What is it about?
This paper presents a probabilistic approach to assess performance of time-critical operations. This approach is used to design a critical payload required for the Mars Sample Return campaign, which aims at bringing to Earth rock cores, regolith and atmospheric samples from Mars.
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Why is it important?
When a system's performance assessment is complex and highly dependent on dynamic external interfaces, processes are required to generate performance targets and methodologies to assess the system against such targets. This work demonstrates a probabilistic approach to assess time-critical operations for a Mars Sample Return mission. Similar thought processes can be applied to other non-traditional technical resources where performance targets are non-existent in the industry.
Perspectives
Yew et al. (2024) tackles a genuinely hard problem: how do you verify that a system will successfully capture a small Orbiting Sample in Mars orbit in a matter of seconds, when critical input parameters are controlled by entirely separate projects with their own uncertainty budgets? Rather than shying away from that complexity, the team embraces it through a Monte Carlo simulation framework paired with a global Sobol' sensitivity analysis to surface the true performance drivers. The results are reassuring — a 46% timing margin and a total probability of capture well above the 99.7% target — but the real contribution is the methodology itself, which offers a replicable blueprint for applying probabilistic thinking to non-traditional performance metrics where no industry-standard margin guidelines exist. For anyone working at the intersection of multi-project missions and systems engineering, this paper is a model for navigating ambiguity with rigor rather than false determinism.
Dr. Giuseppe Cataldo
NASA
Read the Original
This page is a summary of: Probabilistic Approach to Assessing CCRS Capture System Performance Margin, January 2024, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/6.2024-2052.
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