Matching Items (23)
Filtering by

Clear all filters

149092-Thumbnail Image.png
Description

The ASU COVID-19 testing lab process was developed to operate as the primary testing site for all ASU staff, students, and specified external individuals. Tests are collected at various collection sites, including a walk-in site at the SDFC and various drive-up sites on campus; analysis is conducted on ASU campus

The ASU COVID-19 testing lab process was developed to operate as the primary testing site for all ASU staff, students, and specified external individuals. Tests are collected at various collection sites, including a walk-in site at the SDFC and various drive-up sites on campus; analysis is conducted on ASU campus and results are distributed virtually to all patients via the Health Services patient portal. The following is a literature review on past implementations of various process improvement techniques and how they can be applied to the ABCTL testing process to achieve laboratory goals. (abstract)

ContributorsKrell, Abby Elizabeth (Co-author) / Bruner, Ashley (Co-author) / Ramesh, Frankincense (Co-author) / Lewis, Gabriel (Co-author) / Barwey, Ishna (Co-author) / Myers, Jack (Co-author) / Hymer, William (Co-author) / Reagan, Sage (Co-author) / Compton, Carolyn (Thesis director) / McCarville, Daniel R. (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
133908-Thumbnail Image.png
Description

Ultimate Frisbee or "Ultimate," is a fast growing field sport that is being played competitively at universities across the country. Many mid-tier college teams have the goal of winning as many games as possible, however they also need to grow their program by training and retaining new players. The purpose

Ultimate Frisbee or "Ultimate," is a fast growing field sport that is being played competitively at universities across the country. Many mid-tier college teams have the goal of winning as many games as possible, however they also need to grow their program by training and retaining new players. The purpose of this project was to create a prototype statistical tool that maximizes a player line-up's probability of scoring the next point, while having as equal playing time across all experienced and novice players as possible. Game, player, and team data was collected for 25 different games played over the course of 4 tournaments during Fall 2017 and early Spring 2018 using the UltiAnalytics iPad application. "Amount of Top 1/3 Players" was the measure of equal playing time, and "Line Efficiency" and "Line Interaction" represented a line's probability of scoring. After running a logistic regression, Line Efficiency was found to be the more accurate predictor of scoring outcome than Line Interaction. An "Equal PT Measure vs. Line Efficiency" graph was then created and the plot showed what the optimal lines were depending on what the user's preferences were at that point in time. Possible next steps include testing the model and refining it as needed.

ContributorsSpence, Andrea Nicole (Author) / McCarville, Daniel R. (Thesis director) / Pavlic, Theodore (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
135418-Thumbnail Image.png
Description
Solid oxide fuel cells have become a promising candidate in the development of high-density clean energy sources for the rapidly increasing demands in energy and global sustainability. In order to understand more about solid oxide fuel cells, the important step is to understand how to model heterogeneous materials. Heterogeneous materials

Solid oxide fuel cells have become a promising candidate in the development of high-density clean energy sources for the rapidly increasing demands in energy and global sustainability. In order to understand more about solid oxide fuel cells, the important step is to understand how to model heterogeneous materials. Heterogeneous materials are abundant in nature and also created in various processes. The diverse properties exhibited by these materials result from their complex microstructures, which also make it hard to model the material. Microstructure modeling and reconstruction on a meso-scale level is needed in order to produce heterogeneous models without having to shave and image every slice of the physical material, which is a destructive and irreversible process. Yeong and Torquato [1] introduced a stochastic optimization technique that enables the generation of a model of the material with the use of correlation functions. Spatial correlation functions of each of the various phases within the heterogeneous structure are collected from a two-dimensional micrograph representing a slice of a solid oxide fuel cell through computational means. The assumption is that two-dimensional images contain key structural information representative of the associated full three-dimensional microstructure. The collected spatial correlation functions, a combination of one-point and two-point correlation functions are then outputted and are representative of the material. In the reconstruction process, the characteristic two-point correlation functions is then inputted through a series of computational modeling codes and software to generate a three-dimensional visual model that is statistically similar to that of the original two-dimensional micrograph. Furthermore, parameters of temperature cooling stages and number of pixel exchanges per temperature stage are utilized and altered accordingly to observe which parameters has a higher impact on the reconstruction results. Stochastic optimization techniques to produce three-dimensional visual models from two-dimensional micrographs are therefore a statistically reliable method to understanding heterogeneous materials.
ContributorsPhan, Richard Dylan (Author) / Jiao, Yang (Thesis director) / Ren, Yi (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
136490-Thumbnail Image.png
Description
The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs and regulatory requirements set by entities such as unions and

The crew planning problem in the airline industry presents a very computationally complex problem of high importance to the business. Airlines must schedule crew members to ensure that all flights are staffed while remaining in compliance with the business needs and regulatory requirements set by entities such as unions and FAA. With the magnitude of operation of the prominent players in the airline industry today, the crew staffing problem proves very large and has become heavily reliant on operations research solution methodologies. An area of opportunity that has not yet been extensively researched lies in the planning of crew vacation. This paper develops a model driven by the idea of system risk that constructs an optimal vacation grid for the time period of one year. The model generates a daily allocation that maximizes vacation offering while ensuring a given level of system reliability. The model is then implemented using data from US Airways and model improvements are provided for practical application in the airline industry based on the output.
ContributorsFisher, Tignes Noel (Author) / Gel, Esma (Thesis director) / Jacobs, Tim (Committee member) / Clough, Michael (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
136400-Thumbnail Image.png
Description
The purpose of this paper is to provide a new and improved design method for the Formula Society of Automotive Engineering (FSAE) team. There are five tasks that I accomplish in this paper: 1. I describe how the FSAE team is currently designing their car. This allows the reader to

The purpose of this paper is to provide a new and improved design method for the Formula Society of Automotive Engineering (FSAE) team. There are five tasks that I accomplish in this paper: 1. I describe how the FSAE team is currently designing their car. This allows the reader to understand where the flaws might arise in their design method. 2. I then describe the key aspects of systems engineering design. This is the backbone of the method I am proposing, and it is important to understand the key concepts so that they can be applied to the FSAE design method. 3. I discuss what is available in the literature about race car design and optimization. I describe what other FSAE teams are doing and how that differs from systems engineering design. 4. I describe what the FSAE team at Arizona State University (ASU) should do to improve their approach to race car design. I go into detail about how the systems engineering method works and how it can and should be applied to the way they design their car. 5. I then describe how the team should implement this method because the method is useless if they do not implement it into their design process. I include an interview from their brakes team leader, Colin Twist, to give an example of their current method of design and show how it can be improved with the new method. This paper provides a framework for the FSAE team to develop their new method of design that will help them accomplish their overall goal of succeeding at the national competition.
ContributorsPickrell, Trevor Charles (Author) / Trimble, Steven (Thesis director) / Middleton, James (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
136442-Thumbnail Image.png
Description
A model has been developed to modify Euler-Bernoulli beam theory for wooden beams, using visible properties of wood knot-defects. Treating knots in a beam as a system of two ellipses that change the local bending stiffness has been shown to improve the fit of a theoretical beam displacement function to

A model has been developed to modify Euler-Bernoulli beam theory for wooden beams, using visible properties of wood knot-defects. Treating knots in a beam as a system of two ellipses that change the local bending stiffness has been shown to improve the fit of a theoretical beam displacement function to edge-line deflection data extracted from digital imagery of experimentally loaded beams. In addition, an Ellipse Logistic Model (ELM) has been proposed, using L1-regularized logistic regression, to predict the impact of a knot on the displacement of a beam. By classifying a knot as severely positive or negative, vs. mildly positive or negative, ELM can classify knots that lead to large changes to beam deflection, while not over-emphasizing knots that may not be a problem. Using ELM with a regression-fit Young's Modulus on three-point bending of Douglass Fir, it is possible estimate the effects a knot will have on the shape of the resulting displacement curve.
Created2015-05
134380-Thumbnail Image.png
Description
The main objective of this project was to continue research and development of a building integrated solar thermoelectric generator (BISTEG). BISTEG is a promising renewable energy technology that is capable of generating electrical energy from the heat of concentrated sunlight. In order to perform R&D, the performance of different TEG

The main objective of this project was to continue research and development of a building integrated solar thermoelectric generator (BISTEG). BISTEG is a promising renewable energy technology that is capable of generating electrical energy from the heat of concentrated sunlight. In order to perform R&D, the performance of different TEG cells and TEG setups were tested and analyzed, proof-of-concepts and prototypes were built. and the performance of the proof-of-concepts and prototypes were tested and analyzed as well. In order to test different TEG cells and TEG setups, a TEG testing apparatus was designed and fabricated. The apparatus is capable of comparing the performance of TEGs with temperature differentials up to 200 degrees C. Along with a TEG testing apparatus, several proof-of-concepts and prototypes were completed. All of these were tested in order to determine the feasibility of the design. All three proof-of-concepts were only capable of producing a voltage output less than 300mV. The prototype, however, was capable of producing a max output voltage of 17 volts. Although the prototype outperformed all of the proof-of-concepts, optimizations to the design can continue to improve the output voltage. In order to do so, stacked TEG tests were performed. After performing the stacked TEG tests, it was determined that the use of stacked TEGs depended on the Fresnel lens chosen. If BISTEG were to use a point focused Fresnel lens, using a stack of TEGs could increase the power density. If BISTEG were to utilize a linear focused Fresnel lens, however, the TEGs should not be stacked. It would be more efficient to lay them out side by side. They can be stacked, however, if the energy density needs to be increased and the costs of the additional TEGs are not an issue.
ContributorsPark, Andrew (Author) / Seager, Thomas (Thesis director) / Margaret, Hinrichs (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
133532-Thumbnail Image.png
Description
Carbon emissions have become a major concern since the turn of the century. This has increased the demand of hybrid vehicles in United States market. Hence, there is a need to make these vehicles more efficient. This thesis focuses on creating a thermal model that could be used for optimization

Carbon emissions have become a major concern since the turn of the century. This has increased the demand of hybrid vehicles in United States market. Hence, there is a need to make these vehicles more efficient. This thesis focuses on creating a thermal model that could be used for optimization of these vehicles. The project was accomplished in collaboration with EcoCar3, and the temperature data obtained from the model was compared with the experimental temperature data gathered from EcoCar's testing of the vehicle they built. The data obtained through this study demonstrates that the model was accurately able to predict thermal behavior of the electric motor and the high-voltage batteries in the vehicle. Therefore, this model could be used for optimization of the powertrain in a hybrid vehicle.
ContributorsMuthuvenkatesh, Nikhil (Author) / Mayyas, Abdel (Thesis director) / Patel, Jay (Committee member) / W.P. Carey School of Business (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
134111-Thumbnail Image.png
Description
Every year, millions of guests visit theme parks internationally. Within that massive population, accidents and emergencies are bound to occur. Choosing the correct location for emergency responders inside of the park could mean the difference between life and death. In an effort to provide the utmost safety for the guests

Every year, millions of guests visit theme parks internationally. Within that massive population, accidents and emergencies are bound to occur. Choosing the correct location for emergency responders inside of the park could mean the difference between life and death. In an effort to provide the utmost safety for the guests of a park, it is important to make the best decision when selecting the location for emergency response crews. A theme park is different from a regular residential or commercial area because the crowds and shows block certain routes, and they change throughout the day. We propose an optimization model that selects staging locations for emergency medical responders in a theme park to maximize the number of responses that can occur within a pre-specified time. The staging areas are selected from a candidate set of restricted access locations where the responders can store their equipment. Our solution approach considers all routes to access any park location, including areas that are unavailable to a regular guest. Theme parks are a highly dynamic environment. Because special events occurring in the park at certain hours (e.g., parades) might impact the responders' travel times, our model's decisions also include the time dimension in the location and re-location of the responders. Our solution provides the optimal location of the responders for each time partition, including backup responders. When an optimal solution is found, the model is also designed to consider alternate optimal solutions that provide a more balanced workload for the crews.
ContributorsLivingston, Noah Russell (Author) / Sefair, Jorge (Thesis director) / Askin, Ronald (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
137671-Thumbnail Image.png
Description
NGExtract 2 is a complete transistor (MOSFET) parameter extraction solution based upon the original computer program NGExtract by Rahul Shringarpure written in February 2007. NGExtract 2 is written in Java and based around the circuit simulator NGSpice. The goal of the program is to be used to produce

NGExtract 2 is a complete transistor (MOSFET) parameter extraction solution based upon the original computer program NGExtract by Rahul Shringarpure written in February 2007. NGExtract 2 is written in Java and based around the circuit simulator NGSpice. The goal of the program is to be used to produce accurate transistor models based around real-world transistor data. The program contains numerous improvements to the original program:
• Completely rewritten with performance and usability in mind
• Cross-Platform vs. Linux Only
• Simple installation procedure vs. compilation and manual library configuration
• Self-contained, single file runtime
• Particle Swarm Optimization routine
NGExtract 2 works by plotting the Ids vs. Vds and Ids vs. Vgs curves of a simulation model and the measured, real-world data. The user can adjust model parameters and re-simulate to attempt to match the curves. The included Particle Swarm Optimization routine attempts to automate this process by iteratively attempting to improve a solution by measuring its sum-squared error against the real-world data that the user has provided.
ContributorsVetrano, Michael Thomas (Author) / Allee, David (Thesis director) / Gorur, Ravi (Committee member) / Bakkaloglu, Bertan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05