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Record W4407806036 · doi:10.1093/gji/ggaf054

Seismic wavefield injection based on interface discontinuity: theory and numerical implementation based upon the spectral-element method

2025· article· en· W4407806036 on OpenAlexafffund
Tianshi Liu, Nanqiao Du, Ting Lei, Kai Wang, Bin He, Ping Tong, Giovanni Grasselli, Qinya Liu

Bibliographic record

VenueGeophysical Journal International · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Toronto
FundersAir Force Research LaboratoryNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsDiscontinuity (linguistics)GeologySpectral element methodSeismologyFinite element methodInterface (matter)Seismic waveGeophysicsExtended finite element methodMathematical analysisMechanicsMathematicsStructural engineeringPhysics

Abstract

fetched live from OpenAlex

SUMMARY In seismology, wavefield injection refers to the propagation of seismic waves generated by remote sources into local domains bounded by enclosed surfaces. The simulations of wavefield injection, primarily focused on the interaction between incoming seismic waves and local structures, are key to earthquake hazard modelling and full-waveform seismic tomography using tele-seismic waves. In this paper, we show that simulating wavefield injection is equivalent to solving the wave equation subject to interface discontinuity conditions. To provide a general framework to study wavefield injection, we formally define the interface discontinuity problem, and discuss its representation theorem and uniqueness. We also develop an efficient interface-discontinuity-based numerical algorithm to solve the wavefield injection problem through implementations of spectral-element methods, and show with numerical examples that wavefield injection can be accurately simulated at different scales with this algorithm. Under this framework, we draw connections with previously proposed wavefield injection algorithms/hybrid methods, and clarify several theoretical questions on wavefield injection from previous research. We demonstrate the efficiency and accuracy of our approach through wavefield injection examples at local and continental scales. Furthermore, we illustrate the applicability of the interface discontinuity approach to performing kinematic fault simulations through a numerical example.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.009
GPT teacher head0.295
Teacher spread0.287 · 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

Citations5
Published2025
Admission routes2
Has abstractyes

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