This thesis proposes hardware and software security enhancements to the robotic explorer of a capstone team, in collaboration with the NASA Psyche Mission Student Collaborations program. The NASA Psyche Mission, launching in 2022 and reaching the metallic asteroid of the same name in 2026, will explore from orbit what is hypothesized to be remnant core material of an early planet, potentially providing key insights to planet formation. Following this initial mission, it is possible there would be scientists and engineers interested in proposing a mission to land an explorer on the surface of Psyche to further document various properties of the asteroid. As a proposal for a second mission, an interdisciplinary engineering and science capstone team at Arizona State University designed and constructed a robotic explorer for the hypothesized surfaces of Psyche, capable of semi-autonomously navigating simulated surfaces to collect scientific data from onboard sensors. A critical component of this explorer is the command and data handling subsystem, and as such, the security of this system, though outside the scope of the capstone project, remains a crucial consideration. This thesis proposes the pairing of Trusted Platform Module (TPM) technology for increased hardware security and the implementation of SELinux (Security Enhanced Linux) for increased software security for Earth-based testing as well as space-ready missions.

Automated vehicles are becoming more prevalent in the modern world. Using platoons of automated vehicles can have numerous benefits including increasing the safety of drivers as well as streamlining roadway operations. How individual automated vehicles within a platoon react to each other is essential to creating an efficient method of travel. This paper looks at two individual vehicles forming a platoon and tracks the time headway between the two. Several speed profiles are explored for the following vehicle including a triangular and trapezoidal speed profile. It is discovered that a safety violation occurs during platoon formation where the desired time headway between the vehicles is violated. The aim of this research is to explore if this violation can be eliminated or reduced through utilization of different speed profiles.

For this Creative Project, I decided to explore the elements that set novellas apart from other genres and then experiment writing in the form. In doing so, I took into account three main categories: Plot Structure, Character Development, Style/Format, and then used my findings to write 45 pages of a novella titled Emmy and Me.

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.

Self-efficacy in engineering, engineering identity, and coping in engineering have been shown in previous studies to be highly important in the advancement of one’s development in the field of engineering. Through the creation and deployment of a 17 question survey, undergraduate and first year masters students were asked to provide information on their engagement at their university, their demographic information, and to rank their level of agreement with 22 statements relating to the aforementioned ideas. Using the results from the collected data, exploratory factor analysis was completed to identify the factors that existed and any correlations. No statistically significant correlations between the identified three factors and demographic or engagement information were found. There needs to be a significant increase in the data sample size for statistically significant results to be found. Additionally, there is future work needed in the creation of an engagement measure that successfully reflects the level and impact of participation in engineering activities beyond traditional coursework.

My project is designed to provide art education to incarcerated youth in Arizona. This project will address two current issues in Arizona; the underfunding of art programs and high rates of incarceration. As of 2021, there are no state-funded art programs in Arizona. Arizona is tied with Texas for the eighth highest rate of incarceration in the country. In Arizona, 750 out of every 100,000 people are incarcerated. This project is an art course for incarcerated youth. The project includes a packet detailing the course content and assignment details, a class syllabus, a course flyer, and a certificate of completion. The course is intended to be taught at the Adobe Mountain School facility. The course is designed so that it can be implemented in other facilities in the future. The class will be taught by volunteers with a background in studio art, design, or art education. Each student will receive a course packet that they can use to keep track of information and assignments. Instructors will use the course packet to teach the class. The course focuses on drawing with charcoal and oil pastel, which will build a foundation in drawing skills. The course covers a twelve-week semester. The course content packet includes a week-by-week breakdown of the teaching material and project descriptions. The course consists of two main projects and preparatory work. The preparatory work includes vocabulary terms, art concepts, drawing guides, brainstorming activities, and drawing activities. The two main prompts are designed for students to explore the materials and to encourage self-reflection. The class is curated so that students can create art in a low-risk, non-judgemental environment. The course will also focus on establishing problem-solving and critical thinking skills through engaging activities.

The colossal global counterfeit market and advances in cryptography including quantum computing supremacy have led the drive for a class of anti-counterfeit tags that are physically unclonable. Dendrites, previously considered an undesirable side effect of battery operation, have promise as an extremely versatile version of such tags, with their fundamental nature ensuring that no two dendrites are alike and that they can be read at multiple magnification scales. In this work, we first pursue a simulation for electrochemical dendrites that elucidates fundamental information about their growth mechanism. We then translate these results into physical dendrites and demonstrate methods of producing a hash from these dendrites that is damage-tolerant for real-world verification. Finally, we explore theoretical curiosities that arise from the fractal nature of dendrites. We find that uniquely ramified dendrites, which rely on lower ion mobility and conductive deposition, are particularly amenable to wavelet hashing, and demonstrate that these dendrites have strong commercial potential for securing supply chains at the highest level while maintaining a low price point.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde River Watershed. This Story Map is intended for an audience of students in late middle school and early high school but can be a resource to teachers for a wider age range. The integration of interactive technology and virtual tools in educational practices is likely to continue past the immediate circumstances of the COVID-19 pandemic. The purpose of this Story Map is to showcase one of the many uses for geospatial web applications beyond the immediate realm of GIS.