Risk Targeted Seismic Design of 10-storey RC Frame Building
Bibliographic record
Abstract
Current seismic design practices, primarily based on uniform hazard spectra, often fail to guarantee a consistent collapse probability for structures across different regions.Such failures are mainly due to inherent uncertainties in collapse capacity and variations in hazard curve shapes, leading to an unequal distribution of seismic risk.The present study investigates a typical 10-storey RC frame building designed according to Indian seismic codes located in zone III.The full-scale model of the RC frame is analysed using the Incremental Dynamic Analysis (IDA), considering a suite of scaled ground motion records to assess their collapse behaviour under varying earthquake intensities.The results from IDA are then utilised to generate building-specific fragility curves, quantifying the probability of collapse as a function of spectral acceleration.Furthermore, site-specific hazard curves are developed for the chosen locations, considering the regional seismicity and ground motion characteristics.A risk-targeted design approach is used to convolve the hazard curves with the building-specific fragility curves to estimate the annual collapse rate and the collapse risk over a 50-year period.This study highlights the importance of transitioning from the uniform hazard spectrum paradigm to risk-targeted design methodologies to achieve a more equitable and consistent level of seismic safety across various locations and building types, with findings revealing that risk-targeted designs are approximately 50% heavier than those based on IS codes, particularly impacting the columns of lower floors for 1% target collapse risk.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".