Evaluating the Seismic Behavior of Segmental Unbounded Posttensioned Concrete Bridge Piers Using Factorial Analysis
Bibliographic record
Abstract
Segmental unbounded posttensioned concrete bridge piers can resist large lateral drifts and eliminate residual deformation during an earthquake. The seismic behavior of posttensioned bridge piers depends on several factors, including concrete strength, posttensioning (PT) force, aspect ratio, and axial-load ratio. This study investigated the effects of these factors and their interactions on the seismic behavior of such piers, which are not adequately addressed in the existing literature. Here, finite-element models of unbounded posttensioned concrete piers were generated to perform a parametric study. These models were first validated with experimental results and then used to predict the seismic behavior of unbounded posttensioned concrete piers. At the initial stage, full factorial analysis was performed by considering the following three factors: PT level, PT ratio, and concrete strength. The results indicate that none of them in combination resulted negatively on pier yielding capacity and postelastic stiffness, as long as the axial-load ratio was within 20%. After this preliminary study, a more comprehensive fractional factorial study, including seven factors, was performed. In the fractional factorial analysis, each of the factors was considered at two levels. The piers were analyzed under reverse cyclic loading. Based on the lateral load-displacement responses of the piers, regression analysis was performed to propose equations for calculating global yielding and stiffness of piers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".