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A macro-scale generalized search and rescue (SAR) model for the coastal regions of Eastern Canada and the Arctic

Par Conseil national de recherches du Canada

DOITrouver le DOI : https://doi.org/10.4043/32486-MS
AuteurRechercher : ; Rechercher : ; Rechercher : Identifiant ORCID : https://orcid.org/0000-0001-8423-0572; Rechercher : ; Rechercher : ; Rechercher :
FormatTexte, Article
ConférenceOffshore Technology Conference, May 1-4, 2023, Houston, Texas, USA
Sujetair transportation; helicopter; rescue time; artificial intelligence; scenario; contingency planning; survivor; ground transportation; canada government; distress
Résumé
Given the complexity of Search and Rescue (SAR) activities in the coastal regions of Eastern Canada and the Arctic, there is a need to objectively assess system capabilities at a high level to determine the expected rescue time for multiple scenarios and system configurations. This paper outlines a new macro-scale generalized SAR model to simulate the main activities within the SAR system in Eastern Canada and the Arctic. The model uses discrete event simulation to represent the SAR operations and a probabilistic Monte Carlo approach to incorporate uncertainties in performance data for the different components of the system. Algorithms are first developed to identify the major decision-relevant components of SAR response, including the time to interpret emergency notifications and mobilize helicopter resources, the operability of assets in given environmental conditions, and the proximity and capability of resources. Following this, the model is coded in MATLAB, using a time-stepping approach, enabling changes in the scenario, asset status, and system configuration at any time step. Case scenarios are used as initial verification, beginning with a simplistic approach, and building complexity in the model parameters. For this paper, we will discuss simple and complex scenarios which are based on common incident occurrences and SAR system operational details in eastern Canada's coastal regions and the Arctic. We assess the sensitivity of the overall SAR system to various input parameters to better understand how factors such as the Location of Incident (LOI) and number of People in Distress (PID) influence SAR response time in remote coastal areas, as well as the impact of refueling station locations for more distant and longer duration scenarios.
Date de publication
Maison d’éditionOTC
Dans
  • Offshore Technology Conference 2023, OTC-32486-MS (1 mai 2023).
Langueanglais
Publications évaluées par des pairsOui
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Identificateur de l’enregistrement3485210a-9c1b-44f2-bdf8-6f6890338e1b
Enregistrement créé2024-06-14
Enregistrement modifié2024-06-14
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