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Record W3065078114 · doi:10.2514/6.2020-3518

Two-Dimensional Simulation of Laser Thermal Propulsion Heating Chamber

2020· article· en· W3065078114 on OpenAlexaff
Zhuo Fan Bao, Andrew Higgins

Bibliographic record

VenueAIAA Propulsion and Energy 2020 Forum · 2020
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsMcGill University
Fundersnot available
KeywordsLaser propulsionSpacecraft propulsionInterplanetary spaceflightLaserAerospace engineeringPropulsionThermalRocket (weapon)Combustion chamberCombustionOpticsMaterials sciencePhysicsEngineeringPlasmaMeteorologyNuclear physicsChemistry

Abstract

fetched live from OpenAlex

In light of the development of novel and potentially disruptive laser array systems, laser thermal propulsion as a candidate propulsion architecture for interplanetary travel is investigated. This study surveys past literature from the 1970s and 1980s on numerically resolving the temperature profile of a laser-supported combustion wave and presents an updated version of those models for 1.06 micron laser. Through such an analysis, it is concluded that a laser thermal rocket, complemented by the novel laser array, can achieve heating chamber temperatures on the order of 20,000-40,000 K, suitable for rapid interplanetary flight.

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 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 score0.068
Threshold uncertainty score0.579

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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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
Published2020
Admission routes1
Has abstractyes

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