Application of Supply Chain Optimization and Protocol Environment Architecture to ALS Modeling and Visualization

Michael Lasinski
James F. Russell
Seza Orcun
Joseph Pekny
Raj Arangarasan
Meiqi Ren
Kenny Redman
Jimmy Stine

Document Type Article


A significant amount of software has been developed to model the advanced life support aspects of a Mars surface habitat. Models, such as the BIO-Plex Baseline Simulation Model (Finn, 1999), have been useful in studying advanced life support systems. These models have been used to conduct trade study comparisons to determine which Advanced Life Support (ALS) technologies should currently be used in a habitat design. However, the present models and approaches require significant overhead to exchange one technology for another mostly because the models are mission centric and assume either that the habitat will be stationary or that the life of the habitat will be same as the mission duration. In other words, these models lack the desired level of modularity necessary to quickly complete multiple trade studies of different missions as the habitat evolves from mission to mission. The XML-based (Extensible Markup Language) Supply Chain Optimization and Protocol Environment (SCOPE) architecture provides a mechanism to achieve the required level of plug-and-play capability. SCOPE has previously been used to study policy interactions within several different supply chain networks (Orcun et. al). In this work, the SCOPE methodology is applied to a Mars surface habitat simulation without optimization. This results in a network of components such as crew members, storage, and ALS technologies. Each component is represented as a self-contained node in the network. For each node, there is an XML description of the required material inputs and outputs. The simulation engine interprets each description to form the entire network and to properly handle the interactions between each node in the network. In this work we will present a preliminary implementation of this architecture for habitat analysis and three case studies that demonstrate the challenges of habitat evolution. We also describe a virtual environment that visually displays the results from the simulation architecture.