Effect of Trench Geometry on the Behavior of Negative Projecting Box Culverts
Bibliographic record
Abstract
Marston’s theory is typically used to predict earth loads acting on culverts installed in negative projecting trenches. This theory assumes that trench walls are vertical; however, many excavations are done with sloping walls for constructability and safety. In this study, the effect of trench geometry on the loading conditions of negative projecting box culverts was evaluated. Centrifuge testing and numerical modeling was performed to evaluate the influence of trench wall angle, trench depth, and trench width on the vertical and horizontal earth pressures exerted on the box culvert. Sixteen model geometries were evaluated, and the experimental and numerical results are shown to be in reasonably good agreement. It was found that Marston’s theory is appropriate for negative projecting culverts constructed in trenches with vertical sidewalls; such an approach is conservative and overestimated the vertical loading conditions by approximately 15%. However, for configurations with inclined trench walls, it was found that the culvert loading was increased considerably and Marston’s theory was not appropriate. Very little positive arching and load reduction was realized when such culverts were installed in trenches with sloped walls. It is recommended that numerical modeling be performed during design of negative projecting culverts constructed with sloped sidewalls, or that positive projecting conditions be assumed to ensure that design loads are conservative.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".