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Record W4396929117 · doi:10.1061/jsendh.steng-13007

Probabilistic Postearthquake Vertical Load-Carrying Capacity Loss Model and Rapid Functionality Assessment for Reinforced Concrete Circular Bridge Columns

2024· article· en· W4396929117 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Structural Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsBridge (graph theory)Structural engineeringReinforced concreteProbabilistic logicCarrying capacityGeotechnical engineeringEngineeringComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The rapid and accurate postearthquake traffic capacity or functionality loss assessment for highway bridges after a strong earthquake is crucial to the decision-making for postearthquake emergency rescue and recovery, as well as seismic resilience analysis. The postearthquake traffic capacity of a simply supported highway girder bridge designed based on the capacity design philosophy is generally dominated by the loss of postearthquake vertical load-carrying capacity of the damaged bridge column, which, however, cannot be rapidly and quantitatively evaluated by previous studies. This study develops a postearthquake vertical load-carrying capacity loss model for flexure-dominated circular RC bridge columns using multiple linear regression, which is a function of column-related structural parameters and a selected damage indicator (i.e., residual drift ratio). The database of the postearthquake vertical load-carrying capacity loss for the damaged but before collapsed RC columns is generated through numerical simulations using a loading scheme consisting of nonlinear time-history analysis followed by pushdown analysis. In order to generate a sufficient database of the vertical capacity loss of RC columns, an incremental dynamic analysis (IDA) approach is adopted to produce different damage levels on the column. The significance of the loss regression model and the significance of each corresponding regression coefficient are checked by statistical tests. In addition, the generalization ability of the loss model is also tested by 10-fold cross-validation. After that, a probabilistic postearthquake vertical load-carrying capacity loss model is developed in this study. Based on this probabilistic model, a traffic capacity fragility curve conditioned on the residual drift ratio of a given column is proposed in this study for the first time to assess the remaining functionality of a given RC column. This proposed traffic capacity fragility curve is further validated by two example columns with and without considering the uncertainty, respectively. The traffic fragility curve can be quickly generated for the target circular RC bridge column and facilitate the postearthquake decision-making for the damaged but before-collapsed column, thus forwarding to the introduced rapid postearthquake assessment for simply supported highway girder bridges.

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Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.234
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it