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Record W4414021765 · doi:10.1002/eqe.70048

Automated Recovery of Permanent Displacement in Near‐Fault Ground Motions with Fling‐Step Effects

2025· article· en· W4414021765 on OpenAlex
Zhiwang Chang, Katsuichiro Goda, Zhenxu Yan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarthquake Engineering & Structural Dynamics · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsWestern University
FundersNatural Science Foundation of Sichuan ProvinceNational Natural Science Foundation of China
KeywordsDisplacement (psychology)Structural engineeringFault (geology)Ground motionGeologyComputer scienceEngineeringSeismology

Abstract

fetched live from OpenAlex

ABSTRACT The fling‐step is a result of the permanent tectonic offset of the ground in the near‐fault regions of large earthquakes. Ground motions containing the fling typically feature a one‐sided pulse in the velocity and a non‐zero permanent displacement (PD) at the end of shaking. Generally, the information regarding PD is not available in many worldwide databases due to the presence of various errors, as well as the limitations of current practices in eliminating the errors that are contained in the raw or unprocessed ground motions. The sources of the errors are usually complex and unpredictable, making the work of retrieving PD challenging. To address this issue, an automated baseline correction approach is proposed to recover the PD of interest. Raw ground motions are first assumed as consisting of the low‐frequency (LF) and the high‐frequency (HF) contents, with the former and the latter containing the PD and the errors, respectively. The LF contents are extracted from the raw motion by using a modified progressive iterative approach, while the HF contents are filtered to remove the error. The corrected ground motions are then obtained by combining the extracted LF and the filtered HF contents. Ninety‐eight ground motions are next identified as containing the fling, and used for validation of the proposed approach. It is shown that the obtained PDs agree well with the geodetic data and existing empirical models, demonstrating the desirable performance of the proposed algorithm. Finally, the effects of baseline corrections on the properties of near‐fault ground motions are discussed. The proposed approach does not require the selection of any key time instants that have to be specified in previous studies, thereby avoiding the subjectivity and uncertainty involved in performing relevant algorithms. Besides, it enables an objective criterion for characterizing fling‐step ground motions, facilitating the quantitative and systematic investigation of PD. Effective correction of raw ground motions recorded in the near‐fault areas is crucial for seismological and earthquake engineering in studying slips on the fault plane, assessing the effect of fling on the seismic hazard, and analyzing the seismic response of near‐fault or fault‐crossing buildings and infrastructure. Summary An automated approach is proposed for the baseline correction of near‐fault ground motions containing fling‐step effects. Permanent displacements resulting from the fling‐step effects can be recovered from raw ground motions by using a modified progressive approach. The derived permanent displacements match reasonably well with the geodetic data and existing empirical models. Investigations of the effects of baseline correction indicate that there are no major changes in the tested intensity measures of near‐fault ground motions.

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.

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 score0.397
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.002
GPT teacher head0.192
Teacher spread0.190 · 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