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Record W2110527991 · doi:10.1061/9780784413357.212

Large-Scale Testing of Low-Ductility, Concentrically-Braced Frames

2014· article· en· W2110527991 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 2014 · 2014
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsPolytechnique Montréal
FundersLehigh University
KeywordsDuctility (Earth science)Structural engineeringBraced frameSeismic analysisFrame (networking)Structural systemSeismic hazardHazardComputer scienceEngineeringCivil engineeringMaterials scienceMechanical engineering

Abstract

fetched live from OpenAlex

In regions of moderate seismic hazard, the costly structural detailing necessary to ensure adequate ductile performance of a braced frame during an earthquake event can be difficult to justify economically. Structural engineers, however, are permitted to design low-ductility systems if larger demands are assumed. In regions of moderate seismic hazard, this philosophy has proved to be economical and has resulted in widespread use of such low-ductility braced frame systems. Despite this popularity, the inelastic behavior and collapse performance of these systems are not currently understood at a fundamental level. A broadened understanding of the inelastic behavior of low-ductility braced frames can lead to an improved seismic design philosophy and provide practicing structural engineers with a coherent, rational, and transparent design approach applicable to moderate seismic regions. This research aims to identify low-ductility braced frame failure mechanisms and the sequence in which they occur, as well as to draw conclusions on the implications of the observed behavior contextually in building collapse performance.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.657

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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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