Long‐Term Deformation Analysis of Recycled Construction Waste Subgrade Filler
Bibliographic record
Abstract
The application of construction waste to subgrade has important economic and environmental significance. In order to study the long‐term deformation characteristics of recycled construction waste filler, a series of laboratory tests and field measurement have been carried out. Through compaction, sieving, and California bearing ratio (CBR) tests, the gradation and CBR value of recycled construction waste filler meet the requirements of expressway subgrade. Long‐term deformation tests include laboratory creep tests and field settlement measurement. The creep tests were carried out for about 500 days by a self‐made consolidation creep instrument, the creep type of recycled construction waste filler under the test load is stable creep, as the load increases, not only the creep deformation increases but also the time to reach creep stability is longer, and the breakage and compaction of particles are the main reasons for long‐term deformation. Through measurement and analysis, it is found that the settlement stability of the construction waste subgrade takes a long time; after the operation of road, the settlement of the subgrade has grown rapidly. Furthermore, the Burgers model can be used to predict the deformation of creep tests, and the maximum settlement of construction waste subgrade can be predicted. The research can provide reference for the application of recycled construction waste filler, and it is conducive to the promotion of construction waste subgrade.
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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 | 0.001 |
| 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".