Investigating the Influence of Micro-scale Heterogeneity and Microstructure on the Failure and Mechanical Behaviour of Geomaterials
Bibliographic record
Abstract
The mechanical response of geomaterials is highly influenced by geometrical and material heterogeneity. To date, most modelling practices consider heterogeneity qualitatively and the choice of input parameters can be subjective. In this study, a novel approach to combine detailed micro-scale characterization with modelling of heterogeneous geomaterials is presented. The influence of micro-scale heterogeneity and microcracks on the mechanical response and brittle fracture of a crystalline rock was studied using numerical and experimental tools. An existing Combined Finite-Discrete element (FEM/DEM) code was extended to suit heterogeneous, discontinuous, brittle rocks.\n\nBy conducting grid micro-indentation and micro-scratch tests, the Young's modulus and fracture toughness of the constituent phases of the rock were obtained and used as accurate input parameters for the numerical models. The models incorporated the exact phase mapping obtained from a MicroCT-scanned specimen and the existing microcrack density obtained from thin section analysis. The results illustrated that by incorporating accurate micromechanical input parameters and the intrinsic rock geometric features, the numerical simulations could more accurately predict the mechanical response of the specimen, including the fracture patterns and tensile strength.\n\nThe numerical simulations illustrated that microstructural flaws such as microcracks should be included in the models to more accurately reproduce the rock strength. In addition, the differential elastic deformations caused by rock heterogeneity altered the stress distribution in the specimen, creating zones of local tensile stresses, in particular, on the boundaries between different mineral phases. As a result, heterogeneous models exhibited rougher fracture surfaces. \n\nMicroCT observations emphasized the influence of heterogeneity and, in particular, biotite grains on the fracture trajectories in the specimens. Favourably oriented biotite flakes and cleavage splitting significantly deviated the cracks. The interaction of the main crack with perpendicular cleavage planes of biotite caused strong crack deviation and termination.\n\nConsidering heterogeneity and the strength degradation caused by microcracks, the simulations captured reasonably accurate mechanical responses and failure mechanisms for the rock, namely, the nonlinear stress-strain relationships. The insights presented in this study improve the understanding of the role of heterogeneity and microstructure on damage and mechanical behaviour of brittle rock.
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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 | 0.000 |
| 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 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".