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Exploring Antarctic subglacial lakes with scientific probes: a formal probabilistic approach for operational risk management

Exploring Antarctic subglacial lakes with scientific probes: a formal probabilistic approach for operational risk management
Exploring Antarctic subglacial lakes with scientific probes: a formal probabilistic approach for operational risk management
Since their discovery, Antarctic subglacial lakes have become of great interest to the
science community. It is hypothesized that they may hold unique forms of biological life and that they
hold detailed sedimentary records of past climate change. According to the latest inventory, a total of
387 subglacial lakes have been identified in Antarctica (Wright and Siegert, 2011). However,
exploration using scientific probes has yet to be performed. We propose a generic, formal approach to
manage the operational risk of deploying probes during clean access to subglacial lake exploration. A
representation of the entire probe deployment process is captured in a Markov chain. The transition
from one state to the next depends on several factors, including reliability of components and processes.
We use fault trees to quantify the probability of failure of the complex processes that must take place to
facilitate the transition from one state to another. Therefore, the formal framework consists of
integrating a Markov chain, fault trees, component and subsystem reliability data and expert judgment.
To illustrate its application we describe how the approach can be used to address a series of what-if
scenarios, using the intended Ellsworth Subglacial Lake probe deployment as a case study.
1085-1097
Brito, M.P.
82e798e7-e032-4841-992e-81c6f13a9e6c
Griffiths, G.
2887c3c7-95f2-4834-b3f6-0284344d3580
Mowlem, M.
6f633ca2-298f-48ee-a025-ce52dd62124f
Brito, M.P.
82e798e7-e032-4841-992e-81c6f13a9e6c
Griffiths, G.
2887c3c7-95f2-4834-b3f6-0284344d3580
Mowlem, M.
6f633ca2-298f-48ee-a025-ce52dd62124f

Brito, M.P., Griffiths, G. and Mowlem, M. (2012) Exploring Antarctic subglacial lakes with scientific probes: a formal probabilistic approach for operational risk management. Journal of Glaciology, 58 (212), 1085-1097. (doi:10.3189/2012JoG12J007).

Record type: Article

Abstract

Since their discovery, Antarctic subglacial lakes have become of great interest to the
science community. It is hypothesized that they may hold unique forms of biological life and that they
hold detailed sedimentary records of past climate change. According to the latest inventory, a total of
387 subglacial lakes have been identified in Antarctica (Wright and Siegert, 2011). However,
exploration using scientific probes has yet to be performed. We propose a generic, formal approach to
manage the operational risk of deploying probes during clean access to subglacial lake exploration. A
representation of the entire probe deployment process is captured in a Markov chain. The transition
from one state to the next depends on several factors, including reliability of components and processes.
We use fault trees to quantify the probability of failure of the complex processes that must take place to
facilitate the transition from one state to another. Therefore, the formal framework consists of
integrating a Markov chain, fault trees, component and subsystem reliability data and expert judgment.
To illustrate its application we describe how the approach can be used to address a series of what-if
scenarios, using the intended Ellsworth Subglacial Lake probe deployment as a case study.

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More information

Published date: 2012
Organisations: Civil Maritime & Env. Eng & Sci Unit, Ocean Technology and Engineering

Identifiers

Local EPrints ID: 343354
URI: http://eprints.soton.ac.uk/id/eprint/343354
PURE UUID: 523c8e9f-9845-416b-9b82-9022658310b0
ORCID for M.P. Brito: ORCID iD orcid.org/0000-0002-1779-4535
ORCID for M. Mowlem: ORCID iD orcid.org/0000-0001-7613-6121

Catalogue record

Date deposited: 02 Oct 2012 08:31
Last modified: 15 Mar 2024 03:31

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Contributors

Author: M.P. Brito ORCID iD
Author: G. Griffiths
Author: M. Mowlem ORCID iD

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