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Seismic reliability-based assessment and design optimization of shape memory alloy bars in concrete bridge piers

2024· article· en· W4403842131 on OpenAlex
Lianxu Zhou, M. Shahria Alam

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEngineering Structures · 2024
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaOkanagan University College
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStructural engineeringPierBridge (graph theory)Reliability (semiconductor)EngineeringSeismic analysisComputer science

Abstract

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Utilizing shape memory alloy (SMA) bars to reinforce the plastic hinge of concrete bridge piers is regarded as an effective alternative to enhance the seismic performance and resilience of highway bridges. However, how to evaluate the seismic reliability of such a performance enhancement scheme and optimize the usage of SMA to reach a better economic performance is still lacking in the field of performance-based earthquake engineering. To this end, this study provides a reliability-based methodology to evaluate the seismic performance of bridge piers with a hybrid reinforcement consisting of SMA and regular steel bars and to optimize the usage of SMA in the plastic hinge of the bridge pier. A reliability-based assessment and design optimization methodology is introduced first in this study. The finite element (FE) model of a benchmark bridge pier with five different replacement ratios of SMA is then modeled considering the uncertainty of material-related parameters and the bond-slip effect of longitudinal bars. A shake table test on an SMA-reinforced concrete bridge column available in the literature is selected to validate the numerical model. Based on the seismic hazard curve of the bridge site, a set of site-specific ground motions is selected through the uniform risk spectra. The peak drift ratio and residual drift ratio are separately adopted as the damage indicator, which is linked to the damage state of the bridge pier. The seismic fragility and reliability index associated with each damage state is presented as a surface varying with the ground motion intensity measure (IM) level and the SMA replacement ratio, according to the incremental dynamic analysis results. Finally, the reliability-based design optimization approach is implemented in this study to optimize the usage of SMA. The results indicate that the SMA can significantly reduce the conditional damage probability and failure probability when using the residual drift ratio as a damage indicator, resulting in an improvement in seismic reliability. Optimizing the usage of the SMA bar in the plastic hinge of bridge piers can balance the bridge’s construction cost and structural performance. • A seismic reliability assessment of the concrete bridge pier with different proportions of SMA reinforcements is performed. • Seismic reliability-based design optimization of SMA bars in concrete bridge piers is proposed and implemented in this study. • The initial construction cost of a regular RC pier, pre-optimized and post-optimized SMA piers is compared. • The post-optimized SMA pier not only meets the prescribed performance but also reduces the initial constriction cost.

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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 score0.304
Threshold uncertainty score0.641

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 head0.007
GPT teacher head0.225
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