Establishment and Application of Microseismic Monitoring System to Deep-Buried Underground Powerhouse
Bibliographic record
Abstract
The right bank underground powerhouse of Houziyan hydropower station is a typical deep-buried type with high geostress and complicated geological conditions. To monitor and analyze the stability of surrounding rock mass during continuous excavation of the powerhouse excavation and locate the potential failure zones, an ESG (Engineering Seismology Group) microseismic monitoring system manufactured in Canada was installed in April, 2013. The wave velocity of the monitoring system was determined through fixed blasting tests. And the average location error is the minimum while P-wave velocity is 5700m/s, less than 10m and meeting the system request. By combining the temporal and spatial distribution regularity of microseimic events with field excavation, micro-crack clusters and potential instability zones were identified and delineated. The results will provide a reference for later excavations and supports of the underground powerhouse. Furthermore, a new monitoring method can also be supplied for the stability analysis of surrounding rock mass in deep-buried underground powerhouses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".