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Record W2181166343 · doi:10.1139/cjce-2015-0198

Nonlinear behaviour of reinforced concrete conical tanks under hydrostatic pressure

2015· article· en· W2181166343 on OpenAlexafffundvenue
Ahmed Elansary, Ashraf A. El Damatty, Ayman M. El Ansary

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsWestern University
FundersLa Trobe UniversityGovernment of Ontario
KeywordsConical surfaceFinite element methodHydrostatic pressureStructural engineeringDeflection (physics)Hydrostatic equilibriumNonlinear systemMaterials sciencePlasticityWater tanksGeotechnical engineeringEngineeringMechanicsComposite materialMarine engineeringPhysics

Abstract

fetched live from OpenAlex

Among the different shapes available, conical vessels are commonly used as water reservoirs because of their large storage capacities. Motivated by the lack of guidelines available for their analysis and design in the existing codes of practice, this study focuses on analyzing reinforced concrete conical tanks under the effect of hydrostatic pressure. A finite element model (FEM), which accounts for material nonlinearity experienced in reinforced concrete, is developed. This nonlinearity is considered by implementing a concrete plasticity constitutive model in the developed FEM. Analysis of a set of 12 tanks with different practical dimensions is performed under hydrostatic water pressure. The variations of meridional and hoop stresses through the thickness of the tanks are determined by plotting the stresses at the outer faces of the tank’s wall. The effect of including material nonlinearity in the FEM on the deformed shape is assessed. The developed FEM is used to find the location of maximum deflection and stresses. The variations in the maximum deflection and stresses with the dimensional parameters of the conical vessel are reported.

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 score0.003
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.214
Teacher spread0.203 · 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

Citations10
Published2015
Admission routes3
Has abstractyes

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