Research & Development

This summer is seeing many exciting updates for SIMOC, with an in depth story for each coming soon!

• The SIMOC Live development team continue to improve the code and test the platform, with the original and new 64-bit Raspberry Pi Zeros tested and functional.
    
• Several new Adafruit sensors are being tested, including light intensity, a microphone, and IR sensor for proximity awareness. The goal is to give SIMOC Live the ability to capture movement inside a habitat such that the approximate location of the crew members can be correlated to CO2 levels in each room, but without video capture or individual identity tracking.
    
• An Adafruit GPS and accelerometer are being tested as well, looking to a future in which SIMOC Live may be redesigned as a hand-held unit or deployed in a pressure suit during EVAs.
    
• The Arizona Science Center is installing an interactive SIMOC Live kiosk! More to come, soon!
    
• The Analog Astronaut Conference has accepted our proposal for SIMOC Live to be deployed in each of the nine habitats world-wide as a ELCSS monitoring system. While each habitat already has some level of air quality monitoring, the installation of SIMOC Live across the entire domain will provide a singular data format and seamless, (delayed) real-time monitoring from the central Mission Control Center.
    
• Ezio and Franco will venture to Poland to install SIMOC Live at the famous Lunares habitat analog for their upcoming mission for the month of September. This will be a proof of concept for remote monitoring of a habitat beyond SAM.  
• The National Science Teachers Association will soon publish a feature article about SIMOC—stay tuned!

Again, each of the above will be expanded into individual photo essays … stay tuned!

The new SIMOC Live version 2.0 now incorporates an ad hoc, mesh network, with full data redundancy across all nodes. Sensor arrays built on a Raspberry Pi Zero and Adafruit sensors captured data in each of the four primary nodes of SAM: lung, Test Module, Engineering Bay, and Crew Quarters.

More photos, data, and a complete story coming soon!

For now, visit samb2.space/blog …

Lead developer of SIMOC Ezio Melotti arrive to SAM at Biosphere 2 mid February. He receive Christopher Murtagh, Systems Architect and colleague of Kai Staats for more than twenty years. Together they built the point-to-point wireless feed from the SAM Operations Center to the Mars yard and into the SAM habitat analog. Chris built a new version of the SAM light-travel time delayed email server while Ezio continued to fine tune the form and function of the latest build of SIMOC Live and its sensor array.

Chris departed and Franco Carbognani arrived, a Sr. Engineer at the VIRGO gravitational wave observatory to work with Ezio on the SIMOC Live ad hoc, full mesh sensor array. This is a vast improvement on the version installed in SAM for the first two crew in that a unique sensor array will now be placed in the SAM lung, Test Module (green house), engineering bay, and crew quarters for a 4x increase in data generation and fidelity in air quality analysis.

To learn more, visit SAM …

As we move into 2024 we simultaneously look forward to our ongoing work in this current development cycle, and what we accomplished in the prior years. As with any open source computer software project, the team continues to shift and reform with some steady, stable members and others who contributed as they were able and then move on.

This brings us into our seventh year of SIMOC development! I first conceived of the project as my Masters research in 2014 but did not actually dive in for three years until attending the International Space University SSP in Cork Ireland simultaneous to two years funding from Arizona State University. This team has enjoyed additional support at the University of Arizona, Biosphere2, and now four years support by the National Geographic Society. We have taken SIMOC into directions I could not have envisioned in 2017 and surely, a few years from now, I will say something similar.

As a project lead my greatest joy is when SIMOC takes on a form and function motivated by one of my team members, and a velocity far greater than I could do on my own. Yet, I am never truly satisfied. My vision and that of my team members is always greater than what are engaging at any given moment. That’s what drives us forward.

As we look to 2024 we see an opportunity to slow down a bit in the actual writing of code and focus more on the quality of our website content, educational material, and guides for developers who will take SIMOC in even directions our own team did not consider.

While this blog may sometimes be left to ponder on its own for several weeks, even a few months at a time, our development team remains engaged with two meetings each week, more than 800 meetings to date.

Do you have talent in Python programming? Do you enjoy creative writing and web content generation? Want to help bring SIMOC into classrooms around the world? We’d love to hear from you …

The Agent-Based Model (ABM) at the heart of SIMOC has been rewritten from scratch for consistency and speed. Over the years, many individuals had contributed to the SIMOC ABM, each bringing their own programming skills and vision for how SIMOC could develop into the future. Now, as we take SIMOC open-source, it’s a good time to remove inconsistencies and establish norms going forward.

Some key features of the updated ABM are:

• A single agent schema is used throughout the entire application: defining the agent, defining the configuration, initializing the ABM, exporting data and saving the ABM. This will greatly reduce the learning curve for new-comers.
• All agent parameters are stored as either `properties` (static, e.g. ‘harvest_ratio’) or `attributes` (dynamic, e.g. ‘daily_growth_factor’). Besides streamlining the code, this will make the SIMOC web app compatible with custom agents out-of-the-box.
• Unit testing and documentation are incorporated from the start.

We’re seeing up to 85% speedup for large simulations, meaning it’s much faster for users and the demand on our servers is lower.

Altogether, the new ABM is a tremendous upgrade for our users, and puts us on a better footing for long-term growth and collaboration.

The SIMOC development team has just a few, finishing touches to apply to the code and documentations before providing both the back-end server (Agent-Based Model, or ABM) and front-end client (Dashboard) available via the GPL3 and Community Commons licenses, respectively.

We are eager to take six years of development and provide it to you, for free, to gain your input, ideas, and ultimately improved code.

Stay tuned!

For better or for worse, all modern homes, offices, and classrooms are fairly tightly enclosed to reduce energy loss. This results in greater than outdoor ambient carbon dioxide levels, higher than most people realize. With ambient global CO2 at 420 parts per million (ppm) it is not unusual for an indoor, occupied space to be well over 1000 ppm, sometimes 1500, 2500, or more. Offices, classrooms, conference halls, even your dining room with a family gathering are in these higher ranges for extended periods of time.

OSHA suggests that the upper, safe limit is exposure to 5000 ppm for up to 8 hours. The International Space Station operates between 3000 and 6500 ppm. And the US Navy submarines are unconfirmed to operated as high as 10,000 ppm. There is little evidence to suggest that any short- or long-term health issues are associated with the upper ranges of CO2 for brief (a few hours) exposures. The astronauts on the ISS live with 5000 ppm for up to a year. While some research shows reduced cognitive function (e.g. math problem solving), there are is no risk of long term damage.

As SAM is hermetically sealed, we must monitor the CO2 levels even more carefully than in our homes, schools, and places of work. While an office might rise over 1500 on a frequent basis, the door is likely being opened, with people moving in and out with the effect of mixing the air.

For these first two mission, SAM is operating in Mode 2 (pressurized, flow-through). The crew is able to adjust valves in the Test Module, airlock and crew quarters and then the speed of the in-bound blower. The combination of the two affects the overall carbon dioxide in SAM.

Crew Inclusion I reached out on Day 2 with concern for the rising CO2. Director of Research Kai Staats logged into the SIMOC Live server to retrieve the data to that moment. SIMOC Live captures carbon dioxide, oxygen, relative humidity, temperature, pressure, and a number of other values for the duration of the mission. This data is exported to a local .csv file which the SIMOC-SAM team members can copy through a data backdoor that bypasses the router which limits crew to email only.

As with all time-series data, it takes a full cycle (in this case day-night-day) to recognize a trend. Indeed, the initial rise in CO2 climbed over 2500. This is nothing to be concerned about, but the crew wanted to bring it down, in part to demonstrate their ability to control the quality of air.

Crew Inclusion I worked extensively with SAM Mission Control to monitor and maintain the carbon dioxide levels. Crew engineer Bailey Burns conducted spot assessments of CO2 throughout the habitat while the SIMOC Live sensor array was capturing a time series dataset from closure to the end of the mission. Bailey’s data confirmed the air flow from SAM Lung to TM to Engineering Bay to Crew Quarters with an increasing density of carbon dioxide.

Mission Control advised that the sound muffler be removed from the outlet at the end of the crew quarters and an additional port be opened in the airlock. While the airlock is not at the termination of the designated airflow path, it does invoke the need to increase the blower in order to keep the lung at a nominal height, and therefore is in fact moving more air with the effect of bringing overall CO2 levels down.

In response to the crew’s request for assistance, acting CapCom Kai Staats wrote, “You have done well to reduce your carbon dioxide over the past two days. You started at roughly 700 ppm (due to all the activity inside SAM prior to entry) and rose to nearly 3000 ppm which is when you reached out for guidance. The day/night activity/sleep cycle is clearly present with a leveling of CO2 while you sleep. But overall, the trend has been down with a reading this morning of just under 1000 ppm. According to the data, you rose at 6 am.”

(see plot above for associated data points and graphical narrative)

The temperature held relatively steady, between 20 and 25C, with a dip to 16C the first night. The relative humidity ranges from 30% to 70%, clearly following a day/night cycle. This is due to “relative” humidity as a measure of moisture in the context of changing temperature, and therefore density of air. But is also due to the fact that at night the A/C units stop running their condensers, therefore the dehumidification function terminates and the humidity rises until the temperature is again high enough to activate the cooling cycle.

In the end, Crew Inclusion I was able to control their CO2 levels effectively (as demonstrated in the graph above). Given initial concerns for CO2 levels, the SAM team now realizes the importance of asking our visiting research crew to reduce their caffeine and processed sugar intake prior to arrival to SAM.

The SIMOC developer team is preparing to open source the entire platform, from back-end server to front-end web client so that developers, educators, and citizen scientists too can benefit from this unique, powerful agent-based model and simulation around the world, for free.

Stay tuned!

by Grant Hawkins, lead developer for SIMOC B2 at Over the Sun, LLC

The final step of integrating Biosphere 2 into SIMOC was validating the outputs. From the beginning, we’ve focused on telling the story of oxygen depletion during Mission 1, as described in the paper Oxygen Loss in Biosphere 2, published in 1994. This paper describes the overall O2 and CO2 behavior within B2 for the first ~18 months of Mission 1, as well as the rates of O2 and CO2 consumption and production for key agents such as the concrete and soil.

First, we compared overall levels of O2 and CO2 throughout the mission:

We also compared net effects of processes specified in the paper:

These figures help us identify where the model is reliable, and where it needs to be improved. Below is the ‘Discussion’ section of a paper we’ve written on this process:

The results of the simulation are directionally accurate, but with a low degree of precision. Relatively few measurements of plant productivity are available from the B2 experiments, and SIMOC’s other validation reference is a highly dissimilar experiment. To improve precision of the plant model, we make the following recommendations:

• Include fruit trees and other perennial plants in addition to vegetables. These made up a large part of the B2 crew’s actual diet, and follow a different growth cycle.
• Model the impact of specific pests and parasites. As records allow, match periods of low productivity for specific plants with their causes – most often fungi or mites. In the case of corn, no edible food was produced in Mission 1a and 1b because it is wind-pollinated, and there was no wind inside the structure. This and other species-specific behaviors could increase the accuracy as well as the educational potential of SIMOC.
• Include some metric of human wellness besides simple survival. Some of the difference in plant productivity between Missions 1 and 2 can be attributed to crew energy levels and morale. Taking into account nutrition, workload, variety of diet, etc. and giving an overall indication of crew’s well-being will be useful in optimizing these systems, and for making the simulations more engaging.

Despite this imprecision, the measured system-level behaviors of the B2 missions are observable in the simulation. By making adjustments the base configurations, users can also observe the following phenomena:

• Plant growth can be increased by adding supplemental lighting (at the cost of increased electric consumption), or decreased by reducing CO2 setpoint to <700ppm.
• Crop layouts can be adjusted to add higher-yield crops, or crops which transpire and photosynthesize at different rates, affecting overall gas balances.
• The starting concrete carbonation rate can be adjusted, which affects the rate at which it consumes CO2. This is also affected by the ambient CO2 levels, with lower rates of carbonation when CO2 levels are lower.
• Adjusting the areas of each biome impacts (1) the size of the air sink, and therefore the overall changes in concentrations, (2) O2 and CO2 exchanges, as each biome has a different rate.