Modeling and Validation of the Ambient and Variable Pressure Growth Chamber Models

Edeen, Marybeth A.; McFadden, Carl D.; Miller, Adam

doi:10.4271/932171

Cited by 8 publications

(2 citation statements)

References 4 publications

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“…The crops also produce biomass when they are harvested. The production and consumption of resources are modeled according to [5], [6], and [7].…”

Section: Biomass Modulementioning

confidence: 99%

“…The biomass module has its own environment that contains an atmosphere for the plants. The default configuration has separate biomass and crew environments because the ideal gas composition for growing plants is different from the safe gas composition for people [5]. Because the simulation is reconfigurable it can be initialized with a single environment for crew and crops or with multiple environments for different crops.…”

Section: Biomass Modulementioning

confidence: 99%

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Simulating Advanced Life Support Systems for Integrated Controls Research

Kortenkamp¹,

Bell²

2003

SAE Technical Paper Series

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This paper describes a simulation of an integrated advanced life support system. It contains models of the major components of an Advanced Life Support (ALS) system including crew, biomass, water recovery, air revitalization, food processing and power supply. The simulation also models malfunctions and stochastic processes. Sensors and actuators are modeled to allow controllers to interact with the simulation. The simulation is designed for testing and evaluation of life support control approaches. We use an example of a simple genetic algorithm to demonstrate how a control application might use the simulation. The simulation is implemented in Java to make it portable and easy to use.

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“…The crops also produce biomass when they are harvested. The production and consumption of resources are modeled according to [5], [6], and [7].…”

Section: Biomass Modulementioning

confidence: 99%

Section: Biomass Modulementioning

confidence: 99%

Simulating Advanced Life Support Systems for Integrated Controls Research

Kortenkamp¹,

Bell²

2003

SAE Technical Paper Series

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The human component of an atmosphere regeneration simulation tool

Tichenor

Edeen²

Proceedings 32nd Annual Simulation Symposium

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Reinforcement Learning in the Control of a Simulated Life Support System

Quasny

Pyeatt

2004

SAE Technical Paper Series

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To make extended space missions, such as missions to Mars, a reality, an advanced life support system (ALS) must be developed that is able to utilize resources to their fullest capabilities [2]. In order to make such a system a reality, a robust control system must be developed that is able to cope with the complexity of an ALS. This work applies reinforcement learning (RL), a machine learning technique, to the task of controlling the water recovery system of a simulated ALS. The RL agent learns an effective control strategy that extends the mission length to the point that lack of water is no longer the cause of mission termination.

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Modeling and Validation of the Ambient and Variable Pressure Growth Chamber Models

Cited by 8 publications

References 4 publications

Simulating Advanced Life Support Systems for Integrated Controls Research

Simulating Advanced Life Support Systems for Integrated Controls Research

The human component of an atmosphere regeneration simulation tool

Reinforcement Learning in the Control of a Simulated Life Support System

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