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.

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 thesis project has been conducted in accordance with The Founder’s Lab initiative which is sponsored by the W. P. Carey School of Business. This program groups three students together and tasks them with creating a business idea, conducting the necessary research to bring the concept to life, and exploring different aspects of business, with the end goal of gaining traction. The product we were given to work through this process with was Hot Head, an engineering capstone project concept. The Hot Head product is a sustainable and innovative solution to the water waste issue we find is very prominent in the United States. In order to bring the Hot Head idea to life, we were tasked with doing research on topics ranging from the Hot Head life cycle to finding plausible personas who may have an interest in the Hot Head product. This paper outlines the journey to gaining traction via a marketing campaign and exposure of our brand on several platforms, with a specific interest in website traffic. Our research scope comes from mainly primary sources like gathering opinions of potential buyers by sending out surveys and hosting focus groups. The paper concludes with some possible future steps that could be taken if this project were to be continued.