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Record W3164870752 · doi:10.2514/6.iac-06-c1.5.05

General Dynamics in the Restricted Full Three-Body Problem

2006· article· en· W3164870752 on OpenAlexfundno aff
Julie Bellerose, Daniel J. Scheeres

Bibliographic record

Venue57th International Astronautical Congress · 2006
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsnot available
FundersJet Propulsion LaboratoryNatural Sciences and Engineering Research Council of CanadaCalifornia Institute of Technology
KeywordsComputer scienceDynamics (music)Physics

Abstract

fetched live from OpenAlex

Abstract The problem of a binary system and a spacecraft in its gravity field is studied. As the mass distribution of the bodies is considered, the two problems are referred as the Full Two Body Problem (F2BP) and the Restricted Full Three Body Problem (RF3BP), respectively. The conditions for relative equilibria and their stability in the F2BP were derived for an ellipsoid–sphere system. As the non-equilibrium problem is more common in nature, we look at periodic orbits in the F2BP close to the relative equilibrium conditions. It is found that families of periodic orbits can be computed where the minimum energy state of one family is the relative equilibrium state. An approximation method was derived in order to facilitate the computation of periodic orbits near relative equilibria while keeping the interesting dynamical features. The next step is to make the connection between the dynamics of the RF3BP and the F2BP. In the current paper, we solve for the dynamics of the F2BP and substitute this model in the RF3BP. We provide a basic investigation of the dynamics of a particle in the gravitational field of this binary system. We show results in the F2BP and the RF3BP.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.210
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 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
Published2006
Admission routes1
Has abstractyes

Explore more

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