The research presented in this Honors Thesis provides development in machine learning models which predict future states of a system with unknown dynamics, based on observations of the system. Two case studies are presented for (1) a non-conservative pendulum and (2) a differential game dictating a two-car uncontrolled intersection scenario. In the paper we investigate how learning architectures can be manipulated for problem specific geometry. The result of this research provides that these problem specific models are valuable for accurate learning and predicting the dynamics of physics systems.<br/><br/>In order to properly model the physics of a real pendulum, modifications were made to a prior architecture which was sufficient in modeling an ideal pendulum. The necessary modifications to the previous network [13] were problem specific and not transferrable to all other non-conservative physics scenarios. The modified architecture successfully models real pendulum dynamics. This case study provides a basis for future research in augmenting the symplectic gradient of a Hamiltonian energy function to provide a generalized, non-conservative physics model.<br/><br/>A problem specific architecture was also utilized to create an accurate model for the two-car intersection case. The Costate Network proved to be an improvement from the previously used Value Network [17]. Note that this comparison is applied lightly due to slight implementation differences. The development of the Costate Network provides a basis for using characteristics to decompose functions and create a simplified learning problem.<br/><br/>This paper is successful in creating new opportunities to develop physics models, in which the sample cases should be used as a guide for modeling other real and pseudo physics. Although the focused models in this paper are not generalizable, it is important to note that these cases provide direction for future research.

High-entropy alloys possessing mechanical, chemical, and electrical properties that far exceed those of conventional alloys have the potential to make a significant impact on many areas of engineering. Identifying element combinations and configurations to form these alloys, however, is a difficult, time-consuming, computationally intensive task. Machine learning has revolutionized many different fields due to its ability to generalize well to different problems and produce computationally efficient, accurate predictions regarding the system of interest. In this thesis, we demonstrate the effectiveness of machine learning models applied to toy cases representative of simplified physics that are relevant to high-entropy alloy simulation. We show these models are effective at learning nonlinear dynamics for single and multi-particle cases and that more work is needed to accurately represent complex cases in which the system dynamics are chaotic. This thesis serves as a demonstration of the potential benefits of machine learning applied to high-entropy alloy simulations to generate fast, accurate predictions of nonlinear dynamics.

Over the past several decades, the incarceration rates have continued to rise in the United States with seemingly no end in sight. Many of the prisons within America are experiencing major overcrowding of incarcerated persons in addition to an ever expanding budget that seems impossible to adhere to. Qualitative and quantitative studies conclude that preventative and post release programs reduce crime rates and recidivism which saves taxpayer dollars. This paper addresses how much prisons cost, why this is important to the taxpayer, and possible solutions to make the penal system more efficient.

This thesis explores the potential for software to act as an educational experience for engineers who are learning system dynamics and controls. The specific focus is a spring-mass-damper system. First, a brief introduction of the spring-mass-damper system is given, followed by a review of the background and prior work concerning this topic. Then, the methodology and main approaches of the system are explained, as well as a more technical overview of the program. Lastly, a conclusion and discussion of potential future work is covered. The project was found to be useful by several engineers who tested it. While there is still plenty of functionality to add, it is a promising first attempt at teaching engineers through software development.

Water quality and accessibility can impact most aspects of life such as hygiene, medicine,<br/>thermal comfort, sewage disposal, and health, to name a few. Rising concerns related to the<br/>quality of drinking water in the United States caused by municipal water utility failures such as<br/>in Texas or in Michigan has led to an inquiry into the root cause of how a supply-chain for a<br/>basic necessity such as water can run into issues. After initial research and investigation, one<br/>hypothesis for this was the nature of how recyclable materials in a linear economy eventually run<br/>into production or storage problems as exhaustible resources (or space) become less accessible<br/>over time. To remedy this issue, LifeGear360 is introduced to allow individual users the liberty<br/>to treat their water directly if needed, while also remaining in a circular economy for the<br/>lifecycle of the product. As a backpack with water treatment capabilities, natural plant fibers are<br/>used to ensure a renewable cycle of production while also redefining the traditional<br/>“plastic-taste” characteristics many people associate with water pouches to a smoother, cleaner<br/>taste. Engineering, sustainability, and business and public service practice have been used in an<br/>interdisciplinary way to prepare this product for its intended use such as in school, for travel, and<br/>for the outdoors. According to the collected outreach, many indicated that they feel as though<br/>there is a need for a product that allows for the feeling of water security which can include<br/>carrying any personal belongings as well. Marketing strategies such as logo creating and online<br/>outreach continually influence product design, up until production would take place following<br/>the finalized design.

Dreadnought is a free-to-play multiplayer flight simulation in which two teams of 8 players each compete against one another to complete an objective. Each player controls a large-scale spaceship, various aspects of which can be customized to improve a player’s performance in a game. One such aspect is Officer Briefings, which are passive abilities that grant ships additional capabilities. Two of these Briefings, known as Retaliator and Get My Good Side, have strong synergy when used together, which has led to the Dreadnought community’s claiming that the Briefings are too powerful and should be rebalanced to be more in line with the power levels of other Briefings. This study collected gameplay data with and without the use of these specific Officer Briefings to determine the precise impact on gameplay. Linear correlation matrices and inference on two means were used to determine performance impact. It was found that, although these Officer Briefings do improve an individual player’s performance in a game, they do not have a consistent impact on the player’s team performance, and that these Officer Briefings are therefore not in need of rebalancing.

As temperatures increase across the United States, some populations are more at risk for heat-related death and illness than others. One of these at-risk demographics is mobile home and trailer park inhabitants, who are disproportionately represented among indoor heat-related deaths (Solís, “Heat, Health”). In this paper, we outline a cost-benefit analysis that was used to calculate the net present economic value of projects related to reducing heat burden on mobile home owners and parks in Maricopa County. We use this model to assess solutions developed by student teams under the Knowledge Exchange for Resilience’s Summer Heat Resilience Challenge. We find that one of the seven solutions has a positive net present value (NPV) even in the lowest effectiveness (10%), while three more solutions have a positive NPV in the mid-level (50%) effectiveness scenario, showcasing their economic viability.

This thesis project will be investigating the interactions and organizational theory within the student housing market at Arizona State University. The focus of the project will be around the partnership that makes up many of the communities, the public company known as American Campus Communities, and the auxiliary of Arizona State University Housing. The paper will analyze the organization through the four frames outlined by Bolman and Deal’s Reframing Organizations. These four are the structural, human resource, political, and symbolic frames. The paper will confront two main issues found in the organization. The first is the frequent turnover of staff. The second will be the separation between the departments, leading to unstable communication. Solutions will be proposed that could take some pressure off the problems that are identified. Compensation for staff and adjustments to summer living may allow retention to improve. Adjusted training and top-level management communication and interaction may improve the stark separation between areas of the organization. Analyzing these issues and solutions through the organizational frames allows us to better understand the reasoning behind and possible effects of any decision. This project has been very insightful, and I learned a lot with my studies and am proud to be a part of this organization and its mission to serve the students.

The threat of global climate change to the world’s water resources has jeopardized access to clean drinking water across the world and continues to devastate biodiversity and natural life globally. South Africa operates as a useful case study to understand and analyze the effectiveness of public policy responses to the perils of climate change on issues of water access and ecosystem preservation. After the new South African Constitution was enacted in 1997, protecting water resources and ensuring their equitable distribution across the nation’s population was a paramount goal of the young democratic government. The National Water Act was passed in 1998, nationalizing the country’s water infrastructure and putting in place programs seeking to ensure equitable distributive and environmental outcomes. Thus far, it has failed. Access to South Africa’s water resources is as stratified as access to its economy; its aquatic ecosystems remain in grave danger; and many of the same problems of South Africa’s Apartheid era still plague its efforts to create an equitable water system. Decision-making power continues to be concentrated in the hands of the wealthy, at the expense of historically marginalized groups, whose voices are still not adequately heard. Corporate actors still exert undue influence over legislative policy that favors economic growth over environmental sustainability. The looming threat of climate change is exponentially increasing the chances of disasters like Cape Town’s 2018 feared ‘Day Zero’. The National Water Act’s noble intentions were never actualized, and therefore the people of South Africa remain in serious danger of acute and chronic threats to their water supply.