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Record W2400483809 · doi:10.1139/cjce-2015-0419

Seismic performance comparison between force-based and performance-based design as per Canadian Highway Bridge Design Code (CHBDC) 2014

2016· article· en· W2400483809 on OpenAlexafffundvenueabout
Qi Zhang, M. Shahria Alam, Saqib Khan, Jianping Jiang

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsBritish Columbia Centre on Substance UseUniversity of British Columbia, Okanagan Campus
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReturn periodStructural engineeringSeismic analysisBridge (graph theory)EngineeringComputer scienceCivil engineering

Abstract

fetched live from OpenAlex

Performance-based design (PBD) was first introduced in Canadian Highway Bridge Design Code (CHBDC) in 2014. Performance-based design is the design that meets multiple performance criteria under different earthquake hazards. To investigate the impact of changes in CHBDC 2014, a four-span concrete highway bridge is designed and evaluated using force-based design (FBD) and PBD methods as per CHBDC 2014, and FBD method as per CHBDC 2006. By incorporating soil–structure interaction (using p–y curves) nonlinear pushover and dynamic time history analyses are conducted to assess the seismic performance of these bridges. Maximum strains of concrete and reinforcing steel are compared among the three designs to determine their performance levels. It is concluded that PBD (CHBDC 2014) is highly conservative compared to FBD (for both CHBDC 2014 and 2006). For the three-level PBD approach, the design is governed by the criterion of reinforcing steel not yielding under the design earthquake (with 475 years return period).

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.367
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.197
Teacher spread0.177 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2016
Admission routes4
Has abstractyes

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