Notice bibliographique
Résumé
With the increased demand for hydrocarbon and mineral resources, as well as tourism, marine transportation in the arctic continues to increase. The region is harsh and fragile, making safety and environmental protection paramount. A key concern is how to estimate extreme design events that first and foremost satisfy safety and then economy. A rational approach to design of arctic ships based on probabilistic methods is detailed in this paper, including global impact forces and local panel design. Using a probabilistic approach, extreme design events can be identified by combining annual, seasonal and regional variability in environmental conditions with model uncertainty, and integrating these directly in the design methodology. Extreme design loads are estimated based on the annual number of interaction events, and the design strategy - target exceedence criteria established based on general public safety. The approach also provides a comprehensive basis for the selection of an appropriate ice class given certain operational requirements (e.g. an icebreaker for facility protection, or suitability of a cruise liner, having minimal ice class, to operate through a particular season). Otherwise, design for extremes is largely based on observational experience and judgment from one or more experts and such experience only reflects a relatively short span of natural occurrence. Neither is it appropriate to arbitrarily establish the most extreme condition imaginable. For extremal analysis, a parent distribution of global impact forces is first developed either through numerical ship-ice simulations or directly from measured full scale ship ram trial data. Using the parent distribution, and the expected annual number of ram events, a new design distribution representing the maximum of n annual force events is developed. Based on the global analysis, mean penetration and duration can be estimated which, when combined with number of interactions per year, provides a measure of exposure, a key input for local design analysis. A rational local pressure design model is presented that is derived based on measured ship ram data. Peak pressures through the full ram duration are considered and not just realizations at some arbitrary point of maximum force. A local scale effect is measured where pressures on smaller areas (i.e. <10m2) increase considerably above the global scale effect. A design pressure area curve based on a design strategy (e.g. 100 yr return period) is produced. A hypothetical design illustration is provided for a ship along a particular route including estimates of global forces and local design pressures. A linear trend in forces based on logarithmic trend in number of ramming events is observed. This illustrates that linking the design forces and pressures directly with expected number of interaction events is most reasonable and appropriate. Vertical impact forces estimated using the Polar Class rules are compared with estimates using the rational probabilistic approach and measured full scale MV Arctic data. The analysis illustrates how measured forces and expected exposure can be used for design and classification, as well as calibration. Preliminary results indicate that the higher PC1 and PC2 class forces seem rather conservative and a large gap exists between PC2 and PC3. Further calibration is needed. Introducing different design strategies (e.g. elastic-plastic and fully plastic) for corresponding load levels (e.g. 10−2extreme and 10−4abnormal) should be considered, allowing the designer to better understand the performance of his design.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».