Value-of-Information-Based Inspection Planning for Post-Tensioned Bridges Affected by Tendon Degradation
Palma, Vittorio LU ; Celati, Simone LU
; Natali, Agnese
; Mattei, Francesca
; Mazzatura, Isabella
; Salvatore, Walter
and Thöns, Sebastian
LU
(2026)
3rd Fabre Conference: Existing Bridges, Viaducts, and Tunnels: Research, Innovation, and Applications, 2026
In Procedia Structural Integrity
84.
p.1318-1325
- Abstract
The estimation of the number of defective tendons in post-tensioned concrete bridges is a key input for the reliability assessment of prestressed girders. However, special inspection methods for detecting voids and assessing tendon condition are intrusive, time-consuming, and costly, and the quantitative definition of an inspection sample size that meaningfully reduces epistemic uncertainty while keeping operational effort manageable is still rarely addressed in research and practice. This paper proposes a Value of Information approach, based on Bayesian methods to quantify and reduce uncertainty in tendon defectiveness by explicitly accounting for (i) the finite tendon population, (ii) prior information from past inspection campaigns,... (More)
The estimation of the number of defective tendons in post-tensioned concrete bridges is a key input for the reliability assessment of prestressed girders. However, special inspection methods for detecting voids and assessing tendon condition are intrusive, time-consuming, and costly, and the quantitative definition of an inspection sample size that meaningfully reduces epistemic uncertainty while keeping operational effort manageable is still rarely addressed in research and practice. This paper proposes a Value of Information approach, based on Bayesian methods to quantify and reduce uncertainty in tendon defectiveness by explicitly accounting for (i) the finite tendon population, (ii) prior information from past inspection campaigns, and (iii) imperfect detection through inspection sensitivity and specificity. The updated defectiveness model is coupled with a probabilistic flexural capacity assessment via Monte Carlo simulation and embedded in a Bayesian decision-theoretic formulation. The inspection sample size is selected by maximizing the predicted information value including inspection costs, balancing the expected reduction in decision risk (expected loss, including failure consequences) and the inspection effort. Results show a sharp increase in information value for small sample sizes followed by saturation, enabling identification of an optimal number of tendons to inspect and supporting cost-effective planning consistent with structural reliability requirements.
(Less)
- author
- Palma, Vittorio
LU
; Celati, Simone
LU
; Natali, Agnese
; Mattei, Francesca
; Mazzatura, Isabella
; Salvatore, Walter
and Thöns, Sebastian
LU
- organization
- publishing date
- 2026
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- imperfect detection, post-tensioned bridges, predicted information value, special inspections, tendon defectiveness
- in
- Procedia Structural Integrity
- volume
- 84
- pages
- 8 pages
- publisher
- Elsevier
- conference name
- 3rd Fabre Conference: Existing Bridges, Viaducts, and Tunnels: Research, Innovation, and Applications, 2026
- conference location
- Rome, Italy
- conference dates
- 2026-02-16 - 2026-02-19
- external identifiers
-
- scopus:105049539273
- ISSN
- 2452-3216
- DOI
- 10.1016/j.prostr.2026.06.168
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: Copyright © 2026. Published by Elsevier B.V.
- id
- bdb9f869-6506-4a24-90ba-ea9eaaf9659d
- date added to LUP
- 2026-09-18 07:56:49
- date last changed
- 2026-09-29 12:55:12
@article{bdb9f869-6506-4a24-90ba-ea9eaaf9659d,
abstract = {{<p>The estimation of the number of defective tendons in post-tensioned concrete bridges is a key input for the reliability assessment of prestressed girders. However, special inspection methods for detecting voids and assessing tendon condition are intrusive, time-consuming, and costly, and the quantitative definition of an inspection sample size that meaningfully reduces epistemic uncertainty while keeping operational effort manageable is still rarely addressed in research and practice. This paper proposes a Value of Information approach, based on Bayesian methods to quantify and reduce uncertainty in tendon defectiveness by explicitly accounting for (i) the finite tendon population, (ii) prior information from past inspection campaigns, and (iii) imperfect detection through inspection sensitivity and specificity. The updated defectiveness model is coupled with a probabilistic flexural capacity assessment via Monte Carlo simulation and embedded in a Bayesian decision-theoretic formulation. The inspection sample size is selected by maximizing the predicted information value including inspection costs, balancing the expected reduction in decision risk (expected loss, including failure consequences) and the inspection effort. Results show a sharp increase in information value for small sample sizes followed by saturation, enabling identification of an optimal number of tendons to inspect and supporting cost-effective planning consistent with structural reliability requirements.</p>}},
author = {{Palma, Vittorio and Celati, Simone and Natali, Agnese and Mattei, Francesca and Mazzatura, Isabella and Salvatore, Walter and Thöns, Sebastian}},
issn = {{2452-3216}},
keywords = {{imperfect detection; post-tensioned bridges; predicted information value; special inspections; tendon defectiveness}},
language = {{eng}},
pages = {{1318--1325}},
publisher = {{Elsevier}},
series = {{Procedia Structural Integrity}},
title = {{Value-of-Information-Based Inspection Planning for Post-Tensioned Bridges Affected by Tendon Degradation}},
url = {{http://dx.doi.org/10.1016/j.prostr.2026.06.168}},
doi = {{10.1016/j.prostr.2026.06.168}},
volume = {{84}},
year = {{2026}},
}