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Record W7008254183

Assessment of seismic design parameters for midply wood shear wall system

2008· article· en· W7008254183 on OpenAlexaboutno aff

Bibliographic record

VenueIris (Roma Tre University) · 2008
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsShear wallShear (geology)StiffnessSeismic analysisShear forceShear strength (soil)Seismic loadingEuropean standard
DOInot available

Abstract

fetched live from OpenAlex

A midply shear wall provides greater lateral load capacity per unit length than a standard shear wall. The improved performance is achieved by placing the sheathing between wall stud members, which subjects the nails to double-shear when the wall is loaded in shear. Tests have shown that the average lateral load capacities and energy dissipations of midply walls can be more than three times that of standard shear walls, while their stiffness can be between two to three times the average stiffness of standard shear walls. A proposal for implementation of the midply wall system in wood design codes in North America is presented. Non-linear dynamic analyses of a four-storey wood-frame building were used to determine the seismic design parameters for midply shear walls. The analysis utilized a suite of 22 selected earthquake records scaled to the peak ground acceleration stipulated in the National Building Code of Canada 2005 for Vancouver, British Columbia. The probability of failure was determined for building built with both standard and midply shear walls. Using the standard shear walls as the bench mark, this study indicates that a ductility-related force modification factor R d = 3 could be safely assigned for the midply shear wall system to achieve the same safety level as the standard shear wall system.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.592

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 head0.022
GPT teacher head0.197
Teacher spread0.174 · 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 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

Citations2
Published2008
Admission routes1
Has abstractyes

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