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Record W4290465959 · doi:10.3390/buildings12081175

Seismic Performance Target and Fragility of Masonry Infilled RC Frames under In-Plane Loading

2022· article· en· W4290465959 on OpenAlex
Chunhui Liu, Bo Liu, Xiaomin Wang, Jingchang Kong, Yuan Gao

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

VenueBuildings · 2022
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of ChinaYantai University
KeywordsMasonryFragilityStructural engineeringFrame (networking)Reinforced concreteSeismic analysisEngineeringPlane (geometry)GeologyMathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

Masonry infilled RC frames are one of the most common structural forms, the damage of which, in earthquake events, usually cause serious losses. The determination of the seismic performance target is the key foundation of performance-based seismic evaluation and design for masonry infilled RC frames. In this paper, an extensive database of experimental tests on infilled RC frames loaded in an in-plane direction is collated. According to the crack propagation and elastic-plastic characteristics of infilled RC frames, the damage process is divided into four stages, and then the criteria of the damage states (DS) are proposed. In addition, the seismic performance targets expressed as inter-story drift ratio (IDR) for the four stages are suggested, which would support the performance-based in-plane seismic analysis of infilled RC frames. Finally, the proposed in-plane seismic performance target is utilized to analyze the fragility of two masonry infilled RC frame structures.

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.

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 score0.047
Threshold uncertainty score0.638

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)0.0010.000

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 head0.187
Teacher spread0.182 · 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