The impact of fractures on the Biot and Skempton coefficients of fractured rocks  
Bibliographic record
Abstract
The Hydro-Mechanical (HM) behavior of fluid-saturated porous materials is crucial in determining the response of the subsurface to natural processes, such as glaciation, and to engineering applications, such as construction/excavation, reservoir impoundments, geo-energy extraction, and deep geological disposal of used nuclear fuel. Two fundamental coefficients, i.e., the Biot coefficient and the Skempton coefficient, define the contribution of the fluid in subsurface media to maintain the mechanical equilibrium against perturbations in stress and pore fluid pressure. Despite the central importance of these two coefficients, which may broadly range between 0 and 1, their estimation is often oversimplified in most scientific and engineering studies that treat large-scale saturated problems by assuming a uniform geological material, with the coefficients estimated experimentally at the laboratory sample-scale or analytically through expressions valid for isotropic homogeneous materials.In this work, we analyze the impact of fractures on the HM behavior of fractured rocks by looking at the equivalent Biot coefficient and Skempton coefficient. We adopt a recently defined framework in which the equivalent coefficients are estimated from the properties of both the porous intact rock and the discrete fracture network (DFN), including fracture size, orientation and mechanical properties. We extend this theory to incorporate more realistic assumptions on fractures, such as size-dependent and stress-dependent fracture properties. This setting allows us to explore the range of variability of the two equivalent coefficients with respect to the stochastic distribution of fracture size and orientation in the rock, and with respect to depth and stress faulting regime. We show that the coefficients are larger if 1) the network is placed in shallow rocks (i.e., low stress regime), 2) the network is populated by a few large fractures rather than by many small fractures, and 3) the fractures are oriented parallel to the in-situ maximum principal stress and normal to the applied stress.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".