Understanding and Including the Dynamics of Extreme Natural Hazard Event Uncertainty Within the Overall Offshore Wind Farm Project Risk Assessment Using a Causality-Based Graphical Modelling Approach

Rafael Zamora, Jianjun Qin, Anders Schmidt Kristensen, Saqib Mehmood, Shakeel Ahmed, S. Cuthbert

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Abstract

Offshore wind structures are subject to the combined action of wind and wave loads. A change of these loads may significantly affect the integrity of the structural elements. Increased instabilities in the Earth’s climate system could increase the frequency of extreme events (e.g. rogue waves) well beyond the frequency values currently recommended within structural design standards. Inherent to extreme event modelling is the need to use expert (subjective) judgement and sparse data sets. In this context, a Bayesian Belief Network (BBN) can be applied to describe the effect of these changes on the frequency of rogue waves within wind farms located in shallow water depths of 20–60 meters. This graphical modelling approach provides the structure to effectively communicate, among others, parameter uncertainty, causality across multiple risk factors, quantitative definition of assessment subjectivity or potential impact of a change in rogue wave frequency relative to that described in current design standards.
Original languageEnglish
Title of host publicationSafety and Reliability - Safe Societies in a Changing World : Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, norway
EditorsStein Haugen, Anne Barros, Coen van Gulijk, Trond Kongsvik, Jan Erik Vinnem
Place of PublicationLondon
PublisherCRC Press
Publication dateJun 2018
Edition1.
Pages1517-1525
ISBN (Print)978-0-8153-8682-7
ISBN (Electronic)78-1-351-17466-4
Publication statusPublished - Jun 2018
EventEuropean Safety and Reliability Conference 2018: ESREL 2018 - Norwegian University of Science and Technology, NTNU, Trondheim, Norway
Duration: 17 Jun 201821 Jun 2018

Conference

ConferenceEuropean Safety and Reliability Conference 2018
LocationNorwegian University of Science and Technology, NTNU
CountryNorway
CityTrondheim
Period17/06/201821/06/2018

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wind farm
natural hazard
risk assessment
extreme event
modeling
risk factor
water depth
shallow water
project
climate

Cite this

Zamora, R., Qin, J., Kristensen, A. S., Mehmood, S., Ahmed, S., & Cuthbert, S. (2018). Understanding and Including the Dynamics of Extreme Natural Hazard Event Uncertainty Within the Overall Offshore Wind Farm Project Risk Assessment Using a Causality-Based Graphical Modelling Approach. In S. Haugen, A. Barros, C. V. Gulijk, T. Kongsvik, & J. E. Vinnem (Eds.), Safety and Reliability - Safe Societies in a Changing World: Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, norway (1. ed., pp. 1517-1525). London: CRC Press.
Zamora, Rafael ; Qin, Jianjun ; Kristensen, Anders Schmidt ; Mehmood, Saqib ; Ahmed, Shakeel ; Cuthbert, S. . / Understanding and Including the Dynamics of Extreme Natural Hazard Event Uncertainty Within the Overall Offshore Wind Farm Project Risk Assessment Using a Causality-Based Graphical Modelling Approach. Safety and Reliability - Safe Societies in a Changing World: Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, norway. editor / Stein Haugen ; Anne Barros ; Coen van Gulijk ; Trond Kongsvik ; Jan Erik Vinnem. 1. ed. London : CRC Press, 2018. pp. 1517-1525
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abstract = "Offshore wind structures are subject to the combined action of wind and wave loads. A change of these loads may significantly affect the integrity of the structural elements. Increased instabilities in the Earth’s climate system could increase the frequency of extreme events (e.g. rogue waves) well beyond the frequency values currently recommended within structural design standards. Inherent to extreme event modelling is the need to use expert (subjective) judgement and sparse data sets. In this context, a Bayesian Belief Network (BBN) can be applied to describe the effect of these changes on the frequency of rogue waves within wind farms located in shallow water depths of 20–60 meters. This graphical modelling approach provides the structure to effectively communicate, among others, parameter uncertainty, causality across multiple risk factors, quantitative definition of assessment subjectivity or potential impact of a change in rogue wave frequency relative to that described in current design standards.",
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Zamora, R, Qin, J, Kristensen, AS, Mehmood, S, Ahmed, S & Cuthbert, S 2018, Understanding and Including the Dynamics of Extreme Natural Hazard Event Uncertainty Within the Overall Offshore Wind Farm Project Risk Assessment Using a Causality-Based Graphical Modelling Approach. in S Haugen, A Barros, CV Gulijk, T Kongsvik & JE Vinnem (eds), Safety and Reliability - Safe Societies in a Changing World: Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, norway. 1. edn, CRC Press, London, pp. 1517-1525, European Safety and Reliability Conference 2018, Trondheim, Norway, 17/06/2018.

Understanding and Including the Dynamics of Extreme Natural Hazard Event Uncertainty Within the Overall Offshore Wind Farm Project Risk Assessment Using a Causality-Based Graphical Modelling Approach. / Zamora, Rafael; Qin, Jianjun; Kristensen, Anders Schmidt; Mehmood, Saqib; Ahmed, Shakeel; Cuthbert, S. .

Safety and Reliability - Safe Societies in a Changing World: Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, norway. ed. / Stein Haugen; Anne Barros; Coen van Gulijk; Trond Kongsvik; Jan Erik Vinnem. 1. ed. London : CRC Press, 2018. p. 1517-1525.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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N2 - Offshore wind structures are subject to the combined action of wind and wave loads. A change of these loads may significantly affect the integrity of the structural elements. Increased instabilities in the Earth’s climate system could increase the frequency of extreme events (e.g. rogue waves) well beyond the frequency values currently recommended within structural design standards. Inherent to extreme event modelling is the need to use expert (subjective) judgement and sparse data sets. In this context, a Bayesian Belief Network (BBN) can be applied to describe the effect of these changes on the frequency of rogue waves within wind farms located in shallow water depths of 20–60 meters. This graphical modelling approach provides the structure to effectively communicate, among others, parameter uncertainty, causality across multiple risk factors, quantitative definition of assessment subjectivity or potential impact of a change in rogue wave frequency relative to that described in current design standards.

AB - Offshore wind structures are subject to the combined action of wind and wave loads. A change of these loads may significantly affect the integrity of the structural elements. Increased instabilities in the Earth’s climate system could increase the frequency of extreme events (e.g. rogue waves) well beyond the frequency values currently recommended within structural design standards. Inherent to extreme event modelling is the need to use expert (subjective) judgement and sparse data sets. In this context, a Bayesian Belief Network (BBN) can be applied to describe the effect of these changes on the frequency of rogue waves within wind farms located in shallow water depths of 20–60 meters. This graphical modelling approach provides the structure to effectively communicate, among others, parameter uncertainty, causality across multiple risk factors, quantitative definition of assessment subjectivity or potential impact of a change in rogue wave frequency relative to that described in current design standards.

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Zamora R, Qin J, Kristensen AS, Mehmood S, Ahmed S, Cuthbert S. Understanding and Including the Dynamics of Extreme Natural Hazard Event Uncertainty Within the Overall Offshore Wind Farm Project Risk Assessment Using a Causality-Based Graphical Modelling Approach. In Haugen S, Barros A, Gulijk CV, Kongsvik T, Vinnem JE, editors, Safety and Reliability - Safe Societies in a Changing World: Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, norway. 1. ed. London: CRC Press. 2018. p. 1517-1525