Resumé

In the present paper, we propose a novel decision analytical framework for systems modeling in the context of risk informed integrity management of offshore facilities. Our focus concerns the development of system models representing environmental loads associated with storm events. Appreciating that system models in general serve to facilitate the optimal ranking of decision alternatives, we formulate the problem of systems modeling as an optimization problem to be solved jointly with the ranking of decision alternatives. Taking offset in recent developments in structure learning and Bayesian regression techniques, a generic approach for the modeling of environmental loads is established, which accommodates for a joint utilization of phenomenological understanding and knowledge contained in databases of observations. In this manner, we provide a framework and corresponding techniques supporting the combination of bottom-up and topdown modeling. Moreover, since phenomenological understanding as well as analysis of databases may lead to the identification of several competing system models, we include these in the formulation of the optimization problem. The proposed framework and utilized techniques are illustrated on a principal example. The example considers systems modeling and decision optimization in the context of possible evacuation of an offshore facility in the face of an emerging storm event.

OriginalsprogEngelsk
TitelASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE
Antal sider10
Vol/bind7B: Ocean Engineering
ForlagAmerican Society of Mechanical Engineers
Publikationsdato2018
SiderV07BT06A006
ArtikelnummerOMAE2018-77674
ISBN (Elektronisk)978-0-7918-5127-2
DOI
StatusUdgivet - 2018
Begivenhed37th International Conference on Ocean, Offshore and Arctic Engineering - Madrid, Spanien
Varighed: 17 jun. 201822 jun. 2018
Konferencens nummer: 37
https://www.asme.org/events/omae

Konference

Konference37th International Conference on Ocean, Offshore and Arctic Engineering
Nummer37
LandSpanien
ByMadrid
Periode17/06/201822/06/2018
Internetadresse
NavnInternational Conference on Offshore Mechanics and Arctic Engineering. Proceedings
ISSN1523-651X

Fingerprint

Identification (control systems)

Citer dette

Glavind, S. T., & Nielsen, M. H. F. (2018). A framework for offshore load environment modeling. I ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE (Bind 7B: Ocean Engineering, s. V07BT06A006). [OMAE2018-77674] American Society of Mechanical Engineers. International Conference on Offshore Mechanics and Arctic Engineering. Proceedings https://doi.org/10.1115/OMAE2018-77674
Glavind, Sebastian Tølbøll ; Nielsen, Michael Havbro Faber. / A framework for offshore load environment modeling. ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE. Bind 7B: Ocean Engineering American Society of Mechanical Engineers, 2018. s. V07BT06A006 (International Conference on Offshore Mechanics and Arctic Engineering. Proceedings).
@inproceedings{15f9f6dfca554cddbfeae35f9e4e65ce,
title = "A framework for offshore load environment modeling",
abstract = "In the present paper, we propose a novel decision analytical framework for systems modeling in the context of risk informed integrity management of offshore facilities. Our focus concerns the development of system models representing environmental loads associated with storm events. Appreciating that system models in general serve to facilitate the optimal ranking of decision alternatives, we formulate the problem of systems modeling as an optimization problem to be solved jointly with the ranking of decision alternatives. Taking offset in recent developments in structure learning and Bayesian regression techniques, a generic approach for the modeling of environmental loads is established, which accommodates for a joint utilization of phenomenological understanding and knowledge contained in databases of observations. In this manner, we provide a framework and corresponding techniques supporting the combination of bottom-up and topdown modeling. Moreover, since phenomenological understanding as well as analysis of databases may lead to the identification of several competing system models, we include these in the formulation of the optimization problem. The proposed framework and utilized techniques are illustrated on a principal example. The example considers systems modeling and decision optimization in the context of possible evacuation of an offshore facility in the face of an emerging storm event.",
author = "Glavind, {Sebastian T{\o}lb{\o}ll} and Nielsen, {Michael Havbro Faber}",
year = "2018",
doi = "10.1115/OMAE2018-77674",
language = "English",
volume = "7B: Ocean Engineering",
pages = "V07BT06A006",
booktitle = "ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE",
publisher = "American Society of Mechanical Engineers",
address = "United States",

}

Glavind, ST & Nielsen, MHF 2018, A framework for offshore load environment modeling. i ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE. bind 7B: Ocean Engineering, OMAE2018-77674, American Society of Mechanical Engineers, International Conference on Offshore Mechanics and Arctic Engineering. Proceedings, s. V07BT06A006, Madrid, Spanien, 17/06/2018. https://doi.org/10.1115/OMAE2018-77674

A framework for offshore load environment modeling. / Glavind, Sebastian Tølbøll; Nielsen, Michael Havbro Faber.

ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE. Bind 7B: Ocean Engineering American Society of Mechanical Engineers, 2018. s. V07BT06A006 OMAE2018-77674.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - A framework for offshore load environment modeling

AU - Glavind, Sebastian Tølbøll

AU - Nielsen, Michael Havbro Faber

PY - 2018

Y1 - 2018

N2 - In the present paper, we propose a novel decision analytical framework for systems modeling in the context of risk informed integrity management of offshore facilities. Our focus concerns the development of system models representing environmental loads associated with storm events. Appreciating that system models in general serve to facilitate the optimal ranking of decision alternatives, we formulate the problem of systems modeling as an optimization problem to be solved jointly with the ranking of decision alternatives. Taking offset in recent developments in structure learning and Bayesian regression techniques, a generic approach for the modeling of environmental loads is established, which accommodates for a joint utilization of phenomenological understanding and knowledge contained in databases of observations. In this manner, we provide a framework and corresponding techniques supporting the combination of bottom-up and topdown modeling. Moreover, since phenomenological understanding as well as analysis of databases may lead to the identification of several competing system models, we include these in the formulation of the optimization problem. The proposed framework and utilized techniques are illustrated on a principal example. The example considers systems modeling and decision optimization in the context of possible evacuation of an offshore facility in the face of an emerging storm event.

AB - In the present paper, we propose a novel decision analytical framework for systems modeling in the context of risk informed integrity management of offshore facilities. Our focus concerns the development of system models representing environmental loads associated with storm events. Appreciating that system models in general serve to facilitate the optimal ranking of decision alternatives, we formulate the problem of systems modeling as an optimization problem to be solved jointly with the ranking of decision alternatives. Taking offset in recent developments in structure learning and Bayesian regression techniques, a generic approach for the modeling of environmental loads is established, which accommodates for a joint utilization of phenomenological understanding and knowledge contained in databases of observations. In this manner, we provide a framework and corresponding techniques supporting the combination of bottom-up and topdown modeling. Moreover, since phenomenological understanding as well as analysis of databases may lead to the identification of several competing system models, we include these in the formulation of the optimization problem. The proposed framework and utilized techniques are illustrated on a principal example. The example considers systems modeling and decision optimization in the context of possible evacuation of an offshore facility in the face of an emerging storm event.

UR - http://proceedings.asmedigitalcollection.asme.org/volume.aspx?conferenceid=4034&volumeid=18608#tocHeading_66017

UR - http://www.scopus.com/inward/record.url?scp=85055540433&partnerID=8YFLogxK

U2 - 10.1115/OMAE2018-77674

DO - 10.1115/OMAE2018-77674

M3 - Article in proceeding

VL - 7B: Ocean Engineering

SP - V07BT06A006

BT - ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE

PB - American Society of Mechanical Engineers

ER -

Glavind ST, Nielsen MHF. A framework for offshore load environment modeling. I ASME 2018 Proceedings of the 37th International Conference on Offshore Mechanics and Arctic Engineering - OMAE. Bind 7B: Ocean Engineering. American Society of Mechanical Engineers. 2018. s. V07BT06A006. OMAE2018-77674. (International Conference on Offshore Mechanics and Arctic Engineering. Proceedings). https://doi.org/10.1115/OMAE2018-77674