Periodic Reporting for period 1 - SERENITY (Space & Earth Reliable greENhouse desIgn meThodologY)
Période du rapport: 2022-09-01 au 2024-08-31
With the return of human exploration missions to the Moon in the late 2020s, along with preparations for longer-duration missions to Mars and beyond, large-scale, sustainable, and reliable food production systems will be essential. To date, only small-scale plant growth systems have operated in space, and they continue to present numerous challenges. For space greenhouse modules (GHM) to be sustainable, they must use minimal resources, present low risk, and be robust, reliable, and resilient. The SERENITY project’s overarching scientific aim was to develop a systematic approach to generate and compare space greenhouse module design options, analyzing them across multiple criteria within a constrained environment.
The first objective was to analyze constraints and objectives by defining and reviewing environmental parameters, stability and reliability criteria for GHMs, and subsystem modeling requirements. The second objective focused on systematically generating competing designs and interpreting results, using simulation tools informed by the constraints from Objective 1 and criteria related to resource usage (energy, water, crew time), resource production (food, oxygen, water), as well as reliability, sustainability, and risk. The third objective was to establish a systematic approach to identify the optimal solution and make recommendations for designing plant growth systems for varying gravity scenarios.
The first objective was to analyze constraints and objectives by defining and reviewing environmental parameters, stability and reliability criteria for GHMs, and subsystem modeling requirements. The second objective focused on systematically generating competing designs and interpreting results, using simulation tools informed by the constraints from Objective 1 and criteria related to resource usage (energy, water, crew time), resource production (food, oxygen, water), as well as reliability, sustainability, and risk. The third objective was to establish a systematic approach to identify the optimal solution and make recommendations for designing plant growth systems for varying gravity scenarios.
Four main scenarios—Moon surface, Mars surface, interplanetary, and space station—and their associated sub-scenarios were defined. The Mars Climate Database (Forget et al. 1999 and Millour et al. 2018) was identified as the primary location database for Martian surface conditions. Parameters for other scenarios were compiled from a literature review, leading to the creation of a comprehensive location database. Greenhouse module subsystems and their interactions were defined, and a plant database was established to inform the design. Relevant subsystems were then modeled to facilitate multi-objective optimization.
The OSMOSE platform supported multi-criteria optimization, and a modular coding architecture was developed to allow flexible designs and further advancements. Initial design generation and comparison were conducted on simplified cases, showing the dependence of space greenhouse designs on astronaut diet and mission scenario. This process underscored the importance of accurate plant databases, encouraging collaborations to enhance this aspect.
A systematic approach to space greenhouse module design was developed, accompanied by the creation of a GitHub platform for open access. Recommendations for Earth-based facilities led to a spin-off project, which was proposed for funding to the European Space Agency (ESA) (though unsuccessful) and is pending with the French National Research Agency (ANR). With no immediate partnership with Interstellar Labs, new collaborations were established with various organizations to apply the methodology to their projects, including the German Aerospace Center (DLR), the Canadian Space Agency (CSA), Plant for Space (P4S, Australia), and the Korean architecture firm Space Group.
A key outcome was the development of a terrestrial application with potential for commercialization and the initiation of new collaborations.
The OSMOSE platform supported multi-criteria optimization, and a modular coding architecture was developed to allow flexible designs and further advancements. Initial design generation and comparison were conducted on simplified cases, showing the dependence of space greenhouse designs on astronaut diet and mission scenario. This process underscored the importance of accurate plant databases, encouraging collaborations to enhance this aspect.
A systematic approach to space greenhouse module design was developed, accompanied by the creation of a GitHub platform for open access. Recommendations for Earth-based facilities led to a spin-off project, which was proposed for funding to the European Space Agency (ESA) (though unsuccessful) and is pending with the French National Research Agency (ANR). With no immediate partnership with Interstellar Labs, new collaborations were established with various organizations to apply the methodology to their projects, including the German Aerospace Center (DLR), the Canadian Space Agency (CSA), Plant for Space (P4S, Australia), and the Korean architecture firm Space Group.
A key outcome was the development of a terrestrial application with potential for commercialization and the initiation of new collaborations.
This project enabled the creation of an open-source platform that allows users to calculate the resources needed to design a space greenhouse and compare different technological solutions. It also resulted in a spin-off project focused on a cost calculator for plant-based astronaut diets. The methodology developed in this project will be applied by four major users—space agencies, university consortia, and industry partners—in the development of practical lunar greenhouse systems.
The identified terrestrial application offers an integrated approach to agriculture by leveraging knowledge from space research, plant growth modeling, and optimization tools. This approach aims to address climate-related challenges and supports five of the United Nations’ 17 Sustainable Development Goals.
The identified terrestrial application offers an integrated approach to agriculture by leveraging knowledge from space research, plant growth modeling, and optimization tools. This approach aims to address climate-related challenges and supports five of the United Nations’ 17 Sustainable Development Goals.