Evaluating In-Span Hinge Connections: Empirical Methods and Strut-and-Tie Analysis
Bibliographic record
Abstract
Shiplap hinge joints (SHJs) can alter the intended load paths and affect the structural performance of various bridge components, including the deck and piers.This issue is especially significant for older bridges with SHJs designed using traditional methods, which may not meet the minimum reinforcing, anchorage, and development length requirements specified in the AASHTO LRFD Bridge Design Specifications.The detailed finite element (FE) models are employed to examine load paths, mechanical contributions, and effective stress along rebar.It aims to compare the ultimate capacity and associated failure mechanisms of beam ledges with SHJs as predicted by both empirical and strut-and-tie methods.The analyses, conducted according to current AASHTO LRFD standards, illustrate the consequences of older bridge designs and their associated failure mechanisms when assessing beam ledges with SHJs.Additionally, the study offers insights into applying strutand-tie methods for evaluating existing bridges with in-span hinge connections and properly accounting for development lengths using the strut-and-tie method compared to the empirical method.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".