At the International Conference on Environmental Systems (ICES) 2019, Kai Staats, project lead for the Interplanetary Initiative pilot project SIMOC will present the procedure and findings of the barley growth experiment conducted at the Biosphere 2, Feb-Mar 2019, with an emphasis on the non-linear functions developed for SIMOC.
Title: An agent-based model for high-fidelity ECLSS and bioregenerative simulation.
Abstract: Mathematical models can combine baseline assumptions about relatively simple, real-world systems into complex simulations, providing researchers with access to otherwise difficult to build or cost prohibitive environments. An agent-based model (ABM) employs the actions and interactions of individual and collective, autonomous agents such that their behavior, when allowed to unfold over a specified time, may exhibit non-linear, dynamic, and probabilistic behavior. SIMOC (a scalable, interactive model of an off-world community) is a Python agent-based model with both a research and educational component, developed to simulate hybrid ECLSS and bioregenerative closed systems, as those considered for long-term human habitation of the Moon or Mars. The SIMOC web-based agent editor enables rapid design of new agents to approximate real-world systems. While SIMOC was built upon data for both humans and plants extracted from the NASA Baseline Assumptions and Values Document, this publication sees first application of this novel approach to modeling the growth cycle of a single plant species in a semi-sealed, controlled environment, from seed to harvest, tracking air temperature, relative humidity, PAR, carbon dioxide, water run-off and biomass accumulation.