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Record W1996152544 · doi:10.1139/t08-045

A modified approach for determination of nonlinear properties in seismic response analyses for 200 m high core rock-fill dams

2008· article· en· W1996152544 on OpenAlexvenueno aff
Hongjun Li, Shichun Chi, Gao Lin, Hong Zhong

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyNational Natural Science Foundation of China
KeywordsNonlinear systemGeotechnical engineeringGeologyShearing (physics)Response analysisOverburden pressureRange (aeronautics)Materials scienceStructural engineeringEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

Equivalent linear analyses are widely used for estimation of site response and safety status of rock-fill dams subjected to strong earthquakes. However, the average normalized curves incorporated in the equivalent-linear iterative process cannot precisely depict the variations of dynamic parameters with shearing strain for one type of soil material under a wide range of confining pressures. Thus, a modified approach for the determination of nonlinear properties for soil elements confined under a broad range of effective pressures in site response analyses for high rock-fill dams (>200 m) is proposed. In this approach, the normalized confining-pressure-interpolating curves (CPI curves) of each soil element under different effective stress are obtained by linearly interpolating or extrapolating by its in situ stress. By comparing the results obtained by equivalent linear analyses incorporating the average curves and the CPI curves, respectively, the impact of utilizing the recommended curves when determining nonlinear soil properties on site response analyses of high rock-fill dams (>200 m) is discussed. It is shown that the refinement in the determination of nonlinear properties during site response can be utilized in the near future by incorporating the results of this study in practice.

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: none
Teacher disagreement score0.629
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.048
GPT teacher head0.256
Teacher spread0.209 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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