Simulation of the MELiSSA closed loop system as a tool to define its integration strategy

Abstract

Inspired by a terrestrial ecosystem, Micro-Ecological Life Support System Alternative (MELiSSA) is a project focused on a closed-loop life support system intended for future long-term manned missions (Moon and Mars bases). Started by the ESA in 1989, this 5-compartment concept has evolved through a mechanistic engineering approach designed to acquire both theoretical and technical knowledge. In its current state of development, the project can now start to demonstrate the MELiSSA loop concept at pilot scale. Thus, an integration strategy for a MELiSSA Pilot Plant (MPP) has been defined, describing the different test phases and connections between compartments. The integration steps are due to be started in 2008 and completed with a complete operational loop in 2015. The ultimate objective is to achieve a closed liquid and gas loop fulfiling 100% of oxygen requirements and at least 20% of food requirements for one-man. Although the integration logic could start with the most advanced processes in terms of knowledge and hardware development, this logic needs to be expanded to encompass a high-level simulation policy. This simulation exercise will make it possible to run effective demonstrations of each independent process, followed by progressive coupling with other processes in operational conditions mirroring as far as possible the final configuration. The theoretical approach described in this paper is based on mass balance models of each MELiSSA compartment which are used to simulate each integration step and the complete MPP loop itself. These simulations will help identify criticalities in each integration step and check consistency between objectives, flows, recycling efficiencies and sizing of the pilot reactors. An MPP scenario compatible with current knowledge on the operation of the pilot reactors was investigated, and the theoretical performances of the system were compared against the objectives assigned to the MPP. This scenario makes it possible to highlight the most important integration milestones and simulate their behaviour.