Elasto-plastic and post-yield weakening jointed rockmass response in a comparison of equivalent-continuum and explicit structural models
Bibliographic record
Abstract
The strength and stiffness of a composite rockmass (intact material, defects, joints, bedding, etc.) are primary inputs for the engineering analysis of rock slopes and underground excavations. The Geological Strength Index (GSI) has served rock engineering for three decades as a rockmass assessment system based on the blockiness of the rockmass and discontinuity condition. GSI is used to factor the Hoek–Brown strength envelope for intact rock to represent jointed rockmasses in conventional equivalent-continuum numerical modelling. Modern numerical tools can represent networks of discrete (explicit) structure with assigned discontinuity properties. This provides an opportunity to compare explicit structural modelling with the conventional implicit equivalent-continuum approach. In this paper, explicit structural models are developed using elasto-plastic (constant-strength) constitutive models for intact rock and realistic parametric ranges for explicit structure properties. Explicit model results are compared to equivalent-continuum results, validating the classical implicit approach while also identifying key limitations. Explicit models with post-yield weakening of the intact and structural elements are then developed and compared to post-yield weakening implicit models that use post-yield dilation and empirical relationships between peak and residual GSI. The results provide guidance for practical modelling in strain-weakening rockmasses, including recommendations for post-yield dilation in the traditional implicit approach.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".