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Record W2807525930 · doi:10.1061/9780784481486.052

Selecting Moduli Reduction and Damping Curves Based on Cone Penetration Test Soil Behaviour Type

2018· article· en· W2807525930 on OpenAlexaff
Mark A. Styler, John Rogie, Ilmar Weemees

Bibliographic record

VenueGeotechnical Earthquake Engineering and Soil Dynamics V · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsConetec Investigations
Fundersnot available
KeywordsCone penetration testPenetration testModuliPenetration (warfare)Geotechnical engineeringShear modulusDamping ratioShear (geology)Materials scienceMathematicsGeologyPhysicsSubgradeComposite materialAcoustics

Abstract

fetched live from OpenAlex

A ground response analysis is performed to evaluate site-specific seismic ground motions. The seismic cone penetration test can be used to obtain shear wave velocity profiles and estimate unit weight profiles for ground response analyses. These analyses also require selection of normalized moduli reduction curves and damping curves. These are often selected from published curves for different soil types including gravels, sands, and clays with different plasticity indices. In this paper we examined if the cone penetration test soil behaviour type index, IC, could be used to inform the selection of published normalized moduli and damping curves. We compiled a set of published curves and cone penetration test (CPT) results in known soil units. We observed that the soil-behaviour-type index from the CPT could be correlated to the shape parameters for normalized moduli and damping reduction curves. The CPT penetration resistance can also be used to estimate the friction angle and limiting shear stress. CPT results can be used to add support to the selected parameters for ground response analyses.

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 categoriesMeta-epidemiology (narrow)
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 score0.065
Threshold uncertainty score1.000

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 head0.005
GPT teacher head0.194
Teacher spread0.189 · 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.

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
Published2018
Admission routes1
Has abstractyes

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