Analytical Prediction and Finite-Element Simulation of the Lateral Response of Rocking Steel Bridge Piers with Energy-Dissipating Steel Bars
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Bibliographic record
Abstract
This paper presents the extension of controlled rocking technology to steel bridge piers through analytical expression and finite-element (FE) simulation. As an outcome of the rocking behavior, the seismic damage is prevented due to reduced flexural stresses in the columns. However, local buckling can happen if the column wall thickness is too thin, which has detrimental impacts, including the loss of self-centering ability and reduced lateral load/deformation capacity. A simple analytical method is proposed to predict the monotonic rocking response for preliminary design purposes. When using more-detailed models and FE analysis, it is shown that localized inelastic deformations of the column can occur upon rocking and the simple force distribution at the column base can cause an overestimation of lateral load capacity. The use of a base plate can lead to a higher lateral load capacity and less damage to the column by improving the stress distribution at the base of the column. To account for the base plate, previously proposed modified monolithic beam analogy (MBA) was expanded in this study, referenced as extended MBA (EMBA) to predict the rocking column lateral load-displacement response. An optimized design can be achieved with a lighter cross section in the upper part of the column where longitudinal straining is limited. Different axially yielding elements comprised of tension-only, tension-compression, and buckling-restrained energy dissipators (EDs) are investigated. For EDs with comparable force capacities, the study indicates that energy dissipation is increased from the former to the latter dissipator type, while the lateral load capacity of the system remains almost the same. The proposed pier exhibits recentering capability, high ductility, and stable hysteretic response with the majority of damage confined within external sacrificial elements.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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