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Record W4392506181 · doi:10.1061/9780784485316.026

Liquefaction Timing and Post-Triggering Seismic Energy: A Comparison of Crustal and Subduction Zone Earthquakes

2024· article· en· W4392506181 on OpenAlexaff
Trevor J. Carey, Atira Naik, Andrew J. Makdisi, H. Benjamin Mason

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSubductionGeologySeismologySeismic energyLiquefactionEpisodic tremor and slipEnergy (signal processing)Geotechnical engineeringTectonics

Abstract

fetched live from OpenAlex

The objective of the study is to assess when liquefaction is triggered in a suite of ground motions following simplified approaches and measure the remaining post-triggering energy content of those ground motions. For liquefaction-induced deformations, current simplified analysis procedures do not directly incorporate temporal effects and rely on peak transient intensity measurements. Liquefaction hazard from short-duration, small to moderate-magnitude (M) earthquakes (M4.5–7.5) is adequately expressed using transient intensity measurements. However, subduction-zone interface earthquakes can have magnitudes greater than 9.0, with ground-motion durations exceeding 300 s. Using 525 ground motions from the NGA-Subduction (NGA-Sub) database for subduction-zone earthquakes with M8.25–9.25, the timing of liquefaction was calculated using cyclic counting procedures by assuming a reference stress condition and incorporating cyclic strengths from laboratory element testing. A complementary analysis was completed using 514 crustal ground motion records from the NGA-West2 database for M6.75–7.75. Several trends were identified during this study. First, liquefaction will likely trigger during the first half of the ground motion duration, independent of the earthquake source type. However, subduction-zone motions have larger post-triggering energy content compared to crustal earthquakes. The findings from this work indicate that accurately predicting liquefaction-induced deformations from subduction-zone earthquakes may be substantially improved by using robust time-based liquefaction analysis procedures.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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