Deterioration of concrete due to reinforcement steel corrosion

Cabrera, J G

doi:10.1016/0958-9465(95)00043-7

Cited by 545 publications

(248 citation statements)

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“…Where x cr is the penetration for corrosion in the bar in the moment of that the first visible crack appears on the cover, C/d is the cover/diameter relation, δ is obtained from equation [1], and C/L c is the cover/anodic length relation. Once that x cr (mm) is calculated, x is obtained with the expression ECS Transactions, 15 (1) 267-274 (2008) x = x cr + x p [8] Where x is the penetration in the bar during the process of corrosion (that is, in the two stages).…”

Section: Ecs Transactions 15 (1) 267-274 (2008)mentioning

confidence: 99%

“…The relative displacement between the diameters, δ, represents the oxide layer needed to produce tangential stress equal to the resistance to tension of the concrete and start the cracking in the interface steel-concrete. Resolving then the problem through the Theory of Elasticity (8) the δ value is obtained which is given by equation [1]. bar's center to the nearest free surface of the concrete (see figure 1).…”

Section: Numerical Development: Finite Elementmentioning

confidence: 99%

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Reinforcement Corrosion Measurement in Reinforced Concrete Structures from the Crack's width in the Cover

et al. 2008

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Two experiments of accelerated corrosion are carried out in a reinforced concrete block and a cylinder to calibrate a finite threedimensional element model where the corrosion cracking is simulated due to the expansion of oxides. The model obtained is used then to find a theoretical relationship between the consumed steel (corrosion penetration) and the crack's width. It is found that this relationship is a function of the corroded length, cover, reinforcement diameter and concrete type. The results obtained are validated with three experiments found in literature: a beam subjected to accelerated corrosion, and two beams subjected to natural corrosion conditions. These beams are also subjected to the simultaneous action of flexion and corrosion, as they are expected to be found in use. It is shown that there is a good correlation between the model and experimental results.

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Section: Ecs Transactions 15 (1) 267-274 (2008)mentioning

confidence: 99%

Section: Numerical Development: Finite Elementmentioning

confidence: 99%

Reinforcement Corrosion Measurement in Reinforced Concrete Structures from the Crack's width in the Cover

et al. 2008

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“…Steel corrosion in concrete results in the steel cross-sectional area decreasing, concrete compressive strength falling and bonding capability between steel and concrete playing down, concrete cracking and ultimate structural failure [3][4][5]. In the natural environment, steel corrosion in concrete is a very slow process, so it is difficult to establish the corrosion rate model.…”

Section: Introductionmentioning

confidence: 99%

Impact of Low Calcium Fly Ash on Steel Corrosion Rate and Concrete– Steel Interface

Xu¹,

Chen²,

Xu³

et al. 2012

TOCIEJ

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Abstract:The use of fly ash is not only in harmony with the concept of sustainable development, but also beneficial to some mechanical properties of concrete. This paper discusses steel corrosion rate time-changing law in concrete with different replacing ratios of low calcium fly ash(10%~30%) and the microcosmic characteristic of concrete-steel interface.The steel corrosion rate was tested by linear polarization and weak polarization for corrosion monitoring in man-made climate environment, the microcosmic characteristic of concrete-steel interface was observed by Electronic Microscope and Scanning Electron Microscope. The experimental results showed that addition of 10%~30% fly ash increased the ability of concrete to resist steel corrosion, and the concrete with 20% replacement ratio of fly ash had the least corrosion layer thickness. The microscopic and microcosmic results further verified and explained the point of view. The analytical results of present work showed that the addition of fly ash in concrete had dual effects: (a) reducing concrete porosity and (b) improving the concrete-steel interface structure. Therefore, the replacement ratios of 10%~30% low calcium fly ash can be effectively used in structural concrete.

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“…A substantial amount of research related to reinforcement corrosion has been carried out in the past, addressing various issues related to the corrosion process, its initiation and damaging effects. Assessment of the flexural strength of corrosion-damaged RC members has been studied (Azad et al 2010;Cabrera 1996;Huang and Yang 1997;Rodriguez et al 1997;Uomoto and Misra 1988). A number of studies have also been conducted on the prediction of residual flexural strength of corroding concrete beams (Azad et al 2007;Mangat and Elgarf 1999;Nokhasteh and Eyre 1992;Ravindrarajah and Ong 1987;Tachibana et al 1990;Wang and Liu 2008;Jin and Zhao 2001).…”

Section: Introductionmentioning

confidence: 99%

Residual Strength of Corroded Reinforced Concrete Beams Using an Adaptive Model Based on ANN

Imam

Anifowose

Azad

2015

International Journal of Concrete Structures and Materials

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Estimation of the residual strength of corroded reinforced concrete beams has been studied from experimental and theoretical perspectives. The former is arduous as it involves casting beams of various sizes, which are then subjected to various degrees of corrosion damage. The latter are static; hence cannot be generalized as new coefficients need to be re-generated for new cases. This calls for dynamic models that are adaptive to new cases and offer efficient generalization capability. Computational intelligence techniques have been applied in Construction Engineering modeling problems. However, these techniques have not been adequately applied to the problem addressed in this paper. This study extends the empirical model proposed by Azad et al. (Mag Concr Res 62(6):405-414, 2010), which considered all the adverse effects of corrosion on steel. We proposed four artificial neural networks (ANN) models to predict the residual flexural strength of corroded RC beams using the same data from Azad et al. (2010). We employed two modes of prediction: through the correction factor (C f ) and through the residual strength (M res ). For each mode, we studied the effect of fixed and random data stratification on the performance of the models. The results of the ANN models were found to be in good agreement with experimental values. When compared with the results of Azad et al. (2010), the ANN model with randomized data stratification gave a C f -based prediction with up to 49 % improvement in correlation coefficient and 92 % error reduction. This confirms the reliability of ANN over the empirical models.

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Deterioration of concrete due to reinforcement steel corrosion

Cited by 545 publications

References 1 publication

Reinforcement Corrosion Measurement in Reinforced Concrete Structures from the Crack's width in the Cover

Reinforcement Corrosion Measurement in Reinforced Concrete Structures from the Crack's width in the Cover

Impact of Low Calcium Fly Ash on Steel Corrosion Rate and Concrete– Steel Interface

Residual Strength of Corroded Reinforced Concrete Beams Using an Adaptive Model Based on ANN

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