Thermo-hydraulic numerical modelling of in-soil conditions in reinforced soil walls
Bibliographic record
Abstract
The role of temperature and relative humidity in long-term mechanical and chemical degradation of polyester fibres due to hydrolysis and creep is well documented. This study presents the results of a thermo-hydraulic 2D finite-element model used to estimate the magnitude and distribution of in situ temperature, relative humidity, and degree of saturation in the backfill of reinforced soil walls (RSWs) due to changes in atmospheric boundary conditions. Boundary conditions for in-air temperature, relative humidity and daily precipitation were taken from weather databases for continental, Mediterranean, desert, and tropical climates. Scenarios with different water tables, and permeable or impermeable zones around the reinforced soil zone were analyzed. Numerical outcomes show that mean in-soil temperature values can be related to the mean annual atmospheric value for each geographical location, with relevant fluctuations limited to the first 3 m of distance from the vertical and horizontal boundaries. In-soil relative humidity values depended on the climate dataset and the permeability of the zones adjacent to the reinforced soil. The results of this study and lessons learned are a valuable precursor for future studies of coupled thermo-hydro-mechanical modelling of polyester geosynthetic RSWs under in situ operational conditions.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".