Parametric Optimization and Prediction Tool for Lunar Surface Systems Excavation Tasks, Phase I

Honeybee Robotics proposes to develop a software tool for facilitating lunar excavation system trades in support of selecting an optimal architecture. This will provide engineers with the ability to quickly examine "What if?" scenarios within a trade space by specifying an excavation architecture and receiving data and graphs evaluating that architecture's performance in terms relevant metrics, such as total energy used or total duration. Excavation tasks supporting outpost development and lunar ISRU will require moving hundreds to thousands of tons of regolith per year. Moving this much regolith will require substantial machinery, but transportation costs on the order of $50K to $100K per kilogram to the surface of the Moon make it an economic necessity to make optimal use of lunar excavation equipment. An architecture that saves a few thousand kilograms in equipment will save hundreds of millions in program dollars a substantial return on investment. This software aims to be (a) user friendly, (b) relevant to LSS's priorities, and (c) accurate for lunar excavation. Phase 1 will address user-friendliness, relevance, and the theoretical side of accuracy. Phase 2 will expand the tool's relevance to a larger trade space, and attack selected gaps on the empirical side of accuracy. This tool will be based on the very best models and data available, and will benefit from the knowledge and experience of both Dr. Kris Zacny, the Principal Investigator, and Dr. David Carrier, a subcontractor in this effort. Phase 1 will result produce the basic framework for the software, which will be capable of performing analyses for a selected set of excavation scenarios. Phase 2 will then add depth to that framework to address a wide range of excavation tasks and tools, and will involve experimentation to validate and fine tune the software.

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Maintainer TECHPORT SUPPORT
Last Updated July 30, 2019, 23:05 (CDT)
Created July 30, 2019, 23:05 (CDT)