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Record W4244958476 · doi:10.22215/etd/2020-13957

Validating the Deployment of a Novel Tether Design for Net-Based Orbital Debris Removal Missions

2020· dissertation· en· W4244958476 on OpenAlexaff
Kevin Stadnyk

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsCarleton University
Fundersnot available
KeywordsSpace debrisSoftware deploymentDebrisAerospace engineeringOrbit (dynamics)PopulationNode (physics)EngineeringSimulationOrbital mechanicsContainer (type theory)Computer scienceSatellitePhysicsStructural engineeringMechanical engineeringMeteorology

Abstract

fetched live from OpenAlex

With the global push to commercialize space, humans are launching objects into orbit faster than natural effects are removing them. Orbital debris is especially dangerous as it is capable of exponential growth due to cascading collisions between orbiting objects. To ensure the long-term accessibility to space, high-risk objects must be actively removed to limit growth of the orbital debris population. One method of active debris removal is with a tethered-net to capture and tow an object out of orbit. This thesis continues the validation of a proposed novel tether configuration by focusing on its deployment dynamics. Tether elements are simulated using two numerical models, a lumped mass node system connected by massless spring-damper elements, and an absolute nodal coordinate formulation model. Their accuracy to predict the deployment motion of a tether is experimentally determined, and a complete capture scenario using the novel tether design is presented for the fist time.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.866
Threshold uncertainty score0.715

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 head0.032
GPT teacher head0.256
Teacher spread0.224 · 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
GenreMethods

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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