MétaCan
Menu
Back to cohort
Record W2035718737 · doi:10.4043/19233-ms

Emergency Response Training Using Simulators

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

Bibliographic record

VenueOffshore Technology Conference · 2008
Typearticle
Languageen
FieldEngineering
TopicMarine and Coastal Research
Canadian institutionsMemorial University of Newfoundland
FundersAtlantic Canada Opportunities AgencyCanadian Association of Petroleum Producers
KeywordsTraining (meteorology)Emergency responseCompetence (human resources)Computer scienceVirtual realityVirtual trainingSimulation trainingFidelityEngineering managementRisk analysis (engineering)SimulationEngineeringHuman–computer interactionBusiness

Abstract

fetched live from 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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.076
GPT teacher head0.289
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueOffshore Technology ConferenceSame topicMarine and Coastal ResearchFrench-language works237,207