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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Online Access: | http://hdl.handle.net/11250/2639807 https://doi.org/10.1115/OMAE2019-95139 |
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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 |
_version_ |
1766294410892410880 |