Engineering Commons^™

Coherent Control Of Dispersive Waves, Jimmie Adriazola

Dissertations

This dissertation addresses some of the various issues which can arise when posing and solving optimization problems constrained by dispersive physics. Considered here are four technologically relevant experiments, each having their own unique challenges and physical settings including ultra-cold quantum fluids trapped by an external field, paraxial light propagation through a gradient index of refraction, light propagation in periodic photonic crystals, and surface gravity water waves over shallow and variable seabeds. In each of these settings, the physics can be modeled by dispersive wave equations, and the technological objective is to design the external trapping fields or propagation media such …

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

End Milling Process Modeling Using Artificial Neural Networks, Khaled Abdel-Hamid Elsayed

Archived Theses and Dissertations

No abstract provided.

Leveraging Choice Modeling Technique For Enhancing The Cyber Resilience Of The Smart Grid, Kesava Karishma Devi Dadi

Theses and Dissertations

This research focuses on the cyber-attack of the smart grid and its retrieval to a normal state by estimating the smart grid's resilience. This study developed a theoretical model to estimate the resilience of the smart grid using choice modeling. A utility function is formulated based on various factors and sub-factors of resilience to estimate the resilience of the smart grid. Choice modeling is applied to estimate the model parameters in various fields such as marketing, energy, transportation, and health and to predict the outcome.

Deep Multi-Modal U-Net Fusion Methodology Of Infrared And Ultrasonic Images For Porosity Detection In Additive Manufacturing, Christian E. Zamiela

Theses and Dissertations

We developed a deep fusion methodology of non-destructive (NDT) in-situ infrared and ex- situ ultrasonic images for localization of porosity detection without compromising the integrity of printed components that aims to improve the Laser-based additive manufacturing (LBAM) process. A core challenge with LBAM is that lack of fusion between successive layers of printed metal can lead to porosity and abnormalities in the printed component. We developed a sensor fusion U-Net methodology that fills the gap in fusing in-situ thermal images with ex-situ ultrasonic images by employing a U-Net Convolutional Neural Network (CNN) for feature extraction and two-dimensional object localization. We …

Testing Of Methods For Reducing Motivational Bias In Multi - Criteria Decision Analysis Problems, Chadwick Samuel Kerr

Theses and Dissertations

The idea of multi-criteria decision making has been around for quite a while. All judgement tasks are potential points of bias introduction. Each judgement task was assessed to identify common biases introduced through an extensive literature review for each task and bias. In several other studies, the distinction is made between cognitive and motivational biases. Cognitive biases are widely studied and well known with mitigations that have been validated. Motivational biases are judgements influenced by the decision maker’s desire for a specific outcome, also referred to as intentional bias, that are hard to correct and received very little testing and …

Using A Systemic Skills Model To Build An Effective 21st Century Workforce: Factors That Impact The Ability To Navigate Complex Systems, Morteza Nagahi

Theses and Dissertations

The growth of technology and the proliferation of information made modern complex systems more fragile and vulnerable. As a result, competitive advantage is no longer achieved exclusively through strategic planning but by developing an influential cadre of technical people who can efficiently manage and navigate modern complex systems. The dissertation aims to provide educators, practitioners, and organizations with a model that helps to measure individuals’ systems thinking skills, complex problem solving, personality traits, and the impacting demographic factors such as managerial and work experience, current occupation type, organizational ownership structure, and education level. The intent is to study how these …

Effects Of The Inclusion Of Rice Hull Derived Bio-Oil On Wood Pellet Production, Tyler E. Lowe

Theses and Dissertations

Wood pellet production has become an advancing industry for the sake of reducing greenhouse emissions into the atmosphere especially, in European Union countries. Researchers and industry executives seek new methods and materials to improve the pelletization process. Rice hulls or husks has the potential to aid in wood pelletization as they possess high calorific values. This study focuses on using rice hull derived bio-oil from pyrolysis, which will also decrease ash content, as an additive to aid in the wood pelletization process. Using two groups of rice hull derived bio-oil as an additive in wood pelletization: Group 1 uses heavy …

A Dual Perspective Towards Building Resilience In Manufacturing Organizations, Steven A. Fazio

Theses and Dissertations

Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures …

The Development Of Authentic Virtual Reality Scenarios To Measure Individuals’ Level Of Systems Thinking Skills And Learning Abilities, Vidanelage L. Dayarathna

Theses and Dissertations

This dissertation develops virtual reality modules to capture individuals’ learning abilities and systems thinking skills in dynamic environments. In the first chapter, an immersive queuing theory teaching module is developed using virtual reality technology. The objective of the study is to present systems engineering concepts in a more sophisticated environment and measure students learning abilities. Furthermore, the study explores the performance gaps between male and female students in manufacturing systems concepts. To investigate the gender biases toward the performance of developed VR module, three efficacy measures (simulation sickness questionnaire, systems usability scale, and presence questionnaire) and two effectiveness measures (NASA …

Process Improvement Of Honeysuckle Biscuits And Bakery, Jevon Franklin, Kaela Bellamy, Manuel Quintal, Suheyl Polat

Senior Design Project For Engineers

Honeysuckle Biscuits and Bakery is a locally owned restaurant in Downtown Kennesaw, Georgia. Mitch and Lori Phillips, the owners, opened the restaurant in 2018. The restaurant serves breakfast (with biscuits as its specialty), lunch, coffee, desserts, and specialty cakes. As the business is beginning to outgrow itself, the project manager, Kaela Bellamy, felt it was a need to look at how to best accommodate the growing demand within the new space.

Intelligent Computer System For Enhancing Value Engineering Implementation In The Egyptian Construction Industry, Hazem M. El-Senoussi

Archived Theses and Dissertations

No abstract provided.

Genetic Algorithm For Production Scheduling, Mary El-Mallakh

Archived Theses and Dissertations

No abstract provided.

Workflow Optimization Of World Micro, Inc. Quality Department, Nicholas Ricci, Rosa Lopez Gomez, Darius Ruffin, Josh Fennell

Senior Design Project For Engineers

Our group member Nick is currently an intern at World Micro, which is an electronic components distributor for companies manufacturing a variety of commercial, aerospace and military products. When electrical components are purchased from the open market, they need to be traced back to the OEM (Original Equipment Manufacturer) or have a series of tests performed to verify that the parts are authentic and work. The current process time for World Micro’s quality testing and inspection is not efficient causing long lead times, extra work hours, and extra expenses in outsourcing services.

Forecasting Nigeria's Electricity Demand And Energy Efficiency Potential Under Climate Uncertainty, Olawale Olabisi

Doctoral Dissertations

The increasing population and socio-economic growth of Nigeria, coupled with the current, unmet electricity demand, requires the need for power supply facilities expansion. Of all Nigeria’s electricity consumption by sector, the residential sector is the largest and growing at a very fast rate. To meet this growing demand, an accurate estimation of the demand into the future that will guide policy makers to adequately plan for the expansion of electricity supply and distribution, and energy efficiency standards and labeling must be made. To achieve this, a residential electricity demand forecast model that can correctly predict future demand and guide the …

Applications In Multi-Band Isolation Of Spectra With Data-Adaptive Sub-Banding (Midas): Using Multi-Criteria Decision Analysis To Optimize Midas-Based De-Noising Methods When Processing Infrasound And Other Signals Of Interest, Everett Raymond Coots

Theses and Dissertations

The ever-present challenge faced by the signal processing analyst is to get more from the available data, whether it be exploiting the same data in new ways to garner new information, or simply to increase the confidence in existing qualitative metrics. Traditional techniques include filtering (to improve the signal to noise ratio of detected signals or images or to isolate and possibly remove interfering signals), feature detection/extraction (identifying key characteristics within the signal) and signal decomposition (identification of dominant signals of interest relative to noise terms). Current research by our team began with an emphasis on the filtering of signals …

A Joint Soft Warping And Clustering Approach To Detecting Time Series Anomalies, Christopher John Schuchmann

Theses and Dissertations

Unsupervised anomalous time series detection methods focus on identifying outliers without prior knowledge of the dataset. However, these methods often require multiple parameters to be optimized, with adequate performance tied to their careful tuning and prior domain knowledge. In this work, two methods are proposed for detecting outlier time series that adopt a joint clustering and alignment optimization to filter out the desired signals. The time series are globally clustered while simultaneously being aligned to other signals in their same cluster group. This alternating optimization employs time-warping similarity measures to help identify closely matching time series as well as the …

Predicting Zero Bin In The Semiconductor Manufacturing Industry: Machine Learning Algorithms, Yazmin Montoya

Open Access Theses & Dissertations

The semiconductor industry has faced supply chain manufacturing shortages that ultimately led to a worldwide chip shortage during the COVID-19 pandemic. These chip manufacturers use sophisticated and advanced manufacturing machinery in their fabs to manufacture chips. As experienced during the pandemic, manufacturing unavailability is often due to the lack of critical manufacturing-related spare parts. This thesis evaluates the effectiveness of machine learning algorithms to identify significant factors contributing to manufacturing part outages (i.e., zero-bin) to keep manufacturing equipment running at total capacity within the organization. We propose clustering methods to segment the data and use logistic regression, logistic lasso regression, …

Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He

Theses and Dissertations

Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …

Development Of Metaheuristic Algorithms For The Efficient Allocation Of Power Flow Control Devices, Eduardo Jose Castillo Fatule

Open Access Theses & Dissertations

Modern energy grids have become extremely complex systems, requiring more variable and active flow control. As a remedy to this, Distributed Flexible AC Transmission Systems (D-FACTS) are cost-efficient devices used to mitigate power flow congestion and integrate renewable energies. The objective of this research is then to propose an efficient multiple objective evolutionary algorithm to solve a stochastic model for D-FACTS allocation, which aims to optimize various objectives related to cost, grid health, and environmental impacts. The model was implemented on a modified RTS-96 test system, and the results show that optimally allocating D-FACTS modules using the proposed model can …

Decomposition Approach To Parametric Nonconvex Regression; Nuclear Resonance Analysis, Jordan L. Armstrong

Masters Theses

Parameterized nonconvex regression is a difficult problem for any optimization solver packages, often resulting in approximations and linearizations of the problem in order to be able to arrive a solution, if the problem is even solvable at all. These changes to the initial problem are largely dependent upon having appropriate domain knowledge and still often times result in a sizable gap between the achieved solution and the best true solution. We propose a novel method of decomposing the global problem into small, overlapping windows. Thus, the independent windows are now solvable. Subsequently, we offer a novel, sequential method of parameter …

Supply Chain Optimization Of A Local Small Business From The Food-Service Industry Using Simulation Models, Aimee Montalvo

Open Access Theses & Dissertations

Various supply chain disruptions can cause revenue losses, low productivity, and damaged reputations. Some examples of such disruptions include increased supply costs, labor shortages, pandemics, natural disasters, or transportation delays. For instance, during the COVID-19 pandemic, several small and medium enterprises (SMEs) suffered greatly from labor shortages, delayed and costly supplies, and decreased demand. In this research, we present a case study of a small local business from the fast-food industry that experienced the loss of employees and delays and analyzed the increased cost of supplies. We created visualization modules with the SMEs supply chain performance measures to see the …

Understanding The Behavior Of The Covid-19 Pandemic Using Data Analytics, Mohammad Reza Davahli

Electronic Theses and Dissertations, 2020-2023

In December 2019, China announced the breakout of a new virus identified as coronavirus SARS-CoV-2 (COVID-19), which soon grew exponentially and became a global pandemic. Despite strict actions to mitigate the spread of the virus in various countries, the COVID-19 pandemic resulted in a significant loss of human life in 2020 and 2021. To better understand the pandemic, this doctoral research incorporated data analytics to evaluate the behavior and impacts of the virus. The doctoral research contributed to the scientific body of the knowledge in different ways including (1) presenting a systematic literature review of current research and topics about …

Airspace Integration Of New Entrants And Safety Risk Management Models, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

In recent years, the demand for airspace access of Unmanned Aerial Systems (UAS) increased significantly and is continuously increasing for different altitude-types UAS. A similar evolution is expected from Commercial Space Operations (CSO) in the next years. These aviation/aerospace systems will need to be seamlessly integrated into the National Airspace System (NAS), at their operational altitude levels, and accounted for from all perspectives, including proactively addressing their safety hazards. This thesis captures the requirements for the new entrants’ integration, and then identifies and analyzes the safety risks added to the NAS operations by its new entrants, the future omnipresent UAS …

Identifying An Optimization Technique For Maker Usage To Address Covid-19 Supply Shortfalls, Michael J. Wilson

Doctoral Dissertations

Fused Deposition Modeling (FDM) can be purchased for under five hundred dollars. The availability of these inexpensive systems has created a large hobbyist (or maker) community. For makers, FDM printing is used numerous uses.

With the onset of the COVID-19 pandemic, the needs for Personal Protective Equipment (PPE) skyrocketed. COVID-19 mitigation strategies such as social distancing, businesses closures, and shipping delays created significant supply shortfalls. The maker community stepped in to fill gaps in PPE supplies.

In the case of 3DP, optimization remains the domain of commercial entities. Optimization is, at best, ad-hoc for makers. With the need to PPE …

An Algorithm For Biobjective Mixed Integer Quadratic Programs, Pubudu Jayasekara Merenchige

All Dissertations

Multiobjective quadratic programs (MOQPs) are appealing since convex quadratic programs have elegant mathematical properties and model important applications. Adding mixed-integer variables extends their applicability while the resulting programs become global optimization problems. Thus, in this work, we develop a branch and bound (BB) algorithm for solving biobjective mixed-integer quadratic programs (BOMIQPs). An algorithm of this type does not exist in the literature.

The algorithm relies on five fundamental components of the BB scheme: calculating an initial set of efficient solutions with associated Pareto points, solving node problems, fathoming, branching, and set dominance. Considering the properties of the Pareto set of …

Development And Application Of A Digital Twin For Chiller Plant Performance Assessment, Mihir Kale

All Theses

As the complexity of industrial equipment continues to increase, the management of the individual machines and integrated operations becomes difficult without computer tools. The availability of streaming data from manufacturing floors, plant operations, and deployed fleets can be overwhelming to analyze, although it provides opportunities to improve performance. The use of dedicated monitoring systems in the plant and field to troubleshoot machinery can be integrated within a product lifecycle management (PLM) architecture to offer greater features. PLM offers virtual processes and software tools for the design, analysis, monitoring, and support of engineering systems and products. Within this paradigm, a digital …

Machine Learning Application For Mission Data Reprogramming, Paolo A. Bingham

Theses and Dissertations

Before entering a conflict or theater, USAF aircraft require updated mission data software reprogramming. Mission data controls all electronic warfare (EW) operations of the aircraft. EW operations include identifying and jamming radar operated systems, whether they are friendly or hostile. The process of reprogramming software is continuous and routinely updated for every EW system annually. On specific circumstances, the process can be expedited to months, but this puts a strain on the development team and shifts all attention to one specific mission data file. Unfortunately, a growing number of requests to upgrade mission data to a higher priority state, has …

Assessment Of Visual Field Performance Asymmetries While Utilizing Aircraft Attitude Symbology, George A. Reis

Theses and Dissertations

Two experiments were conducted to examine visual performance asymmetries when perceiving complex, meaningful visual stimuli, such as the Arc Segment Attitude Reference (ASAR). The ASAR symbology represents an aircraft’s attitude. Experiment 1 examined participants’ performance while recalling and reporting various attitudes of ASAR symbology and a Gabor patch, which were briefly presented in the peripheral visual field. Performance was assessed for coordinate and categorical judgments at various display locations. The results were consistent with the horizontal-vertical anisotropy literature, which implies that performance would be better for stimuli placed on the horizontal meridian as compared to stimuli placed on the vertical …

Compact In-Rack Dielectric Immersion Cooling System, Salvador Landeros Jr, Joshua M. Hannaman, Marshall D. Reid

Mechanical Engineering

The Compact Dielectric Cooling team consisting of Josh Hannaman, Marshall Reid, and Salvador Landeros worked with Aria Technologies to create a thermal management system for data centers that can easily implement liquid cooling into current infrastructure for high density computing servers. The project was to design, build, and test a compact immersion cooling system for a senior project at California Polytechnic State University – San Luis Obispo. Immersion cooling is a liquid-cooling process that involves the immersion of electrical IT equipment and the removal of heat from the hot IT components using dielectric liquid. The goal was to build a …