The purpose of this project was to develop a system capable of launching projectiles at a curved trajectory. This system effectively imparts spin on projectiles, enabling controlled indirect fire for the intended use of military operations. Through this proof of concept, it was determined whether a scaled system would be a viable solution to the issue of controlled indirect fire in dense urban areas. Using a series of coaxial motors with independently controlled speeds, it was possible to alter the horizontal and vertical displacement of objects in flight.

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 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.

As a result of the increase of pollution related to industrialization in Vietnam, acid rain has become a prevalent issue for Vietnamese farmers who are forced to rinse their crops – risking damage due to overwatering and poor harvest. Thus, the team was motivated to develop a solution to harmful impacts of acidic rainwater by creating a system with the ability to capture rainwater and determine its level of acidity in order to optimize the crop watering process, and promote productive crops. By conducting preliminary research on rainfall and tropical climate in Vietnam, existing products on the market, and pH sensors for monitoring and device material, the team was able to design a number of devices to collect, store, and measure the pH of rainwater. After developing a number of initial design requirements based on the needs of the farmers, a final prototype was developed using the best aspects of each initial design. Tests were conducted with varying structural and aqueous materials to represent a broad range of environmental conditions. While the scope of the project was ultimately limited to prototyping purposes, the principles explored throughout this thesis project can successfully be applied to a fully-functioning production model available for commercial use on Vietnamese farms. Given more time for development, improvements would be made in the extent of materials tested, and the configuration of electronics and data acquisition, in order to further optimize the process of determining rainwater acidity.

As a result of the increase of pollution related to industrialization in Vietnam, acid rain has become a prevalent issue for Vietnamese farmers who are forced to rinse their crops – risking damage due to overwatering and poor harvest. Thus, the team was motivated to develop a solution to harmful impacts of acidic rainwater by creating a system with the ability to capture rainwater and determine its level of acidity in order to optimize the crop watering process, and promote productive crops. By conducting preliminary research on rainfall and tropical climate in Vietnam, existing products on the market, and pH sensors for monitoring and device material, the team was able to design a number of devices to collect, store, and measure the pH of rainwater. After developing a number of initial design requirements based on the needs of the farmers, a final prototype was developed using the best aspects of each initial design. Tests were conducted with varying structural and aqueous materials to represent a broad range of environmental conditions. While the scope of the project was ultimately limited to prototyping purposes, the principles explored throughout this thesis project can successfully be applied to a fully-functioning production model available for commercial use on Vietnamese farms. Given more time for development, improvements would be made in the extent of materials tested, and the configuration of electronics and data acquisition, in order to further optimize the process of determining rainwater acidity.