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Enregistrement W2035718737 · doi:10.4043/19233-ms

Emergency Response Training Using Simulators

2008· article· en· W2035718737 sur OpenAlexafffund
Brian Veitch, Randy Billard, Anthony Patterson

Notice bibliographique

RevueOffshore Technology Conference · 2008
Typearticle
Langueen
DomaineEngineering
ThématiqueMarine and Coastal Research
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesAtlantic Canada Opportunities AgencyCanadian Association of Petroleum Producers
Mots-clésTraining (meteorology)Emergency responseCompetence (human resources)Computer scienceVirtual realityVirtual trainingSimulation trainingFidelityEngineering managementRisk analysis (engineering)SimulationEngineeringHuman–computer interactionBusiness

Résumé

récupéré en direct d'OpenAlex

Abstract Assuring the competence of personnel involved in operating offshore petroleum installations or ships is a challenge. Doing so for dangerous or difficult operations is problematic, as conventional training methods can be prohibited. Using simulation to provide training is a potential solution to this need, particularly for safety critical operations, such as emergency response. This paper describes how simulators are being used to provide training for lifeboat coxswains. An example is presented of the cueing systems, training scenarios, and instructor's role for an immersive lifeboat simulator. Consideration is given to how the virtual environment can be used to extend simulation-based training to larger scale, multi-person emergency response drills. Introduction Training personnel for difficult or safety critical operations, such as emergency response, can be particularly challenging as conventional training methods may be effectively prohibited on ethical, logistical, or financial grounds. Nevertheless, the competence of personnel who work in the offshore petroleum and maritime industries must be assured. To address this need, simulators can be used to expose personnel to various scenarios in a virtual environment, thereby affording an opportunity for trainees to gain " artificial?? experience that can serve to enhance their competence, even in safety critical and dangerous operations. To be effective, training simulators must provide a sufficient level of fidelity to evoke behavioral responses appropriate to the training objectives. This requires a combination of credible training scenarios and embedded cueing systems, integrated by an active instructor. Our concern here is with training for emergency response. We begin with a focus on marine evacuation and the competence of personnel to safely embark and launch a lifeboat, and then to clear the installation or ship that is being evacuated. Regulations dealing with evacuation training and drills are reviewed to identify where the minimum standards have been set and where the competence gaps persist in practice. The use of an immersive lifeboat simulator as part of an effective competence assurance program is described, along with its key elements: credible training scenarios, cueing systems and instructor's station. A full escape, evacuation and rescue training drill involving offshore and onshore personnel is contemplated near the end of the paper Competence assurance Minimum standards of competence for crew expected to operate lifeboats or fast rescue craft are set by international conventions, which are enacted nationally through corresponding regulations or legislation, and may be elaborated upon by complementary industry or company guidelines. The basic international benchmarks for competence are set by the International Maritime Organization's Standards of Training, Certification and Watchkeeping (STCW) Convention (IMO 1995). Under this regulation, designated personnel must be competent to launch and recover survival craft, including motor propelled lifeboats, in rough seas. To be deemed competent, personnel must show through a practical demonstration that they can prepare the survival craft for launch, launch it, and clear the vicinity of the platform from which the craft was launched. The practical demonstration generally takes the form of drills done initially in a training school and subsequently onboard at regular intervals. Notwithstanding the requirements of the standards, launching and recovering survival craft in heavy seas is not normally part of a training scheme as such operations have been recognized as dangerous. A lecture on such operations is currently prescribed by the IMO's model training course in lieu of an actual launch (IMO 2000).

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0170,005

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 Opus0,076
Tête enseignante GPT0,289
Écart entre enseignants0,213 · 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 source (Gemma direct ou Codex distillé), 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

Citations13
Publié2008
Routes d'admission2
Résumé présentoui

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