Nicole E Piontek | Search NASA

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More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Current Environmental Control and Life Support System (ECLSS) development and test activities are not generating data fast enough to provide statistically-supportable precise Orbital Replacement Unit (ORU) failure rate estimates for future missions. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches – namely regular resupply and rapid abort capabilities – will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of operations on board the International Space Station (ISS), a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass for future missions. A Bayesian failure rate estimation approach, such as the one currently implemented by the ISS Program, can help reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior failure rate estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, these subjective (and often inaccurate) prior estimates currently have a strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Supportability↗

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Integrated Trajectory, Habitat, and Logistics Analysis and Trade Study for Human Mars Missions

Environmental Control and Life Support System (ECLSS) architecture selection has profound implications for mission cost and mass extending far beyond the ECLSS itself. Similarly, other mission architecture decisions – particularly involving transportation systems – can influence optimal ECLSS architectures. Loop closure influences requirements for water, oxygen, and other consumables. System maintainability and reliability influences spares mass and risk. System, consumables, and spares mass interact with transportation system architectures and propellant demands and propulsion element sizing. All these interactions with other systems must be considered when evaluating ECLSS options. Analyses that focus only on maximizing ECLSS loop closure – or minimizing ECLSS mass, or minimizing ECLSS life cycle cost – may lead to sub-optimal or even counterproductive system architecture and investment decisions at the mission level. For example, an ECLSS architecture that minimizes ECLSS life cycle cost but results in excessively high logistics mass could lead to significantly increased transportation system costs or make interplanetary transportation infeasible. Increased loop closure could result in higher development costs and higher mass if system/spares mass increases outweigh consumables reduction. In addition, systems mass and consumables mass are not directly comparable and have different impacts on propellant requirements, as consumables mass changes over the course of the mission. This paper presents an integrated analysis examining the overall impact of different ECLSS and transportation architectures on mass for a crewed Mars mission, including the habitat and transportation systems as well as consumables, spares, and propellant. Key observations are discussed, along with opportunities for further sensitivity analysis and model development. Overall, ECLSS development activities must consider their impacts at the mission level, as part of an integrated system, rather than in isolation.

Mars↗

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Modeling Logistics and Supportability for Crewed Missions Beyond Low Earth Orbit

NASA’s future missions aim to establish a sustained human presence on the lunar surface and send humans to Mars. These missions will send crews farther from home than previous missions, limiting the opportunities for resupply missions. Additionally, the use of multiple launches and reusable elements will increase mission and campaign complexity. Logistics and supportability analysis evaluates the link between mission and system characteristics and key metrics such as logistics and spares mass and volume, crew time, and risk. As missions become increasingly complex and crews are logistically isolated for longer periods of time, logistics and supportability will become more powerful drivers of risk and cost and, therefore, more important considerations during system and mission development. When logistics and supportability are considered from the beginning of system and mission development, opportunities arise to create more efficient, lower-risk systems. Design choices made without detailed consideration of logistics and supportability have the potential to result in greater risks and increased costs as all options may not have been analyzed. This paper provides an overview of a methodology used for space mission logistics and supportability analysis, including key metrics, assumptions, and required inputs. Example applications of this methodology to explore the impacts of system architecture, dormancy, and synergies between lunar and Mars missions are also presented. Conducting these holistic analyses enables informed decision-making for mission planning and system design, which can help mitigate the risk of loss of mission, vehicle, or crew. Using the knowledge of historical missions, experiences gained on the lunar surface, and logistics and supportability analyses, NASA can examine and optimize supportability characteristics for safer and more effective operations for future lunar and Mars missions.

Supportability↗

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A Historical Review of Logistics Mass and Crew Time Demands for ISS Operations

Following over 20 years of continuously crewed operations on the International Space Station (ISS), NASA is planning to return to the Moon and eventually send humans to Mars. ISS operations provide vital data to inform mission analysts as NASA prepares for longer and more complex missions with increased mission endurance. Endurance, defined as crewed operating time between cargo deliveries (or crew launch and return to Earth), is an important metric when analyzing mission needs. NASA is developing architectures to support sustained deep-space habitats in cislunar space, the lunar surface, Mars transit, and the surface of Mars. Unlike the ISS, these systems will not be continuously crewed, and unlike the Space Shuttle, these systems will not return to Earth for regular refurbishment between missions. Lunar systems will routinely go through long uncrewed periods between crewed missions. The systems on board will need to survive these dormancy periods with no crew present to provide maintenance. Mars systems will experience significantly longer endurance than past experience. Additionally, the inability to have quick aborts to return to Earth increases the need for system reliability, redundancy, and maintainability, as well as plans for contingency operations. This paper examines the historical logistics and crew time demand for ISS operations and mission objectives and provides an overview of missions to the ISS over its operating history, the mass and items delivered with the missions, and the crew time spent during missions. These parameters provide insight and valuable data to inform logistics and crew time estimates for future long-endurance crewed exploration missions.

Crew Logistics↗

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Modeling Logistics and Supportability for Crewed Missions Beyond Low Earth Orbit

NASA’s future missions aim to establish a sustained human presence on the lunar surface and send humans to Mars. These missions will send crews farther from home than previous missions, limiting the opportunities for resupply missions. Additionally, the use of multiple launches and reusable elements will increase mission and campaign complexity. Logistics and supportability analysis evaluates the link between mission and system characteristics and key metrics such as logistics and spares mass and volume, crew time, and risk. As missions become increasingly complex and crews are logistically isolated for longer periods of time, logistics and supportability will become more powerful drivers of risk and cost and, therefore, more important considerations during system and mission development. When logistics and supportability are considered from the beginning of system and mission development, opportunities arise to create more efficient, lower-risk systems. Design choices made without detailed consideration of logistics and supportability have the potential to result in greater risks and increased costs as all options may not have been analyzed. This paper provides an overview of a methodology used for space mission logistics and supportability analysis, including key metrics, assumptions, and required inputs. Example applications of this methodology to explore the impacts of system architecture, dormancy, and synergies between lunar and Mars missions are also presented. Conducting these holistic analyses enables informed decision-making for mission planning and system design, which can help mitigate the risk of loss of mission, vehicle, or crew. Using the knowledge of historical missions, experiences gained on the lunar surface, and logistics and supportability analyses, NASA can examine and optimize supportability characteristics for safer and more effective operations for future lunar and Mars missions.

Supportability↗