Risk and Performance Assessment of Generic Mission Architectures: Showcasing the Artemis Mission

Abstract

Recently, NASA has initiated a strong push to return astronauts to the lunar vicinity and surface. In this work, we assess performance and risk for proposed mission architectures using a new Mission Architecture Risk Assessment (MARA) tool. The MARA tool can produce statistics about the availability of components and overall performance of the mission considering potential failures of any of its components. In a Monte Carlo approach, the tool repeats the mission simulation multiple times while a random generator lets modules fail according to their failure rates. The results provide statistically meaningful insights into the overall performance of the chosen architecture. A given mission architecture can be freely replicated in the tool, with the mission timeline and basic characteristics of employed mission modules (habitats, rovers, power generation units, etc.) specified in a configuration file. Crucially, failure rates for each module need to be known or estimated. The tool performs an event-driven simulation of the mission and accounts for random failure events. Failed modules can be repaired, which takes crew time but restores operations. In addition to tracking individual modules, MARA can assess the availability of predefined functions throughout the mission. For instance, the function of resource collection would require a rover to collect the resources, a power generation unit to charge the rover, and a resource processing module. Together, the modules that are required for a given function are called a functional group. Similarly, we can assess how much crew time is available to achieve a mission benefit (e.g. research, building a base, etc) as opposed to spending crew time on repairs. Here we employ the method on the proposed NASA Artemis mission. Artemis aims to return United States astronauts to the lunar surface by 2024. Results provide insights into mission failure probabilities, upand downtime for individual modules and crew-time resources spent on the repair of failed modules. The tool also allows us to tweak the mission architecture in order to find setups that produce more favorable mission performance. As such, the tool can be an aid in improving the mission architecture and enabling cost-benefit analysis for mission improvement.

A Conceptual Architecture of Fuzzy Risk-Based Decision Support Systems (R+DSS)

“…An architectural framework for a Decision Support System that aims to aid clinicians in evaluating patients' health risks by providing "Risk Prediction as a Service" [21]. [22] aimed to assess the performance and risk of suggested mission architectures by utilising a novel tool called Mission Architecture Risk Assessment (MARA). [23] Aim to investigate the impact of choice architecture on physicians' decision-making process and the subsequent risk of guideline discordance in sepsis.…”