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.

This work describes the numerical process developed for use of rocket engine nozzle ejectors. Ejector nozzles, while applied to jet engines extensively, have not been applied to rockets, and have great potential to improve the performance of endoatmospheric rocket propulsion systems. Utilizing the low pressure, high velocity flow in the plume, this secondary structure entrains a secondary mass flow to increase the mass flow of the propulsion system. Rocket engine nozzle ejectors must be designed with the high supersonic conditions associated with rocket engines. These designs rely on the numerical process described in this paper.

The main field of study research through this project is to study the effect of history of deformation in materials subjected to complex loading, useful for producing lightweight alloys and composites optimized for absorbing shock and impact. This is accomplished by creating a digital model of a system in which the material undergoes tension and compression through colliding bars. The results show that the system generated is accurate when compared to real tests, so the program used to create the model can be used in the future for simulated tests using different materials or applied loads.

This study aims to showcase the results of a quadrotor model and the mathematical techniques used to arrive at the proposed design. Multicopters have made an explosive appearance in recent years by the controls engineering community because of their unique flight performance capabilities and potential for autonomy. The ultimate goal of this research is to design a robust control system that guides and tracks the quadrotor's trajectory, while responding to outside disturbances and obstacles that will realistically be encountered during flight. The first step is to accurately identify the physical system and attempt to replicate its behavior with a simulation that mimics the system's dynamics. This becomes quite a complex problem in itself because many realistic systems do not abide by simple, linear mathematical models, but rather nonlinear equations that are difficult to predict and are often numerically unstable. This paper explores the equations and assumptions used to create a model that attempts to match roll and pitch data collected from multiple test flights. This is done primarily in the frequency domain to match natural frequency locations, which can then be manipulated judiciously by altering certain parameters.

As society's energy crisis continues to become more imminent many industries and niches are seeking a new, sustainable and renewable source of electricity production. Similar to solar, wind and tidal energy, kinetic energy has the potential to generate electricity as an extremely renewable source of energy generation. While stationary bicycles can generate small amounts of electricity, the idea behind this project was to expand energy generation into the more common weight lifting side of exercising. The method for solving this problem was to find the average amount of power generated per user on a Smith machine and determine how much power was available from an accompanying energy generator. The generator consists of three phases: a copper coil and magnet generator, a full wave bridge rectifying circuit and a rheostat. These three phases working together formed a fully functioning controllable generator. The resulting issue with the kinetic energy generator was that the system was too inefficient to serve as a viable system for electricity generation. The electrical production of the generator only saved about 2 cents per year based on current Arizona electricity rates. In the end it was determined that the project was not a sustainable energy generation system and did not warrant further experimentation.

The purpose of this investigation is to computationally investigate instabilities appearing in the wake of a simulated helicopter rotor. Existing data suggests further understanding of these instabilities may yield design changes to the rotor blades to reduce the acoustic signature and improve the aerodynamic efficiencies of the aircraft. Test cases of a double-bladed and single-bladed rotor have been run to investigate the causes and types of wake instabilities, as well as compare them to the short wave, long wave, and mutual inductance modes proposed by Widnall[2]. Evaluation of results revealed several perturbations appearing in both single and double-bladed wakes, the origin of which was unknown and difficult to trace. This made the computations not directly comparable to theoretical results, and drawing into question the physical flight conditions being modeled. Nonetheless, they displayed a wake structure highly sensitive to both computational and physical disturbances; thus extreme care must be taken in constructing grids and applying boundary conditions when doing wake computations to ensure results relevant to the complex and dynamic flight conditions of physical aircraft are generated.

The experimental assessment of cracking distresses in asphalt concrete pavements is crucial to the longevity of pavements. As such, fracture parameters obtained from experiments play a key role in facilitating the use of fracture mechanics theories and prediction of cracking distresses in asphalt concrete (AC) pavements. The stress intensity factor (SIF) is among the fracture parameters derived from fracture mechanics theory. Many fracture mechanics based laboratory tests have been developed with the goal of calculating such key fracture parameters. The C* Fracture test is unique among them because it incorporates rate dependent loading into the calculation of fracture parameters via the theory of the C* Line integral. However, unlike other laboratory fracture tests, the C* Fracture test does not have any analytical solution or previous sources from literature which describe geometric shape factors used in the calculation of SIFs. Numerical modeling of the C* Fracture test specimen is also limited in literature. Therefore, there is a need for a high-fidelity numerical model of this fracture test in order to develop SIF functions. In this thesis, the numerical models of the C* Fracture test were developed using the Generalized Finite Element Method (GFEM). GFEM is particularly effective at modeling problems with discontinuities in complex 3-D structures. The use of the GFEM to solve this problem allows a high-fidelity numerical model to be created without a large computational cost and labor intensive mesh crafting. After verifying the model accuracy using convergence analysis, the specimen geometry was modeled by changing the crack size. A SIF function was developed that includes a specific geometry dependent shape factor for the C* Fracture test based on Linear Elastic Fracture Mechanics (LEFM).

At the beginning of 2020, a global pandemic had left leadership at the large, aerospace conglomerate Raytheon Technologies with a drastic reduction in sales, creating conflicting desires between dissatisfied employees and investors. Unique challenges, such as a pandemic, have been shown to be effectively addressed by leaders using the “reframing” technique. This thesis demonstrates the process of reframing and its ability to reveal additional solutions that Raytheon Technologies leadership should have implemented when there was a drastic drop in company profit. The process of reframing is changing the perspective of a situation, using four different frames: structural, symbolic, human resource, and political. The reframing method uncovers how Raytheon Technologies could have most effectively addressed the needs of the employee, as well as the company, in the context of the COVID pandemic. The well-being of the employees would have been better supported financially and emotionally if Raytheon had used the four framing techniques to approach the company's financial health and better communicated to improve the emotional welfare of the employees. This thesis analyzes the situation of leadership fighting for a company’s survival, while thousands of employees were scared for their job security through each frame to reveal the additional solutions. After analyzing the situation through each frame, the human resource and political frames would be the most impactful for improving employee morale, while reducing overhead. From the human resource frame, increasing the content and frequency of communication between leadership and employees would reduce anxiety caused by uncertainty. The political frame offers ideas for reallocation of resources while avoiding layoffs. The reframing technique is an adaptable model that can be applied by leadership to assess any problem. Each frame has its assumptions and limitations, and leadership’s success is dependent on their ability to choose the proper frames.

The purpose of this project is to assess how well today’s youth is able to learn new skills<br/>in the realm of engineering through online video-conferencing resources. Each semester of this<br/>last year, a class of students in both 3rd and 6th grade learned about computer-aided design (CAD)<br/>and 3D printing through their laptops at school. This was done by conducting online lessons of<br/>TinkerCAD via Zoom and Google Meet. TinkerCAD is a simple website that incorporates easy-to-learn skills and gives students an introduction to some of the basic operations that are used in<br/>everyday CAD endeavors. In each lesson, the students would learn new skills by creating<br/>increasingly difficult objects that would test both their ability to learn new skills and their overall<br/>enjoyment with the subject matter. The findings of this project reflect that students are able to<br/>quickly learn and retain new information relating to CAD. The group of 6th graders was able to<br/>learn much faster, which was expected, but the class of 3rd graders still maintained the<br/>knowledge gained from previous lessons and were able to construct increasingly complicated<br/>objects without much struggle. Overall, the students in both classes enjoyed the lessons and did<br/>not find them too difficult, despite the online environment that we were required to use. Some<br/>students found the material more interesting than others, but in general, the students found it<br/>enjoyable to learn about a new skill that has significant real-world applications