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Record W2094761940 · doi:10.1063/1.3686598

Instabilities and turbulence originating from relaxation phenomena behind shock waves

2012· article· en· W2094761940 on OpenAlexafffund
Matei I. Radulescu, Nick Sirmas

Bibliographic record

VenueAIP conference proceedings · 2012
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsDissipative systemDissipationShock wavePhysicsInelastic collisionMechanicsRelaxation (psychology)Shock (circulatory)Internal energyTurbulenceAmplitudeClassical mechanicsWave turbulenceAtomic physicsThermodynamicsOpticsElectronNuclear physics

Abstract

fetched live from OpenAlex

When a strong shock propagates through a medium with internal degrees of freedom, the thermal equilibration involves the transfer of the mechanical energy imparted by the shock to the medium's internal modes. In gases, for example, this energy relaxation within the shock structure involves the re-distribution of the translational thermal energy of the molecules into rotational, vibrational, and electronic modes via inelastic collisions. In the present work, using a toy molecular model, we study the dynamics of shock waves driven through such a dissipative gas, characterized by inelastic collisions. The medium is modelled as a system of hard disks (2D) undergoing either elastic or inelastic collisions. Inelastic collisions are only allowed if the amplitude of the collision exceeds a certain activation threshold. When the medium allows finite dissipation, we find that the shock waves are unstable and form distinctive high density non-uniformities and convective rolls on their surface. The results obtained may shed light on the instabilities observed experimentally behind strong shock waves triggering ionization, vibrational relaxation and dissociation.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.031
GPT teacher head0.265
Teacher spread0.234 · 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 designTheoretical or conceptual
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
Published2012
Admission routes2
Has abstractyes

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