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Record W2073313926 · doi:10.1080/13632460601031326

Testing of Superelastic Recentering Pre-Strained Braces for Seismic Resistant Design

2007· article· en· W2073313926 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

VenueJournal of Earthquake Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsBracingSMA*Structural engineeringEarthquake shaking tableShape-memory alloyFinite element methodSteel frameFrame (networking)Materials scienceEngineeringComputer scienceMechanical engineeringComposite materialBrace

Abstract

fetched live from OpenAlex

Over the past decade, the use of shape memory alloys (SMAs) in passive control devices has been explored. Nevertheless, some aspects in regards to the cyclic behavior of SMAs and the effect of pre-straining need to be clarified. In this study, small-scale shake table tests have been performed to explore the effectiveness of SMA bracing systems as compared to steel bracing systems. The reduced-scale experimental results imply that SMAs used in braces are more effective in controlling the response of a steel frame compared with a traditional bracing system. A finite element model (FEM) of the frame is developed in order to compare the analytical results with the shake table tests. Further, the effect of pre-straining the SMA braces is evaluated through both experimental and analytical studies. The results show that pre-straining improves the performance of the frame compared to the nonpre-strained case. However, as the level of pre-straining increases above approximately 1.0% to 1.5%, the benefits of pre-straining decrease compared with low-to-moderate pre-strain levels.

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)0.001
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 score0.395
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.019
GPT teacher head0.223
Teacher spread0.204 · 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