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Performance-Based Capacity Design of Steel Plate Shear Walls. II: Design Provisions

2014· article· en· W2090248961 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Structural Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Alberta
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsDuctility (Earth science)Structural engineeringShear (geology)Shear wallContext (archaeology)Materials scienceEngineeringGeologyComposite material

Abstract

fetched live from OpenAlex

This is Part II of two companion papers on performance-based capacity design of steel plate shear walls. These papers aim to provide a holistic and sound basis for capacity design of steel plate shear walls to any of three explicit performance levels (ductile, moderately ductile, and limited-ductility), with emphasis on design requirements for applications involving lower ductility demands. In this paper, Part II, existing design provisions for ductile steel plate shear walls are briefly reviewed and discussed, with some modifications recommended, and capacity design provisions for limited-ductility walls are proposed based on the development principles presented in Part I. Capacity design provisions for moderately ductile walls are then rationalized based on the development principles for the other two performance levels. The proposed capacity design methods for the limited-ductility and moderately ductile performance levels are applied to design examples, and the results are discussed in the context of the observed performance of two multistory steel plate shear walls tested under cyclic lateral loading.

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 categoriesMeta-epidemiology (narrow)
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 score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.190
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