MétaCan
Menu
Back to cohort
Record W4313221317 · doi:10.54097/hset.v27i.3858

Principles of Multistage Rocket Vehicle and Concepts of Propulsion Methods for Rocket Applications

2022· article· en· W4313221317 on OpenAlexaff
Xinyuan Liang

Bibliographic record

VenueHighlights in Science Engineering and Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsQueen's University
Fundersnot available
KeywordsPropulsionAerospace engineeringIn-space propulsion technologiesPayload (computing)Rocket (weapon)Spacecraft propulsionPropellantThrustBooster (rocketry)AeronauticsElectrically powered spacecraft propulsionAutomotive engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

The variety of propulsion methods will reach their peak efficiencies under certain conditions. This paper will focus on the propulsion methods and different propellant choices for certain usage when designing a vehicle or a stage of a rocket with some altitude limitations, their working principles, applications and challenges. The advantages of multistage design for rocket vehicles and the prospects of advanced engine technology using electricity or solar radiation as its main power source will also be discussed. The cost, payload and other attributes such as the thrust-to-weight ratio of every propulsion concept are the main factors for determining the general performance. MRV is the ideal design for rocket vehicles that are launched from the surface of a planet consider the massive amount of energy it requires to get into the orbit or escape the gravity, but the propulsion system can be various depends on the applications under certain conditions of launching and space travel.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.330
Teacher spread0.311 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHighlights in Science Engineering and TechnologySame topicRocket and propulsion systems researchFrench-language works237,207