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Record W2329145856 · doi:10.1061/9780784479117.217

Seismic Design and Performance of High-Rise Steel Buildings under Various International Design Codes

2015· article· en· W2329145856 on OpenAlexaff
Nadeem Hussain, M. Shahria Alam

Bibliographic record

VenueStructures Congress 2015 · 2015
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsSeismic analysisRange (aeronautics)Structural engineeringIncremental Dynamic AnalysisComputer scienceDeformation (meteorology)Seismic loadingEngineeringCivil engineeringGeology

Abstract

fetched live from OpenAlex

The increase in the number of seismic events and their devastations in the recent past has assisted in many developments in seismic codes of various international standards. Codes adopt conventional elastic methods in the design of structures to estimate the strength and deformation demand employing seismic design factors to represent the nonlinear behavior of the structure. Four typical high-rise steel buildings of 8, 12, 16 and 20 stories are designed and detailed using various seismic codes. Seismic response of the reference buildings is assessed with detailed fiber-based models using inelastic pushover and incremental dynamic analyses subject to 20 strong seismic records. The proposed study provides comparisons between different seismic design codes for the range of the reference buildings at different performance levels. This study may help the designers in optimizing their design in the seismic regions and provide an insight to assess the seismic performance and predict the behavior at different performance 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.237
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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