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Record W4392393379 · doi:10.26089/nummet.v25r107

Algorithms of solution correction for numerical simulation of the dynamics of elastic-plastic, granular and porous media

2024· article· ru· W4392393379 on OpenAlexfundno aff
В. М. Садовский, О. В. Садовская

Bibliographic record

VenueVyčislitelʹnye metody i programmirovanie · 2024
Typearticle
Languageru
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsnot available
FundersMinistry of Science and Higher Education of the Russian FederationCentre de Recherches Mathématiques
KeywordsPorous mediumDynamics (music)PorosityMechanicsStatistical physicsMaterials scienceComputer sciencePhysicsComposite materialAcoustics

Abstract

fetched live from OpenAlex

На основе математического аппарата вариационных неравенств разработаны оригинальные корректирующие алгоритмы для численного решения динамических задач теории упругопластического течения Прандтля–Рейсса с произвольным условием пластичности. Применяется метод расщепления по физическим процессам. Аналогичные алгоритмы построены для моделирования динамики сыпучей среды и пористой среды с открытыми порами. Based on the mathematical apparatus of variational inequalities, original corrective algorithms are developed for numerical solution of dynamic problems in the theory of elastic-plastic Prandtl–Reuss flow with an arbitrary plasticity condition. The method of splitting into physical processes is used. Similar algorithms are constructed to simulate the dynamics of a granular medium and a porous medium with open pores.

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)0.001
metaresearch head score (Gemma)0.005
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.228
Teacher spread0.219 · 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
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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