Evaluation of service-life prediction model for reinforced concrete structures in chloride-laden environments

Silvestro, Laura; Andrade, Jairo José de Oliveira; Molin, Denise Carpena Coitinho Dal

doi:10.1007/s41024-019-0059-3

Cited by 12 publications

(5 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These complications can be traced to the fact that degradation mechanism often depends on numerous factors capable of affecting the process in a synergistic way; moreover, the governing failure mode may vary for different environments. Furthermore, the slow pace of degradation makes accelerated tests difficult and the large number of degradation agents make comparison with actual in-use degradation environment complicated (Martin, Saunders, Floyd, and Wineburg 1994;Marteinsson, 2005;Silvestro, Andrade, and Dal-Molin, 2019).…”

Section: Service Life and Accelerated Aging Testmentioning

confidence: 99%

Models for the Prediction of Service Life of Buildings – A Review

2022

View full text Add to dashboard Cite

Service life models are a part of critical anchors to achieving sustainable development goals, offering sustainable solutions for infrastructural advancement. In spite of their indisputable usefulness and acceptability in the scientific circle, their real-world deployment is still grossly inadequate. The overall objective of this review is to assess the existing service life prediction models with highlights of their highs and lows. The models identified include deterministic, stochastic and engineering. Areas requiring more intensive research identified include the development of service life database, simplification of the complicated mathematical formats of service life models into simpler more practically-manageable formats, comparative study of expert opinions and computer integrated knowledge, as well as the place of structural elements in service life determination compared to non-structural elements. The study finally notes the areas that will give the required shape and speed of development to service life modeling of reinforced concrete buildings which include the provision of service life database, practical application of service life model for user-guidance, the superiority of service life data from non-destructive testing results to commercial data from manufacturers, placement of experts’ opinions at par with computer integrated knowledge system, and using complete building for service life determination rather than building elements. This review will serve as information base on various service life models which should assist early researchers in the subject area and speed up the application from the rudimentary to more advanced stages within the foreseeable future.

show abstract

Section: Service Life and Accelerated Aging Testmentioning

confidence: 99%

Models for the Prediction of Service Life of Buildings – A Review

2022

View full text Add to dashboard Cite

show abstract

“…In previous studies on chloride diffusion, different types of marine zone have been found to be related to chloride diffusion. Some studies modeled study in environment type: underwater area [5]; tidal area [7] [15]; splash area [32]; atmospheric area or airborne salt [2] [3] [33] [34]; tidal, submerge, atmospheric [22]; tidal area, splash area, atmospheric area [28] [35]; underwater area/submerge, tidal area, splash area, atmospheric area [19] [31] [36]; dry/fully/partially saturated condition (DCC/PSC/FSC) [29].…”

Section: Classification Of Various Type Of Marine Zone and Influencing Factors Of Concretementioning

confidence: 99%

“…] -diameter of steel reinforcement [15] -water absorption [20] -mechanical load [19] -reliability index [28] -marine zone (in section 3.3) -bulk electrical resistivity [10] [25] -age of concrete [6] [17] [31], age factor [28] -effect of cations [11] -collect experimental data from other researchers/ literatures [17] [33] [34] -a visual inspection of the structure to determine the structure's current condition and the nature of testing required. [36] -location of element [36] -the properties of the corrosion inhibitor [18] [25]; -de-icing salt [24] -air content [15] [25] -coated concrete structures (double-layered systems) [37]; hollow cylinder (six-layer cylinder) [4] -the result of RCPT [6] [10] [13] [16]…”

Section: Independent Variables Dependent Variablesmentioning

confidence: 99%

Diffusion of chloride from seawater into the concrete analysis: a literature review on implemented approaches

Ariningsih

Nuralinah

Saputra

2021

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Infrastructures near the sea, such as ports, offshore platforms, bridges, and coastal buildings, are affected by seawater due to the coastal region. Chloride, contained in seawater, causes a decrease in the strength and durability of the concrete. Some researchers have published a paper on analyzing the penetration of chloride ions into concrete under different coastal environments and predicted chloride diffusion in concrete with computational modeling. This paper aims to review the existing literature related to various laboratory work tests and analytical methods in evaluating the diffusion of chloride from seawater into concrete. A set of forty papers were collected and reviewed that were published from 2011 until 2020 for studying. The review showed that chloride diffusion was a complex process and affected by many factors such as material properties, curing time, immersion/exposure time, and environmental conditions. Various experimental methods in the Laboratory were conducted using concrete specimens made from various materials in the exposed and submerged conditions. Researches in the field were carried out on existing structures with a certain building age using non-destructive testing. Meanwhile, the analytical methods applied simple equations and numerical simulation computational software.

show abstract

“…Although, with the proposal of the new structure and the emergence of new building materials, there will be many new structural forms in the future, but it is certain that the reinforced concrete structure is still one of the most commonly used structures in the new century. However, concrete structures gradually become old, damage, or even destroy under long-term natural environment and use, affecting structural functions and safety of structural materials, so structural durability is one of the important connotations of engineering structure [3]. About relevant statistics at home and abroad showed that economic losses caused by the durability of concrete structures, and as the environmental changes and functional requirements occur, durability problems were getting more and more prominent.…”

Section: Introductionmentioning

confidence: 99%

Durability Prediction Method of Concrete Soil Based on Deep Belief Network

Xiao

Zhu

2022

Advances in Civil Engineering

View full text Add to dashboard Cite

To truly reflect the durability characteristics of concrete subjected to multiple factors under complex environmental conditions, it is necessary to discuss the prediction of its durability. In response to the problem of durability prediction of traditional concrete structures, there is a low prediction accuracy, and the predicted time is long, and a concrete structural durability prediction method based on the deep belief network is proposed. The influencing factors of the concrete structural durability parameters are analyzed by two major categories of concrete material and external environmental conditions, and the transmission of chloride ions in the concrete structure is described. According to the disconnection of the steel bars, the durability of the concrete structure is started, and the determination is determined. The concrete structural antiflexural strength, using a deep belief network training concrete structural antiflexural strength judgment data, constructs a concrete structural durability predictive model and completes the durability prediction of the concrete structure based on the deep belief network. The proposed prediction method based on the deep belief network has a high prediction accuracy of 98% for the durability of concrete column structures. The simulation results show that the concrete structural durability’s prediction accuracy is high and the prediction time is short. The prediction of concrete durability discussed here has important guiding significance for the improvement of concrete durability test methods and the improvement of concrete durability evaluation standards in China.

show abstract

Evaluation of service-life prediction model for reinforced concrete structures in chloride-laden environments

Cited by 12 publications

References 32 publications

Models for the Prediction of Service Life of Buildings – A Review

Models for the Prediction of Service Life of Buildings – A Review

Diffusion of chloride from seawater into the concrete analysis: a literature review on implemented approaches

Durability Prediction Method of Concrete Soil Based on Deep Belief Network

Contact Info

Product

Resources

About