Modelling the thermal–hydro-mechanical behaviour of unsaturated soils with a high degree of saturation using an extended precise integration method
Bibliographic record
Abstract
Unsaturated soils with a high degree of saturation (HDS) are commonly encountered in marine and lacustrine sediments. In these soils, the gas phase generally exists in the state of discrete bubbles, which is sensitive to stress and temperature changes and can dramatically change the soil's engineering properties. This paper explores the thermal-induced behaviour of HDS soils using an efficient extended precise integration method (XPIM). Biot poroelasticity theory, extended to include thermal effects and compressibility of gas–water mixture, is employed to analyze the soil behaviour under non-isothermal conditions. Based on the Laplace–Fourier transform and Taylor series expansion, such problems can be solved by XPIM. The robustness of XPIM was confirmed by comparing the present results with analytical solutions and test data. Extensive parametric studies are undertaken to examine both the effects of soil grain thermal expansion and anisotropic permeability on soil behaviour and temperature effects on the degree of saturation ( Sr). The thermal-induced variations in Sr are more pronounced with lower initial values (e.g., 90% compared to 99%). These quantitative results demonstrate the benefits of the proposed method, which proves to be extremely efficient and several orders more precise than conventional numerical approaches, with its precision limited only by the computational effort used.
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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) | 0.001 | 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".