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Record W3119154899 · doi:10.1139/cjce-2019-0583

Nonlinear behavior of ground-supported circular reinforced concrete tanks

2021· article· en· W3119154899 on OpenAlexaffvenue
M. Rafieeraad, M. Reza Kianoush, Mehdi Moslemi

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStructural engineeringNonlinear systemFinite element methodSeismic analysisCurrent (fluid)EngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

This study aims to investigate the effect of various parameters on the seismic behavior of concrete tanks. A finite element method using pushover and time-history analysis is developed to investigate the seismic behavior of circular ground-supported tanks. The response modification factor (R) is evaluated based on nonlinear static and time-history analyses. R-factor is one of the key parameters in seismic design. In liquid containing structures, R-factor in current codes and standards are based on empirical values. Therefore, a justifiable guideline to accurately determine these values is yet to be developed. This study shows that the effect of tank size, material non-linearity, base condition, and earthquake frequency is significant. Also, fixed based and shallow tanks have higher R values compared to hinged based and tall tanks, respectively. Based on the results of this study, it is found that the value of R specified in current practice is not appropriate.

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)0.000
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.007
GPT teacher head0.185
Teacher spread0.177 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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