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Record W3008466188 · doi:10.1061/9780784482810.003

A Synthesized Approach for Assessing the Seismic and Post-Seismic Performance of a Dumped Rockfill Dam with a Shotcrete Face

2020· article· en· W3008466188 on OpenAlexaffabout
Thuraisamy Thavaraj, Garry Stevenson

Bibliographic record

VenueGeo-Congress 2020 · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsKlohn Crippen Berger (Canada)
Fundersnot available
KeywordsShotcreteFace (sociological concept)Geotechnical engineeringGeology

Abstract

fetched live from OpenAlex

Ageing dams located across the west coast of North America, both in the USA and Canada, are threatened by potential for large earthquakes. Assessing the seismic performance of these dams has been a challenge. This paper presents a synthesized approach for assessing the seismic and post-earthquake performance of a dumped rockfill dam built in the 1960s with a gunite (shotcrete) face as the water barrier. The dam may lose its freeboard due to seismic settlements. If loss of freeboard does not occur, the gunite face can still crack and allow leakage. Excessive discharge at the downstream toe due to the through-flow may cause the rockfill at the toe to unravel. Such unraveling and consequent sloughing of the slope may cause a dam breach. The synthesized approach consists of a dynamic analysis and methods for assessing the cracks in the gunite face, leakage through the upstream face, and potential for unraveling and instability of the downstream slope.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.197
Teacher spread0.190 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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