Unified Nonlinear Elasto‐Visco‐Plastic Rheology for Bituminous Rocks at Variable Pressure and Temperature
Bibliographic record
Abstract
Abstract To address nonlinear constitutive relations of rocks containing soft matter such as bitumen, a rigorous rheological model based on Lagrangian mechanics is proposed. The model is general and applies to arbitrary quasi‐static deformations in poroelastic or viscoelastic materials. As an application to bitumen‐rich rock, the model is used for detailed modeling and inversion of laboratory measurements of linear and nonlinear creep in asphalt mastic. Several physically meaningful, loading‐stress and temperature‐dependent material properties are identified and inverted from laboratory observations. By presenting the data on the (strain, strain rate) plane, three distinct regimes of deformation are differentiated: viscoelasticity, linear plasticity (Newtonian viscous flow), and nonlinear plasticity (non‐Newtonian flow). The model accurately predicts all measured creep data from which it was derived without hypothesizing empirical time‐dependent properties of the material. In addition, the model predicts results of several new experiments: rapid unloading, measurement of effective time‐dependent compliance, stress relaxation under static strain, and arbitrary controlled‐strain or constant‐strain‐rate deformations. In constant‐strain‐rate experiments, peak stresses are measured and used as indicators of the onset of nonlinear creep. For a fixed temperature, these peak stresses fall on the same line in the strain‐stress plane, and they are strongly related to rock properties.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".