Simulation of time-dependent response of jointed rock masses using the 3D DEM-DFN modeling approach
Bibliographic record
Abstract
Investigating the mechanical response of jointed rock mass, especially its potential changes over time, is vital for the design of geotechnical structures with a long service lifetime. This article studies time-dependent deformations of jointed rock masses based on the 3D distinct element method (DEM) incorporating discrete fracture networks (DFN). A new 3D creep model for jointed rock masses is developed, emphasizing the structural failure due to the creep sliding of joints while considering the long-term strength and the time-to-failure phenomenon of intact rocks. The creep sliding constitutive model of joints is developed based on Barton's nonlinear strength criterion. First, the model implementation, parameter calibration, and model validations are introduced. Then, a case study of the TAS08 tunnel in Äspö Hard Rock Laboratory (HRL) in Sweden is presented. A DFN model using field mapping data is constructed using Mofrac. The time-dependent response of the TAS08 tunnel is analyzed using the proposed creep model for jointed rock masses. Based on the simulation results, it show that the proposed approach can effectively simulate the time-dependent deformation of jointed rock masses. The DEM-DFN simulation approach provides a valuable tool for analyzing time-dependent responses of excavations and managing hazards associated with structurally controlled failures. • A new 3D creep model is developed for jointed rock masses considering the time-dependent deformation of both rock and joints. • Structurally controlled failure associated with creep deformations of discontinuities is simulated. • A DFN generation tool Mofrac is used to build the DFN model containing deterministic and stochastic fractures. • DEM-DFN modeling approach is adopted to analyze the time-dependent response of a tunnel.
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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 | 0.001 | 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".