Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck
(2019) 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 In Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring 1. p.1504-1511- Abstract
This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression mod-els linking daily averaged pavement temperatures, daily aggregated heavy-traffic counts and derived S-N fatigue damages, all of them derived from... (More)
This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression mod-els linking daily averaged pavement temperatures, daily aggregated heavy-traffic counts and derived S-N fatigue damages, all of them derived from the outcomes of different monitoring campaigns. A probabilistic methodology is utilized to calculate the fatigue reliability profiles of selected instrumented welded joints. The posterior utilities of SHM campaigns are then quantified by considering the structural fatigue reliability, various monitoring campaigns and the corresponding cost-benefit models. The decisions of identifying the optimal monitoring campaign and of extending the service life or not in conjunction with monitoring results are modelled. The optimal monitoring campaign is identified - retrospectively - by maximizing the expected benefits and minimize risks in dependency of the monitoring duration and the monitoring associated costs. The re-sults, despite relying on a number of simplistic assumptions, pave the way towards the use of pre-posterior decision support to optimise the design of monitoring campaigns for similar bridges, with an overall goal to proof the cost efficiency of SHM approaches to civil infrastructure management.
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- author
- Long, Lijia ; Alcover, Isaac Farreras and Thons, Sebastian LU
- publishing date
- 2019-01-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Structural Health Monitoring 2019 : Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring - Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
- series title
- Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
- editor
- Chang, Fu-Kuo ; Guemes, Alfredo and Kopsaftopoulos, Fotis
- volume
- 1
- pages
- 8 pages
- publisher
- DEStech Publications
- conference name
- 12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
- conference location
- Stanford, United States
- conference dates
- 2019-09-10 - 2019-09-12
- external identifiers
-
- scopus:85074397858
- ISBN
- 9781605956015
- DOI
- 10.12783/shm2019/32273
- language
- English
- LU publication?
- no
- id
- ff15cc3c-65f6-4f60-ac5a-969b31108813
- date added to LUP
- 2020-09-08 19:01:42
- date last changed
- 2025-04-04 14:45:18
@inproceedings{ff15cc3c-65f6-4f60-ac5a-969b31108813,
abstract = {{<p>This paper contains a quantification and decision theoretical optimization of the posterior utilities for several options for monitoring campaigns on the particular case of fatigue life predictions of an orthotropic steel deck. The monitoring campaigns are defined by varying monitoring durations and phases. The decision analysis is performed with real data from the Structural Health Monitoring (SHM) of the Great Belt Bridge (Denmark) which, among others, consist of measured strains, pavement temperatures and traffic intensities. The fatigue loading prediction model is based on regression mod-els linking daily averaged pavement temperatures, daily aggregated heavy-traffic counts and derived S-N fatigue damages, all of them derived from the outcomes of different monitoring campaigns. A probabilistic methodology is utilized to calculate the fatigue reliability profiles of selected instrumented welded joints. The posterior utilities of SHM campaigns are then quantified by considering the structural fatigue reliability, various monitoring campaigns and the corresponding cost-benefit models. The decisions of identifying the optimal monitoring campaign and of extending the service life or not in conjunction with monitoring results are modelled. The optimal monitoring campaign is identified - retrospectively - by maximizing the expected benefits and minimize risks in dependency of the monitoring duration and the monitoring associated costs. The re-sults, despite relying on a number of simplistic assumptions, pave the way towards the use of pre-posterior decision support to optimise the design of monitoring campaigns for similar bridges, with an overall goal to proof the cost efficiency of SHM approaches to civil infrastructure management.</p>}},
author = {{Long, Lijia and Alcover, Isaac Farreras and Thons, Sebastian}},
booktitle = {{Structural Health Monitoring 2019 : Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring}},
editor = {{Chang, Fu-Kuo and Guemes, Alfredo and Kopsaftopoulos, Fotis}},
isbn = {{9781605956015}},
language = {{eng}},
month = {{01}},
pages = {{1504--1511}},
publisher = {{DEStech Publications}},
series = {{Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring}},
title = {{Quantification of the posterior utilities of SHM campaigns on an orthotropic steel bridge deck}},
url = {{http://dx.doi.org/10.12783/shm2019/32273}},
doi = {{10.12783/shm2019/32273}},
volume = {{1}},
year = {{2019}},
}