SUBMARINE SAFETY AND SPATIAL AWARENESS: THE SUBSAFE GAMES-BASED TRAINING SYSTEM
Notice bibliographique
Résumé
In many countries, submarines – be they conventional diesel or nuclear “hunterkiller” boats (SSKs and SSNs) or strategic missile platforms (SSBNs) – help maintain a level of deterrence in increasingly fragile socio-political situations. Once described in the early 1900s byViceAdmiral ArthurWilson as “underhand, unfair, and damned un-English”, submarine fleets are, today, routinely deployed in support of a range of duties, from coastal protection and patrol duties to the support of scientific research in some of the most inhospitable places on the planet. Of course, with such a range of hostile natural and conflict-ridden environments, danger is inevitable and, since the year 2000, there have been a number of incidents involving submarines from some of the world’s major sea powers (e.g. see “Major Submarine Incidents Since 2000”, catalogued by Wikipedia (2008)). Two incidents in particular, both involving submarines of British origin, drove the motivation to reassess the way in which present-day submariners are trained, particularly with regard to their spatial knowledge relating to the layout of safetycritical systems and items of life-saving equipment. The first occurred onboard Her Majesty’s Canadian Submarine HMCS Chicoutimi (an ex-UK Upholder Class SSK). On October 5, 2004 the Chicoutimi was running on the surface through heavy seas to the northwest of Ireland. The submarine was struck by a large wave and some 2000 litres of water entered the vessel through open fin hatches. Thewater caused electrical shorting in the vicinity of the captain’s cabin and the ensuing fire disabled 9 members of the crew as a result of smoke inhalation. Unfortunately one of the crew later died. The second incident occurredonboardHMSTireless (shown inFigure 1) inMarch 2007. Tireless was taking part in under-ice exercises along with a US submarine north ofAlaska. Duringwhat should have been a routine lighting of aSelf-Contained Oxygen Generator (SCOG) – part of the survival equipment in the submarine’s Forward Escape Compartment – the generator exploded, killing two crewmembers and seriously injuring a third. The submarine’s crew managed to manoeuvre the vessel to thin ice, some 2 miles away, at which point she was able to surface safely and implement ventilation procedures. There is absolutely no evidence to suggest that deficiencies in current basic sub- marine qualification (SMQ) training contributed to the outcomes of these incidents. Indeed, in both cases, the actions of the submarine crews were highly praised by the Boards of Inquiry. However, there is anecdotal evidence to suggest that these two incidents have prompted both the Canadian and Royal Navies (and, indeed, the Royal Australian Navy) to review submarine safety training in general, particularly for naval personnel joining vessels for the first time (or after a long period of detachment). Part of these reviews involves an assessment of current forms of classroom-based (or SubmarineQualification (Dry) – SMQ(D)) trainingmedia that are in use and the potential benefits offered by more interactive digital systems, including interactive 3D (i3D). This paper addresses one such interactive media review being conducted by the UK’s Human Factors Integration Defence Technology Centre ( www.hfidtc.com ), in conjunction with instructor and student submariners from the Royal Navy. In particular, the paper describes a pilot study evaluating a prototype i3D product called SubSafe – a “Virtual Reality” (VR) simulator based on contemporary video games technologies and designed to enhance spatial awareness training during SMQ(D) classroom exercises.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
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 ».