Studentische Abschlussarbeiten

The next generation of human space exploration missions will necessitate increasingly sophisticated Life Support Systems (LSSs) to ensure astronauts stay alive, healthy and happy. These LSSs come with a variety of individual challenges, complexity and dynamic behavior. To further enable development of individual subsystems in the context of a modular LSS, a small-scale LSS is constructed at the Institute of Space System. The test rig will consist of three chambers, with the main focus of this work being on the Habitat Chamber (HC) to simulate spacecrafts, stations or habitats. Due to the modular approach, many different variations of experiment placement at the HC flanges are possible.
This thesis aims to provide a first insight into the spatial distribution of gases inside the HC. Areas of high or low density, possible problems due to experiment configurations and the optimal placement of the inside fan and heater should be analyzed. The goal is to provide a recommendation for good sensor placement independent of configuration and identify operational limitations for the use of the HC.

The next generation of human space exploration missions will take crews farther away from Earth than ever before. These missions will necessitate increasingly sophisticated Life Support Systems (LSSs) to ensure astronauts stay alive, healthy and happy. Mission scenarios of this kind therefore require greater autonomy, relying on simulations as well as laboratory setups to recreate the nominal behaviour of the LSS during all mission phases.
In order to be able to simulate these complex LSSs at the Institute of Space Systems (IRS), a small-scale laboratory model of a LSS is being constructed. Since such a complex undertaking requires detailed planning, a Model Based Systems Engineering (MBSE) approach is suggested to optimize the development process. This approach can also be combined with a Digital Twin of the laboratory model that is currently being implemented at the IRS.
This thesis explores MBSE for developing a Life Support System from the ground up. It covers foundational knowledge of MBSE and Requirements Engineering, reviews relevant tools and system architecture, examines integrating MBSE with the Digital Twin, and evaluates the resulting approach.

The next generation of human space exploration missions will require increasingly sophisticated life support systems (LSS) to sustain crews on long-duration missions far from Earth. V HAB, a powerful simulation system for modeling complex LSS, employs a unique bottom-up approach that allows for high-precision modeling of all LSS components up to a user-defined granularity. This approach enables V HAB to maintain high modeling accuracy by providing detailed information on mass flow, temperature, pressure, humidity, and composition for each individual process and subsystem.
Currently, V HAB operates entirely within MATLAB without requiring additional packages or toolboxes. It offers a library of pre-defined basic LSS components, allowing users to integrate existing subsystems into their designs rather than starting from scratch. However, V HAB lacks a user-friendly graphical interface. (GUI), hindering its accessibility and usability, especially for new users. This master's thesis will work in parallel with the ongoing development of the V HAB GUI to compare the suitability of Synera as an alternative approach.
Synera, a modern low-code automation platform, offers the potential to address these gaps and enhance V HAB's capabilities. The integration of V HAB with Synera provides significant potential to improve the functionality and user experience of the LSS modeling platform. By leveraging Synera's capabilities, the integrated system could provide a user-friendly graphical interface, streamline the design process with quick options and arranging tools, and offer real-time feedback through automated logic tests and live updating feeds. These features would make V HAB more accessible to new users while providing comprehensive overviews of designed LSS and enhancing understanding of their operations.
This master's thesis aims to investigate and implement this integration, creating an advanced modeling platform that enables more efficient data generation, improved visualization of simulation results, and enhanced automation of modeling workflows.