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Enregistrement W2900157453

Stick-slip behavior of ice interacting with concrete surfaces

2018· article· en· W2900157453 sur OpenAlexaboutno aff
Nynke Nuus

Notice bibliographique

RevueResearch Repository (Delft University of Technology) · 2018
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueArctic and Antarctic ice dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésStiffnessGeotechnical engineeringSea iceSlip (aerodynamics)Submarine pipelineGeologyArcticStructural engineeringEngineeringMaterials science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

When sea or lake ice interacts with concrete offshore structures in Arctic regions, the frictional forces between the ice and the structure cause abrasion of the concrete surface of the structure. This may endanger the structural integrity when the steel reinforcement gets exposed and experiences corrosion, and must therefore be taken into account in the design process. For the design of concrete offshore structures in Arctic conditions, an accurate description and prediction of ice-structure interaction is required. The interaction between moving ice and concrete surfaces is mainly governed by friction and the so-called stick-slip phenomenon. This phenomenon has been observed during laboratory and field testing and, although the physics of this phenomenon are believed to be well understood, the corresponding static and kinetic friction coefficients reported in literature have a widespread range and are inconclusive. This thesis aims at a more accurate identification of the ice-concrete friction coefficients.<br/><br/>For this graduation project, an experimental set-up was designed and stick-slip tests were carried out at Memorial University of Newfoundland, Canada. Additionally, a numerical model describing stick-slip behavior between ice and concrete was created. For the experimental set-up, a cylindrical fresh water columnar ice sample with a 50 mm radius and 50 mm height was attached to four springs with the same stiffness. The springs were attached to a support structure and throughout the test campaign, the stiffness of these springs was varied between 20 - 70 N/m per spring. To simulate one-dimensional ice-concrete interaction, the ice sample was placed near the edge of a rotating concrete slab. The normal load on the ice sample was varied from 0.7 to 2 kg by adding weight. In addition, the concrete velocity as experienced by the ice was varied between 0.15 and 0.82 m/s by increasing the rotational rate of the concrete slab. The static and kinetic friction coefficients were obtained from the experimental data and their dependence on normal load, velocity and spring stiffness was analyzed as well. The static friction coefficients found over the whole range of tests varied from 0.1 to 0.5. The analysis showed that the static friction coefficient decreases with increasing normal load and with increasing velocity. The kinetic friction coefficient was found to be in the range of 0.08 to 0.4 and may on average be obtained as 0.7 times the static friction coefficient. The kinetic friction coefficient, too, decreases with an increase in normal load and velocity. The influence of the spring stiffness was not clearly identified.<br/><br/>The friction coefficients that were calculated using the experimental data were provided as input to the numerical stick-slip model. An analysis was performed to verify that the model displays similar regression with the varied mass, velocity and spring stiffness, compared to what was observed in the experiment. The output was compared to the experimental data, and it was found that the model describes the stick-slip behavior as seen during the experiment with an accuracy between 84 and 99%. Although some further improvements to the model can be implemented, in general it is concluded that under the made assumptions, the model is valid for the prediction of stick-slip behavior as observed during the experiment.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,270
Score d'incertitude au seuil0,862

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,002
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,250
Écart entre enseignants0,230 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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