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Record W3211718183 · doi:10.32920/ryerson.14648880.v1

Comparison of analysis techniques for the seismic evaluation of an 88-storey concrete building

2021· preprint· en· W3211718183 on OpenAlexaff
Andrew Shaffu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStructural engineeringResponse spectrumSeismic analysisEarthquake resistanceModalNonlinear systemReinforced concreteDeformation (meteorology)Static analysisEngineeringIncremental Dynamic AnalysisModal analysisFinite element methodComputer scienceGeologyMaterials sciencePhysics

Abstract

fetched live from OpenAlex

This thesis presents the comparison of results for an 88-storey reinforced concrete building subjected to static and dynamic analyses. Similar to a building designed in a moderate seismic zone, the structure is designed and detailed according to the ACI 318M (2002) Code provisions and the seismic provisions of the UBC (1997). The building is modeled according to structural drawings and element design specifications are used in describing members' deformation characteristics. Resistance to dynamic motion is provided through boxed core-wall assemblies acting as cantilevers walls in one direction and linked with coupling beams at storey levels in the orthogonal direction. The equivalent static, dynamic modal spectrum, linear time-history and nonlinear time-history analyses are employed and a comparison of maximum inter-storey drift response is provided. The results of the analyses show that the linear time-history analysis is the most appropriate method in capturing the behavior of this particular building under dynamic loading.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.051
GPT teacher head0.361
Teacher spread0.310 · 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
Published2021
Admission routes1
Has abstractyes

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