Matching Items (25)
Description
Swarms of animals, fish, birds, locusts etc. are a common occurrence but their coherence and method of organization poses a major question for mathematics and biology.The Vicsek and the Attraction-Repulsion are two models that have been proposed to explain the emergence of collective motion. A major issue for the Vicsek Model is that its particles are not attracted to each other, leaving the swarm with alignment in velocity but without spatial coherence. Restricting the particles to a bounded domain generates global spatial coherence of swarms while maintaining velocity alignment. While individual particles are specularly reflected at the boundary, the swarm as a whole is not. As a result, new dynamical swarming solutions are found.
The Attraction-Repulsion Model set with a long-range attraction and short-range repulsion interaction potential typically stabilizes to a well-studied flock steady state solution. The particles for a flock remain spatially coherent but have no spatial bound and explore all space. A bounded domain with specularly reflecting walls traps the particles within a specific region. A fundamental refraction law for a swarm impacting on a planar boundary is derived. The swarm reflection varies from specular for a swarm dominated by
kinetic energy to inelastic for a swarm dominated by potential energy. Inelastic collisions lead to alignment with the wall and to damped pulsating oscillations of the swarm. The fundamental refraction law provides a one-dimensional iterative map that allows for a prediction and analysis of the trajectory of the center of mass of a flock in a channel and a square domain.
The extension of the wall collisions to a scattering experiment is conducted by setting two identical flocks to collide. The two particle dynamics is studied analytically and shows a transition from scattering: diverging flocks to bound states in the form of oscillations or parallel motions. Numerical studies of collisions of flocks show the same transition where the bound states become either a single translating flock or a rotating (mill).
The Attraction-Repulsion Model set with a long-range attraction and short-range repulsion interaction potential typically stabilizes to a well-studied flock steady state solution. The particles for a flock remain spatially coherent but have no spatial bound and explore all space. A bounded domain with specularly reflecting walls traps the particles within a specific region. A fundamental refraction law for a swarm impacting on a planar boundary is derived. The swarm reflection varies from specular for a swarm dominated by
kinetic energy to inelastic for a swarm dominated by potential energy. Inelastic collisions lead to alignment with the wall and to damped pulsating oscillations of the swarm. The fundamental refraction law provides a one-dimensional iterative map that allows for a prediction and analysis of the trajectory of the center of mass of a flock in a channel and a square domain.
The extension of the wall collisions to a scattering experiment is conducted by setting two identical flocks to collide. The two particle dynamics is studied analytically and shows a transition from scattering: diverging flocks to bound states in the form of oscillations or parallel motions. Numerical studies of collisions of flocks show the same transition where the bound states become either a single translating flock or a rotating (mill).
ContributorsThatcher, Andrea (Author) / Armbruster, Hans (Thesis advisor) / Motsch, Sebastien (Committee member) / Ringhofer, Christian (Committee member) / Platte, Rodrigo (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this work, I present a Bayesian inference computational framework for the analysis of widefield microscopy data that addresses three challenges: (1) counting and localizing stationary fluorescent molecules; (2) inferring a spatially-dependent effective fluorescence profile that describes the spatially-varying rate at which fluorescent molecules emit subsequently-detected photons (due to different illumination intensities or different local environments); and (3) inferring the camera gain. My general theoretical framework utilizes the Bayesian nonparametric Gaussian and beta-Bernoulli processes with a Markov chain Monte Carlo sampling scheme, which I further specify and implement for Total Internal Reflection Fluorescence (TIRF) microscopy data, benchmarking the method on synthetic data. These three frameworks are self-contained, and can be used concurrently so that the fluorescence profile and emitter locations are both considered unknown and, under some conditions, learned simultaneously. The framework I present is flexible and may be adapted to accommodate the inference of other parameters, such as emission photophysical kinetics and the trajectories of moving molecules. My TIRF-specific implementation may find use in the study of structures on cell membranes, or in studying local sample properties that affect fluorescent molecule photon emission rates.
ContributorsWallgren, Ross (Author) / Presse, Steve (Thesis advisor) / Armbruster, Hans (Thesis advisor) / McCulloch, Robert (Committee member) / Arizona State University (Publisher)
Created2019
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 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
Description
Simulation games are widely used in engineering education, especially for industrial engineering and operations management. A well-made simulation game aids in achieving learning objectives for students and minimal additional teaching by an instructor. Many simulation games exist for engineering education, but newer technologies now exist that improve the overall experience of developing and using these games. Although current solutions teach concepts adequately, poorly-maintained platforms distract from the key learning objectives, detracting from the value of the activities. A backend framework was created to facilitate an educational, competitive, participatory simulation of a manufacturing system that is intended to be easy to maintain, deploy, and expand.
ContributorsChandler, Robert Keith (Author) / Clough, Michael (Thesis director) / Pavlic, Theodore (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
At Arizona State University, the Disability Resource Center provides disabled students transportation around campus. This transportation service known as DART is composed of approximately 20 student workers and 9 carts that pick riders up based on pre-determined pick-up times and locations. With the current system, the scheduling of drivers to riders is inefficient, and in response, a tool was developed to schedule the rides in a faster manner. A demonstration of the new tool resulted in a time reduction of 98%.
ContributorsFranke, Alexandra Nicole (Author) / Clough, Michael (Thesis director) / Jennings, Cheryl (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
The efficient refurbishment of rotable parts on an aircraft proves to be a main concern for airline carriers today. Airlines must be able to seamlessly rotate parts into and out of the system for maintenance in accordance with FAA requirements while leaving daily operations uninterrupted. In this paper, we develop an airline maintenance scheduling model that constructs an optimal schedule for part maintenance over a given time horizon using deterministic forecasting techniques. The model generates a schedule that minimizes the total cost of a maintenance schedule solution while maximizing the utility of all parts in the system. The model is then tested against actual network data of three part types crucial to airline operations and used to investigate the current data collection processes of US Airways maintenance lead time metrics. Manual sensitivity analysis is performed to generate the marginal value of each parameter and potential model extensions are highlighted as a result of these conclusions.
ContributorsDunham, Nicole Elizabeth (Author) / Gel, Esma (Thesis director) / Jacobs, Timothy (Committee member) / Clough, Michael (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-12
Description
The listing price of residential rental real estate is dependent upon property specific attributes. These attributes involve data that can be tabulated as categorical and continuous predictors. The forecasting model presented in this paper is developed using publicly available, property specific information sourced from the Zillow and Trulia online real estate databases. The following fifteen predictors were tracked for forty-eight rental listings in the 85281 area code: housing type, square footage, number of baths, number of bedrooms, distance to Arizona State University’s Tempe Campus, crime level of the neighborhood, median age range of the neighborhood population, percentage of the neighborhood population that is married, median year of construction of the neighborhood, percentage of the population commuting longer than thirty minutes, percentage of neighborhood homes occupied by renters, percentage of the population commuting by transit, and the number of restaurants, grocery stores, and nightlife within a one mile radius of the property. Through regression analysis, the significant predictors of the listing price of a rental property in the 85281 area code were discerned. These predictors were used to form a forecasting model. This forecasting model explains 75.5% of the variation in listing prices of residential rental real estate in the 85281 area code.
ContributorsSchuchter, Grant (Author) / Clough, Michael (Thesis director) / Escobedo, Adolfo (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Carbon Capture and Storage (CCS) is a climate stabilization strategy that prevents CO2 emissions from entering the atmosphere. Despite its benefits, impactful CCS projects require large investments in infrastructure, which could deter governments from implementing this strategy. In this sense, the development of innovative tools to support large-scale cost-efficient CCS deployment decisions is critical for climate change mitigation. This thesis proposes an improved mathematical formulation for the scalable infrastructure model for CCS (SimCCS), whose main objective is to design a minimum-cost pipe network to capture, transport, and store a target amount of CO2. Model decisions include source, reservoir, and pipe selection, as well as CO2 amounts to capture, store, and transport. By studying the SimCCS optimal solution and the subjacent network topology, new valid inequalities (VI) are proposed to strengthen the existing mathematical formulation. These constraints seek to improve the quality of the linear relaxation solutions in the branch and bound algorithm used to solve SimCCS. Each VI is explained with its intuitive description, mathematical structure and examples of resulting improvements. Further, all VIs are validated by assessing the impact of their elimination from the new formulation. The validated new formulation solves the 72-nodes Alberta problem up to 7 times faster than the original model. The upgraded model reduces the computation time required to solve SimCCS in 72% of randomly generated test instances, solving SimCCS up to 200 times faster. These formulations can be tested and then applied to enhance variants of the SimCCS and general fixed-charge network flow problems. Finally, an experience from testing a Benders decomposition approach for SimCCS is discussed and future scope of probable efficient solution-methods is outlined.
ContributorsLobo, Loy Joseph (Author) / Sefair, Jorge A (Thesis advisor) / Escobedo, Adolfo (Committee member) / Kuby, Michael (Committee member) / Middleton, Richard (Committee member) / Arizona State University (Publisher)
Created2017
Description
Most staff planning for airline industries are done using point estimates; these do not account for the probabilistic nature of employees not showing up to work, and the airline company risks being under or overstaffed at different times, which increases costs and deteriorates customer service. This model proposes utilizing a stochastic method for American Airlines to schedule their ground crew staff. We developed a stochastic model for scheduling that incorporates the risks of absent employees and as well as reliability so that stakeholders can determine the level of reliability they want to maintain in their system based on the costs. We also incorporated a preferences component to the model in order to increase staff satisfaction in the schedules they get assigned based on their predetermined preferences. Since this is a general staffing model, this can be utilized for an airline crew or virtually any other workforce so long as certain parameters about the population can be determined.
ContributorsOtis, Matthew (Co-author) / Reyes, Katherine (Co-author) / Gel, Esma (Thesis director) / Jacobs, Tim (Committee member) / Clough, Michael (Committee member) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development of a physical distancing index based on three significant attributes. This index was then compared to the expenditure and case counts to support decision making.
A regression model was developed to analyze and compare how different states case counts played out against the regression model and the risk index.
ContributorsJaisinghani, Shaurya (Author) / Mirchandani, Pitu (Thesis director) / Clough, Michael (Committee member) / McCarville, Daniel R. (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Department of Information Systems (Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05