Modeling the Mars-Earth Logistics and Transfer Architecture:
Focus on Conducting Inexpensive Exploration through Variance of Key Mission Requirements
Dr. Charles Martin Reynerson
Ball Aerospace and Technologies Corp.
creyners@ball.com
This presentation addresses a concept-level model that produces technical design parameters and economic feasibility information addressing future Mars Exploration platforms. In this context, the platforms considered include those currently chosen in the NASA Mars Design Reference Mission.
This paper uses a design methodology and analytical tools to create feasible concept design information for these space platforms. The design tool has been validated against a number of actual facility designs, and appropriate modal variables are adjusted to ensure that statistical approximations are valid for subsequent analyses. The tool is then employed in the examination of the impact of various payloads on the power, size (volume), and mass of the platform proposed.
The development of the analytical tool employed an approach that accommodated possible payloads characterized as simplified parameters such as power, weight, volume, crew size, and endurance. In creating the approach, basic principles are employed and combined with parametric estimates as necessary. Key system parameters are identified in conjunction with overall system design. Typical ranges for these key parameters are provided based on empirical data extracted from actual human space flight systems.
In order to provide a credible basis for a valid engineering model, an extensive survey of existing manned space platforms was conducted. This survey yielded key engineering specifications that were incorporated in the engineering model. Data from this survey is also used to create parametric equations and graphical representations in order to establish a realistic range of engineering quantities used in the design of manned space platforms. Using this tool a sample Mars exploration architecture is formulated with emphasis on cost minimization through variance of key mission requirements. This paper is based on work Dr. Reynerson recently completed at George Washington University in fulfillment for the degree of Doctor of Science in Astronautics. Dr. Mike Griffin was a member of the dissertation committee.