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SIMOC is an interactive model of a scalable, human community located on a remote planet or moon. It provides a novel integration of an agent-based model built upon data from real-world, closed ecosystem studies at NASA and universities world-wide with a platform for research, citizen science, and game play. The goal is to design a habitat that sustains human life through a combination of physio-chemical (machine) and bioregenerative (plant) systems.
Sound simple? Science fiction has made it look far too easy with airlocks that never require decompression, food materializing out of thin air, and terraforming in a matter of hours, not thousands of years. In the real cosmos, living off-world is far more challenging. Finding a balance of machines, plants, algae, and humans is a complex endeavor. The slightest incongruity in waste management, power production, or CO2 scrubbing can result in catastrophic failure and abandonment of the habitat, or worse.
While research analogs have for more than 50 years conducted research in this field, the solutions for living in space remain heavily biased toward mechanical systems, machines and freeze-dried food to keep the humans alive. This is not a long-term solution, not if we desire to move off this planet and establish new homes among the stars. SIMOC is a place to experiment, test theories and make mistakes, and to explore.
What is the best balance of physio-chemical and bioregenerative systems? What can we learn about the resources required to effectively scale a habitat tens of millions of kilometers from home? What systems will self-sustain while others break down?
Perhaps you will find the answers …
A still of the 3D environment in which SIMOC users visualize their designed habitat
The Phase II release of SIMOC has a fully rebuilt back-end server, designed to be hosted on a single laptop or across a widely distributed cloud computing network. The fully rebuilt web interface provides an elegant means to log in, configure the mission, and then monitor its progress during the full simulation. In addition, researchers may elect to run SIMOC from the command line, enabling multiple, parallel simulations each with a unique configuration. The data may be collected and analyzed no matter the interface used.
The agent based model itself is incredibly agile, with each agent defined by a user engaged file, either directly or through a web-based editor. While most users will configure a simulation using existing agents, advanced users can define unique characteristics for life support systems, plants, and power production modules.
As of the start of November, the SIMOC Phase II beta is being tested and refined. The team intends to deliver a public-facing product in early 2019. Stay tuned!
Kai Staats Project Lead
Judd Bowman Associate Lead
Danny Jacobs Associate Lead
Sheri Klug Boonstra Associate Lead
Don Boonstra Educational Lead
Iurii Milovanov Developer
Greg Schoberth Developer
Thomas Curry Developer
Joey McCord Environmental Engineer
Bryan Versteeg Habitat Architect and 3D Artist
Christopher Murtagh Systems Administrator
Jake Fedie Website Manager