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A Systems Analysis of Life-Support Systems in Space Travel

Ryan is currently studying for his master's degree in Systems Engineering at Drexel University, participating in several discussions weekly.

The Importance of a Systems Perspective

Systems engineering, while a relatively new field, is already showing its importance in the aerospace scene. When it comes to leaving Earth’s atmosphere, the profession reaches an entirely new level of necessity, as all the systems immediately become more complicated, as the stakes are raised.

Systems engineers have to plan for surprises and make their systems resilient. A prime example of this is the life-support system on any rocket, shuttle, or space station. In space, the life-support system has to be self-sustaining and be able to recycle many of its components. This introduces many feedback loops and minimal outputs in order to keep the system functional for as long as possible.

Diagram 1

Diagram 1

Modeling in the International Space Station (ISS)

Modeling and testing provide vital insights into how a system (or systems) may perform under certain conditions. The conditions can range from drastic changes to the system to minimal use over a long period of time. Either way, knowing how a system responds to feedback and external forces is crucial to producing a reliable product.

In the case of a life-support system, many models explore the potential results of a piece of technology breaking. If oxygen can’t be produced fast enough (or at all), how long does the crew have to fix the problem? In space, there are many levels of redundant safety. These models show what needs to happen in the case of a surprise.

Some measures the controlling organization may take involve installing more systems (such as more air generation machines) and running more frequent tests to assess the stability of the system. Monitoring the closed-loop clean-water levels reassures the astronauts that they are not losing water. This is where the resilience of a system comes in. If an astronaut drinks more water, urinates more, and/or showers more, how effective is the system at returning to the ideal level? When an astronaut exercises, how effective is the system at producing more oxygen to make up for the astronaut's higher intake?

Models like these are also an effective way of dealing with surprises. In the event of a gas leak on the International Space Station (ISS), procedure involves moving to the other side of the station and sealing it off before further action is taken, according to Terry Verts, a former astronaut who was on the International Space Station when this happened.

A frequent surprise in systems, despite being predicted, is delays. In the case of the life-support system, delays come from machines taking time to work. It takes time to move resources or gases throughout the system, and it takes even more time for the process to occur and the gas to be sent back out into circulation. The power in the batteries comes from solar power, so when the ISS is on the other side of the planet, there is a delay before they can recharge.

Communication with Earth is pretty much instantaneous for the ISS, but when space travel takes mankind to the further reaches of space, there will be a very long wait between messages being sent and received. Additionally, in instances like the one Terry experienced, there is a delay while engineers on the ground try to figure out what actions to take moving forward in the event of a failure.

Minimizing delays is frequently vital to the success of a system and to help it run smoothly. Models help plan for system performance and can provide a guideline as to how the system should be behaving.

The system can also be observed as a network. The physical part of the system is a network of machines, with gases and water linking the nodes. The electrical part of the system is composed of sensors and computers and is a network of communication and data.

The network is so tightly knit that it is possible to connect any one node with another in three or four linkages. Similarly, the connection between the various systems on the spacecraft makes network mapping pretty straightforward and clear. As Mobus describes it, “network analysis will thus help us comprehend systems whether they are physical, conceptual, or a combination of both” (Mobus 141).

Engineers will certainly use network mapping to analyze systems in the future, as it is an easy way to organize a system. Networks account for the number of nodes of a certain kind in a system, so engineers can use this information to decide whether or not more of a specific machine is needed.

In combination, all of these methods of mapping and measuring systems contribute to systems engineering and the prognostication of the given system. Engineers can predict the effect on the system if additional astronauts were introduced and make adjustments to the rate at which oxygen is generated. The boundaries of a system can be expanded to include astronauts training on Earth, which can have an effect on the length of delays (more delay if less educated, less delay if more educated).

Based on feedback, organizations can put more or less emphasis on certain courses when training astronauts. Mobus, in chapter 13.6.2 of Principles of Systems Science, emphasizes that “if there is one message [the authors] hope has been conveyed in this book, it is that real systems in the world need to be understood from all perspectives” (Mobus 696). When it comes to a system like life support, this is all the more true. Mapping networks of information between machines can assess performance, while observing hierarchies of NASA, SpaceX, and other space administrations and companies around the globe can streamline the decision-making process and speed up production.

Mapping the dynamics of the system over time can help not only predict the future but inspire processes that account for surprises. Modeling system performance before application can improve the system, as errors are discovered, accounted for, and corrected before it’s too late. Drawing diagrams of systems allows an engineer or analyst to not only see the connections between components but to understand how they work together to make the system whole.

Graph Analysis

One of the many systems that are constantly and closely monitored is the oxygen (O2) system. Graph 1 shows how oxygen levels deplete over the course of months while in the International Space Station (without specific numeral data—this visualizes the behavior).

The initial spike represents a delivery of oxygen gas from the planet to the space station. While most oxygen is recycled, shown by the close-to-horizontal points on the graph, oxygen is lost during experiments performed by the crew and every time the airlock is depressurized. That is why there is a downward slope to the data, and each time it goes up is representative of either the process of hydrolysis and obtaining oxygen from water or a shipment of more gas from the surface of the planet. At all times, however, the oxygen supply is well over what’s needed, and NASA never lets it fall anywhere near dangerous levels.

The line modeling CO2 levels shows that, with minor deviation, the levels of carbon dioxide remain somewhat constant. The only source of it is astronauts exhaling, and it is collected and split into atoms, with the oxygen atoms combining with leftover hydrogen atoms from oxygen generation to make water, and the carbon atoms combining with hydrogen to make methane before being vented overboard. The process is balanced so that CO2 levels never reach a dangerous amount.

Graph 1

Graph 1

Graph 2 is representative of the ideal behavior of the clean water levels aboard the station. As a closed loop, no water should leave the system. Water that astronauts drink is recycled after they urinate and sent back into the system. Water is used to make oxygen, and any leftover hydrogen atoms are combined with the oxygen from carbon dioxide to form water once again.

As stated before, this graph represents the ideal behavior of the system. This could be used as a model that scientists would try to achieve upon improving equipment and collection techniques. In reality, the graph would have a small decline, as hydrogen is lost in trace amounts through methane that humans exhale and sweat after a workout, which usually reabsorbed into the body, although some is sure to escape into clothing.

Graph 2

Graph 2

The Bigger Picture

All in all, modeling is a vital way of planning ahead and analyzing results in interdisciplinary fields and is not limited to engineers and scientists. Businesses often approach new products with a system mindset to optimize their profit, and people running for elections often model data from surveys to know where to campaign and what topics to cover.

Everything a person interacts with is either a system or a product of a system—usually both! Even writing a term paper or an article is a system. It’s modeled, energy is put in, it receives feedback, and it produces a product. It can contain more or less information, depending on where the author places the boundaries. There is delay due to busy schedules and, naturally, procrastination.

Despite the many differences in various systems, they all have the same fundamental qualities. A system is made up of interlocking components that contribute to each other to work toward a common goal.

Thinking with a system mindset allows one to view the bigger picture and allows for an understanding of how an event happening to one thing can have an unforeseen effect on something else. Ideally, every company and engineer would use a systems-thinking approach in their endeavors, as the benefits cannot be overstated.


  • Meadows, Donella H., and Diana Wright. Thinking in Systems: a Primer. Chelsea Green Publishing, 2015.
  • Verts, Terry. “Speaking.” View From Above. View From Above, 17 Jan. 2019, Philadelphia, Kimmel Center.

This content is accurate and true to the best of the author’s knowledge and is not meant to substitute for formal and individualized advice from a qualified professional.

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