Use of CANDE and Design Codes to Assess Stability of Deteriorated Metal Culverts
Bibliographic record
Abstract
Three design cases are used to study the effects of corrosion, burial depth, and staged construction on the capacity of steel culverts. The finite element packages CANDE and ABAQUS are used to perform the numerical investigation. The results of these numerical models are compared to current and proposed design methods to determine which approach gives the most conservative estimation of thrust force for both new and corroded culverts. Simple ring compression theory (springline thrust equal to half the soil prism load) produced thrusts that were 42%, 16% and 7% lower than those based on “staged construction” finite element analysis for the 4m diameter example culvert buried 1.5m, 3m, and 10m respectively. The American Association of State Highway and Transportation Officials (AASHTO), Canadian, and proposed design equations all underestimated thrust compared to those finite element results (by 46%, 22% and 24% respectively for 4m diameter culvert at 1.5m burial depth, and with 12.5% wall thickness remaining). Thrust forces obtained using CANDE were slightly lower than those produced by ABAQUS, and it appears that CANDE can be used to estimate thrust forces after corrosion, even though the CANDE analysis featured uniform wall loss around the whole pipe circumference and ABAQUS was used to model wall loss across the invert only.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".