Operations Research, Systems Engineering and Industrial Engineering Commons^™

The Tabu Ant Colony Optimizer And Its Application In An Energy Market, David Donald Haynes

Doctoral Dissertations

"A new ant colony optimizer, the 'tabu ant colony optimizer' (TabuACO) is introduced, tested, and applied to a contemporary problem. The TabuACO uses both attractive and repulsive pheromones to speed convergence to a solution. The dual pheromone TabuACO is benchmarked against several other solvers using the traveling salesman problem (TSP), the quadratic assignment problem (QAP), and the Steiner tree problem. In tree-shaped puzzles, the dual pheromone TabuACO was able to demonstrate a significant improvement in performance over a conventional ACO. As the amount of connectedness in the network increased, the dual pheromone TabuACO offered less improvement in performance over the …

Weld Penetration Identification Based On Convolutional Neural Network, Chao Li

Theses and Dissertations--Electrical and Computer Engineering

Weld joint penetration determination is the key factor in welding process control area. Not only has it directly affected the weld joint mechanical properties, like fatigue for example. It also requires much of human intelligence, which either complex modeling or rich of welding experience. Therefore, weld penetration status identification has become the obstacle for intelligent welding system. In this dissertation, an innovative method has been proposed to detect the weld joint penetration status using machine-learning algorithms.

A GTAW welding system is firstly built. Project a dot-structured laser pattern onto the weld pool surface during welding process, the reflected laser pattern …

Curricular Optimization: Solving For The Optimal Student Success Pathway, William G. Thompson-Arjona

Theses and Dissertations--Electrical and Computer Engineering

Considering the significant investment of higher education made by students and their families, graduating in a timely manner is of the utmost importance. Delay attributed to drop out or the retaking of a course adds cost and negatively affects a student’s academic progression. Considering this, it becomes paramount for institutions to focus on student success in relation to term scheduling.

Often overlooked, complexity of a course schedule may be one of the most important factors in whether or not a student successfully completes his or her degree. More often than not students entering an institution as a first time full …

Energy Efficiency Evaluation Of Blower Heater Non-Purge Compressed Air Dryers, Alexandra M. Botts

Graduate Theses, Dissertations, and Problem Reports (ETD)

There are several compressed air dryers available for industrial use including, refrigerant, desiccant, and membrane. This research focuses on twin tower regenerative closed loop desiccant dryers, specifically: blower heater non-purge (BHNP) with and without cooling water pumps, Compressed-air Heater Purge (CHP), Blower Heater Purge (BHP), and Pressure Swing Heaterless (PSH). These styles of dryers are used mainly in industries that require extremely dry air such as, food manufacturing, medical air, or sensitive technology manufacturers. The research was conducted by collecting and analyzing real time current draw data on air compressors and associated dryers at eight different facilities (13 compressor systems) …

Detecting Special-Cause Variation 'Events' From Process Data Signatures, Timothy M. Young, Olga Khaliukova, Nicolas André, Alexander Petutschnigg, Timothy G. Rials, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using …

Cost Benefit Analysis Of Led Vs Florescent Lighting, Kurtis Clark, Phillip Humphrey

Student Research

Over the last few years, the state of Oklahoma has been looking at ways to reduce expenses to address concerns about a budget deficit. There have been efforts made to reduce expenses due to the use of energy. It has been said, when the lights are on, work is getting done. Running lights is therefore the cost of doing business. Our research examines the question, “is there a way to provide better lighting while operating at a lower cost.” This research examines the current lighting at Southwestern State University, primarily fluorescent lighting (FL), and a cost benefit analysis of switching …

Impact Of Communication Latency On The Bus Voltage Of Centrally Controlled Dc Microgrid During Islanding, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

Maintaining a sustainable and reliable source of energy to supply critical loads within a renewable energy based microgrid (MG) during blackouts is directly related to its bus voltage variations. For example, voltage variation might trigger protection devices and disconnect DERs within the MG. Centrally controlled MGs (CCMGs) type is dependent on communication. Therefore, it is very important to analyze the impact of communication networks performance degradation, such as latency, on the bus voltage of CCMGs. This paper investigates the effect of wireless communication technologies latency on the bus voltage and performance of centralized DC MGs. Two mathematical models were developed …

Robust Engineering Of Dynamic Structures In Complex Networks, Walter Botongo Bomela

McKelvey School of Engineering Graduate Student Theses & Dissertations

Populations of nearly identical dynamical systems are ubiquitous in natural and engineered systems, in which each unit plays a crucial role in determining the functioning of the ensemble. Robust and optimal control of such large collections of dynamical units remains a grand challenge, especially, when these units interact and form a complex network. Motivated by compelling practical problems in power systems, neural engineering and quantum control, where individual units often have to work in tandem to achieve a desired dynamic behavior, e.g., maintaining synchronization of generators in a power grid or conveying information in a neuronal network; in this dissertation, …

Economic Model Predictive Control Design Via Nonlinear Model Identification, Laura Giuliani, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Increasing pushes toward next-generation/smart manufacturing motivate the development of economic model predictive control (EMPC) designs which can be practically deployed. For EMPC, the constraints, objective function, and accuracy of the state predictions would benefit from process models that describe the process physics. However, obtaining first- principles models of chemical process systems can be time-consuming or challenging such that it is preferable to develop physics-based process models automatically from process operating data. In this work, we take initial steps in this direction by suggesting that because experiments that are used to characterize first-principles models often target specific types of data, an …

Data-Based Nonlinear Model Identification In Economic Model Predictive Control, Laura Giuliani, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Many chemical/petrochemical processes in industry are not completely modeled from a first-principles perspective because of the complexity of the underlying physico-chemical phenomena and the cost of obtaining more accurate, physically relevant models. System identification methods have been utilized successfully for developing empirical, though not necessarily physical, models for advanced model-based control designs such as model predictive control (MPC) for decades. However, a fairly recent development in MPC is economic model predictive control (EMPC), which is an MPC formulated with an economics-based objective function that may operate a process in a dynamic (i.e., off steady-state) fashion, in which case the details …

Farmbot Trackless Redesign, Cole Thomas, Cailey Kamm, Clayton Alderson, Otto Akerstrom

Industrial and Manufacturing Engineering

For this project the team PLANT3D worked along with Rory Aronson and FarmBot to generate a cheaper more user-friendly design for the FarmBot Genesis 1.3. Working with Rory and FarmBot, we as a team generated a list of design requirements and engineering specifications for the project. These requirements centered around creating a more accessible FarmBot model for the average person to be able to purchase and set up with ease. Much of this required taking the existing system and eliminating the most common problem areas. These were the track system, built using 1.5 meter aluminum extrusions and the complex interchangeable …

Applications Of Complex Network Analysis In Electric Power Systems, Mahmoud Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper provides a review of the research conducted on complex network analysis (CNA) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement in this paper points to the location that will result in enhanced grid resilience, reduced power losses and line loading, better voltage stability, and a supply to critical loads during a blackout. The criteria used to point out the optimal placement of the MGs were predicated on the centrality analysis selected from the complex network theory, the …

Design Of A Distributed Real-Time E-Health Cyber Ecosystem With Collective Actions: Diagnosis, Dynamic Queueing, And Decision Making, Yanlin Zhou

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we develop a framework for E-health Cyber Ecosystems, and look into different involved actors. The three interested parties in the ecosystem including patients, doctors, and healthcare providers are discussed in 3 different phases. In Phase 1, machine-learning based modeling and simulation analysis is performed to remotely predict a patient's risk level of having heart diseases in real time. In Phase 2, an online dynamic queueing model is devised to pair doctors with patients having high risk levels (diagnosed in Phase 1) to confirm the risk, and provide help. In Phase 3, a decision making paradigm is proposed …

The Eco-Smart Can V2.0, Darack B. Nanto

Appalachian Student Research Forum

I noticed that the workers had the same itinerary when emptying trashcans, meanwhile trashcans needed urgently to be emptied. Traditionally, ETSU maintenance operate on daily routes to pick trash on designated time, regardless the level of the containers. This leads to overflown trashcan in busy areas or during rush hours in certain areas. This overflown trashcan result in an unclean environment for the community and an unpleasant look of our beautiful campus. The time, resources and labor invested in collecting the trash could be saved. Therefore, I decided to use the Internet of Things (IoT) to create a device that …

Implementing A Total Productive Maintenance Approach Into An Improvement At S Company, Xiaomeng Sun

Masters Theses & Specialist Projects

The study improved the overall equipment effectiveness (OEE) of machines and processes through the implementation of a total productive maintenance (TPM) approach at Company S over a three-month period. By comparing the OEE of equipment before and after the implementation of autonomous maintenance, this study concluded that autonomous maintenance improves OEE. The target of this study was one general product line at a polytetrafluoroethylene (PTFE) plant. Due to time limitations, the study only applied autonomous maintenance to operational activities. This research involved machine and processes selection, condition assessment, baseline OEE assessment, operator training, execution of autonomous maintenance, and OEE measurement. …

Collaborative Appearance-Based Place Recognition And Improving Place Recognition Using Detection Of Dynamic Objects, Juan Pablo Munoz

Dissertations, Theses, and Capstone Projects

This dissertation makes contributions to the problem of Long-Term Appearance-Based Place Recognition. We present a framework for place recognition in a collaborative scheme and a method to reduce the impact of dynamic objects on place representations. We demonstrate our findings using a state-of-the-art place recognition approach.

We begin in Part I by describing the general problem of place recognition and its importance in applications where accurate localization is crucial. We discuss feature detection and description and also explain the functioning of several place recognition frameworks.

In Part II, we present a novel framework for collaboration between agents from a pure …

Communication Based Control For Dc Microgrids, Mahmoud S. Saleh, Yusef Esa, Ahmed Mohamed

Publications and Research

Centralized communication-based control is one of the main methods that can be implemented to achieve autonomous advanced energy management capabilities in DC microgrids. However, its major limitation is the fact that communication bandwidth and computation resources are limited in practical applications. This can be often improved by avoiding redundant communications and complex computations. In this paper, an autonomous communication-based hybrid state/event driven control scheme is proposed. This control scheme is hierarchical and heuristic, such that on the primary control level, it encompasses state-driven local controllers, and on the secondary control level, an event-driven MG centralized controller (MGCC) is used. This …

Pathology-Informed Approach In Vulnerability Assessment Methods, Polinpapilinho F. Katina, Adrian V. Gheorghe, Charles B. Keating

Engineering Management & Systems Engineering Faculty Publications

A system pathology is a circumstance, condition, or pattern that acts to limit system performance, or lessen system viability, such that the likelihood of a system achieving performance expectation is reduced. The idea of pathology has been described in multiple fields, including computer science, organizational studies, policy analysis, system-of-systems engineering, and systems engineering. However, there is scarcity of literature describing relationship between system pathology and vulnerability assessment. The aim of this study lies at the intersection of system pathology and vulnerability assessment in engineered systems. First, authors provide the state of the art review of literature on system pathology. Second, …

Anomaly Inference Based On Heterogeneous Data Sources In An Electrical Distribution System, Yachen Tang

Dissertations, Master's Theses and Master's Reports

Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as …

Understanding The Impact Of Large-Scale Power Grid Architectures On Performance, Ange-Lionel Toba

Engineering Management & Systems Engineering Theses & Dissertations

Grid balancing is a critical system requirement for the power grid in matching the supply to the demand. This balancing has historically been achieved by conventional power generators. However, the increasing level of renewable penetration has brought more variability and uncertainty to the grid (Ela, Diakov et al. 2013, Bessa, Moreira et al. 2014), which has considerable impacts and implications on power system reliability and efficiency, as well as costs. Energy planners have the task of designing infrastructure power systems to provide electricity to the population, wherever and whenever needed. Deciding of the right grid architecture is no easy task, …

Evaluating The Role Of Energy Demand Prediction And Renewable Energy Utilization On Energy Dependency Management: A Generic System Dynamics Model, Emad Rabiei Hosseinabad

Graduate Research Theses & Dissertations

Supplying energy has become one of the biggest concerns of developed countries due to the growing energy needs in the last decades. Security of energy supply has forced countries to rely more on energy imports from external sources, and become energy dependent to a greater extent. Utilizing available renewable energy resources has been characterized as a reliable indicator to mitigate energy dependency in countries as well as securing the supplying of energy-based needs in the future. This research explores the impact of renewable energies as trustful resources in mitigating energy imports form external sources with investigation of its viability with …

Extrinsic And Intrinsic Control Of Integrative Processes In Neural Systems, Anirban Nandi

McKelvey School of Engineering Graduate Student Theses & Dissertations

At the simplest dynamical level, neurons can be understood as integrators. That is, neurons accumulate excitation from afferent neurons until, eventually, a threshold is reached and they produce a spike. Here, we consider the control of integrative processes in neural circuits in two contexts. First, we consider the problem of extrinsic neurocontrol, or modulating the spiking activity of neural circuits using stimulation, as is desired in a wide range of neural engineering applications. From a control-theoretic standpoint, such a problem presents several interesting nuances, including discontinuity in the dynamics due to the spiking process, and the technological limitations associated with …

Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani

Psychology Faculty Articles and Research

The emerging technology of connected vehicles generates a vast amount of data that could be used to enhance roadway safety. In this paper, we focused on safety applications of a real field connected vehicle data on a horizontal curve. The database contains connected vehicle data that were collected on public roads in Ann Arbor, Michigan with instrumented vehicles. Horizontal curve negotiations are associated with a great number of accidents, which are mainly attributed to driving errors. Aggressive/risky driving is a contributing factor to the high rate of crashes on horizontal curves. Using basic safety message data in connected vehicle data …

Chaotic Behavior In High-Gain Interleaved Dc-Dc Converters, Ahmad Alzahrani, Pourya Shamsi, Mehdi Ferdowsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, chaotic behavior in high gain dc-dc converters with current mode control is explored. The dc-dc converters exhibit some chaotic behavior because they contain switches. Moreover, in power electronics (circuits with more passive elements), the dynamics become rich in nonlinearity and become difficult to capture with linear analytical models. Therefore, studying modeling approaches and analysis methods is required. Most of the high-gain dc-dc boost converters cannot be controlled with only voltage mode control due to the presence of right half plane zero that narrows down the stability region. Therefore, the need of current mode control is necessary to …

Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi

Electrical and Computer Engineering Faculty Research & Creative Works

Predicting solar irradiance has been an important topic in renewable energy generation. Prediction improves the planning and operation of photovoltaic systems and yields many economic advantages for electric utilities. The irradiance can be predicted using statistical methods such as artificial neural networks (ANN), support vector machines (SVM), or autoregressive moving average (ARMA). However, they either lack accuracy because they cannot capture long-term dependency or cannot be used with big data because of the scalability. This paper presents a method to predict the solar irradiance using deep neural networks. Deep recurrent neural networks (DRNNs) add complexity to the model without specifying …

Modeling And Simulation Of Microgrid, Ahmad Alzahrani, Mehdi Ferdowsi, Pourya Shamsi, Cihan H. Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

Complex computer systems and electric power grids share many properties of how they behave and how they are structured. A microgrid is a smaller electric grid that contains several homes, energy storage units, and distributed generators. The main idea behind microgrids is the ability to work even if the main grid is not supplying power. That is, the energy storage unit and distributed generation will supply power in that case, and if there is excess in power production from renewable energy sources, it will go to the energy storage unit. Therefore, the electric grid becomes decentralized in terms of control …

Answering Food Insecurity: Serving The Community With Food And Knowledge Using Technology, Courtney Simpson

Purdue Journal of Service-Learning and International Engagement

The courses of Tech120, CGT110, and ENGT 180/181 and Red Gold at Purdue collaborated to design a robot that would plant and water a garden for a local community charter school. The students centered the project on the users’ needs for fresh food, nutrition education, and early exposure to STEM for children. The school, Anderson Preparatory Academy (APA), is comprised of many children who come from low-income families and are in the free or reduced lunch program. Inspired from “Farm Bot,” a similar system that allows for almost hands-free gardening, the “Boiler Bot” is designed to be scalable so children …

Quantitative Analysis Of Regenerative Energy In Electric Rail Traction Systems, Mahmoud Saleh, Oindrilla Dutta, Yusef Esa, Ahmed Mohamed

Publications and Research

This paper aims at determining the influential factors affecting regenerative braking energy in DC rail transit systems. This has been achieved by quantitatively evaluating the dependence of regenerative energy on various parameters, such as vehicle dynamics, train scheduling, ground inclination and efficiency of the electrical devices. The recuperated power and energy have been presented by a mathematical model, comprising of a set of empirical forms, which allows for thorough analysis. A detailed simulation model of a typical DC-traction system has been developed to validate the developed empirical forms. The results verified the validity of the proposed mathematical model, and demonstrated …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco

Libraries' Newsletters

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Numerical Methods For Nonlinear Optimal Control Problems And Their Applications In Indoor Climate Control, Runxin He

McKelvey School of Engineering Graduate Student Theses & Dissertations

Efficiency, comfort, and convenience are three major aspects in the design of control systems for residential Heating, Ventilation, and Air Conditioning (HVAC) units. In this dissertation, we study optimization-based algorithms for HVAC control that minimizes energy consumption while maintaining a desired temperature, or even human comfort in a room. Our algorithm uses a Computer Fluid Dynamics (CFD) model, mathematically formulated using Partial Differential Equations (PDEs), to describe the interactions between temperature, pressure, and air flow. Our model allows us to naturally formulate problems such as controlling the temperature of a small region of interest within a room, or to control …