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Record W2316018513 · doi:10.1061/41000(315)37

Modelling Post-and-Beam Wooden Buildings under Seismic Loads

2008· article· en· W2316018513 on OpenAlex

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

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsShear wallStructural engineeringRoofStructural loadDiagonalStiffnessEarthquake shaking tableBeam (structure)Nonlinear systemSeismic loadingFinite element methodEngineeringStructural systemGeotechnical engineeringGeologyMathematicsGeometry

Abstract

fetched live from OpenAlex

This paper presents a nonlinear finite element structural model — "PB3D" to simulate the seismic response of Japanese post and beam (P&B) wooden buildings. A versatile mechanics-based "pseudo nail" wall model is used to represent the nonlinear load-drift characteristics of the shear walls under lateral loads. The roof/floor diaphragms are modeled as structural frames with equivalent diagonal bracings to consider the influence of the roof/floor in-plane stiffness on the lateral force distribution among the walls. This approach significantly reduced the overall system degrees-of-freedom while allow the model to represent the key characteristics of the system under lateral loads. Experimental studies on shear walls and floor diaphragm were conducted to calibrate the wall models and the equivalent floor diaphragms. The model prediction agrees well with the shake table test results of a single-storey P&B building. The "PB3D" model provides an efficient tool to evaluate the seismic performance of general Japanese P&B wooden 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.

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 score0.284
Threshold uncertainty score0.901

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 head0.016
GPT teacher head0.196
Teacher spread0.180 · 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