Numerical investigation of the performance of geocell-reinforced granular base in inverted pavement systems using nonlinear finite element modeling
Bibliographic record
Abstract
The quality of granular base materials plays a key role in the enhanced performance of inverted pavement systems (IPSs). Typically, premium-quality materials are required for the construction of IPS structures. This study investigates the feasibility of geocell reinforcement of lower quality materials to be used as an alternative when premium base materials are not available. To this end, 16 different pavement structures were studied using nonlinear finite element (NL-FEM) models in ABAQUS. The results are validated using those of a full-scale field project, which confirms the reliability of the developed FEM model. It was concluded that geocell reinforcement of granular base layer can increase the fatigue and rutting performances. In all the cases, lower quality aggregates with reinforcement exhibited better performance than the non-reinforced base materials with premium aggregate quality. The findings confirm that in the absence of premium-quality aggregates, good-performing inverted pavement structures can still be achieved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".