A systematic model- and experimental approach to hydro-mechanical and thermo-mechanical fracture processes in crystalline rocks
Bibliographic record
Abstract
The paper presents the key findings of Task G SAFENET of the DECOVALEX 2023 project “Safety Assessment of Fluid Flow, Shear, Thermal and Reaction Processes within Crystalline Rock Fracture NETworks”. It utilizes a systematic and experimental approach to numerically simulate mechanical (M), hydro-mechanical (HM), and thermo-mechanical (TM) fracture processes in brittle rocks. The Task team introduced, applied, and compared a wide range of numerical methods, including both continuum and discontinuum methods, for simulating related fracture processes. Task G is based on three key experiments: the Freiberg, GREAT cell, and KICT experiments, which analyze M, HM, and TM processes respectively. Classic HM and THM benchmark exercises serve as a common basis by using analytical solutions for a plane line discontinuity in a poro-elastic medium (Sneddon and Lowengrub, 1969) and a point heat source in a thermo-poro-elastic medium (Booker and Savvidou, 1985), (Chaudhry et al., 2019). These solutions also serve as a reference for rough fractures and simple fracture networks. A systematic set of new benchmark cases has been derived based on the GREAT cell experiments. An analysis of the constant normal load (CNL) experiment has been conducted using micro- and macroscopic approaches, based on the Freiberg experiment. The GREAT cell experiments provided a database for evaluating the mechanical and hydro-mechanical responses of various rock samples (resin, greywacke, gneis) in triaxial tests with a rotational stress field. Fracture permeability was determined as a function of normal stresses in the rotational stress field. The KICT experiments were used to investigate thermally induced shear slip and dilation processes. The SAFENET Task contributed to the Open Science concept in DECOVALEX by providing a freely accessible Jupyter notebooks for selected benchmark exercises. • Systematic and experimental-based approach to numerical simulation of fracture processes • Large variety of numerical methods, continuum and discontinuum methods compared • Benchmark suite based on Freiberg, GREAT and KICT laboratory experiments • Experiments covering mechanically, hydraulically and thermally induced fracturing • Open Science contribution: Initiation of a DECOVALEX Jupyter Lab (Appendix C).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".