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Record W4229788516 · doi:10.32920/ryerson.14646663

Seismic design of liquid-containing concrete structures

2021· preprint· en· W4229788516 on OpenAlexaff
Au Lu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicEarthquake and Tsunami Effects
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSlosh dynamicsStructural engineeringFreeboardSeismic analysisBendingBucklingEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

The seismic design of structures is a requirement for any places [sic] where earthquake [sic] occurs, and the design is based upon the codes that vary according to the jurisdictions in which the code was developed for. This study introduces and assesses the document ACI 350.3-06 which was developed by the ACI Committee to guide the design of liquid containing structures, and compares to other codes such as ACI 350.3-01 and NZS 3106 of New Zealand Standard. The importance of liquid containing structures cannot be stressed further, as it is apparent in nuclear applications. The failure of tanks could be due to many reasons: 1) Shell buckling, caused by axial compression due to overall bending. 2) Roof damage as a result of sloshing of the upper portion of the containing liquid due to insufficient provision of freeboard. 3) Failure of inlets and outlets due to their inability to accommodate the deformations of the flexible tank. 4) Differential settlement or failure of supporting soil. The pressures resulted from earthquake [sic] can cause catastrophic disaster, and they [sic] are the impulsive and convective mode which exerts pressures on the walls of the tank. The hydrodynamic model used to estimate these pressures in the ACI 350.3-06 document has also adopted earlier works from Housner, Veletsos, and Shivakumar. Throughout the years, the code has transformed tremendously, and this study shows that the codes are very similar in many ways, yet their differences can yield significantly different results. Furthermore, the results from the various codes are illustrated using the same example, and the validity of the results are determined as well. The effects on seismic design due to the types of structure, whether the tank is rigid or flexible, and the support system are also introduced; moreover, their absences and the variations in the estimation of seismic parameters in some codes are also shown to have a large effect on the load estimation.

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)0.000
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.225
Teacher spread0.209 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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