Our Idea: As a team of engineers, two in the engineering field and one in computer science and software development, we wanted to find a way to put these skills to use in our company. As we did not have a revolutionary idea to build our own product, we wanted to base our company on the assumption that people have great ideas and lack the ability to execute on these ideas. Our mission is to enable these people and companies to make their ideas a reality, and allow them to go to market with a clean and user friendly product. We are using our skills and experience in hardware and device prototyping and testing, as well as software design and development to make this happen. Implementation: To this point, we have been working with a client building a human diagnostic and enhancement AI device. We have been consulting on mostly the design and creation of their first proof of concept, working on hardware and sensor interaction as well as developing the software allowing their platform to come to life. We have been working closely with the leaders of the company, who have the ideas and business knowledge, while we focus on the technology side. As for the scalability and market potential of our business, we believe that the potential market is not the limiting factor. Instead, the limiting factor to the growth of our business is the time we have to devote. We are currently only working with one client, and not looking to expand into new clients. We believe this would require the addition of new team members, but instead we are happy with the progress we are making at the moment. We believe we are not only building equity in business we believe in, but also building a product that could help the safety and wellness of our users.

Our Idea: As a team of engineers, two in the engineering field and one in computer science and software development, we wanted to find a way to put these skills to use in our company. As we did not have a revolutionary idea to build our own product, we wanted to base our company on the assumption that people have great ideas and lack the ability to execute on these ideas. Our mission is to enable these people and companies to make their ideas a reality, and allow them to go to market with a clean and user friendly product. We are using our skills and experience in hardware and device prototyping and testing, as well as software design and development to make this happen. Implementation: To this point, we have been working with a client building a human diagnostic and enhancement AI device. We have been consulting on mostly the design and creation of their first proof of concept, working on hardware and sensor interaction as well as developing the software allowing their platform to come to life. We have been working closely with the leaders of the company, who have the ideas and business knowledge, while we focus on the technology side. As for the scalability and market potential of our business, we believe that the potential market is not the limiting factor. Instead, the limiting factor to the growth of our business is the time we have to devote. We are currently only working with one client, and not looking to expand into new clients. We believe this would require the addition of new team members, but instead we are happy with the progress we are making at the moment. We believe we are not only building equity in business we believe in, but also building a product that could help the safety and wellness of our users.

This thesis examines how a recently proposed concept for a highly-truncated aerospike nozzle can be expected to perform at altitudes corresponding to ambient pressures from sea-level to full vacuum conditions, as would occur during second-stage ascent and during second-stage descent and return to Earth. Of particular importance is how the base pressure varies with ambient pressure, especially at low ambient pressures for which the resulting highly underexpanded flows exiting from discrete thrust chambers around the truncated aerospike merge to create a closed (unventilated) base flow. The objective was to develop an approximate but usefully accurate and technically rooted way of estimating conditions for which the jets issuing from adjacent thrust chambers will merge before the end of the truncated aerospike is reached. Three main factors that determine the merging distance are the chamber pressure, the altitude, and the spacing between adjacent thrust chambers. The Prandtl-Meyer expansion angle was used to approximate the initial expansion of the jet flow issuing from each thrust chamber. From this an approximate criterion was developed for the downstream distance at which the jet flows from adjacent thrust chambers merge. Variations in atmospheric gas composition, specific heat ratio, temperature, and pressure with altitude from sea-level to 600 km were accounted for. Results showed that with decreasing atmospheric pressure during vehicle ascent, the merging distance decreases as the jet flows become increasingly under-expanded. Increasing the number of thrust chambers decreases the merging distance exponentially, and increasing chamber pressure results in a decrease of the merging distance as well.

This project involved research into solar thermal and geothermal energy generation as possible solutions to the growing U.S. energy crisis. Background research into this topic revealed the effects of climate and environmental impacts as major variables in determining optimal states. Delving into thermodynamic engineering analyses, the main deliverables of this research were mathematical models to analyze plant efficiency improvements in order to optimize the cost of operating solar thermal and geothermal power plants. The project concludes with possible future research areas relating to this field.

This project involved research into solar thermal and geothermal energy generation as possible solutions to the growing U.S. energy crisis. Background research into this topic revealed the effects of climate and environmental impacts as major variables in determining optimal states. Delving into thermodynamic engineering analyses, the main deliverables of this research were mathematical models to analyze plant efficiency improvements in order to optimize the cost of operating solar thermal and geothermal power plants. The project concludes with possible future research areas relating to this field.

The purpose of this paper is to establish the rules governing current combat robotics and showcase an idea on how to create a more powerful robot. The robot would use its weapon to spin the rest of its body while having the weapon's gyro forces lift the entire robot and move it a set distance while spinning. Performing both of these actions simultaneously would create a more powerful robot through the use of a more destructive weapon system. Many initial tests were conducted to verify that the electronics and code worked and that the wheels could withstand the significant gyro forces when spinning. Multiple prototype chassis were designed and optimized to better handle the shape and the electronics went through several revisions so that they could be packaged in a cleaner and more space efficient way. A final prototype was designed with the knowledge from the initial tests which was then manufactured and tested to verify that the weapon could rotate the entire robot.

The Tesla valve, originating from Nikola Tesla's "valvular conduit" patent in 1920, offers a unique solution to fluid control challenges by enabling unidirectional flow while impeding reverse flow. With applications ranging from fluid pumps to high-power engines, Tesla's design functions as a fluidic diode, inducing pressure drops across the valve to define its efficiency through diodicity. Through computational fluid dynamics (CFD) simulations using ANSYS Fluent, the impact of removing the bifurcated section on Tesla valve efficiency is explored. The T45-R, D-Valve, and GMF Valve designs are analyzed across a range of Reynolds numbers (Re). Results show that while the absence of bifurcation can lead to higher diodicity values due to increased flow divergence and vortex formation, efficiency varies depending on flow conditions. The T45-R valve exhibits linear diodicity increase with Reynolds number, plateauing at higher values due to reduced fluid inertia influence. Conversely, the D-Valve with bifurcation excels at lower Re values, while the non-bifurcated version proves more efficient at higher Re values. The GMF Valve with bifurcation demonstrates efficiency at lower Re values but decreases in effectiveness as Re rises, with the non-bifurcated version showing lower efficiency overall. Overall, this research provides insights into the fundamental physics and design considerations of Tesla valves, offering guidance for optimizing fluid control applications across diverse industries. The study underscores the importance of considering geometric variations and flow conditions when designing Tesla valves for specific applications, highlighting the intricate relationship between valve geometry, flow dynamics, and efficiency.

With the growth of the additive manufacturing (AM) industry for metal components, there is an economic pressure for improved AM processes to overcome the shortcomings of current AM technologies (i.e., limited deposition rates, surface roughness, etc.). Unfortunately, the development of these processes can be time and capital-intensive due to the large number of input parameters and the sensitivity of the process’s outputs to said inputs. There consequently has been a strong push to develop computational design tools (such as CFD models) which can decrease the time and cost of AM technology developments. However, many of the developments that have been made to simulate AM through CFD have done so on custom CFD packages (as opposed to commercially available packages), which increases the barrier to entry of employing computational design tools. For that reason, this paper has demonstrated a method for simulating fused deposition modeling using a commercially available CFD package (Fluent). The results from this implementation are qualitatively promising when compared to samples produced by existing metal AM processes, however additional work is needed to validate the model more rigorously and to reduce the computational cost. Finally, the developed model was used to perform a parameter sweep, thereby demonstrating a use case of the tool to help in parameter optimization.