To understand the role communication and effective management play in the project management field, virtual work was analyzed in two phases. Phase one consisted of gaining familiarity within the field of project management by interviewing three project managers who discussed their field of work, how it has changed due to Covid-19, approaches to communication and virtual team management, and strategies that allow for effective project management. Phase two comprised a simulation in which 8 ASU student volunteers were put into scenarios that required completing and executing a given project. Students gained project experience through the simulation and had an opportunity to reflect on their project experience.

Currently, autonomous vehicles are being evaluated by how well they interact with humans without evaluating how well humans interact with them. Since people are not going to unanimously switch over to using autonomous vehicles, attention must be given to how well these new vehicles signal intent to human drivers from the driver’s point of view. Ineffective communication will lead to unnecessary discomfort among drivers caused by an underlying uncertainty about what an autonomous vehicle is or isn’t about to do. Recent studies suggest that humans tend to fixate on areas of higher uncertainty so scenarios that have a higher number of vehicle fixations can be reasoned to be more uncertain. We provide a framework for measuring human uncertainty and use the framework to measure the effect of empathetic vs non-empathetic agents. We used a simulated driving environment to create recorded scenarios and manipulate the autonomous vehicle to include either an empathetic or non-empathetic agent. The driving interaction is composed of two vehicles approaching an uncontrolled intersection. These scenarios were played to twelve participants while their gaze was recorded to track what the participants were fixating on. The overall intent was to provide an analytical framework as a tool for evaluating autonomous driving features; and in this case, we choose to evaluate how effective it was for vehicles to have empathetic behaviors included in the autonomous vehicle decision making. A t-test analysis of the gaze indicated that empathy did not in fact reduce uncertainty although additional testing of this hypothesis will be needed due to the small sample size.

A novel CFD algorithm called LEAP is currently being developed by the Kasbaoui Research Group (KRG) using the Immersed Boundary Method (IBM) to describe complex geometries. To validate the algorithm, this research project focused on testing the algorithm in three dimensions by simulating a sphere placed in a moving fluid. The simulation results were compared against the experimentally derived Schiller-Naumann Correlation. Over the course of 36 trials, various spatial and temporal resolutions were tested at specific Reynolds numbers between 10 and 300. It was observed that numerical errors decreased with increasing spatial and temporal resolution. This result was expected as increased resolution should give results closer to experimental values. Having shown the accuracy and robustness of this method, KRG will continue to develop this algorithm to explore more complex geometries such as aircraft engines or human lungs.

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.

Covid-19 is unlike any coronavirus we have seen before, characterized mostly by the ease with which it spreads. This analysis utilizes an SEIR model built to accommodate various populations to understand how different testing and infection rates may affect hospitalization and death. This analysis finds that infection rates have a significant impact on Covid-19 impact regardless of the population whereas the impact that testing rates have in this simulation is not as pronounced. Thus, policy-makers should focus on decreasing infection rates through targeted lockdowns and vaccine rollout to contain the virus, and decrease its spread.

This thesis presents the design and simulation of an energy efficient controller for a system of three drones transporting a payload in a net. The object ensnared in the net is represented as a mass connected by massless stiff springs to each drone. Both a pole-placement approach and an optimal control approach are used to design a trajectory controller for the system. Results are simulated for a single drone and the three drone system both without and with payload.

Most asteroids originated in larger parent bodies that underwent accretion and heating during the first few million years of the solar system. We investigated the parent body of S-type asteroid 25143 Itokawa by developing a computational model which can approximate the thermal evolution of an early solar system body. We compared known constraints on Itokawa’s thermal history to simulations of its parent body and constrained its time of formation to between 1.6 and 2.5 million years after the beginning of the solar system, though certain details could allow for even earlier or later formation. These results stress the importance of precise data required of the material properties of asteroids and meteorites to place better constraints on the histories of their parent bodies. Additional mathematical and computational details are discussed, and the full code and data is made available online.

NASA has partnered with multiple colleges, including ASU, on a mission to study an asteroid called Psyche. Psyche is the first asteroid discovered made of metal, mostly iron, that is close enough for us to study and could give insight into what Earth’s core is like. The mission plans and research documents on how the various measurement tools work are not engaging to those without a background in STEM. This serves as inspiration to make a web-based game in order to make the information more engaging to the player. This web-based game will take the user through the Psyche mission going from the assembly of the measurement tools all the way to when the satellite is orbiting the asteroid. The creative project consisted of creating a simulation for a young audience, between ages 10 and 18, to experience what the mission could look like once the satellite is at the Psyche asteroid and what the data collected could mean. The asteroid could have been formed through a process called the dynamo process or it could be a piece of a larger parent body. It could be made mostly of metal or silicates, which will be determined during the mission. These are some of the results that will be generalized and relayed to the player. This creative project includes the four main sections of the orbit phase of the mission in which the users will perform tasks to collect some data in order to see some of the generalized possible results of the study of Psyche. Some of the data collected would be the amount of metal making up the asteroid and figuring out what the gravitational pull is. The first main section will use the magnetometer, the second section will use the multispectral imager, the third section will use X-Band Radio Waves, and the fourth section will use the gamma ray and neutron spectrometer.