Matching Items (38)
Filtering by
- All Subjects: engineering
- Creators: Engineering Programs
- Creators: Electrical Engineering Program
- Member of: Theses and Dissertations
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
Description
This dissertation treats a number of related problems in control and data analysis of complex networks.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
ContributorsWang, Lezhi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Papandreoou-Suppappola, Antonia (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
The field of robotics is rapidly expanding, and with it, the methods of teaching and introducing students must also advance alongside new technologies. There is a challenge in robotics education, especially at high school levels, to expose them to more modern and practical robots. One way to bridge this gap is human-robot interaction for a more hands-on and impactful experience that will leave students more interested in pursuing the field. Our project is a Robotic Head Kit that can be used in an educational setting to teach about its electrical, mechanical, programming, and psychological concepts. We took an existing robot head prototype and further advanced it so it can be easily assembled while still maintaining human complexity. Our research for this project dove into the electronics, mechanics, software, and even psychological barriers present in order to advance the already existing head design. The kit we have developed combines the field of robotics with psychology to create and add more life-like features and functionality to the robot, nicknamed "James Junior." The goal of our Honors Thesis was to initially fix electrical, mechanical, and software problems present. We were then tasked to run tests with high school students to validate our assembly instructions while gathering their observations and feedback about the robot's programmed reactions and emotions. The electrical problems were solved with custom PCBs designed to power and program the existing servo motors on the head. A new set of assembly instructions were written and modifications to the 3D printed parts were made for the kit. In software, existing code was improved to implement a user interface via keypad and joystick to give students control of the robot head they construct themselves. The results of our tests showed that we were not only successful in creating an intuitive robot head kit that could be easily assembled by high school students, but we were also successful in programming human-like expressions that could be emotionally perceived by the students.
ContributorsRathke, Benjamin (Co-author) / Rivera, Gerardo (Co-author) / Sodemann, Angela (Thesis director) / Itagi, Manjunath (Committee member) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The Phoenix CubeSat is a 3U Earth imaging CubeSat which will take infrared (IR) photos of cities in the United Stated to study the Urban Heat Island Effect, (UHI) from low earth orbit (LEO). It has many different components that need to be powered during the life of its mission. The only power source during the mission will be its solar panels. It is difficult to calculate power generation from solar panels by hand because of the different orientations the satellite will be positioned in during orbit; therefore, simulation will be used to produce power generation data. Knowing how much power is generated is integral to balancing the power budget, confirming whether there is enough power for all the components, and knowing whether there will be enough power in the batteries during eclipse. This data will be used to create an optimal design for the Phoenix CubeSat to accomplish its mission.
ContributorsBarakat, Raymond John (Author) / White, Daniel (Thesis director) / Kitchen, Jennifer (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Current technology does not allow for the full amount of power produced by solar arrays (PV) on spacecraft to be utilized. The arrays are designed with non-reconfigurable architectures and sent on fifteen to twenty year long missions. They cannot be changed once they are in space, so the arrays are designed for the end of life. Throughout their lifetime, solar arrays can degrade in power producing capabilities anywhere from 20% to 50%. Because there is such a drastic difference in the beginning and end of life power production, and because they cannot be reconfigured, a new design has been found necessary in order to increase power production. Reconfiguration allows the solar arrays to achieve maximum power producing capabilities at both the beginning and end of their lives. With the potential to increase power production by 50%, the reconfiguration design consists of a switching network to be able to utilize any combination of cells. The design for reconfiguration must meet the power requirements of the solar array. This thesis will explore different designs for reconfiguration, as well as possible switches for implementation. It will also review other methods to increase power production, as well as discuss future work in this field.
ContributorsJohnson, Everett Hope (Author) / Kitchen, Jennifer (Thesis director) / Ozev, Sule (Committee member) / School of International Letters and Cultures (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In this paper, we propose an autonomous throwing and catching system to be developed as a preliminary step towards the refinement of a robotic arm capable of improving strength and motor function in the limb. This will be accomplished by first autonomizing simpler movements, such as throwing a ball. In this system, an autonomous thrower will detect a desired target through the use of image processing. The launch angle and direction necessary to hit the target will then be calculated, followed by the launching of the ball. The smart catcher will then detect the ball as it is in the air, calculate its expected landing location based on its initial trajectory, and adjust its position so that the ball lands in the center of the target. The thrower will then proceed to compare the actual landing position with the position where it expected the ball to land, and adjust its calculations accordingly for the next throw. By utilizing this method of feedback, the throwing arm will be able to automatically correct itself. This means that the thrower will ideally be able to hit the target exactly in the center within a few throws, regardless of any additional uncertainty in the system. This project will focus of the controller and image processing components necessary for the autonomous throwing arm to be able to detect the position of the target at which it will be aiming, and for the smart catcher to be able to detect the position of the projectile and estimate its final landing position by tracking its current trajectory.
ContributorsLundberg, Kathie Joy (Co-author) / Thart, Amanda (Co-author) / Rodriguez, Armando (Thesis director) / Berman, Spring (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This project examines the science of electric field sensing and completes experiments, gathering data to support its utility for various applications. The basic system consists of a transmitter, receiver, and lock-in amplifier. The primary goal of the study was to determine if such a system could detect a human disturbance, due to the capacitance of a human body, and such a thesis was supported. Much different results were obtained when a person disturbed the electric field transmitted by the system than when other types of objects, such as chairs and electronic devices, were placed in the field. In fact, there was a distinct difference between persons of varied sizes as well. This thesis goes through the basic design of the system and the process of experimental design for determining the capabilities of such an electric field sensing system.
ContributorsBranham, Breana Michelle (Author) / Allee, David (Thesis director) / Papandreou-Suppappola, Antonia (Committee member) / Phillips, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor) / School of International Letters and Cultures (Contributor)
Created2013-05
Description
A hybrid PV/T module was built, consisting of a thermal liquid heating system and a photovoltaic module system that combine in a hybrid format. This report will discuss the work on the project from Fall 2012 to Spring 2013 and the extended section on the economics for the Honors Thesis. Three stages of experiments were completed. Stage 1 showed our project was functional as we were able to verify our panel produced electricity and increased the temperature of water flowing in the system by 0.65°C. Stage 2 testing included “gluing” the flow system to the back of the panel resulting in an average increase of 4.76°C in the temperature of the water in the system. Stage 3 testing included adding insulating foam to the module which resulted in increasing the average temperature of the water in our flow system by 6.95°C. The economic calculations show the expected energy cost savings for Arizona residents.
ContributorsHaines, Brent Robert (Author) / Roedel, Ronald (Thesis director) / Aberle, James (Committee member) / Rauch, Dawson (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2013-05
Description
The field of soft robotics is a very quickly growing field that has yet to be fully explored or implemented in all of the possible applications. Soft robotics shows the greatest degree of possibility for mimicking biological systems effectively and accurately. This study seeks to set the groundwork for the development of a biomimetic nautilus using soft robotic methods. The study shows background research and discusses the methods used to develop a nautilus themed sub aquatic robot that uses a double bladder system and a pump to generate thrust for movement. The study shows how the unit would be fabricated and constructed. The study also explores why the second stage of the design failed and how it could potentially be fixed in future iterations.
ContributorsCarlson, Caleb Elijah (Author) / Polygerinos, Panagiotis (Thesis director) / Parsey, John (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The goal of our research was to develop and validate a method for predicting the mechanical behavior of Additively Manufactured multi-material honeycomb structures. Multiple approaches already exist in the field for modeling the behavior of cellular materials, including the bulk property assumption, homogenization and strut level characterization [1]. With the bulk property approach, the structure is assumed to behave according to what is known about the material in its bulk formulation, without regard to its geometry or scale. With the homogenization technique, the specimen that is being tested is treated as a solid material within the simulation environment even if the physical specimen is not. Then, reduced mechanical properties are assigned to the specimen to account for any voids that exist within the physical specimen. This approach to mechanical behavior prediction in cellular materials is shape dependent. In other words, the same model cannot be used from one specimen to the next if the cell shapes of those lattices differ in any way. When using the strut level characterization approach, a single strut (the connecting member between nodes constituting a cellular material) is isolated and tested. With this approach, there tends to be a significant deviation in the experimental data due to the small size of the isolated struts. Yet it has the advantage of not being shape sensitive, at least in principle. The method that we developed, and chose to test lies within the latter category, and is what we have coined as the Representative Lattice Element (RLE) Method. This method is modeled after the well-established Representative Volume Element (RVE) method [2]. We define the RLE as the smallest unit over which mechanical tests can be conducted that will provide results which are representative of the larger lattice structure. In other words, the theory is that a single member (or beam in this case) of a honeycomb structure can be taken, tests can be conducted on this member to determine the mechanical properties of the representative lattice element and the results will be representative of the mechanical behavior whole structure. To investigate this theory, we designed specimens, conducted various tensile and compression tests, analyzed the recorded data, conducted a micromechanics study, and performed structural simulation work using commercial Finite Element Analysis software.
ContributorsSalti, Ziyad Zuheir (Co-author) / Eppley, Trevor (Co-author) / Bhate, Dhruv (Thesis director) / Song, Kenan (Committee member) / Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05