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Record W4283802839 · doi:10.1002/msd2.12044

Dynamic modeling and analysis of the looped space tether transportation system based on ANCF

2022· article· en· W4283802839 on OpenAlexaff
Jie Yang, Wang Qing-tao, Zhiyong Zhang, Zhendong Liu, Shidong Xu, Gangqiang Li

Bibliographic record

VenueInternational journal of mechanical system dynamics · 2022
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsYork University
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsMultibody systemCollisionLibration (molecule)PhysicsMechanicsDynamics (music)Structural engineeringMotion (physics)Relative motionControl theory (sociology)SimulationComputer scienceClassical mechanicsEngineeringPoint (geometry)MathematicsGeometryAcoustics

Abstract

fetched live from OpenAlex

Abstract A high‐fidelity multibody‐system dynamic model of the looped tether transportation system (L‐TTS) is proposed in this study to study its large deformation as well as large overall motion. The absolute nodal coordinate formulation (ANCF)‐based gradient‐deficient beam element is employed to establish the accurate model of the two flexible tethers subject to large deformations. The relative movement of climbers along tethers is described by using the sliding joint model based on ANCF. To reduce the collision risks between tethers and climbers, two libration suppression strategies, namely, the decelerated motion of climbers relative to tethers and multiple climbers per tether are investigated in this study. Several numerical simulations not only validate the effectiveness of the two strategies in reducing the collision risks between climbers and tethers, the overall librations of L‐TTS, and the magnitudes of the longitudinal elastic force of tethers, but also verify the good performance of the high‐fidelity model proposed in this study for dynamic simulation of the L‐TTS in microgravity conditions.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.199
Teacher spread0.195 · 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

Citations30
Published2022
Admission routes1
Has abstractyes

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