Seismic Site Effect Investigation for Future Moonquake-Resistant Structures by Considering Geometrical and Geotechnical Characteristics of Lunar Bases
Bibliographic record
Abstract
The near-surface lunar characterization and seismic site effect analysis plays an important role in the establishment of future human colonization on the Moon. NASA, CSA, and other agencies are following an ambitious program to “go to the Moon to stay, by 2024.” The seismic experiments data collected during the Surveyor, Apollo, and Luna missions provided preliminary information of the lunar inner structure and corresponding mechanical properties. The collected seismic data can be used to generate a dispersion image of the lunar subsurface. In this paper, the mechanical properties of each layer are determined firstly through the proposed surface wave inversion algorithm. The inversion applies the spectral element method and the trust region method, which effectively reduces the difference (Euclidean distance) between the measured and predicted data. Then, a two-dimensional (2D) seismic site effect analysis is performed based on the predicted lunar soil properties using HYBRID FE/BE numerical code. The seismic responses are obtained for various predefined geometrical points at the Moon surface. The results can be used as a preliminary seismic site effect evaluation for future resilient infrastructure subjected to impact or moonquake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".