1. Introduction

The paper focuses on the critical challenge of developing life cycle cost (LCC) models to evaluate alternative architectures for life support systems (LSS) needed to enable long-duration autonomous habitation on crewed spacecraft for deep space missions. LSS are essential for sustaining human life during months or years in the harsh space environment by continuously providing critical consumable resources like breathable air, potable water, nutritious food, waste recycling, and thermal regulation. Different LSS architectures provide varying levels of sustainability and autonomy through closed-loop regeneration and recycling of consumable resources versus reliance on intermittent resupply missions from Earth.

The introductory section provides an extensive review of prior works examining existing and experimental LSS implementations on the International Space Station, for future conceptual lunar and Mars habitats, and emerging bioregenerative technologies. It highlights the urgent need to perform comprehensive LSS life cycle cost analyses during early design stages in order to determine the optimal balance between meeting critical life support performance and reliability requirements while remaining within budget constraints for missions lasting months or years far from Earth.

The paper proposes developing an adaptable mathematical model to provide first-order estimates of the life cycle costs associated with different LSS architectures based on mission duration and key factors like:

• LSS complexity, autonomy levels, redundancy
• Development, production, operations, maintenance costs
• Logistical challenges associated with external resupply

The analysis focuses on modeling three primary LSS architecture alternatives:

1. Open LSS relies completely on externally resupplied consumable resources, reducing technological complexity but increasing logistical challenges.
2. Closed LSS operates fully autonomously by regenerating essential resources like air, water, and food internally, but has higher upfront development costs.
3. Mixed LSS strategically combines external supply of some resources along with internal recycling of others to balance logistics versus autonomy.

The paper aims to develop modular parametric life cycle cost equations to model each architecture type over the full mission timeline from early design through operations. Key cost factors accounted for include:

• Initial LSS development, production, integration, and implementation costs
• Recurring operating costs for maintaining resupply capabilities or autonomous recycling systems
• Consumables costs directly associated with crew metabolic needs
• Transportation costs for delivering resupply cargo missions

The goal is to create a flexible modeling methodology that allows identification of transition points where increased LSS closure and autonomy become more cost-effective than reliance on open resupply as mission duration grows. This early stage modeling capability provides guidance on selecting an optimal LSS architecture that meets both sustainability performance needs and budget constraints for a particular mission profile.

2. RMotivation, Contelated Workxt, and Challenges Associated with Developing Life Cycle Cost Models for Autonomous Life Support Systems

This section comprehensively reviews and synthesizes prior literature related to the motivation, context, and challenges associated with developing life cycle cost models for autonomous life support systems. It provides an overview of existing and planned long-duration crewed autonomous transport systems like the International Space Station, lunar orbiting outposts, Martian habitats, and interplanetary transit vehicles. These ambitious missions highlight the criticality of closed-loop life support systems to enable multi-year habitation far from Earth.

The review discusses major governmental and commercial space agency plans related to autonomous transportation systems, inhabitable orbital outposts, lunar surface bases, Martian research settlements, and deep space transit spacecraft. This underscores the timeliness and importance of researching life support system architectures.

The review also closely examines prior work investigating the unique technical challenges of different life support capabilities like atmosphere revitalization, water purification, waste recycling, food production, and thermal regulation needed to create a habitable environment. The complexities of developing biological and physiochemical process technologies that can operate reliably for years in the harsh space environment are highlighted.

In terms of architectural approaches to meet these challenges, the review contrasts open loop life support systems reliant on resupply from Earth versus closed loop systems aimed at full recycling and regeneration of consumables to minimize external dependencies. Hybrid approaches are also discussed. Prior studies providing technical analyses of these options are synthesized. The review covers recent research into innovative bioregenerative technologies that utilize biological processes like photosynthesis, plant cultivation, and microbial bioreactors to regenerate oxygen, water, and food. Implementations on the ISS and ground-based simulated missions are examined. The immense challenges involved in maturing such technologies for operational reliability over decade-long missions is emphasized.

The review summarizes the limited prior art examining the cost modeling and economic feasibility assessment of life support system capabilities and architectures. The gaps in research related to comprehensive life cycle cost modeling methodologies are highlighted, forming the motivation for the present paper. The detailed literature review provides a holistic overview of the state-of-the-art, open challenges, and context for developing advanced life cycle cost models to guide the design of reliable, sustainable and cost-effective life support systems for future autonomous space transportation systems over extended missions.

3. Modeling Approach

This section provides background on the typical architecture of environmental control and life support systems, and contrasts the differences between open loop, closed loop, and hybrid approaches. It describes the scope of functions required in a crewed spacecraft life support system architecture, including atmosphere revitalization, water recovery, waste management, food production, and thermal control. Different technologies that can be utilized for each function are summarized, including both physicochemical and bioregenerative systems.

The section then delineates an open loop architecture where consumables like air, water and food are supplied only through periodic resupply from Earth. This reduces complexity but creates logistical challenges and the risk of disruption if resupply is interrupted. In comparison, a closed loop architecture uses regenerative systems to recycle and reuse resources with minimal inputs from Earth after the initial outfitting. This provides near autonomy but requires more complex recycling systems and higher development costs. Finally, a hybrid approach is presented which combines external consumable supplies with some regenerative systems to create a more flexible and robust architecture. This leverages the strengths of both open and closed loop approaches.

The trade-offs between these architectures in terms of technological maturity, complexity, reliability, autonomy, initial costs, recurring costs, and sustainability are explored. This background provides context for formulating an evaluative framework to compare life cycle costs of different architectures using quantitative models.

This section outlines the proposed mathematical modeling approach to estimate and compare the life cycle costs of open, closed, and hybrid life support system architectures over a defined mission duration. It delineates the key assumptions, cost factors, and model parameters that need to be considered, including:

• Crew size, mission duration, and metabolic consumable needs
• Development costs for architecture complexity and degree of closure
• Production and integration costs based on technological maturity
• Operations costs for maintenance, repair, and resupply
• Logistic costs for transportation of externally supplied consumables
• Failure rates and redundancy requirements
• Technological improvement and uncertainty factors

The section then describes the formulation of parametric cost estimation relationships for each life support architecture type, encompassing both initial and recurring costs. It discusses how these cost estimation relationships can be tailored for a particular mission scenario using appropriate parameter values. The framework for integrating the modular LSS architecture models into an overall life cycle cost model is presented. The capabilities for varying the degree of openness or closure in a hybrid architecture are delineated. The methodology for optimizing the system architecture for minimum life cycle cost based on the mission duration is described. The utility of the modeling approach for performing trade-off analyses between performance factors like autonomy, reliability, and sustainability and budget factors like development, operations, and logistics costs is highlighted. This provides an analytical basis for informed LSS architecture decision making.

Section demonstrates the application of the proposed life cycle cost modeling methodology. Key trade-offs are identified, such as how above a certain mission duration threshold the hybrid and eventually closed loop architecture become more cost effective than open loop due to the recurring cost of resupply. These results demonstrate how the model provides insights into the life cycle cost implications of different design decisions.

The section also explores using the model to perform optimization studies to determine the architectures with minimum life cycle cost based on the mission duration. It illustrates the utility of the life cycle cost modeling methodology for performing insightful LSS architecture studies to identify affordable solutions tailored to specific mission requirements and constraints.

There are some limitations of the study. The paper acknowledges the limitations involved in early-stage modeling of complex and lengthy space missions with many technology, operations, and cost uncertainties. It discusses the restricted fidelity and accuracy at the conceptual design phase before detailed subsystem definitions and technology selections are complete. The reliance on analogy-based estimations and assumptions from past missions is noted. The paper emphasizes that the objective is to develop a flexible cost modeling methodology for gaining directional insights rather than precise forecasts. The model outputs help guide analysis trade-offs rather than provide quantitatively accurate predictions, especially this early in the design cycle.

Recommendations are provided for refinement as a program progresses, including integration of higher-fidelity subsystem and operations models, updating cost factors based on maturing technologies, adding network and probabilistic modeling capabilities, and incorporating real options valuation.

Areas needing further research are highlighted, including modeling the risks and benefits associated with increased system closure and complexity, analyzing interactions between life support architecture selection and overall vehicle design, and extending the methodology to surface habitation scenarios.

The modular, adaptable framework developed provides a foundation for incremental expansion in scope, fidelity, and accuracy as a mission concept matures through its life cycle to maximize the value of life cycle cost modeling.

4. Conclusions

The paper concludes by summarizing the critical need for comprehensive life cycle cost modeling capabilities to enable affordable, sustainable life support system design for ambitious long-duration autonomous space habitation missions planned in the coming decades. It reiterates how the proposed flexible modeling methodology provides an early-stage assessment framework to gain insight into the cost implications of key architecture decisions related to open versus closed loop approaches, redundancy needs, technology selections, and logistics strategies. While approximate, these initial analyses create an understanding of cost drivers and trade-offs that influence concept development phases when the design is still fluid and major changes are feasible.

The model provides an analytical basis for articulating the return on investment and mission benefits associated with developing increasingly closed-loop, regenerative life support technologies. It can build the qualitative case for supporting such development despite their initial high costs compared to proven open loop architectures.

The paper emphasizes that applying the methodology presented will support stakeholder decision making, technology prioritization, and mission planning to ultimately enable sustainable and affordable life support system architectures for humanity’s expansion into deep space.

The proposed approach forms a critical piece of the complex puzzle involved in transforming the immense challenges of multi-year crewed space missions from futuristic visions into tangible realities in the coming era of space exploration.