Determination of in-situ stress field using back-analysis approach: a case study of Jwaneng Mine
Bibliographic record
Abstract
ABSTRACT: A good understanding of the mine-scale stress field is essential for the underground mining design. When the geological condition is complex, variation of local stresses can be significant, which brings difficulties for the interpretation of stress measurement data. In this case, to obtain the best-fit stress field, the back analysis approach using the detailed numerical model can be an effective methodology. This article presents a case study of the assessment of the in-situ stress field of Jwaneng Mine in Botswana. A mine-scale numerical model is built using 3DEC, in which the stratigraphy information, major faults as well as the excavation effect of the open pit are considered. The stress variation of the measurement data collected using the overcoring method from 2013 to 2019 is simulated. By using a new iteration approach based on the least square method, the best-fit mine-scale stress field is obtained. It demonstrates that the proposed approach can be effective in the determination of the mine-scale stress field with complex geological conditions.
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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 | 0.001 |
| 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".