Numerical implementation and application of an internal state variable model to analyze the time-dependent behavior of mining excavations in rock salt
Bibliographic record
Abstract
The geomechanical behavior of rock salt has been investigated extensively over the years. Experimental studies have identified distinctive features associated with nonlinear inelastic response that shows strong time and loading history dependencies. In this paper, a relatively simple constitutive model is presented and implemented into the numerical code FLAC, and then applied to analyze the time-dependent behavior of excavations in salt mines. The unified creep-plasticity model includes an internal state variable (ISV) with an evolution law that induces progressive strain hardening (SH) until a steady state is reached. Numerical analyses are performed with the proposed ISV–SH model to evaluate material parameters, based on creep test results on natural rock salt, and to simulate the response of a circular opening and of rectangular mining excavations created in sequence. The results are analysed and compared with those obtained with the well-known Norton power law equation, commonly used in salt mine engineering. The time-dependent calculation results illustrate key aspects of rock salt behavior and highlight the major influence of transient inelastic behavior and stress redistribution on the response of underground openings. The proposed modelling approach constitutes an advantageous alternative to analyses based on stationary creep laws, often used in rock salt mining operations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".