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Record W4232444356 · doi:10.32920/ryerson.14644305

Using A High Repetition Rate Nd: YAG Laser For Pulsed Laser Ablation Propulsion

2021· preprint· en· W4232444356 on OpenAlexaff
Daniel Hayek

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSpecific impulseLaser propulsionLaserThrustPropulsionPropellantMaterials scienceImpulse (physics)AmplifierOpticsLaser ablationSpacecraft propulsionAblationAerospace engineeringAcousticsPhysicsEngineeringOptoelectronics

Abstract

fetched live from OpenAlex

Laser propulsion is a relatively new technology being researched for its vast potential. A test apparatus was developed to measure small forces using piezoelectric films and a developed amplifier tuned to the specific frequencies expected from the system. The system provided consistent results comparable to published values. The tests conducted in this thesis evaluated the effects of using a high repetition rate laser for laser propulsion. The results are on the micropropulsion scale, however, the findings are expected to perform similarly on a larger scale. The thrust, moment coupling coefficient, and specific impulse values were evaluated for aluminum, brass, and PVC of differing thicknesses. The results concluded that the repetition rate in fact did not have much effect on the thrust; thrust was primarily dependent on the pulse energy and the material thickness. The repetition rate was found to affect the specific impulse values; a result of the heat affected zone created by the laser ablation, thereby reducing the effective propellant used for propulsion.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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