Analytical formulation of maximum length limits of integral bridges on cohesive soils
Bibliographic record
Abstract
This paper presents an analytical approach for predicting the length limits of integral bridges built on cohesive soils based on the flexural strength of the abutments and the low cycle fatigue performance of the steel H-piles at the abutments under cyclic thermal loading. First, H-piles that can accommodate large inelastic deformations are determined considering their local buckling instability. Then, a damage model is used to determine the maximum cyclic deformations that such piles can sustain. Next, nonlinear static pushover analyses of typical integral bridges subjected to cyclic thermal variations are conducted to study the effect of various geometric, structural, and geotechnical parameters on their performance. Equations are derived by using the analyses results to determine the maximum length limits of integral bridges built on cohesive soils. It is found that the maximum length limits of integral bridges is affected by the stiffness of the deck, height of the abutment, properties, and orientation of the piles as well as stiffness of the cohesive soils.Key words: bridges, integral, steel, piles, fatigue, inelastic, thermal, clay, soil, length.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".