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Record W4377290673 · doi:10.1002/eqe.3923

Pseudo‐dynamic hybrid simulations of steel eccentrically braced frames equipped with cast steel replaceable modular yielding links

2023· article· en· W4377290673 on OpenAlexafffund
Pedram Mortazavi, Oh‐Sung Kwon, Constantin Christopoulos

Bibliographic record

VenueEarthquake Engineering & Structural Dynamics · 2023
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStructural engineeringModular designBenchmark (surveying)EngineeringFinite element methodSet (abstract data type)Dissipative systemComputer scienceGeology

Abstract

fetched live from OpenAlex

Abstract Previous studies have underlined the importance of establishing a database of high‐fidelity benchmark experimental test results under random loading histories such as earthquake excitations for both existing structural systems as well as newly proposed ones. Such experimental results are useful for understanding the limitations of previously developed numerical models, proposing new numerical models for more recently developed structural systems, better assessing the ultra‐low cycle fatigue (ULCF) life of energy dissipative components, and improving the loading protocols used for element assessments or developments of numerical model. This paper presents experimental results from pseudo‐dynamic hybrid simulations on steel eccentrically braced frames (EBF) equipped with novel cast steel replaceable modular yielding links. The first set of experiments are carried out on a four‐story EBF, with the first‐floor yielding link physically tested in the laboratory. The second set of experiments are performed on a two‐story EBF where the second‐floor link is physically tested in the laboratory, while considering axial loads due to the imbalanced distribution of the seismic weight in the building. Each building structure is subjected to three Maximum Credible Event (MCE) level earthquakes. A framework for performing hybrid simulations on EBFs is proposed where the response of the yielding link is physically captured in a single degree of freedom control system, with or without axial loads. A substructuring strategy is proposed in conjunction with a modeling approach in the integration module. The results confirm the effectiveness of the hybrid simulation framework, which can be adopted in similar studies. Two numerical models are proposed for capturing the response of cast steel links using a simplified and a more advanced approach. The models are first calibrated using incremental reversed‐cyclic experimental test results, and then refined using the hybrid simulation test results. The effects of this calibration improvement are quantified through critically comparing the response prediction for different response parameters before and after improving the calibration with the experimental results. The numerical model which captures the physical mechanism of the cast steel links provides a more accurate response prediction compared to the simplified numerical model using a phenomenological truss with calibrated force‐deformation. The remaining ULCF life of the tested yielding links is experimentally investigated after having sustained three MCE level earthquakes, which indicates a large reserve ductility capacity which is more than twice the required plastic rotation capacity for cast steel links after seismic events.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations21
Published2023
Admission routes2
Has abstractyes

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