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Frontiers of Structural and Civil Engineering

ISSN 2095-2430

ISSN 2095-2449(Online)

CN 10-1023/X

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2018 Impact Factor: 1.272

Front Struc Civil Eng    2013, Vol. 7 Issue (4) : 379-390    https://doi.org/10.1007/s11709-013-0223-9
RESEARCH ARTICLE
Evaluating effect of chloride attack and concrete cover on the probability of corrosion
Sanjeev Kumar VERMA1(), Sudhir Singh BHADAURIA2, Saleem AKHTAR1
1. Civil Engineering Department, University Institute of Technology, Rajiv Gandhi Technological University, BHOPAL Madhya Pradesh 462036, India; 2. S.G.S. Institute of Technology and Science, INDORE Madhya Pradesh 452003, India
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Abstract

Corrosion of reinforced concrete (RC) structures is one of the significant causes of deterioration of reinforced concrete (RC) structures. Chlorination is a major process governing the initiation and advancement of the injurious corrosion of steel bars. Now, several researches on the chlorination of concrete structures have been ongoing around the world. Present article reviews several recently performed chlorination studies, and from results of a field survey evaluates the effect of chloride content on the probability of corrosion and the influence of concrete compressive strength on the chloride content and penetration, also evaluates the effect of concrete cover over the chloride content of the RC structures at rebar depth and on the probability of corrosion.

Keywords concrete      chloride      reinforcement      corrosion      deterioration      cover     
Corresponding Author(s): VERMA Sanjeev Kumar,Email:sanjeev.apm@gmail.com   
Issue Date: 05 December 2013
 Cite this article:   
Sanjeev Kumar VERMA,Sudhir Singh BHADAURIA,Saleem AKHTAR. Evaluating effect of chloride attack and concrete cover on the probability of corrosion[J]. Front Struc Civil Eng, 2013, 7(4): 379-390.
 URL:  
https://academic.hep.com.cn/fsce/EN/10.1007/s11709-013-0223-9
https://academic.hep.com.cn/fsce/EN/Y2013/V7/I4/379
methodprinciple/procedurelimitations
quantab testReaction between silver dichromate and chloride ion produces white marks on the stripsIt is expensive, hazardous and appropriate for low thickness.
potentiometric titrationUsing acid or water soluble methods, the final volume will indicates chloride content.Skilled personal are required.
rapid chloride testPotential difference of unknown solution is compared with potential difference of solutions with known chloride concentration.Results are affected by the presence of certain materials.
salt ponding test (resistance of concrete against penetration of chloride ion)A 3% NaCl solution is ponded on the top surface of the 28 days dried specimen, bottom face is exposed to environment, and the chloride concentration of 0.5 inch thick slice is measured.Long-term test, complicated testing conditions, provides only average value in place of actual
bulk diffusion test (resistance of concrete against penetration of chloride ion)Same as above with few changes, first is it samples initial moisture condition, specimen is saturated with limewater instead of keeping dried.Long-term test.
rapid chloride permeability testTotal charge passed is measured to evaluate ionic movement.Current passed indicates movement of all the ions instead of chloride ion.
electrical resistance testTwo cooper plate electrodes are connected on the opposite faces of specimen by thin wet sponges. Then electrodes are connected to resistivity meter.Results are affected with change in temperature.
Tab.1  methods for testing chloride content
Fig.1  Two phases of the service life (based on tuutti’s model, 1982)
referencesstudy performedconsiderable research/ findingscomments
Cusson et al. [4]Presented the development of probablistic mechanistic modeling approach supported by durability monitoring to obtain improved predictions of service life. Developed a model to predict service life of concrete bridge decks exposed to chloride by analyzing surface chloride content, chloride diffusion coefficient, threshold chloride content, corrosion and deterioration rate.Demonstrated that service life predictions using probabilistic models calibrated with selected monitored field data can provide more reliable assessments of the probabilities of reinforcement corrosion and corrosion-induced damage, when compared to using deterministic models based on standard data from the literature. Such probabilistic models can improve life cycle performance of structures by extending its service life and reducing its life cycle cost.All the four parameters responsible for chloride ingress rate have been considered and model is validated by experimental results.
Gouping et al. [2]Observed steel corrosion caused by chloride penetration as the most significant problem related to durability of concrete structures. Performed experiments on stressed specimens exposed to salt solution, to study the effect of stress on chloride ion penetration resistance. Diffusion of chlorides in concrete has been evaluated by Fick’s 2nd law of diffusion.Chloride contents in un-cracked concrete with different w/c ratio, states and level of stress and environmental conditions have been analyzed.Normally chloride studies are performed on unstressed concrete. However, evaluating the effect of stress over the chloride penetration provides more realistic results.
Balafas and Buroyne [5]observed that life of a bridge controlled by corrosion has two phases, in first phase chloride penetrates to the depth of rebar and starts corrosion, and in second phase rust produced with higher volume puts pressure on the cover and led to spalling of concrete cover. Developed a model to determine the time span of two periods.New formula is proposed for the rate of rust production, based on Faraday’s law.Results are in good agreement with existing experimental data on specimens under uniform corrosionConsidered two phase service life and evaluated propagation time on the basis of fracture mechanics.
Yuan et al. [6]Used multispecies model to describe the chloride transport in saturated concrete, which has been solved using FDM by inputting parameters such as porosity, density, chemical composition of pore solution, diffusion coefficient and chloride binding isotherm. And used extension of Nernst-Planck equation to describe multispecies model.Diffusion coefficient used in this model was depth dependent instead of fixed.J=-D[(αc/αx)+(C/Y)(αY/αX)+ZC(F/RT)(αE(x,t)/αX)-CV(X)]Where D = effective diffusion coefficient; i= ionic concentration in pore solution; g = chemical activity coefficient; E = electric potential; F = Faraday constant; R = universal gas constant; z = valence.In this model in place of constant diffusion coefficient a depth-dependent diffusion coefficient has been considered. This is a good approach as it has been observed by many researchers that diffusion coefficient is a variable. And the results are verified by experimental results.
Wang et al. [7]Chloride concentration and diffusion coefficient decreases with the increase of compressive stress and increases with the increase of flexural stress. Considering the above statement a model for predicting the chloride ingress has been developed for different loading conditions based on Fick’s 2nd law of diffusion.Results of performed experiment shows that diffusion coefficient have inverse relationship with compressive stress and direct relationship with flexural stress, and apparent diffusion coefficient decreases with the increase in compressive stress and increased with the increase of flexural stress.Developed model accounts for parameters such as stress level, water/ cement ratio, curing time, temperature, concrete age, humidity, and chloride diffusion coefficient.Predicted values of chloride diffusion coefficient from the proposed model are comparable with experimental results. More validation of this model is required.
Chai et al. [8]Investigated corrosion of steel during the accelerated corrosion test and critical chloride ion concentration. Service life prediction equation of concrete structures has been established through the experimental results. Defined concrete service life as the period from the initial use to depassivation or to the corrosion of steel. Two different types of experiments were performed to evaluate critical chloride ion concentration and concrete service life. Specimens prepared are having water cement ratio of 0.48.Threshold value of chloride ion concentration has been determined as for different specimens as 0.485% and 0.461% (percent mass of concrete).Also observed that Mineral admixtures in concrete can preserve protective passive film over rebar and improve the resistance to corrosion of steel rebar, also decrease the free chloride ion content by absorbing large number of free chloride ions.Considered threshold chloride concentration as the criteria of the end of service life. Service life of concrete constructed by replacing cement fly ash and slag is more than a concrete constructed by ordinary Portland cement.
Zhang and Ba [9]Conducted accelerated life test by chloride migration equipment to save time and money, and found that the negative algorithm of chloride ion concentration has been linear with the electrochemical potential.Presented a accelerated curve to predict the Service life of concrete in natural diffusion test.The result shows that in chloride environment service life of concrete structures with 10 mm cover to rebar has been between 11.89 and 12.45 years.Service life obtained experimentally is comparable with the results of Life-365 models.
Lin et al. [10]Developed an integrated FE based numerical model for predicting service life of RC structures exposed to chloride environments, which accounts for the environmental humidity, temperature fluctuations, chloride binding-diffusion and convection, as well as decay of concrete structural performance.Results of numerical model were validated by comparing with analytical solutions and experimental observations, and its application for predicting its service life has been demonstrated on RC slab.Chemical attack, environmental conditions, temperature and age of structures, combination of all these parameters have been required for performance evaluation of concrete structures.
Sun [11]Proposed a service life prediction model for RC structures exposed to chloride environment based on the analytical solution of Fick’s 2nd law of diffusion, also presented time and depth dependent chloride diffusion coefficient obtained from the analytical solution of the nonlinear chloride diffusion equations.Service life predicted by this model is found to be comparable with well known Light Con model.Considered time and depth diffusion coefficient for better results, as now several researchers realized that diffusion coefficient is not a constant, it depends on the quality of concrete and exposure conditions. To obtain more accurate results inspection period must be longer. And to obtain more realistic predictions different environmental factors can be considered.
Andrade and Andrea [12]Fick’s law has been used to calculate the diffusion coefficient for predicting the concentration of the aggressive agents at a certain depth and at several periods of time. Electrical resistivity property has been used to calculate both the initiation and propagation periods, as well as for predicting age of concrete related to durability and for measuring the efficiency of curing.Observed resistivity as the property based on the concrete porous system and its degree of moisture content. Concrete mix can be designed for a target resistivity and this parameter can also be used as a performance parameter (corrosion indicator).Considered diffusion coefficient as the significant factor governing the chloride ingress and service life of the structures.
Wang et al. [13]Presented service life prediction model for chloride environment based on Fick’s 2nd law using above Eqs. (1 to 4), also developed a service life prediction program using Monte-Carlo method.This model is comparable with life-365 model.Provides realistic results as it considered environmental conditions with usage.
Conciatori et al. [14]Presented a numerical model “TransChlor” based on Finite element method (FEM) and Finite difference method (FDM). This model combines various transport modes such as thermal transfer, hydrous transfer of vapor water and liquid water by capillary suction, CO2 diffusion, Chloride ion diffusion and chloride ion convection by the hydrous movement. Microscopic and macroscopic models have been often used to model the movement of chloride ions. Microscopic models describe chloride ion movements in concrete and macroscopic models consider the chemical conversions and the thermal, hydrous and chloride ion variations by simulating overall chemical effects on transport.Carbonation influences the capacity of concrete to capture chloride ion.Provide results by combining various transport modes and ingress of harmful agents.
Song and kwon [15]Proposed a neural network algorithm to determine chloride diffusion in high performance concrete (HPC) using micro pore structures. Electrically driven chloride penetration tests for diffusion coefficient are performed for the concretes with various parameters such as w/c ratio and various mineral admixtures.Experimental data had been compared with numerical simulation results, and it has been found that developed technique is applicable for different mixture design of HPC.It has been observed that by applying neural network diffusion coefficient can be estimated successfully. However, by utilizing more data from more number of test specimens a more effective model can be developed.
Zhang and Lounis [16]Presented a performance-based durability design of concrete structures using simplified diffusion-based model based on Fick’s law of diffusion. Numerical nonlinear relationship between the four parameters governing the corrosion initiation period of reinforced concrete structures including chloride diffusion coefficient, chloride threshold value of reinforcement, concrete cover and surface chloride exposure condition has been determined.it has been observed that in aggressive chloride-laden environment increasing concrete cover is more effective than using corrosion resistant steel, it is necessary to use both high performance concrete and corrosion-resistant steel, a relative decrease in the concrete cover has to be compensated by a much greater increase in the corrosion resistance of steel, and values of critical chloride content and concrete cover are governed by chloride diffusion coefficient.This study considered all the significant parameters required for evaluating chloride ingress in concrete structures using Fick’s law of diffusion.
Cheung et al. [17]Developed a 2-D FE coupled model to evaluate the chloride penetration process for predicting the corrosion initiation time. Found that corrosion initiation time is significantly governed by the speed of chloride transfer and depassivation process with in the structure. Variation in environmental conditions to which structure is exposed had very significant impact on the corrosion process, therefore variation in microclimate on the concrete surface has been investigated. The corrosion performance model is developed to consider change in environmental conditions and simulate the coupled diffusion process and corrosion performance in time domain. Also Proposed a set of realistic environmental conditions based on material properties.The parametric analysis results suggest that the corrosion initiation time in tropical/ subtropical regions depends mainly on the annual mean relative humidity (h), the source chloride Concentration (C), concrete covers depth (d) and w/c ration.Surface chloride concentration shows a quasi-linear increase with the nth root of time and this increase is relatively fast and reaches a quasi-constant content in about five years time.This model considers the effect of environmental conditions, which have a very significant effect on the chlorination of concrete structures. Hence, it provides more realistic results
Alizadeh et al. [18]Determined values of diffusion coefficient and surface chloride content in concrete specimens exposed to seawater in the Persian Gulf. Also effect of various curing regimes had been investigated on the estimation of time to corrosion initiation of reinforced concrete structures during the DuraPGulf model.Fick’s second law of diffusion (Eqs. (1) to (4)) has been used to evaluate chloride penetration rate as a function of depth from the concrete surface and time.Evaluated diffusion coefficient and surface chloride content are not real diffusion coefficient and surface chloride content, but only represents the regression coefficients.
Shekarchi et al. in [19]Presented the development of DuraPGulf (service life design model based on Fick’s law) to predict the chloride induced corrosion initiation of RC structures in the south of IRAN.Model has been developed using the FE technique and user friendly software was programmed for practical engineering applications.Ingress of chloride ion and service life of a RC structure depends on the exposure conditions. Therefore, it is required to develop local models based on local exposure conditions. Hence, it is good to develop this DuraPGulf as local model for the structures in Gulf region.
Anoop and Rao [20]Demonstrated the use of data from field inspections for the assessment of remaining life of corrosion affected RC bridge by determining the time taken for a given performance measure to deteriorate to a target value using the concept of additive fuzzy logic. Corrosion initiation time has been determined using Fick’s 2nd Law of diffusion. Uncertainities in the values of the parameters characterizing the enviroment and variables affecting the time to corrosion initiation and corrosion propogation are taken into account by treating them as fuzzy variables.Usefulness of proposed methodology has been illustrated through a case study, by comparing the time to reach different damage levels for a severly distressed beam.Utilizing field inspection data for modeling chloride ingress or other deterioration mechanism provides the variation of these parameters with the age of structures.
Evans and Richardson [21]Analyzed the chloride diffusivity of Irish Portland cement concretes in chloride environment, also influence of secondary cementitious materials has been investigated.It has been observed that in concretes with secondary cementitious materials diffusion coefficient is lower than the concretes with Portland cement.Results of this study can be used to design and develop concrete structures with increased durability.
Polder and Rooij [22]Presented investigations series performed on six concrete structures between the ages of 18 to 41 years, most of them are constructed using blast furnace slag cement. Interpretation is based on the Dura-Crete model developed using Fick’s 2nd law of diffusion for chloride ingress. Curve fitting of chloride profiles has been performed to evaluate chloride surface contents and apparent diffusion coefficients.Comparison has been made with previously published data on chloride ingress and electrical resistivity of similar concretes.Classifying structures according to their age and condition is a good practice for short-term monitoring of structures.
Khatri and Sirivivatnan [23]Presented a model to determine service life of concrete structures in marine environments, chloride ingress model based on Fick’s 2nd law of diffusion has been assumed. Effect of severity of environment is also demonstrated. Service life of RC structures found to be governed by cover depth, diffusion coefficient, surface chloride concentration and critical chloride level.It has been observed that cover depth is more important than diffusion coefficient, and surface chloride concentration affects service life more than critical chloride value. Hence, to improve service life it is better to provide sufficient cover depth.Findings of this research is useful of engineers and researchers, recommendation can be used for improving the durability of concrete structures.
Martin-Perez and Lounis [24]Presented an approach for predicting service life of RC structures exposed to chloride environment, which combines a FE based chloride transport model with a reliability based approach to evaluate the damage.The probabilistic distributions of the chloride penetration front and corrosion initiation time are generated by using Monte Carlo simulation.Combining two different approaches for predicting service life and chloride ingress usually provides good results.
Liang et al. [25]Examined mathematical service life prediction models for RC bridges in chloride laden environment. The service model consists of three stages of corrosion initiation time (tc), depassivation time (tp) and propagation time (tcorr). Hence, total service life of existing RC bridge is t = tc + tp + tcorr. Model is based on based on Fick’s 2nd law of diffusion.Solution of Fick’s law depends on the initial chloride content and surface chloride content.Degree of deterioration can be obtained by using the value of integrity of structures.Here constant surface chloride content has been used. However, to improve the results time and depth dependent surface chloride content can be used.
Cao and Sirivivatnan [26]Presented a simple model to predict the service life of RC structures based on the solution derived from Fick’s 2nd law of diffusion. Defined service life as time after construction until the chloride content at the reinforcement is high enough to initiate steel corrosion.Suggested that acceptable steel corrosion rate can be used for predicting service life of deteriorating concrete structures.Diffusion coefficient and surface chloride content obtained are more than real value so correction factors are required.
Scheremans and Gemert [27]Chloride Ingress in the concrete is mainly governed by diffusion process and evaluated using Fick’s 2nd law of diffusion. Also conducted experiments on concrete structures exposed to marine environment and observed significant influence of depth on chloride diffusion coefficient, however, no effect of time on diffusion coefficient have been observed.Updated a probability based model for interpretation of test results and prediction of the service life of RC structures.From several researches it has been observed that diffusion coefficient is time and depth dependent. So, better results can be obtained by considering effect of time on diffusion coefficients.
Costa and Appleton [28]Presented an experimental study for calibrating the parameters in model based on Fick’s second law of diffusion used to predict the chloride penetration, and concluded that both the concrete cover and concrete quality affects the service life.Studied time dependence of chloride diffusion coefficient and surface chloride concentration for the various marine conditions. It has been found from results that chloride diffusion coefficient and surface chloride concentration depends on the time and depth. For a service life of more than 50 years concrete cover must be more than 40mm.This study is useful of researchers as it provide values of chloride diffusion coefficient and surface chloride concentration for different regions and also provides time and depth dependence of these parameters.
Ann et al. [29]Concluded from a literature review that in marine environment chloride content increases with time and properties like W/C, cement content and binder governed the diffusivity of chloride ion.Considered various significant factors affecting chloride ingress, while evaluating chloride content in concrete structures.Considered constant diffusion coefficient (2x10-12 m2/s), but it has been observed that chloride diffusion coefficient depends on time and depth.
Sharma and Mukherjee [30]Studied progress of corrosion in chloride and oxide conditions using Ultrasonic guided waves. Observed that corrosion rate is different in chloride and non- chloride conditions.Corrosion rate depends on the ingress of various agents responsible for initiating the corrosion, chloride content increases the corrosion rate after initiating the corrosion of rebars.Application of Ultrasonic guided waves for evaluating the corrosion rate and for comparing different environmental conditions has been identified as good approach.
Costa and Appleton [3]Performed study on three concrete mixes in different exposure conditions, and concluded from the results that diffusion coefficient and surface chloride concentration are time dependent.Simple models based on Fick’s second law of diffusion were used to predict the chloride penetration. However, it has been observed that these models are required to be calibrated using experimental results.Evaluated values of diffusion coefficient and surface chloride concentration cannot be used for long-term monitoring, as these values are strongly time dependent.
Sengul and Tasdemir [31]Investigated the effect of replacing cement with supplementary materials on compressive strength and rapid chloride permeability of concrete. And it has been observed that partial replacement (about 50%) of Portland cement with ground fly ash and ground granulated blast furnace slag significantly reduce the permeability of chloride in concrete.Considered three aspects minimum chloride permeability for more durability, high compressive strength for safety and cost of concrete. It has been required to estimate an optimized mix percentage to satisfy all the above aspects (durability, safety, cost).All the three aspects, durability, safety and cost, are significantly influence the utility of a structure.Permeability is the main cause influencing the ingress of harmful ions in the concrete surrounding the rebars, so this study provides useful results for reducing the permeability of the concrete.
Tab.2  Few recent chlorination studies
Fig.2  concrete cover and values of chloride content (×100) of the surveyed structures
Fig.3  effect of chloride content at rebar depth on probability of corrosion
Fig.4  Effect of compressive strength on the chloride content at rebar depth
groupchloride penetration period/yearNo. of structures
A10 to 1522
A216 to 3033
A331 to 5028
A451 to 6013
Tab.3  Classification of data considering chloride penetration period or age of the structures
groupcompressive strength/MPaNo. of structures
C10 to 1544
C216 to 2533
C4more than 2521
Tab.4  Classification of data considering compressive strength of the structures
Fig.5  relation between chloride content and concrete cover
Fig.6  Effect of concrete cover on the probability of corrosion
Fig.7  Relation between concrete cover () and chloride content () for A1 group
Fig.8  Relation between concrete cover () and chloride content () for A2 group
Fig.9  Relation between concrete cover () and chloride content () for A3 group
Fig.10  Relation between concrete cover () and chloride content () for A4 group
Fig.11  Relation between concrete cover () and chloride content () for C1 group
Fig.12  Relation between concrete cover () and chloride content () for C2 group
Fig.13  Relation between concrete cover () and chloride content () for C3 group
1 Wardhana K, Hadipriono F C. Analysis of recent bridge failures in the United States. Journal of Performance of Constructed Facilities , 2003, 17(3): 144-150
doi: 10.1061/(ASCE)0887-3828(2003)17:3(144)
2 Gouping L, Fangjian H, Yongxian W. Chloride ion penetration in stressed concrete. Journal of Materials in Civil Engineering , 2011, 23(8): 1145-1153
doi: 10.1061/(ASCE)MT.1943-5533.0000281
3 Costa A, Appleton J. Chloride penetration in marine environment—part I: Main parameters affecting chloride penetration. Materials and Structures , 1999, 32(4): 252-259
doi: 10.1007/BF02479594
4 Cusson D, Lounis Z, Daigle L. Durability monitoring for improved service life predictions of concrete bridge decks in corrosive environments. Comp Aid Civil and Infr Eng , 2011, 26: 1-40
5 Balafas I, Burgoyne C J. Modeling the structural effects of rust in concrete cover. Journal of Engineering Mechanics , 2011, 137(3): 175-185
doi: 10.1061/(ASCE)EM.1943-7889.0000215
6 Yuan Q, Shi C, De Schutter G, Deng D, He F. Numerical models for chloride penetration into saturated concrete. Journal of Materials in Civil Engineering , 2011, 23(3): 305-311
doi: 10.1061/(ASCE)MT.1943-5533.0000168
7 Wang H, Lu C, Jin W, Bai Y. Effect of external loads on chloride transport in concrete. Journal of Materials in Civil Engineering , 2011, 23(7): 1043-1049
doi: 10.1061/(ASCE)MT.1943-5533.0000265
8 Chai W, Li W, Ba H. Experimental study on predicting service life of concrete in the marine environment. Open Civil Eng J , 2011, 5: 93-99
9 Zhang W, Ba H. Accelerated life test of concrete in chloride environment. Journal of Materials in Civil Engineering , 2011, 23(3): 330-334
doi: 10.1061/(ASCE)MT.1943-5533.0000182
10 Lin G, Liu Y, Xiang Z. Numerical modeling for predicting service life of reinforced concrete structures exposed to chloride environments. Cement and Concrete Composites , 2010, 32(8): 571-579
doi: 10.1016/j.cemconcomp.2010.07.012
11 Sun Y, Chang T, Liang M. Service life prediction for concrete structures by time-depth dependent chloride diffusion coefficient. Journal of Materials in Civil Engineering , 2010, 22(11): 1187-1190
doi: 10.1061/(ASCE)MT.1943-5533.0000098
12 Andrade C, Andrea R.Electrical resistivity as microstructural parameter for the modeling of service life of reinforced concrete structures. In: Proceedings of the 2nd Int Sym on Ser Life Des Inf- 2010. Delft Netherlands , 2010, 379-388
13 Wang C J, Zhang G Z, Liu K X, Tu L Q, Li J H, Qin M Q. Research on service life prediction model of concrete structure on sea crossing bridge. J Wuh Univ Tech , 2010, 32(17): 141-146
14 Conciatori D, Laferriere F, Bruhwiler E. Comprehensive modeling of chloride ion and water ingress into concrete considering thermal and carbonation state for real time. Cement and Concrete Research , 2009, 40(1): 109-118
doi: 10.1016/j.cemconres.2009.08.007
15 Song H, Kwon S. Evaluation of chloride penetration in high performance concrete using neural network algorithm and micro pore structure. Cement and Concrete Research , 2009, 39(9): 814-824
doi: 10.1016/j.cemconres.2009.05.013
16 Zhang J Y, Lounis Z. Nonlinear relationship between parameters of simplified diffusion-based model for service life design of concrete structures exposed to chlorides. Cement and Concrete Composites , 2009, 31(8): 591-600
doi: 10.1016/j.cemconcomp.2009.05.008
17 Cheung M M S, Zhao J, Chan Y B. Service life prediction of RC bridge structures exposed to chloride environments. Journal of Bridge Engineering , 2009, 14(3): 164-178
doi: 10.1061/(ASCE)1084-0702(2009)14:3(164)
18 Alizadeh R, Ghods P, Chini M, Hoseini M, Ghalibafian M, Shekarchi M. Effect of curing conditions on the service life design of RC structures in the persion gulf region. Journal of Materials in Civil Engineering , 2008, 20(1): 2-8
doi: 10.1061/(ASCE)0899-1561(2008)20:1(2)
19 Shekarchi M, Ghods P, Alizadeh R, Chini M, Hoseini M. Durapgulf a local service model for the durability of concrete structures in the south of Iran. Arab J Sci Eng , 2008, 33(1B): 77-88
20 Anoop M B, Balaji Rao K. Application of fuzzy sets for remaining life assessment of corrosion affected reinforced concrete bridge girders. Journal of Performance of Constructed Facilities , 2007, 21(2): 166-171
doi: 10.1061/(ASCE)0887-3828(2007)21:2(166)
21 Evans C, Richardson M G. Service life of chloride- contaminated concrete structures. Concrete Res in Ireland Colloquium , 2005, 131-137
22 Polder R B. Rooij MRd. Durability of marine concrete structures- field investigations and modeling. HERON , 2005, 50(3): 133-153
23 Khatri R P, Sirivivatnanon V. Characteristics service life for concrete exposed to marine environments. Cement and Concrete Research , 2004, 34(5): 745-752
doi: 10.1016/S0008-8846(03)00086-3
24 Martin-Perez B, Lounis Z. Numerical modeling of service life of reinforced concrete structures. In: Proceedings of 2nd Int Rilem w/s on Life Pred Ag. Mang, Paris, France , 2003, 71-79
25 Liang M, Lin L, Liang C. Service life prediction of existing reinforced concrete bridges exposed to chloride environment. J Infra Sys , 2002, 8(3): 76-85
doi: 10.1061/(ASCE)1076-0342(2002)8:3(76)
26 Cao H T, Sirivivatnanon V. Service life modelling of crack-freed and cracked reinforced concrete members subjected to working load. CIB world building congress, Wellington New Zealand , 2001, 1-11
27 Scheremans L, Gemert D V. Service prediction of reinforced concrete structures, based on in-service, chloride penetration profiles. Dur Build Mat Comp , 1999, 8: 83-93
28 Costa A, Appleton J. Chloride penetration in marine environment- part II: prediction of long term chloride penetration. Materials and Structures , 1999, 32(5): 354-359
doi: 10.1007/BF02479627
29 Ann K Y, Ahn J H, Ryou J S. The importance of chloride content at the concrete surface in assessing the time to corrosion of steel in concrete structures. Construction & Building Materials , 2009, 23(1): 239-245
doi: 10.1016/j.conbuildmat.2007.12.014
30 Sharma S, Mukherjee A. Monitoring corrosion in oxide and chloride environments using ultrasonic guided waves. Journal of Materials in Civil Engineering , 2011, 23(2): 207-2011
doi: 10.1061/(ASCE)MT.1943-5533.0000144
31 Sengul O, Tasdemir M A. Compressive strength and rapid chloride permeability of concretes with ground fly ash and slag. Journal of Materials in Civil Engineering , 2009, 21(9): 494-01
doi: 10.1061/(ASCE)0899-1561(2009)21:9(494)
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