Space Transportation Network Model for Rapid Lunar Architectures Analysis

Paper number

IAC-06-D2.7.-A3.7.09

Author

Mrs. Gergana Bounova, Massachussets Institute of Technology (MIT), United States

Coauthor

Dr. Olivier de Weck, Massachussets Institute of Technology (MIT), United States

Year

2006

Abstract

The challenge of space exploration is to do technologically and cost efficient short and long-term missions. With uncertainty in funding and public support, countries with space programs need to ensure program sustainability, especially for faring to the Moon by 2018. The next challenge is integrating new technologies in a traditionally slow development and testing industry. It is difficult and expensive to validate and test new technologies independently in a remote space environment. Often design decisions are made early and critical options are missed. To aid the early design process, we propose a systems engineering mathematical approach to exploring rapidly all architectures with various technology switches to a moderate level of engineering detail.

  The space transportation network model consists of abstract spacecraft states during a lunar mission, such as planetary surfaces (Earth, lunar), orbits (LEO, cislunar, LLO, around a Lagrange point) and operational-sequence states like descent and ascent, launch and re-entry. The latter are modeled as discrete states with timelines similar to the Apollo and Soyuz descent/ascent profiles. 
  In a state, the spacecraft expends fuel for attitude control, stationkeeping or trajectory correction burns and has power-related activities. States are modeled as continuous-discrete blocks with varying discretized time steps. For example, launch and ascent/descent take on order of 10 minutes to 60 minutes, whereas orbiting takes order of hours, and surface exploration - order of days. State transitions are usually related to an instantaneous fuel burn. Surface operations are not modeled in detail except for considering science and mobility payload and ISRU fractions. A surface habitat is designed at the same level as other in-space, descend, ascent and (combinations of) habitats. 

  Architectures are generated by considering all possible (sensible) paths from a node to node and then assigning all combinations of vehicle fleets that satisfy the mission requirements. Around 20000 architectures, of varying degrees of similarity, feasibility and interest, are generated. The number is high because of the Lagrange point analysis and vehicle combinatorics. Rankings of vehicle mass breakdowns, vehicle types, mission launch weight and other data is available. Analysis of key technologies such as propulsion types, engine types, materials and in general transportation scenarios and vehicle combinations is included. Multiple stakeholder value and technology trade-off analysis is possible. The network description allows to identify key staging locations in space and select enabling technologies for investment. 

Abstract document

IAC-06-D2.7.-A3.7.09.pdf

Manuscript document

IAC-06-D2.7.-A3.7.09.pdf (🔒 authorized access only).

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