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Record W4226247697 · doi:10.22215/etd/2022-14828

The Effects of 2-D Bedrock Profile on Site Specific Seismic Amplifications in Leda Clay

2022· dissertation· en· W4226247697 on OpenAlexaff
Prasanthan Ramakrishnan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsCarleton University
Fundersnot available
KeywordsBedrockGeologyStructural basinLiquefactionGeotechnical engineeringSoil waterGeomorphologySoil science

Abstract

fetched live from OpenAlex

The primary objective of the research is to understand the significance of the effects of the bedrock profile on seismic amplifications in soft soil deposits.Inclined soil-bedrock interfaces lead to simultaneous primary and secondary wave loading on soils, and a numerical study has been undertaken to assess whether ignoring them may lead to design deficiencies.The response of a site in Orleans with a deep Leda clay deposit at the center, but with a concaved bedrock profile, leading to a soft soil-deposit "valley", is evaluated using 2-D numerical analysis.The seismic response of Leda clay on a hypothetical horizontal bedrock (representing conventional practice), and two different natural bedrock basins has been studied.The National building code of Canada (NBCC 2015) design spectra compatible earthquake shaking was considered.The comparisons between the conventional practice and the response of the 2-D basin demonstrate that assessment of the cyclic loading intensity is significantly affected by the basin shape.Higher cyclic stress ratio (CSR) values are realized in the 2-D analysis due to basin geometry, and the magnitude of the CSR is dependent on the configuration of the basin.This indicates that ignoring basin geometry effects might lead to unsafe liquefaction susceptibility assessments.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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