Assessment of Shear Connection through Composite Beam Modeling
Why this work is in the frame
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Bibliographic record
Abstract
Steel-concrete composite construction is used extensively in bridges across North America. The welded shear stud is the standard connector used today, but other connectors, such as the through-bolt connector, may have advantages for precast construction or applications where better fatigue resistance or deconstructability is desired. The standard method of assessing the performance of a shear connector is through the use of push tests. However, the load-slip curves that result from these tests do not accurately predict load-slip behavior at the shear interface of the beams and girders they are meant to simulate. In this paper, a model is presented that predicts composite beam behavior using elastic material properties and nonlinear shear connector load-slip curves. The finite element (FE) model features link connector elements between a steel beam and concrete slab that can be programmed to simulate different connector types. Although the model can be used with push test load-slip curves as inputs, it is shown that a much better prediction can be made using force-deformation data from experimental beam tests or FE analysis. Results are discussed for stud connectors and through-bolt connectors, and it is shown that while through-bolts allow more interfacial slip and overall deflection, material stresses and composite interaction are not affected as much as might be expected. The outcome of this work is a comparison tool which can be used to assess the viability of current and future shear connection alternatives with the goal of achieving an economical and structurally sound shear connector.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it