Understanding NASA-ESA Mars Sample Return (MSR) Campaign Concept by Model-Based Systems Engineering (MBSE) Design and Analysis

Abstract

View Video Presentation: https://doi.org/10.2514/6.2022-2134.vid The NASA-ESA Mars Sample Return (MSR) Program is an ambitious and complex space system engineering endeavor. The reference architecture for the proposed NASA-ESA Mars Sample Return (MSR) Campaign Concept as agreed in the joint statement of intent signed on April 26, 2018 in Berlin, Germany consists of three flight elements and one ground element, the Mars Returned Sample Handling (MRSH) facility. NASA Mars 2020 Perseverance Rover was launched on July 30, 2020 and successfully landed in the Jezero Crater on February 18, 2021. The Mars 2020 Rover has the capability to collect samples of Martian rocks and regolith and hermetically seal them in collection tubes for depositing them in select depot locations. The second flight element is the NASA-led Mars Sample Retrieval Lander (SRL) carrying the Mars Ascent Vehicle (MAV), a two-stage to orbit solid propellant rocket and the ESA supplied Sample Fetch Rover (SFR) with a robotic Sample Transfer Arm (STA). The third flight element is the ESA-led Earth Return Orbiter (ERO) with NASA provided Capture, Containment and Return System (CCRS) payload in an Earth Entry Vehicle (EEV). This paper attempts to understand the proposed NASA-ESA Mars Sample Return (MSR) Campaign Concept through the Model Based Systems Engineering (MBSE) Framework. The stakeholder Domain package defines the MSR Campaign elements, launch and deep space environments, Mars orbit and surface environments, and external constraints. The external constraints include planetary protection regulations and Earth-Mars launch window periods. The overview of the MSR Campaign Concept is further explored through the SysML based visualization diagrams on requirements, structure (package and block definition), and behaviors (use case and activity). The key aspects of MBSE model governance necessary in a federated modeling environment for Agile Model Management Plan are also identified.