1 Matrix Methods for Optimal Manifesting of Multi-Node Space Exploration Systems

• Main Authors: Paul T. Grogan, Afreen Siddiqi, Olivier L. De Weck
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: ci = cargo capacity of; South Pole; South pole
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.663.2699; http://strategic.mit.edu/docs/2_38_JSR_MatrixManifesting_final.pdf

This paper presents matrix-based methods for determining optimal cargo manifests for space exploration. An exploration system is defined as a sequence of in-space and on-surface transports between multiple nodes coupled with demands for resources. The goal is to maximize value and robustness of exploration while satisfying logistical demands and physical constraints at all times. To reduce problem complexity, demands are abstracted to a single class of resources and one metric (e.g. mass or volume) governs capacity limits. Matrices represent cargo carried by transports, cargo used to satisfy demands, and cargo transferred to other transports. A system of equations enforces flow conservation, demand satisfaction, and capacity constraints. Exploration system feasibility is evaluated by determining if a solution exists to a linear program or network flow problem. Manifests are optimized subject to an objective function using linear or non-linear programming techniques. In addition to modeling the manifesting problem, a few metrics such as the transport criticality index are formulated to enable analysis and interpretation. The proposed matrix manifest modeling methods are demonstrated with a notional lunar exploration system comprised of 32 transports including 8 cargo and 9 crewed landings at an outpost at the Lunar South Pole and several surface excursions to Malapert Crater and Schrodinger Basin. It is found that carry-along and pre-positioning logistics strategies yield different manifesting solutions in which transport criticality varies. For the lunar scenario, transport criticality is larger for a pre-positioning strategy (mean value of 3.02) as compared to an alternative carry-along case (mean-value of 1.99).