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Seismic Safety of Gravity Dams: From Shake Table Experiments to Numerical Analyses

2000· article· en· W2020909870 on OpenAlexafffund
René Tinawi, Pierre Léger, Martin Leclerc, G. Cipolla

Bibliographic record

VenueJournal of Structural Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsPolytechnique Montréal
FundersCore Research for Evolutional Science and TechnologyNatural Sciences and Engineering Research Council of Canada
KeywordsEarthquake shaking tableAccelerationGravity damCrackingStructural engineeringGeologyPeak ground accelerationDisplacement (psychology)MechanicsNonlinear systemGeotechnical engineeringFracture mechanicsFinite element methodMaterials scienceEngineeringPhysicsGround motionClassical mechanicsComposite material

Abstract

fetched live from OpenAlex

The purpose of this paper is to present shake table experiments conducted on four 3.4-m-high plain concrete gravity dam models to study their dynamic cracking and sliding responses. The experimental results are then compared with a smeared cracked finite-element simulation using a nonlinear concrete constitutive model based on fracture mechanics. For the sliding mechanism, the numerical simulations use rigid body dynamics with frictional strength derived from the Mohr-Coulomb criterion. From the cracking tests, it is shown that a single triangular acceleration pulse could initiate and propagate a crack. The numerical correlation with the observed response is good. However, viscous damping varies experimentally from 1% in an uncracked situation to over 20% in a partially cracked case. For the sliding mechanism when the critical acceleration is exceeded, it is shown experimentally that sliding could occur due to a single triangular acceleration pulse. For actual seismic records, the cumulative sliding displacement for a given peak ground acceleration due to low frequency western North American records can be 3–4 times larger than the corresponding sliding displacements due to high frequency eastern records. For simplified pseudostatic or pseudodynamic sliding analyses, the concept of an effective acceleration is developed.

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)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.013
GPT teacher head0.266
Teacher spread0.253 · 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

Citations82
Published2000
Admission routes2
Has abstractyes

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