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Record W2099515327 · doi:10.1193/081413eqs230m

Application of Simplified Analysis Procedures for Performance‐Based Earthquake Evaluation of Steel Special Moment Frames

2015· article· en· W2099515327 on OpenAlex
Dimitrios G. Lignos, Christopher M. Putman, Helmut Krawinkler

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

VenueEarthquake Spectra · 2015
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsMcGill University
FundersNational Institute of Standards and Technology
KeywordsNonlinear systemStructural engineeringMoment (physics)ResidualEngineeringMode (computer interface)Work (physics)Incremental Dynamic AnalysisGeologyGeotechnical engineeringComputer scienceSeismic analysisAlgorithmMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

This paper evaluates the effectiveness of single and multi‐mode nonlinear static procedures (NSPs) as well as the FEMA P58 simplified approach versus rigorous nonlinear response history analyses (NRHA) for estimating seismic demands of steel special moment frames (SMFs). This work was mostly conducted within the framework of the ATC‐76‐6 project and indicates the level to which simplified analysis procedures in combination with commonly used nonlinear component models can reliably predict story‐level engineering demand parameters (EDPs) such as, story drift ratios, story shear forces, overturning moments, residual deformations and peak floor absolute accelerations. It is advisable to employ a combination of NSP and NRHA to understand the seismic performance of steel SMFs and quantify important EDPs.

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 score0.077
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.271
Teacher spread0.243 · 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