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Record W2331119965 · doi:10.1061/9780784413357.216

Three-Dimensional, Nonlinear, Dynamic Analysis of Modular Steel Buildings

2014· article· en· W2331119965 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
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOpenSeesModular designStructural engineeringNonlinear systemDiscontinuity (linguistics)Ground motionComputer scienceEngineeringFinite element methodMathematics

Abstract

fetched live from OpenAlex

Modular construction is a relatively new technique where prefabricated units are assembled on-site to produce a complete building. Due to detailing requirements for the assembly of the modules, these systems are prone to undesirable failure mechanisms during large earthquakes. Specifically, for multi-story modular steel buildings (MSBs), column discontinuity coupled with possible high inelasticity concentration in vertical connections can be an area of concern. Diaphragm interaction, relative displacements and rotations between modules, and the way forces are transferred through horizontal connections are other important aspects that are considered in this study. To have an assessment of seismic demand and capacity of MSBs, using OpenSees, three-dimensional (3D), nonlinear dynamic analyses of a detailed, 4-story, MSB structure with 48 modules have been carried out. Since nonlinear analysis is inherently sensitive to ground motion characteristics, Incremental Dynamic Analyses (IDA) have been performed and conclusions have been made to provide a better understanding.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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