Brown Bag Seminar
Thursday, April 6, 2023
11:00 am – 12:00 pm
Guggenheim 442
Presenters:
Avik Banerjee
Braden Kerstin
Catherine Schlabach
Avik Banerjee
Title: Digital Engineering and Modeling with SysML for Aerospace Applications
Abstract:
Digital engineering has revolutionized the aerospace industry by using integrated digital technologies to accelerate the development and delivery of complex systems and the design of missions. Model-based systems engineering (MBSE) has become a key component of digital engineering, with Systems Modeling Language (SysML) being a popular graphical modeling language that supports MBSE activities such as requirements analysis, design, verification, and validation. SysML enables aerospace engineers to create and manage system models that capture the structure, behavior, and interactions of system components and stakeholders. This language also supports formal methods and reasoning to ensure the consistency and correctness of system models. In this research project, we will leverage the power of SysML software, MagicDraw, to model a space mission inspired by NASA’s FireSat Mission. Our primary focus will be on the modeling and definition of the ground station, as it is the key element behind the mission's success. Additionally, we will demonstrate how SysML models can be transformed into Modelica and SIMULINK to take advantage of the data analysis capabilities offered by different software. By doing so, we aim to showcase the versatility and power of SysML for model-based systems engineering.
Advisor: Prof. Selcuk Cimtalay
Braden Kerstin
Title: Combustion Instability for 3D Printed Injectors
Abstract:
Combustion instability is one of the most important topics in jet/rocket propulsion, and plays a key role in system design, optimization, and component effectiveness. Siemens Energy requires combustion instability data for a wide range of operating conditions including exhaust chamber volume and mass flow. Testing is to be conducted with a set of 3D printed fuel injectors provided by Siemens Energy, and a specialized experimental testing rig is being constructed to vary exhaust volume and other parameters during a single test. This data will eventually be used for energy generating engines for commercial power plants.
Advisor: Prof. Timothy Lieuwen
Catherine Schlabach
Title: Deep Space Network Interface with University Space Operations
Abstract:
The Deep Space Network (DSN) is an international collection of radio antennas operated by NASA. This study follows staffing, scheduling, and strategic mission operations in conjunction with the DSN. Specifically, this research presents the relationship between the DSN and a CubeSat project with a team of university students. In order to fully support operators who interface with the DSN, effective collaborative development and project management is employed. The schedule demand that the DSN faces from multiple space missions, maximum allotted project time, and minimum time between radio transmission are limiting factors for determining when contacts can be scheduled. Contact planning is considered in the form of scheduling and communicating Operational Procedure Deviations. OPDs are deviations to default parameters that configure the DSN assembly. Tactical connection with the DSN is defined in four ways: operators to DSN personnel via phone line, DSN station to the Lunar Flashlight Iris Radio, Iris to DSN station, and DSN signal to mission operations data system. The discussion follows contact planning, communications protocol, connection anomalies, and the challenges experienced.
Advisor: Prof. Glenn Lightsey