Abstract

Nowadays, the trend in lunar exploration missions is shifting from prospecting lunar surface to utilizing in-situ resources and establishing sustainable bridgehead. In the past, experiments were mainly focused on rover maneuvers and equipment operations. But the current shift in trend requires more complex experiments that includes preparations for resource extraction, space construction and even space agriculture. To achieve that, the experiment requires a sophisticated simulation of the lunar environment, but we are not yet prepared for this. Particularly, in the case of lunar regolith simulants, precise physical and chemical composition with a rapid development speed rate that allows different terrains to be simulated is required. However, existing lunar regolith simulants, designed for 20th-century exploration paradigms, are not sufficient to meet the requirements of modern space exploration. In order to prepare for the latest trends in space exploration, it is necessary to innovate the methodology for producing simulants. In this study, the basic framework for lunar regolith simulant development was established to realize this goal. The framework not only has a sample database and a database of potential simulation target compositions, but also has a built-in function to automatically calculate the optimal material mixing ratio through the particle swarm optimization algorithm to reproduce the target simulation, enabling fast and accurate simulant development. Using this framework, we anticipate a more agile response to the evolving needs toward simulants for space exploration.

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