Fidelity Evaluation Model for Planetary Mission Simulators: Part I - Simonaut Survey

Abstract

Space agencies are planning the next generation simulators in preparation for future human missions to Moon and Mars. Simulators serve as tools to test new technologies, habitat design, procedures, protocols, physiological requirements and psychological countermeasures. This paper focuses on simulator fidelity. Simulator fidelity, as defined by the research team, is: The degree to which a simulator system accurately reproduces the habitat (and/or transit vehicle) conditions, the Planetary Body of Interest (PBI) environment, procedures, protocols and operations of a real mission. Simulator fidelity is critical because the data collected and lessons learnt from simulations are intended for application towards the design of real space missions in the future. If simulator fidelity is compromised, then the simulation data generated might lead to erroneous conclusions. If such data is then used in the design of real missions, it has the potential to adversely affect the crew and in the worst case, even jeopardize the mission. The paper begins with the definition and overview of simulators. This is followed by a discussion about fidelity standards outlined in a recent study by the European Space Agency and recommendations emerging from a workshop in Colorado focusing on improving the quality of future simulators. These recommendations reinforce the need for a ‘Fidelity Evaluation Model’ to measure, compare and improve fidelity of future simulators. As a first step towards the development of a Fidelity Evaluation Model, the authors gather data associated with simulator fidelity via a questionnaire-based survey of simulator crew members, referred to as simonauts. The authors debrief simonauts from the NASA Lunar Mars Test Project and the Mars Society simulations. The paper concludes with a summary of the survey outcome and a brief discussion of what the authors envision as the next steps in the development of the Fidelity Evaluation Model.