Affiliation:
1. Georgia Institute of Technology, Atlanta, Georgia 30332
Abstract
As space exploration moves toward long-duration, sustainable campaigns, operations such as in-space rendezvous, multiple launches, and in-space rendezvous or In-Situ Resource Utilization plants complicate campaign planning. The field of spaceflight logistics has been developed to perform the logistical planning for these new campaigns in an automated manner. Though previous tools have included aggregated vehicle concepts consisting of multiple vehicles, they have key limitations that may not be able to assess campaigns with more complex vehicle architectures and mission operations. This works aims to address these limitations by formulating a method to include independently operating vehicles that can also operate as an element within a larger stack across various different mission segments. Because of the use of the path-arc formulation, the optimizer has the flexibility to decide to use the independent vehicle stages independently, or within a stack. To prove the usefulness of this formulation, the methodology will be applied to a sample case that uses some of these aggregated space vehicles. In particular, a case study of a government reference Human Landing System mission will be used due to its inclusion of aggregated space vehicles.
Publisher
American Institute of Aeronautics and Astronautics (AIAA)
Subject
Space and Planetary Science,Aerospace Engineering
Reference20 articles.
1. Campaign-level dynamic network modelling for spaceflight logistics for the flexible path concept
2. IshimatsuT. “Generalized Multi-Commodity Network Flows: Case Studies in Space Logistics and Complex Infrastructure Systems,” Ph.D. Dissertation, Massachusetts Inst. of Technology, Cambridge, MA, 2013.
3. Concurrent Design of Scientific Crewed Space Habitats and Their Supporting Logistics System
4. ChenH. “Interdisciplinary Space Logistics Optimization Framework for Large-Scale Space Exploration,” Ph.D. Dissertation, Georgia Inst. of Technology, Atlanta, GA, 2021.
5. Event-Driven Network Model for Space Mission Optimization with High-Thrust and Low-Thrust Spacecraft