Cyclic heating effects on thermal volume change of silt
Bibliographic record
Abstract
This study focuses on the thermal volume change of compacted, saturated silt during temperature cycles. A temperature-regulated oedometer with backpressure control was used to measure the thermal consolidation of silt specimens under normally consolidated to heavily overconsolidated initial stress states. During initial heating, the silt specimens displayed thermal volume changes similar to those reported in the technical literature, with the normally consolidated specimen showing contraction and the heavily overconsolidated specimens showing expansion. The specimens all showed elastic contraction during cooling, as expected. However, subsequent heating and cooling cycles led to additional permanent volume change. This observation contradicts thermo-elasto-plastic theories, which predict plastic contraction only during initial heating of soils with low overconsolidation ratios and elastic volume changes during subsequent heating and cooling cycles. A source of error in the experiments was a softer response during heating due to differential radial expansion of the oedometer ring, followed by exaggerated axial expansion of the soil during cooling when the ring contracted. Nonetheless, the accumulation of permanent strain during cyclic heating and cooling indicates that the thermal yield surface history may not be locked in during the cooling process, implying that kinematic thermal hardening or thermal creep mechanisms should be explored.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".