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Record W4408442897 · doi:10.3390/act14030145

Numerical Simulation of the Performance of a Combustion-Driven SparkJet Actuator a with Laval Outlet Configuration

2025· article· en· W4408442897 on OpenAlexaboutno aff
Hai Chen, Hongyan Zuo, Guohai Jia

Bibliographic record

VenueActuators · 2025
Typearticle
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsActuatorComputer simulationCombustionAerospace engineeringControl theory (sociology)EngineeringMechanicsMechanical engineeringComputer sciencePhysicsChemistryControl (management)Artificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

To increase the jet momentum and improve the environmental adaptability, a combustion-driven SparkJet actuator with a Laval-configured outlet is proposed to improve the performance of the actuator. Numerical simulation results show that, compared to straight outlet combustion-driven actuators with outlet diameters of 2 mm and 2.8 mm, the maximum jet velocity of the Laval-configured actuator increases by approximately 100 m/s and 350 m/s, separately. while the peak times decrease by about 50% and 12%, respectively. The work frequency of the Laval-structured combustion-driven actuator is 1333 Hz, which is higher than the 1176 Hz of the straight-tube-structured combustion-driven actuator with an outlet diameter of 2 mm. The Laval configuration effectively improves the working performance of the actuator. As the equivalence ratio increases from 0.6 to 1, the actuator’s jet velocity increases by approximately 65 m/s and 311 m/s, respectively, and its maximum combustion temperature is raised from 2700 K to 3000 K. The saturation work frequency is nearly the same. The pressure and jet mass flow rate in the actuator drop as the atmospheric pressure declines, while the combustion-driven actuator still exhibits high working performance when the atmospheric pressure is low. The maximum outlet velocity, Mach number, pressure, and temperature increase by about 20%, 13%, 25%, and 6%, while the peak time increases by about 40% as the ignition position moves from the middle position to a 2.8 mm displacement toward the outlet.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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
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
Published2025
Admission routes1
Has abstractyes

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