Towards a low-damage seismic design: Developing and validating a performance-based design framework for segmental post-tensioned precast concrete piers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Segmental post-tensioned precast concrete (SPPC) piers show significant potential for enhancing post-earthquake rehabilitation, yet a practical performance-based seismic design framework remains undeveloped. In this respect, the current study develops and validates a comprehensive framework, demonstrating SPPC piers’ ability to minimize damage to individual pier components while maintaining the integrity of the overall bridge system. The framework employs a two-tier design methodology that integrates a capacity-demand-diagram approach with fragility analysis. The capacity-demand-diagram method is used to ensure that the displacement demands of the SPPC piers are consistent with predefined seismic displacement targets at the design earthquake level, thus facilitating the efficient determination of preliminary design parameters. Subsequently, fragility analysis is employed to assess the probability of failure, allowing iterative refinement of the design parameters to meet damage tolerance requirements. The developed framework is validated through a case study that compares SPPC piers with conventional piers in high-seismic regions. This step-by-step analysis confirms the applicability of the framework and shows that SPPC piers can be effectively integrated into current seismic design practices, supporting a performance-based framework with ease and reliability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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