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.