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Record W4249332822 · doi:10.29173/mocs185

Experimental and Numerical Study of Seismic Performance of Precast Prestressed Concrete Frame Internal Connection

2015· article· en· W4249332822 on OpenAlexvenueno aff
Xiandong Liao, Xiang Hu

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2015
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsPrecast concreteStructural engineeringConnection (principal bundle)Frame (networking)Prestressed concreteHysteresisFlexural strengthBeam (structure)Finite element methodGeotechnical engineeringFailure mode and effects analysisMaterials scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The seismic performance of the internal connection of precast prestressed concrete frame was studied systematically, based on the experiment of full-scale model under low cyclic reversed loading. This study was mainly focused on failure pattern, load-carrying capacity, skeleton curves, and hysteresis curves. Furthermore, a nonlinear finite element analysis using Abaqus was carried out to study the characteristics of the internal connection of precast prestressed concrete frame. Results revealed that the damage was concentrated mainly on beam end owing to flexural action, while steel bars in the columns and stirrups in the core region remained elastic until failure occurred. The calculated value of the load-carrying capacity of the internal connection was similar to the experimental one. Present study can be referenced for the application of precast prestressed concrete frame in high seismic zones.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.936

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2015
Admission routes1
Has abstractyes

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