun Zhang

Dissertations - ALL

Large-scale deep neural networks (DNNs) have made breakthroughs in a variety of tasks, such as image recognition, speech recognition and self-driving cars. However, their large model size and computational requirements add a significant burden to state-of-the-art computing systems. Weight pruning is an effective approach to reduce the model size and computational requirements of DNNs. However, prior works in this area are mainly heuristic methods. As a result, the performance of a DNN cannot maintain for a high weight pruning ratio. To mitigate this limitation, we propose a systematic weight pruning framework for DNNs based on mathematical optimization. We first formulate …

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …

Aggregated Water Heater System (Awhs) Optimization For Ancillary Services, Manasseh Obi

Dissertations and Theses

In this dissertation, I present a two-stage optimization routine that schedules an Aggregated Water Heater System (AWHS) to concurrently provide three utility ancillary services, namely, frequency regulation, frequency response, and peak demand mitigation.

Water heaters can be controlled to manage their energy take, the amount of energy a water heater can absorb upon command. The AWHS is a model aggregation of thousands of water heaters, the energy take and power characteristics of which are based on U.S Census household data and usage behavior patterns. The aggregate energy take available in the AWHS may be dispatched en masse for participation in …

The Optimization Of Machining Parameters For Milling Operations By Using The Nelder Mead Simplex Method, Yubin Lee

Dissertations and Theses

Machining operations need to be optimized to maximize profit for computer numerical control (CNC) machines. Although minimum production time could mean high productivity, it can not guarantee maximum profit rate in CNC milling operations. The possible range of machining parameters is limited by several constraints, such as maximum machine power, surface finish requirements, and maximum cutting force for the stability of milling operations. Among CNC machining parameters, cutting speed and feed have the greatest effect on machining operations. Therefore, cutting speed and feed are considered as main process variables to maximize the profit rate of CNC milling operations.

A variety …

Efficient Methods For Robust Circuit Design And Performance Optimization For Carbon Nanotube Field Effect Transistors, Muhammad Ali

Dissertations and Theses

Carbon nanotube field-effect transistors (CNFETs) are considered to be promising candidate beyond the conventional CMOSFET due to their higher current drive capability, ballistic transport, lesser power delay product and higher thermal stability. CNFETs show great potential to build digital systems on advanced technology nodes with big benefits in terms of power, performance and area (PPA). Hence, there is a great need to develop proven models and CAD tools for performance evaluation of CNFET-based circuits. CNFETs specific parameters, such as number of tubes, pitch (spacing between the tubes) and diameter of CNTs determine current driving capability, speed, power consumption and area …

Design Optimization For A Cnc Machine, Alin Resiga

Dissertations and Theses

Minimizing cost and optimization of nonlinear problems are important for industries in order to be competitive. The need of optimization strategies provides significant benefits for companies when providing quotes for products. Accurate and easily attained estimates allow for less waste, tighter tolerances, and better productivity. The Nelder-Mead Simplex method with exterior penalty functions was employed to solve optimum machining parameters. Two case studies were presented for optimizing cost and time for a multiple tools scenario. In this study, the optimum machining parameters for milling operations were investigated. Cutting speed and feed rate are considered as the most impactful design variables …

Generalized Differential Calculus And Applications To Optimization, R. Blake Rector

Dissertations and Theses

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations …

Biogeography-Based Optimization For Combinatorial Problems And Complex Systems, Dawei Du

ETD Archive

Biogeography-based optimization (BBO) is a heuristic evolutionary algorithm that has shown good performance on many problems. In this dissertation, three problem1s 1 are researched for BBO: convergence speed and optimal solution convergence of BBO,1 1BBO application to combinatorial problems, and BBO application to complex systems. The first problem is to analyze BBO from two perspectives: how the components of BBO affect its convergence speed and the reason that BBO converges to the optimal solution. For the first perspective, which is convergence speed, we analyze the two essential components of BBO -- population construction and information sharing. For the second perspective, …

Oppositional Biogeography-Based Optimization, Mehmet Ergezer

ETD Archive

This dissertation outlines a novel variation of biogeography-based optimization (BBO), which is an evolutionary algorithm (EA) developed for global optimization. The new algorithm employs opposition-based learning (OBL) alongside BBO migration to create oppositional BBO (OB BO). Additionally, a new opposition method named quasi-reflection is introduced. Quasireflection is based on opposite numbers theory and we mathematically prove that it has the highest expected probability of being closer to the problem solution among all OBL methods that we explore. Performance of quasi-opposition is validated by mathematical analysis for a single-dimensional problem and by simulations for higher dimensions. Experiments are performed on benchmark …

Path Planning And Evolutionary Optimization Of Wheeled Robots, Daljeet Singh

ETD Archive

Probabilistic roadmap methods (PRM) have been a well-known solution for solving motion planning problems where we have a fixed set of start and goal configurations in a workspace. We define a configuration space with static obstacles. We implement PRM to find a feasible path between start and goal for car-like robots. We further extend the concept of path planning by incorporating evolutionary optimization algorithms to tune the PRM parameters. The theory is demonstrated with simulations and experiments. Our results show that there is a significant improvement in the performance metrics of PRM after optimizing the PRM parameters using biogeography-based optimization, …

Moving Horizon Estimation With Dynamic Programming, Mohan Kumar Ramalingam

ETD Archive

Moving Horizon Estimation(MHE) is a optimization based strategy to state estimation. It involves computation of arrival cost, a penalty term, based on the MHE cost function. Minimization of this arrival cost is done through various methods. All these methods use nonlinear programming optimization technique which gives the estimate. The main idea of MHE revolves around minimizing the estimation cost function. The cost function is dependent on prediction error computation from data and arrival cost summarization. The major issue that hampers the MHE is choosing the arrival cost for ensuring stability of the overall estimation and computational time. In order to …

Trajectory Control And Optimization For Responsive Spacecraft, Costantinos Zagaris

Theses and Dissertations

The concept of responsive space has been gaining interest, and growing to include systems that can be re-tasked to complete multiple missions within their lifetime. The purpose of this study is to develop an algorithm that produces a maneuver trajectory that will cause a spacecraft to arrive at a particular location within its orbit earlier than expected. The time difference, delta t, is used as a metric to quantify the effects of the maneuver. Two separate algorithms are developed. The first algorithm is an optimal control method and is developed through Optimal Control Theory. The second algorithm is a feedback …

Hybrid Solution Of Stochastic Optimal Control Problems Using Gauss Pseudospectral Method And Generalized Polynomial Chaos Algorithms, Gerald C. Cottrill

Theses and Dissertations

Two numerical methods, Gauss Pseudospectral Method and Generalized Polynomial Chaos Algorithm, were combined to form a hybrid algorithm for solving nonlinear optimal control and optimal path planning problems with uncertain parameters. The algorithm was applied to two concept demonstration problems: a nonlinear optimal control problem with multiplicative uncertain elements and a mission planning problem sponsored by USSTRATCOM. The mission planning scenario was constructed to find the path that minimizes the probability of being killed by lethal threats whose locations are uncertain to statistically quantify the effects those uncertainties have on the flight path solution, and to use the statistical properties …

Distributed Biogeography Based Optimization For Mobile Robots, Arpit Shah

ETD Archive

I present hardware testing of an evolutionary algorithm (EA) known as distributed biogeography based optimization (DBBO). DBBO is an extended version of biogeography based optimization (BBO). Typically, EAs require a central computer to control the evaluation of candidate solutions to some optimization problem, and to control the sharing of information between those candidate solutions. DBBO, however, does not require a centralized unit to control individuals. Individuals independently run the EA and find a solution to a given optimization problem. Both BBO and DBBO are based on the theory of biogeography, which describes how organisms are distributed geographically in nature. I …

Optimal Detour Planning Around Blocked Construction Zones, Mutasem Jardaneh

Electronic Theses and Dissertations

Construction zones are traffic way areas where construction, maintenance or utility work is identified by warning signs, signals and indicators, including those on transport devices that mark the beginning and end of construction zones. Construction zones are among the most dangerous work areas, with workers facing workplace safety challenges that often lead to catastrophic injuries or fatalities. In addition, daily commuters are also impacted by construction zone detours that affect their safety and daily commute time. These problems represent major challenges to construction planners as they are required to plan vehicle routes around construction zones in such a way that …

Electimize A New Evolutionary Algorithm For Optimization With Applications In Construction Engineering, Raheem, Mohamed Abdel

Electronic Theses and Dissertations

Optimization is considered an essential step in reinforcing the efficiency of performance and economic feasibility of construction projects. In the past few decades, evolutionary algorithms (EAs) have been widely utilized to solve various types of construction-related optimization problems due to their efficiency in finding good solutions in relatively short time periods. However, in many cases, these existing evolutionary algorithms failed to identify the optimal solution to several optimization problems. As such, it is deemed necessary to develop new approaches in order to help identify better-quality solutions. This doctoral research presents the development of a new evolutionary algorithm, named “Electimize,” that …

Determining The Orbit Locations Of Turkish Airborne Early Warning And Control Aircraft Over The Turkish Air Space, Nebi Sarikaya

Theses and Dissertations

The technology improvement affects the military needs of individual countries. The new doctrine of defense for many countries emphasizes detecting threats as far away as you can from your homeland. Today, the military uses both ground RADAR and Airborne Early Warning and Control (AEW&C) Aircraft. AEW&C aircraft has become vital to detect low altitude threats that a ground RADAR cannot detect because of obstacles on the earth. Turkey has ordered four AEW&C aircraft for her air defense system because of the lack of complete coverage by ground RADAR. This research provides optimal orbit locations that can be updated according to …

Centralized Cooperative Control For Route Surveillance With Constant Communication, Joseph D. Rosal

Theses and Dissertations

The route surveillance mission is a new application of unmanned aircraft systems (UASs) to meet the reconnaissance and surveillance requirements of combatant commanders. The new mission intends to field a UAS consisting of unmanned aerial vehicles (UAVs) that can provide day and night surveillance of convoy routes. This research focuses on developing a solution strategy for the mission based on the application of optimal control and cooperative control theory. The route surveillance controller uses the UAS team size to divide the route into individual sectors for each entity. A specifically designed cost function and path constraints are used to formulate …

Adaptive Pareto Set Estimation For Stochastic Mixed Variable Design Problems, Christopher D. Arendt

Theses and Dissertations

Many design problems require the optimization of competing objective functions that may be too complicated to solve analytically. These problems are often modeled in a simulation environment where static input may result in dynamic (stochastic) responses to the various objective functions. System reliability, alloy composition, algorithm parameter selection, and structural design optimization are classes of problems that often exhibit such complex and stochastic properties. Since the physical testing and experimentation of new designs can be prohibitively expensive, engineers need adequate predictions concerning the viability of various designs in order to minimize wasteful testing. Presumably, an appropriate stochastic multi-objective optimizer can …

Biogeography-Based Optimization: Synergies With Evolutionary Strategies, Immigration Refusal, And Kalman Filters, Dawei Du

ETD Archive

Biogeography-based optimization (BBO) is a recently developed heuristic algorithm which has shown impressive performance on many well known benchmarks. The aim of this thesis is to modify BBO in different ways. First, in order to improve BBO, this thesis incorporates distinctive techniques from other successful heuristic algorithms into BBO. The techniques from evolutionary strategy (ES) are used for BBO modification. Second, the traveling salesman problem (TSP) is a widely used benchmark in heuristic algorithms, and it is considered as a standard benchmark in heuristic computations. Therefore the main task in this part of the thesis is to modify BBO to …

Improving Mixed Variable Optimization Of Computational And Model Parameters Using Multiple Surrogate Functions, David Bethea

Theses and Dissertations

This research focuses on reducing computational time in parameter optimization by using multiple surrogates and subprocess CPU times without compromising the quality of the results. This is motivated by applications that have objective functions with expensive computational times at high fidelity solutions. Applying, matching, and tuning optimization techniques at an algorithm level can reduce the time spent on unprofitable computations for parameter optimization. The objective is to recover known parameters of a flow property reference image by comparing to a template image that comes from a computational fluid dynamics simulation, followed by a numerical image registration and comparison process. Mixed …

Search Techniques For Multi-Objective Optimization Of Mixed Variable Systems Having Stochastic Responses, Jennifer G. Walston

Theses and Dissertations

A research approach is presented for solving stochastic, multi-objective optimization problems. First, the class of mesh adaptive direct search (MADS) algorithms for nonlinearly constrained optimization is extended to mixed variable problems. The resulting algorithm, MV-MADS, is then extended to stochastic problems (MVMADS-RS), via a ranking and selection procedure. Finally, a two-stage method is developed that combines the generalized pattern search/ranking and selection (MGPS-RS) algorithms for single-objective, mixed variable, stochastic problems with a multi-objective approach that makes use of interactive techniques for the specification of aspiration and reservation levels, scalarization functions, and multi-objective ranking and selection. A convergence analysis for the …

Energy-Efficient Querying Of Wireless Sensor Networks, Christopher R. Mann

Theses and Dissertations

Due to the distributed nature of information collection in wireless sensor networks and the inherent limitations of the component devices, the ability to store, locate, and retrieve data and services with minimum energy expenditure is a critical network function. Additionally, effective search protocols must scale efficiently and consume a minimum of network energy and memory reserves. A novel search protocol, the Trajectory-based Selective Broadcast Query protocol, is proposed. An analytical model of the protocol is derived, and an optimization model is formulated. Based on the results of analysis and simulation, the protocol is shown to reduce the expected total network …

Optimal Sensor Threshold Control And The Weapon Operating Characteristic For Autonomous Search And Attack Munitions, Roland A. Rosario

Theses and Dissertations

This Thesis considers the optimal employment of a wide area search munition in a battlespace where a target is known to be uniformly distributed among false targets which are Poisson distributed. The Poisson distribution's parameter is obtained from readily available battlespace intelligence. This work formulates and solves the optimal control problem for deriving the optimal sensor threshold schedule in order to maximize the probability of attacking the target during the battlespace sweep while constraining the probability of attacking a false target. The efficiency gained by optimally varying the sensor threshold is compared against the performance achieved with a static, optimum …

Critical Infrastructure Rebuild Prioritization Using Simulation Optimization, Namsuk Cho

Theses and Dissertations

This thesis examines the importance of a critical infrastructure rebuild strategy following a terrorist attack or natural disaster such as Hurricane Katrina. Critical infrastructures are very complex and dependent systems in which their re-establishment is an essential part of the rebuilding process. A rebuild simulation model consisting of three layers (physical, information, and spatial) captures the dependency between the six critical infrastructures modeled. We employ a simulation optimization approach to evaluate rebuild prioritization combinations with a goal of minimizing the time needed to achieve an acceptable rebuild level. We use a simulated annealing heuristic as an optimization technique that works …

Prioritizing Satellite Payload Selection Via Optimization, Benjamin S. Kallemyn

Theses and Dissertations

This thesis develops optimization models for prioritizing payloads for inclusion on satellite buses with volume, power, weight and budget constraints. The first model considers a single satellite launch for which the budget is uncertain and constellation requirements are not considered. Subsequently, we include constellation requirements and provide a more enhanced model. Both single-launch models provide a prioritized list of payloads to include on the launch before the budget is realized. The single-launch models are subsequently extended to a sequence of multiple launches in two cases, both of which incorporate an explicit dependence on the constellation composition at each launch epoch. …