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Record W4310179634 · doi:10.1080/13632469.2022.2148018

Estimation of Vertical Peak Floor Acceleration Demands in Elastic RC Moment-Resisting Frame Buildings

2022· article· en· W4310179634 on OpenAlexafffundabout
Shahabaldin Mazloom, Rola Assi

Bibliographic record

VenueJournal of Earthquake Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBuilding codeAccelerationSlabStructural engineeringMoment (physics)Reinforced concreteGround motionFrame (networking)GeologyPeak ground accelerationGeotechnical engineeringRangingSeismic analysisSeismologyDuctility (Earth science)EngineeringGeodesyPhysics

Abstract

fetched live from OpenAlex

This paper assesses the vertical seismic accelerations in four 3-D elastic RC moment-resisting frame buildings with limited ductility, designed according to the National Building Code of Canada (NBC 2015). 65 near-fault strong motions recorded on dense soil were considered. The greatest amount of amplification of vertical acceleration was observed at the center of the buildings’ interior slab, with maximum median normalized values ranging from 4.0, in the 3-storey building, to 1.24, in the 12-storey building. This study indicates that the vertical earthquake motion should not be overlooked in the analysis and design process, especially in low-rise buildings.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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

Citations4
Published2022
Admission routes3
Has abstractyes

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