From prescriptive to performance-based: An overview of international trends in specifying durable concretes

Wally, Gustavo Bosel; Magalhães, Fábio Costa; Filho, Luiz Carlos Pinto da Silva

doi:10.1016/j.jobe.2022.104359

Cited by 13 publications

(10 citation statements)

References 44 publications

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“…Performance-based specification is a growing area of research within concrete durability design, including design for resistance to carbonation (Younsi et al, 2011; von Greve-Dierfeld and Gehlen, 2016a, 2016b; Wally et al, 2022). Performance-based approaches may allow more economical and sustainable structures to be realized (Teplý and Vořechovská, 2009).…”

Section: Discussionmentioning

confidence: 99%

“…In any large-scale concrete application following a performance-based approach, a variety of mixes are designed using one of these methods and then trial mixes are cast to verify that the final properties of a particular mix are acceptable. Performance-based specification can, therefore, lead to more efficient, optimal mixes being selected (Wally et al, 2022). However, the trial-and-error process can be both time-consuming and costly.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic selection and design of concrete using machine learning

Forsdyke

Zviazhynski

Lees

et al. 2023

DCE

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Development of robust concrete mixes with a lower environmental impact is challenging due to natural variability in constituent materials and a multitude of possible combinations of mix proportions. Making reliable property predictions with machine learning can facilitate performance-based specification of concrete, reducing material inefficiencies and improving the sustainability of concrete construction. In this work, we develop a machine learning algorithm that can utilize intermediate target variables and their associated noise to predict the final target variable. We apply the methodology to specify a concrete mix that has high resistance to carbonation, and another concrete mix that has low environmental impact. Both mixes also fulfill targets on the strength, density, and cost. The specified mixes are experimentally validated against their predictions. Our generic methodology enables the exploitation of noise in machine learning, which has a broad range of applications in structural engineering and beyond.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic selection and design of concrete using machine learning

Forsdyke

Zviazhynski

Lees

et al. 2023

DCE

View full text Add to dashboard Cite

show abstract

“…Performance-based specification is a growing area of research within concrete durability design, including design for resistance to carbonation [26][27][28][29][30]. This enables greater potential for use of novel materials and new concrete technologies which can subsequently improve material efficiency and performance.…”

Section: Performance Based Designmentioning

confidence: 99%

Model fitting to concrete carbonation data with non-zero initial carbonation depth

Forsdyke

Lees

2023

Mater Struct

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Carbonation is a key mechanism for deterioration of reinforced concrete structures. In design for resistance to carbonation, the performance of mixes is often specified and measured in laboratory carbonation tests where initial carbonation is sometimes present in specimens. The coherent interpretation of results from carbonation tests is vital as they enable a more accurate prediction of the performance of concrete structures in situ. This paper assesses two different approaches to considering the initial carbonation depth when extracting the carbonation coefficient from results of carbonation testing. Experimental data is compared to models for either approach using least squares regression. Both linear and non-linear representations of the initial carbonation depth are shown to fit the data well. The non-linear approach gives a larger estimate of carbonation coefficient than the linear approach, and is more consistent with the mathematical derivation of the carbonation equation. The ramifications of this difference will be most significant when the initial carbonation depth is large relative to the depth of the carbonation front. The accurate modelling of carbonation progression underpins performance-based design of new concrete structures and the assessment of existing concrete infrastructure.

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“…Andrade [64] proposed considering four different levels to estimate the service life of reinforced concrete structural elements: deemed to satisfy, hybrid approach, deterministic performance-based, and probabilistic performance-based. This methodology is like that presented by ISO 13823 [63] and has been discussed in some studies (e.g., [7], [65]- [69]).…”

Section: Concrete Service Life Modelingmentioning

confidence: 99%

“…In several cases, in addition to the environmental aggressiveness, the concrete quality does not meet minimum parameters, reducing the service life of the structures. For these reasons, concrete durability specifications are moving from prescriptive to performance-based approaches [7].…”

Section: Introductionmentioning

confidence: 99%

On factors affecting probabilistic service life modeling of concrete structures under marine environments

Wally

Magalhães

Real

et al. 2022

Rev. IBRACON Estrut. Mater.

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Concrete durability design has received increasing importance recently, with specifications moving from prescriptive to performance based. In performance-based approaches, it is essential to evaluate and calibrate service life models capable of reliably representing the phenomenon that triggers the degradation process. This paper aims to discuss the main concepts related to the probabilistic service life modeling of reinforced concrete structures under chloride environments, considering the application of different prediction models. Through numerical analysis, parametric differences among chloride penetration models are evidenced, and the results, their variability, and the admitted failure conditions are analyzed. An overview of the current scenario of the durability design of concrete structures is presented. Aspects associated with characteristic service life, the definitions of durability limit states, and their respective target failure probabilities are discussed.

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From prescriptive to performance-based: An overview of international trends in specifying durable concretes

Cited by 13 publications

References 44 publications

Probabilistic selection and design of concrete using machine learning

Probabilistic selection and design of concrete using machine learning

Model fitting to concrete carbonation data with non-zero initial carbonation depth

On factors affecting probabilistic service life modeling of concrete structures under marine environments

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