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Record W2739378097 · doi:10.1063/1.4992155

Numerical simulation of magneto-acoustic Wave Phase Conjugation with the DG method in the CPR framework

2017· article· en· W2739378097 on OpenAlexaff
Amir Modarreszadeh, Evgeny Timofeev, Alain Merlen, Olivier Bou Matar, Philippe Pernod

Bibliographic record

VenueAIP conference proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsMagnetoLimiterWavelengthComputer simulationPhysicsMathematical analysisNumerical analysisPhase (matter)AcousticsMathematicsMechanicsComputer scienceOpticsTelecommunications

Abstract

fetched live from OpenAlex

The present paper is concerned with the numerical modeling of magneto-acoustic Wave Phase Conjugation (WPC) phenomena. Since ultrasonic waves in the WPC applications have short wavelengths relative to the traveling distances, high-order numerical methods in both space and time domains are required. The numerical scheme chosen for the current research is the Runge-Kutta Discontinuous Galerkin (RKDG) method incorporated into the Correction Procedure via Reconstruction (CPR) framework. In order to avoid non-physical oscillations near high-gradient regions, a Weighted Essentially Non-Oscillatory (WENO) limiter is used to reconstruct the solutions in the affected cells. After being assured that the numerical scheme has appropriate accuracy and performance, the WPC process is modeled in both linear and non-linear regimes. The results in the linear regime are in acceptable agreement with the analytical solution. The only significant deviation between the linear and non-linear results is at the sensor within the passive zone, where the mean pressure starts to grow gradually in the non-linear regime due to overtaking of the low-velocity pressure waves by the high-velocity ones.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.037
GPT teacher head0.337
Teacher spread0.300 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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