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Record W3022757100 · doi:10.1139/tcsme-2020-0021

Creep prediction of GFRP directors in a multiple launch rocket system under long-term stacking storage

2020· article· en· W3022757100 on OpenAlexvenueno aff
Tongsheng Sun, Cungui Yu, Qi Wang, Jianlin Zhong

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNatural Science Foundation of Jiangsu ProvinceGovernment of Jiangsu Province
KeywordsCreepMaterials scienceRocket (weapon)Deformation (meteorology)ViscoelasticityConstitutive equationStructural engineeringFinite element methodComposite materialEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

During long-term stacking storage, creep deformation of polymeric composite directors used in multiple launch rocket systems can appear, which affects rocket launch. In this work, E-glass/epoxy 6509 composite laminates were prepared and 60/60 min creep/creep-recovery tests were carried out in the transverse and shear directions at different stress levels. Parameters of the Schapery’s nonlinear viscoelastic equation were obtained based on the test data. Then, a three-dimensional nonlinear viscoelastic constitutive model based on Schapery’s equation was implemented in the standard finite element code UMAT and a finite element model was developed to predict the creep deformation of the composite directors after 15 years of stacking storage. The effect of creep deformation on rocket launching was also studied. The results show that the residual deformation of the directors is a saddle-shaped distribution in three-dimensional space, the maximum residual deformation is 0.24 mm, and the minimum residual deformation is 0.22 mm. The creep deformation of the director causes a significant increase in the contact-collision force during launching, resulting in a decrease in the rocket run-off track velocity.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.217
Teacher spread0.188 · 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
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

Citations1
Published2020
Admission routes1
Has abstractyes

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