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Record W3165611297 · doi:10.11159/iccste21.137

Experience on Earthquake Safety of Large Embankment DamsConstructed in Turkey

2021· article· en· W3165611297 on OpenAlexvenueno aff
Hasan Tosun

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsLeveeForensic engineeringCivil engineeringEnvironmental scienceGeologyEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Strong ground shaking results in the instability of the embankment and loss of strength at the foundations. Earthquakes can result in damages or failures for dam structures, while dams with large reservoirs can induce to earthquakes. Earthquake safety assessment is an important phenomenon in dam engineering and requires more comprehensive seismic studies for understanding the seismic behavior of dams subjected to severe earthquakes. Seismic hazard and seismic design are important aspects for large dam projects. Case studies about the seismic performance of dams under large earthquakes are available in the literature. Especially active faults on or near dam sites can cause to damaging deformation of the embankment. Turkey has so many dams, which are under the influence of near source zone. This study outlines stability analyses of large embankment dams located on active seismic area, discusses the experience on behavior of large embankment dams located on or near active faults in Turkey and introduces results of total risk analyses of the case studies including large embankment dams, namely Ataturk, Altinkaya, Catalan, Ilisu, Keban, Kilickaya, Menzelet, which have structural heights of 70 to 207 m.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Civil, Structural and Transportation EngineeringSame topicDam Engineering and SafetyFrench-language works237,207