Value of Seismic Structural Health Monitoring Information for Management of Civil Structures Under Different Prior Knowledge Scenarios
Giordano, Pier Francesco ; Iannacone, Leandro and Limongelli, Maria Pina LU
(2023)
Experimental Vibration Analysis for Civil Engineering Structures - EVACES 2023 - Volume 2
In Lecture Notes in Civil Engineering
433 LNCE.
p.11-20
- Abstract
Seismic Structural Health Monitoring (S2HM) provides information about the integrity of civil structures and infrastructure in the aftermath of an earthquake. However, quantifying the benefits of S2HM information is crucial to justify the investment in S2HM systems. The benefit of S2HM can be computed through the Value of Information (VoI) from Bayesian decision theory, which compares the expected costs of alternative actions with prior information (without S2HM information) and with S2HM information (before it is available). This paper aims to analyze the VoI from S2HM in civil structures and infrastructure, considering different prior information scenarios... (More)
Seismic Structural Health Monitoring (S2HM) provides information about the integrity of civil structures and infrastructure in the aftermath of an earthquake. However, quantifying the benefits of S2HM information is crucial to justify the investment in S2HM systems. The benefit of S2HM can be computed through the Value of Information (VoI) from Bayesian decision theory, which compares the expected costs of alternative actions with prior information (without S2HM information) and with S2HM information (before it is available). This paper aims to analyze the VoI from S2HM in civil structures and infrastructure, considering different prior information scenarios regarding seismic action. The theoretical framework of the VoI is adapted to address three prior knowledge scenarios: (i) full information about the earthquake is available (ii) the intensity measure of the seismic motion is obtained using ground motion models, and (iii) no information is available. A numerical case study of a structure in a seismic area is presented, and the effect of different prior information scenarios on the VoI is discussed. The results show that VoI is higher when the prior information is low, indicating that monitoring systems are more valuable when uncertainty about seismic actions is high.
(Less)
- author
- Giordano, Pier Francesco
; Iannacone, Leandro
and Limongelli, Maria Pina
LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Bayesian decision analysis, Civil Structures and Infrastructures, Decision making, Earthquakes, Structural Health Monitoring, Value of Information
- host publication
- Experimental Vibration Analysis for Civil Engineering Structures - EVACES 2023 - Volume 2
- series title
- Lecture Notes in Civil Engineering
- editor
- Limongelli, Maria Pina ; Giordano, Pier Francesco ; Gentile, Carmelo ; Quqa, Said and Cigada, Alfredo
- volume
- 433 LNCE
- pages
- 10 pages
- publisher
- Springer Science and Business Media B.V.
- conference name
- Experimental Vibration Analysis for Civil Engineering Structures - EVACES 2023 - Volume 2
- conference location
- Milan, Italy
- conference dates
- 2023-08-30 - 2023-09-01
- external identifiers
-
- scopus:85174847723
- ISSN
- 2366-2565
- 2366-2557
- ISBN
- 9783031391163
- DOI
- 10.1007/978-3-031-39117-0_2
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
- id
- 7eb86ef1-6806-459b-9e34-93cac91f62b7
- date added to LUP
- 2023-12-18 11:05:25
- date last changed
- 2024-04-16 23:11:41
@inproceedings{7eb86ef1-6806-459b-9e34-93cac91f62b7,
abstract = {{<p>Seismic Structural Health Monitoring (S<sup>2</sup>HM) provides information about the integrity of civil structures and infrastructure in the aftermath of an earthquake. However, quantifying the benefits of S<sup>2</sup>HM information is crucial to justify the investment in S<sup>2</sup>HM systems. The benefit of S<sup>2</sup>HM can be computed through the Value of Information (VoI) from Bayesian decision theory, which compares the expected costs of alternative actions with prior information (without S<sup>2</sup>HM information) and with S<sup>2</sup>HM information (before it is available). This paper aims to analyze the VoI from S<sup>2</sup>HM in civil structures and infrastructure, considering different prior information scenarios regarding seismic action. The theoretical framework of the VoI is adapted to address three prior knowledge scenarios: (i) full information about the earthquake is available (ii) the intensity measure of the seismic motion is obtained using ground motion models, and (iii) no information is available. A numerical case study of a structure in a seismic area is presented, and the effect of different prior information scenarios on the VoI is discussed. The results show that VoI is higher when the prior information is low, indicating that monitoring systems are more valuable when uncertainty about seismic actions is high.</p>}},
author = {{Giordano, Pier Francesco and Iannacone, Leandro and Limongelli, Maria Pina}},
booktitle = {{Experimental Vibration Analysis for Civil Engineering Structures - EVACES 2023 - Volume 2}},
editor = {{Limongelli, Maria Pina and Giordano, Pier Francesco and Gentile, Carmelo and Quqa, Said and Cigada, Alfredo}},
isbn = {{9783031391163}},
issn = {{2366-2565}},
keywords = {{Bayesian decision analysis; Civil Structures and Infrastructures; Decision making; Earthquakes; Structural Health Monitoring; Value of Information}},
language = {{eng}},
pages = {{11--20}},
publisher = {{Springer Science and Business Media B.V.}},
series = {{Lecture Notes in Civil Engineering}},
title = {{Value of Seismic Structural Health Monitoring Information for Management of Civil Structures Under Different Prior Knowledge Scenarios}},
url = {{http://dx.doi.org/10.1007/978-3-031-39117-0_2}},
doi = {{10.1007/978-3-031-39117-0_2}},
volume = {{433 LNCE}},
year = {{2023}},
}