Value-of-Information-Based Material Testing for Existing Reinforced Concrete Members
(2026) In Infrastructures 11(8).- Abstract
This paper presents a predicted information and predicted action (PIPA) decision-analysis approach with Bayesian material updating for planning material testing in existing reinforced concrete members. The objective is to select the number of concrete and reinforcing-steel tests before testing is performed and before a management action is chosen, accounting jointly for the updated structural performance, information-acquisition costs, action costs, and expected failure consequences. Predicted future test outcomes are used to update the material-strength distributions; the updated distributions are then propagated through the shear, flexural, and system reliability analyses to inform outcome-dependent action selection. Management... (More)
This paper presents a predicted information and predicted action (PIPA) decision-analysis approach with Bayesian material updating for planning material testing in existing reinforced concrete members. The objective is to select the number of concrete and reinforcing-steel tests before testing is performed and before a management action is chosen, accounting jointly for the updated structural performance, information-acquisition costs, action costs, and expected failure consequences. Predicted future test outcomes are used to update the material-strength distributions; the updated distributions are then propagated through the shear, flexural, and system reliability analyses to inform outcome-dependent action selection. Management interventions are modelled as system-state actions through action-dependent system failure probabilities. The optimal testing option is identified by minimising a total predicted-information and predicted-action cost-and-risk measure that combines information and expected action costs with the expected consequences of the system states. The approach is applied to a benchmark reinforced-concrete member with transverse shear reinforcement and uncertain concrete compressive strength and reinforcing-steel yield strength, in which the same steel-strength population is adopted for the longitudinal and transverse reinforcement. The decision-optimal testing option consists of six concrete tests and three reinforcing-steel tests, reducing the total expected decision cost-and-risk measure by approximately 58.2% relative to the no-new-information decision. The decision value arises mainly from avoiding unnecessary intervention when favourable material information is acquired. The results formulate material-test planning as a decision-value problem, providing an alternative to fixed sample-size rules while retaining explicit dependence on structural, probabilistic, action, and cost assumptions.
(Less)
- author
- Palma, Vittorio
LU
; Celati, Simone
LU
; Natali, Agnese
; Salvatore, Walter
and Thöns, Sebastian
LU
- organization
- publishing date
- 2026-08
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Bayesian decision analysis, existing reinforced concrete structures, material testing, reliability-based assessment, risk-based management, structural reliability, value of information
- in
- Infrastructures
- volume
- 11
- issue
- 8
- article number
- 286
- publisher
- MDPI AG
- external identifiers
-
- scopus:105048446141
- ISSN
- 2412-3811
- DOI
- 10.3390/infrastructures11080286
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2026 by the authors.
- id
- b41b9875-99ad-49d7-8591-6167577f664e
- date added to LUP
- 2026-09-04 09:17:44
- date last changed
- 2026-09-08 11:40:18
@article{b41b9875-99ad-49d7-8591-6167577f664e,
abstract = {{<p>This paper presents a predicted information and predicted action (PIPA) decision-analysis approach with Bayesian material updating for planning material testing in existing reinforced concrete members. The objective is to select the number of concrete and reinforcing-steel tests before testing is performed and before a management action is chosen, accounting jointly for the updated structural performance, information-acquisition costs, action costs, and expected failure consequences. Predicted future test outcomes are used to update the material-strength distributions; the updated distributions are then propagated through the shear, flexural, and system reliability analyses to inform outcome-dependent action selection. Management interventions are modelled as system-state actions through action-dependent system failure probabilities. The optimal testing option is identified by minimising a total predicted-information and predicted-action cost-and-risk measure that combines information and expected action costs with the expected consequences of the system states. The approach is applied to a benchmark reinforced-concrete member with transverse shear reinforcement and uncertain concrete compressive strength and reinforcing-steel yield strength, in which the same steel-strength population is adopted for the longitudinal and transverse reinforcement. The decision-optimal testing option consists of six concrete tests and three reinforcing-steel tests, reducing the total expected decision cost-and-risk measure by approximately 58.2% relative to the no-new-information decision. The decision value arises mainly from avoiding unnecessary intervention when favourable material information is acquired. The results formulate material-test planning as a decision-value problem, providing an alternative to fixed sample-size rules while retaining explicit dependence on structural, probabilistic, action, and cost assumptions.</p>}},
author = {{Palma, Vittorio and Celati, Simone and Natali, Agnese and Salvatore, Walter and Thöns, Sebastian}},
issn = {{2412-3811}},
keywords = {{Bayesian decision analysis; existing reinforced concrete structures; material testing; reliability-based assessment; risk-based management; structural reliability; value of information}},
language = {{eng}},
number = {{8}},
publisher = {{MDPI AG}},
series = {{Infrastructures}},
title = {{Value-of-Information-Based Material Testing for Existing Reinforced Concrete Members}},
url = {{http://dx.doi.org/10.3390/infrastructures11080286}},
doi = {{10.3390/infrastructures11080286}},
volume = {{11}},
year = {{2026}},
}