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Record W7133063696

Numerical Methods for Solar Sail Trajectory Optimization

2024· dissertation· W7133063696 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSolar sailTrajectoryGeostationary orbitRadiation pressureTrajectory optimizationRadiationPoint (geometry)Observer (physics)
DOInot available

Abstract

fetched live from OpenAlex

The present study investigates direct shooting and Hermite-Simpson minimum-time approaches to the solar sail trajectory problem. The system consists of combining an Elliptical Restricted N-Body Problem with a solar radiation pressure model to accurately simulate a solar sail with realistic surface optical properties. Once this is done, the solar radiation pressure modified equilibrium points are obtained, which are then used to examine case studies.The transfers to various Lagrangian points and escape of a geostationary orbit have been examined using both methods and practical results have been achieved. Furthermore, multiple sources of nonidealities were introduced in order to yield more accurate results. These include absorption and emission effects that a real sail would experience. The direct shooting method for a given trajectory proved to be more flexible in producing solutions to given problems, especially on long range missions to the solar radiation pressure modified L5 point and beyond. The Hermite-Simpson method proved to be more effective for shorter trajectories, such as the Geostorm and polar observer missions, both in computational speed as well as in obtaining more optimal solutions.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.115
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.354
Teacher spread0.342 · 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