Brown Bag Seminar
Friday, September 22
11:00 a.m. -12:00 p.m.
Guggenheim 442
Pizza will be served
Presenters:
Megan Brown
Samuel Luong
Martin Poretti
Megan Brown
Title:
Design and Assembly of an Electrical Enclosure for Instrumentation Control and Data Acquisition in Combustion Research
Abstract:
A data acquisition (DAQ) box, or electrical enclosure, is a vital part of virtually every test rig involved in combustion research. DAQ boxes allow for interfacing between the rig assembly and the operator by receiving information supplied by sensors on the test rig and sending signals from the operator to change the settings of instruments like on/off valves or diverters to alter the test parameters and optimize the results. These enclosures vary in complexity based on the number of sensors and instruments utilized in the test assembly. This presentation demonstrates the process of assembling this enclosure from an empty stainless-steel box to a fully operational data collection and instrument control system in the context of a project exploring supersonic swirling combustion: a project implementing solenoid valves, diverting valves, needle valves, pressure transducers, and more.
Advisor:
Samuel Luong
Title:
Electrical and Power Systems for OrCa2 and WEBS Missions
Abstract:
Electrical and power systems are vital components of space missions, providing the necessary energy to sustain spacecraft and equipment in the harsh and remote environment of outer space. These systems must be highly efficient, reliable, and resilient to extreme conditions, including vibrational and temperature fluctuations. In my presentation, I explore the intricacies of developing such systems for CubeSat missions such as OrCa2 and WEBS. This presentation will take you through the process of planning power budgets, developing specialized equipment, and rigorously testing these systems for space environments.
Advisor:
Prof. Brian Gunter
Martin Poretti
Title:
Modeling a Formula One Optimizer Using SysML
Abstract:
This research leverages the knowledge I gained over two semesters of undergraduate research to develop a Formula One track optimization model for race day qualifications. The study encompasses multiple variables, including tire selection, weather conditions, downforce package, and fuel level, with the primary aim of enhancing qualification performance.
To achieve this, I initially analyzed the factors with the most significant impact on race day qualification. Subsequently, I constructed a Requirement Diagram that delineates three high-level requirements, systematically breaking them down. A Block Definition and Parametric Diagram were then created to provide a structured representation of the system. Finally, I executed an instance of my model to assess its performance.
The results indicate that my model demonstrates the ability to offer preliminary predictions for an optimal qualification strategy at the commencement of qualifying sessions, contingent upon basic input variables, applicable to various track types. However, it also highlights the potential for further refinement and expansion to encompass a broader spectrum of influencing factors. In conclusion, this research underscores the principle that any system can be extended and detailed to accommodate evolving requirements.
Advisor:
Prof. Dimitri Mavris and Prof. Selcuk