Distinct element modeling of hydraulically fractured Lac du Bonnet granite
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this study is to better understand the mechanics of fracture development and propagation during hydraulic fracturing. This paper presents some development and applications of discrete particle modeling of this problem. A discontinuum modeling approach idealizes the material as separate particles bonded together at their contact points and utilizes the breakage of individual structural units or bonds to represent damage. The numerical models are correlated with existing hydrofracture laboratory experiments, which are presented in other publications. A simulation of a laboratory‐scale hydrofracture experiment and the acoustic emission (AE) data from the experiment is used to validate the synthetic AEs produced in the hydrofracture model. This technique has been used to examine the mechanics of fracture initiation and time and spatial distributions of AE. The modeling results demonstrate that the mechanism of hydraulically induced fracture in the Lac du Bonnet (LdB) granite core sample is predominantly tensile failure and that the shear cracks recorded in the hydrofracture experiment were due to slip on preexisting fractures. Numerical modeling of hydrofracture on homogeneous and heterogeneous synthetic samples seems to capture much of the behavior observed in the laboratory hydrofracture experiments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it