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- Title
- Learning paradigms for the identification of elastic properties of composites using ultrasonic guided waves
- Creator
- Gopalakrishnan, Karthik
- Date
- 2020
- Collection
- Electronic Theses & Dissertations
- Description
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Identification of elastic properties of composites is relevant for both nondestructive materials characterization as well as for in-situ condition monitoring to assess and predict any possible material degradation. Learning paradigms have been well explored when it comes to detection and characterization of defects in safety-critical structures, but are relatively unexplored when it comes to structural materials characterization. In this thesis we propose a learning paradigm that includes the...
Show moreIdentification of elastic properties of composites is relevant for both nondestructive materials characterization as well as for in-situ condition monitoring to assess and predict any possible material degradation. Learning paradigms have been well explored when it comes to detection and characterization of defects in safety-critical structures, but are relatively unexplored when it comes to structural materials characterization. In this thesis we propose a learning paradigm that includes the potential use of Machine Learning (ML) and Deep Learning (DL) algorithms to solve the inverse problem of material properties identification using ultrasonic guided waves. The propagation of guided waves in a composite laminate is modelled using two different modelling techniques as part of the forward problem. Here, we use the two fundamental modes of guided waves, i.e. the anti-symmetric (A0) and the symmetric modes (S0) as features for the proposed learning models. As part of the inverse problem, different learning models are used to map feature space to target space that consists of the material properties of composites. The performance of the algorithms is evaluated based on different metrics and it is seen that the networks are able to learn the mapping and generalize well to unseen examples even in the presence of noise at various levels. Overall, we are able to develop a complete framework consisting of many interlinking data processing algorithms that can effectively estimate and predict the material properties of any given composite.
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- Title
- SOCIAL MECHANISMS OF LEADERSHIP EMERGENCE : A COMPUTATIONAL EVALUATION OF LEADERSHIP NETWORK STRUCTURES
- Creator
- Griffin, Daniel Jacob
- Date
- 2020
- Collection
- Electronic Theses & Dissertations
- Description
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Leadership emergence is a topic of immense interest in the organizational sciences. One promising recent development in the leadership literature focuses on the development and impact of informal leadership structures in a share leadership paradigm. Despite its theoretical importance, the network perspective of leadership emergence is still underdeveloped, largely due to the complexity of studying and theorizing about network-level phenomena. Using computational modeling techniques, I...
Show moreLeadership emergence is a topic of immense interest in the organizational sciences. One promising recent development in the leadership literature focuses on the development and impact of informal leadership structures in a share leadership paradigm. Despite its theoretical importance, the network perspective of leadership emergence is still underdeveloped, largely due to the complexity of studying and theorizing about network-level phenomena. Using computational modeling techniques, I evaluate the network-level implications of two existing theories that broadly represent social theories of leadership emergence. I derive formal representations for both foundational theories and expand on this theory to develop a synthesis theory describing how these two processes work in parallel. Results from simulated experiments indicate that group homogeneity is associated with vastly different leadership network structures depending on which theoretical process mechanisms are in play. This thesis contributes significantly to the literature by 1) advancing a network-based approach to leadership emergence research, 2) testing the implications of existing theory, 3) developing new theory, and 4) providing a strong foundation and tool kit for future leadership network emergence research.
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- Title
- AN EVOLUTIONARY MULTI-OBJECTIVE APPROACH TO SUSTAINABLE AGRICULTURAL WATER AND NUTRIENT OPTIMIZATION
- Creator
- Kropp, Ian Meyer
- Date
- 2018
- Collection
- Electronic Theses & Dissertations
- Description
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One of the main problems that society is facing in the 21st century is that agricultural production must keep pace with a rapidly increasing global population in an environmentally sustainable manner. One of the solutions to this global problem is a system approach through the application of optimization techniques to manage farm operations. However, unlike existing agricultural optimization research, this work seeks to optimize multiple agricultural objectives at once via multi-objective...
Show moreOne of the main problems that society is facing in the 21st century is that agricultural production must keep pace with a rapidly increasing global population in an environmentally sustainable manner. One of the solutions to this global problem is a system approach through the application of optimization techniques to manage farm operations. However, unlike existing agricultural optimization research, this work seeks to optimize multiple agricultural objectives at once via multi-objective optimization techniques. Specifically, the algorithm Unified Non-dominated Sorting Genetic Algorithm-III (U-NSGA-III) searched for irrigation and nutrient management practices that minimized combinations of environmental objectives (e.g., total irrigation applied, total nitrogen leached) while maximizing crop yield for maize. During optimization, the crop model named the Decision Support System for Agrotechnology Transfer (DSSAT) calculated the yield and nitrogen leaching for each given management practices. This study also developed a novel bi-level optimization framework to improve the performance of the optimization algorithm, employing U-NSGA-III on the upper level and Monte Carlo optimization on the lower level. The multi-objective optimization framework resulted in groups of equally optimal solutions that each offered a unique trade-off among the objectives. As a result, producers can choose the one that best addresses their needs among these groups of solutions, known as Pareto fronts. In addition, the bi-level optimization framework further improved the number, performance, and diversity of solutions within the Pareto fronts.
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- Title
- Energy Conservation in Heterogeneous Smartphone Ad Hoc Networks
- Creator
- Mariani, James
- Date
- 2018
- Collection
- Electronic Theses & Dissertations
- Description
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In recent years mobile computing has been rapidly expanding to the point that there are now more devices than there are people. While once it was common for every household to have one PC, it is now common for every person to have a mobile device. With the increased use of smartphone devices, there has also been an increase in the need for mobile ad hoc networks, in which phones connect directly to each other without the need for an intermediate router. Most modern smart phones are equipped...
Show moreIn recent years mobile computing has been rapidly expanding to the point that there are now more devices than there are people. While once it was common for every household to have one PC, it is now common for every person to have a mobile device. With the increased use of smartphone devices, there has also been an increase in the need for mobile ad hoc networks, in which phones connect directly to each other without the need for an intermediate router. Most modern smart phones are equipped with both Bluetooth and Wifi Direct, where Wifi Direct has a better transmission range and rate and Bluetooth is more energy efficient. However only one or the other is used in a smartphone ad hoc network. We propose a Heterogeneous Smartphone Ad Hoc Network, HSNet, a framework to enable the automatic switching between Wifi Direct and Bluetooth to emphasize minimizing energy consumption while still maintaining an efficient network. We develop an application to evaluate the HSNet framework which shows significant energy savings when utilizing our switching algorithm to send messages by a less energy intensive technology in situations where energy conservation is desired. We discuss additional features of HSNet such as load balancing to help increase the lifetime of the network by more evenly distributing slave nodes among connected master nodes. Finally, we show that the throughput of our system is not affected due to technology switching for most scenarios. Future work of this project includes exploring energy efficient routing as well as simulation/scale testing for larger and more diverse smartphone ad hoc networks.
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