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Enregistrement W4241360954 · doi:10.4043/15216-ms

Evacuation Performance

2003· article· en· W4241360954 sur OpenAlexaff
António Simões Ré, Brian Veitch

Notice bibliographique

RevueOffshore Technology Conference · 2003
Typearticle
Langueen
DomaineEngineering
ThématiqueShip Hydrodynamics and Maneuverability
Établissements canadiensMemorial University of NewfoundlandNational Research Council Canada
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)HarmHazardProcess (computing)Computer scienceScale (ratio)Risk analysis (engineering)Operations researchBusinessAeronauticsTransport engineeringEngineeringPolitical scienceGeography

Résumé

récupéré en direct d'OpenAlex

Abstract Evacuation system performance deteriorates as weather conditions worsen. A research program based primarily on model scale tests of several different types of evacuation system has quantified how prevailing weather affects performance. To do this, several measures of performance were proposed and their utility confirmed. The most recent phase of the research program investigated performance in extreme weather conditions. Results are presented and discussed in the context of goal-based decision making. Introduction Evacuation of an offshore installation is a process that begins with embarkation of personnel, followed by lowering or delivery to the sea, followed by departure from the splashdown point to a place of safety removed from the immediate hazard that precipitated the evacuation and where a rescue can be attempted. This might be expressed as a goal: In circumstances that necessitate a marine evacuation, personnel must have access to an evacuation system, be able to embark and launch safely, clear the installation, and survive until rescued, and to have a reasonable expectation of successfully escaping harm in the environmental conditions that can reasonably be expected to prevail during operations. Regulations in the offshore and maritime industries in many jurisdictions are moving away from specification-based standards and towards goal-based standards, a move that has prompted debate in both industries. To add to and help inform the debate in the arena of evacuation, a research program has been investigating the performance capabilities of several types of evacuation system, including conventional twin falls davit launched lifeboats, the same system modified by the addition of a flexible boom, and free fall systems [e.g. 1,2]. These investigations have been based on model scale experiments and have focused on quantifying how weather conditions and various evacuation station design parameters affect the performance of evacuation systems. In order to quantify performance, it has been necessary to define performance measures and demonstrate their utility. Recently, the performance of the conventional twin falls davit launched totally enclosed motor propelled survival craft (TEMPSC) was tested in extreme weather conditions with the aims of determining the upper operational weather limit of such a system, the role of wave steepness, and the effects of launch orientation. The results of these experiments complement earlier work and have led to a conceptual framework for assessing performance capabilities and designing to meet safety goals. The framework is presented here along with experimental results. Evacuation Zones and Performance Measures It is useful to consider the evacuation area as consisting of several zones, illustrated in Figure 1 and named here as splash-down, clearing, rescue, and exclusion zones. One measure of the system's performance is how closely the evacuation system delivers the lifeboat to the target launch point, which for the conventional system considered here is vertically below the lifeboat in its deployed position. The closer the actual splash down is to the target, the better. The distance between the target launch point and the installation is the clearance and this can be expected to have an important influence on the likelihood of a successful evacuation, particularly in terms of avoiding collisions after launching.

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: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,663
Score d'incertitude au seuil0,445

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 Opus0,010
Tête enseignante GPT0,197
Écart entre enseignants0,187 · 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'étudeThéorique ou conceptuel
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

Citations1
Publié2003
Routes d'admission1
Résumé présentoui

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