Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters

A model for the computation of failure probabilities for partly reshaping mass-armored berm breakwaters in the Arctic is presented. The model consists of a reliable tool for the design of port structures in the rapidly changing Arctic environment and considers the simultaneous effects of wave and ic...

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Published in:Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
Main Authors: Leira, Bernt Johan, Høyland, Knut Vilhelm, Pontiki, Maria
Format: Book Part
Language:English
Published: ASME 2019
Subjects:
Online Access:http://hdl.handle.net/11250/2639807
https://doi.org/10.1115/OMAE2019-95139
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2639807 2023-05-15T14:21:42+02:00 Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters Leira, Bernt Johan Høyland, Knut Vilhelm Pontiki, Maria 2019 http://hdl.handle.net/11250/2639807 https://doi.org/10.1115/OMAE2019-95139 eng eng ASME ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering (OMAE2019): Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology urn:isbn:978-0-7918-5887-5 http://hdl.handle.net/11250/2639807 http://dx.doi.org/10.1115/OMAE2019-95139 cristin:1777864 Chapter 2019 ftntnutrondheimi https://doi.org/10.1115/OMAE2019-95139 2020-02-12T23:32:26Z A model for the computation of failure probabilities for partly reshaping mass-armored berm breakwaters in the Arctic is presented. The model consists of a reliable tool for the design of port structures in the rapidly changing Arctic environment and considers the simultaneous effects of wave and ice forces. The applied probabilistic approach was based on Bayesian inference. Hydrodynamic and ice historical data from Prudhoe Bay, Alaska were collected and analyzed to supply the Bayesian network with a large pool of information for the analysis. The model performed real-time predictions based on historical data and the user’s prior knowledge and assigned relevant values to load and resistance parameters. The predictive skill of the Bayesian network was validated with log-likelihood tests. Furthermore, the main outputs were applied for a Level III (fully probabilistic) reliability assessment of the structure. The study shows that a well-formulated Bayesian network can be a powerful tool in the design process and for the purpose of reliability analysis of coastal structures in highly unpredictable environments, such as the Arctic. The model can represent the dependencies between wave and ice loads in relation to the characteristics of the breakwater, as well as, its response. The average deviation of computed probabilities of failure relative to the prior estimates was 58.7%. publishedVersion Copyright © 2019 by ASME Book Part Arctic Arctic Prudhoe Bay Alaska NTNU Open Archive (Norwegian University of Science and Technology) Arctic Breakwater ENVELOPE(-63.233,-63.233,-64.800,-64.800) The Breakwater ENVELOPE(-36.583,-36.583,-54.200,-54.200) Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
description A model for the computation of failure probabilities for partly reshaping mass-armored berm breakwaters in the Arctic is presented. The model consists of a reliable tool for the design of port structures in the rapidly changing Arctic environment and considers the simultaneous effects of wave and ice forces. The applied probabilistic approach was based on Bayesian inference. Hydrodynamic and ice historical data from Prudhoe Bay, Alaska were collected and analyzed to supply the Bayesian network with a large pool of information for the analysis. The model performed real-time predictions based on historical data and the user’s prior knowledge and assigned relevant values to load and resistance parameters. The predictive skill of the Bayesian network was validated with log-likelihood tests. Furthermore, the main outputs were applied for a Level III (fully probabilistic) reliability assessment of the structure. The study shows that a well-formulated Bayesian network can be a powerful tool in the design process and for the purpose of reliability analysis of coastal structures in highly unpredictable environments, such as the Arctic. The model can represent the dependencies between wave and ice loads in relation to the characteristics of the breakwater, as well as, its response. The average deviation of computed probabilities of failure relative to the prior estimates was 58.7%. publishedVersion Copyright © 2019 by ASME
format Book Part
author Leira, Bernt Johan
Høyland, Knut Vilhelm
Pontiki, Maria
spellingShingle Leira, Bernt Johan
Høyland, Knut Vilhelm
Pontiki, Maria
Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters
author_facet Leira, Bernt Johan
Høyland, Knut Vilhelm
Pontiki, Maria
author_sort Leira, Bernt Johan
title Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters
title_short Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters
title_full Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters
title_fullStr Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters
title_full_unstemmed Eliminating the Uncertainties in Hydraulic and Ice Loads on Berm Breakwaters
title_sort eliminating the uncertainties in hydraulic and ice loads on berm breakwaters
publisher ASME
publishDate 2019
url http://hdl.handle.net/11250/2639807
https://doi.org/10.1115/OMAE2019-95139
long_lat ENVELOPE(-63.233,-63.233,-64.800,-64.800)
ENVELOPE(-36.583,-36.583,-54.200,-54.200)
geographic Arctic
Breakwater
The Breakwater
geographic_facet Arctic
Breakwater
The Breakwater
genre Arctic
Arctic
Prudhoe Bay
Alaska
genre_facet Arctic
Arctic
Prudhoe Bay
Alaska
op_relation ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering (OMAE2019): Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
urn:isbn:978-0-7918-5887-5
http://hdl.handle.net/11250/2639807
http://dx.doi.org/10.1115/OMAE2019-95139
cristin:1777864
op_doi https://doi.org/10.1115/OMAE2019-95139
container_title Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
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