Flexural Stiffness Reduction Factor of Reinforced Concrete Bridge Pier with Circular Section
Bibliographic record
Abstract
The reduced stiffness method had been adopted to evaluate the material nonlinearity characteristics of reinforced concrete structures to be in compliance with concrete structure standards in the United States and Canada. Concrete structure design code in China also accepts the reduced stiffness method as a supplementary method of considering the second-order effects problem. However, bridge codes of China still use amplified coefficients of eccentricity to consider geometrical nonlinearity characteristics of reinforced concrete bridge pier. The flexural stiffness reduction factor of reinforced concrete bridge piers with rectangular section has been researched as it relates to material nonlinearity and geometrical nonlinearity. However, the flexural stiffness reduction factor of reinforced concrete bridge pier with circular section considering the two kinds of nonlinear characteristics lacks this type of corresponding research. Based on the numerical integral method, the regulation of the flexural stiffness can change in the existed test models of reinforced concrete bridge piers with circular section under different axial load levels and different levels of seismic action. The results are reported and it is concluded that the theoretical values are in agreement with the test values. As a result, the flexural stiffness reduction factor is proposed to consider the characteristics of material nonlinearity and geometrical nonlinearity of reinforced concrete bridge pier with circular sections.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".