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Development of an Achievability Propellant Limit Algorithm for a Piloted, Lunar Lander Public Deposited

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https://scholar.colorado.edu/concern/articles/tx31qk076
Abstract
  • Although all six Apollo lunar landings were successful, the multiple landing site redesignations and landing near hazards suggest crewed planetary landings can be challenging and demand high pilot workload. To assist with landing site selection, the concept of providing “achievability limit” information (that is, where on the planetary surface is landing achievable with the vehicle’s remaining energy) to the pilot has been proposed. However, an approach to accurately estimate the achievability limit for a complex three-dimensional planetary landing task has not yet been developed. An algorithm was developed to estimate the achievability limit that is generalizable to future planetary landings. The algorithm combines three components: 1) vehicle guidance laws, 2) vehicle and environmental dynamics, and 3) a simplified “crossover” pilot model. The algorithm performs multiple closed-loop numerical simulations to predict the propellant remaining to reach various landing points to identify the zero-propellant-remaining points that define the achievability limit area. Here, the algorithm is described and a sensitivity analysis of input parameters is presented to demonstrate its functionality for a lunar landing scenario. The algorithm is envisaged as being able to run in real time during a landing to provide achievability information for the crew, which improves safe landing site selection.

     

Creator
Date Issued
  • 2020
Academic Affiliation
Journal Title
Journal Issue/Number
  • 3
Journal Volume
  • 57
Last Modified
  • 2022-08-05
Resource Type
Rights Statement
DOI
ISSN
  • 1533-6794
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