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Record W2135927000 · doi:10.1139/t10-054

Modeling of low-cement extruded curb of concrete-faced rockfill dam

2010· article· en· W2135927000 on OpenAlexvenueno aff
Ga Zhang, Jian‐Min Zhang

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaState Key Laboratory of Hydroscience and Engineering
KeywordsSlabCementDisplacement (psychology)Geotechnical engineeringFinite element methodMaterials scienceStructural engineeringFace (sociological concept)CushionStress (linguistics)Ideal (ethics)GeologyEngineeringComposite material

Abstract

fetched live from OpenAlex

As the key structure of a practical construction technique, the low-cement extruded curb has been widely used in recent concrete-faced rockfill dams (CFRDs). The extruded curb exhibits significant interactions with the neighboring gravels and with the face slab. These interactions were investigated using element tests, and a new model was proposed. This model is composed of three parts: (i) the equivalent slab that is described using an ideal elastoplasticity model, (ii) the equivalent interface between the curb and the gravel cushion layer that is described using an elastoplasticity damage model, and (iii) the interface between the curb and the face slab that is described using a modified ideal elastoplasticity model. This model was verified via a two-dimensional numerical simulation of an ideal CFRD to capture the main behavior of the extruded curb with interactions between the extruded curb and the neighboring soil – face slab, employing a significantly smaller number of elements and a shorter calculation than direct simulation. The model was used to perform a three-dimensional stress–displacement analysis of the Bakun CFRD (205 m in height), and the results showed that the extruded curb causes a change in the stress of the face slab.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.851

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 integrity0.0000.001
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 head0.007
GPT teacher head0.194
Teacher spread0.188 · 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 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

Citations8
Published2010
Admission routes1
Has abstractyes

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