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Enregistrement W2013793659 · doi:10.4043/17256-ms

Pile Driving Fatigue Damage - Effective Factors and Reduction

2005· article· en· W2013793659 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

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Notice bibliographique

RevueOffshore Technology Conference · 2005
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Structural Analysis Methods
Établissements canadiensConocoPhillips (Canada)
Organismes subventionnairesConocoPhillips
Mots-clésReduction (mathematics)PileStructural engineeringComputer scienceMaterials scienceForensic engineeringEngineering

Résumé

récupéré en direct d'OpenAlex

Abstract Fatigue damage is an important consideration in the design of Tension Leg Platforms (TLP) foundations. The portion of fatigue damage from installation dominates the total damage of the pile foundation. Driving fatigue damage can be affected by factors such as soil resistance to driving (SRD) and hammer efficiency. A parametric study, utilizing data of Magnolia TLP to assess the effect that SRD and hammer efficiency had upon driving fatigue damage was performed. The results provided a database and guidelines for the field engineer to control the pile driving fatigue damage by adjusting hammer efficiency, if the field pile-driving blow counts were different from that predicted. The study proved to be important in reducing pile driving fatigue damage during pile installation. Introduction For pile fatigue design, the combined in-place cumulative and installation damage are considered. The in-place fatigue damage is caused by environmental forces, such as wind, waves and current. The installation fatigue damage is basically generated by hammer blows from pile driving. Our study indicated that approximately 70% to 90% of the total fatigue damage is generated during pile driving. Therefore, how to reduce the driving fatigue damage is an important consideration in pile fatigue design and field driving operation. However, due to the potential for variation in the soil conditions, it is sometimes hard to accurately predict the soil resistance to driving (SRD) and thus the expected corresponding blow counts. During pile installation, the real blow count per foot could be higher or lower than that of predicted or higher at certain penetrations and lower at other penetrations. When variations occur (especially when blow counts are higher than predicted), the field engineer is left with trying to minimize fatigue damage by optimizing the driving plan. The goal of this study had two primary questions which utilized data from the Magnolia TLP that was installed in Gulf of Mexico during early 2004 to assess the effects that SRD and hammer efficiency had upon fatigue damage occurring during installation. These included:The effects of hammer energy to driving fatigue damage in order to determine whether to use high energy, low blow count, or low energy and high blow count to reduce fatigue damage, andThe effects of soil resistance to driving (SRD) so that if the SRD is higher than that predicted, how much more fatigue damage will be added to the pile? The results of the study were used as a guideline during the field pile driving operations to minimize the driving fatigue damage, and it has generated a field method (program) to determine the fatigue damage for each pile during the pile driving operations. If necessary, an alternative driving plan can be generated by following the guideline in case the actual pile driving resistance is notably different from predictions with higher hammer energy and/or blow counts being required. Description of the Study Methodology For pile driving fatigue assessment, the fatigue damage at each girth welds under the impact loads of each hammer blow must be first calculated.

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.

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: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,387
Score d'incertitude au seuil0,775

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
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 Opus0,011
Tête enseignante GPT0,248
Écart entre enseignants0,237 · 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