Corrosion Of Reinforcement In Concrete Structures Research Articles

Corrosion level estimation in reinforced concrete beams by acoustic emission sensing and selective crack measurements

AbstractAccurate corrosion assessment plays an important role in ensuring structural safety of reinforced concrete (RC) structures. However, on‐site assessment of existing concrete structures presents many challenges, including high costs, limited inspection timeframes, and difficult accessibility. To facilitate inspection‐based corrosion assessment, this paper presents a novel approach by combining short‐term acoustic emission (AE) monitoring with selective crack width measurements for corrosion level (CL) assessment. AE sensing is a monitoring technique which can detect ongoing internal degradation mechanisms by analyzing ultrasonic waves emitted by the damage process. Yet, two major challenges arise on site: (1) practical limitations prevent continuous AE monitoring over the structure's entire lifetime and (2) AE can only generate relative results in the absence of reference measurements. This paper addresses both challenges to bridge the gap between laboratory experiments and on‐site monitoring of corroding RC structures. First, short periods of AE monitoring data are analyzed to investigate the potential of AE sensing over limited timeframes. Second, AE data of corroding RC beams are combined with sparse crack width measurements in order to obtain absolute CLs. The proposed methodology is experimentally validated by corroding eight beams with varying dimensions, corrosion zones, and reinforcement layouts. The experimental results prove that the estimated CLs closely match the rebar mass losses, with a mean absolute error of 1.53% CL for beams reaching up to 14% CL, confirming the potential of the combined AE and crack width measurement technique as an efficient and accurate condition assessment approach. Moreover, AE sensing provides detailed spatial variability of the rebar corrosion in the monitored zone, which is challenging to obtain with conventional techniques. By using this dual‐technique approach, shorter monitoring periods prove nearly as effective as continuous AE monitoring in accurately estimating CLs.

Degradation law of bond strength of reinforced concrete with corrosion-induced cracks and machine learning prediction model

During long term operation service, reinforced concrete (RC) structures are subjected to corrosive media such as chloride salts, which results in the degradation of interface bond performance, subsequently reducing the load bearing capacity and service life of the structures. To accurately assess the durability of RC structures in environments such as oceans and salt lakes, this study combines experimental methods with machine learning (ML) techniques to explore the degradation patterns and predictive models of bond performance under chloride salt corrosion. Accordingly, a series of central pull-out tests were conducted based on an electrochemical accelerated-dry-wet cycle corrosion regime to investigate the degradation patterns of bond performance between corroded steel bars and concrete under different corrosion degree and corrosion-induced crack widths. By comparatively analyzing the evolution patterns of cracks and the morphology of the steel bars in reinforced concrete specimens and their failure modes, and integrating the mechanical degradation mechanism with chemical and microscopic corrosion mechanisms, an in-depth analysis of the corrosion-induced degradation patterns at the bond interface was performed. The internal relationships between corrosion degree, corrosion-induced crack width and bond strength were discussed, and the variation patterns of bond strength with corrosion-induced crack width and corrosion degree were explored. Moreover, the bond strength patterns were analyzed from an energy perspective. The results indicate that bond strength and bond energy decrease with an increase in the corrosion-induced crack width of the concrete. Additionally, based on the experimental data from this study, ML predictive models for bond strength were established using corrosion-induced crack width as the control variable. The results show that the ML-based bond strength predictive models fit well with the experimental data, offering higher accuracy and reliability compared to traditional bond strength models. The research findings provide significant theoretical basis and practical guidance for safety assessment, maintenance, reinforcement, and full-life design of corroded RC structures.

Experimental and numerical study on polypropylene fibers reinforced concrete slabs with corroded reinforcement under monotonic loading

The degradation of structural performance due to reinforcement corrosion in reinforced concrete (RC) structures and the subsequent measures to improve the mechanical properties of corroded RC structures have garnered significant interest. This study investigates the structural performance of corroded polypropylene fiber RC slabs through both experimental and numerical approaches. Specimens were subjected to accelerated corrosion via electrochemical methods to simulate rebar corrosion. Key experimental parameters include polypropylene fiber volume fractions of 0% and 3%, design corrosion levels of 0%, 5%, and 10%, and both one-way and two-way constraints. The Digital Image Correlation (DIC) technique was employed for data acquisition. Load, deflection, strain, and crack morphology data were collected during loading. Results indicate that reinforcement corrosion increases the maximum crack width during loading, while a 3% polypropylene fiber volume fraction reduces this width by 20% to 48% at the same load level. Polypropylene fibers also enhance the peak loads and corresponding deflections of unidirectional and bidirectional specimens, with a more pronounced increase in unidirectional specimens of 11.3% and 15.4%, respectively. Although corrosion reduces the load-carrying capacity of the specimens, the inclusion of 3% polypropylene fibers significantly mitigates this reduction. A numerical model, incorporating rebar corrosion and polypropylene fibers through appropriate material constitutive models, was developed and validated against experimental results. The model accurately simulates the mechanical behavior of polypropylene fiber RC slabs with corroded reinforcement.

Bayesian inference of the spatial distribution of steel corrosion in reinforced concrete structures using corrosion-induced crack width

Observations of corrosion-induced crack widths offer crucial information about the corrosion states of steel reinforcements in reinforced concrete (RC) structures, enabling a cost-effective method for inferring corrosion states through inverse analysis. However, the uncertainty associated with the relationship between corrosion-induced cracking and steel weight loss necessitates a probabilistic inference method, especially when considering the spatial distributions of steel weight loss, which provides important information to estimate the load-bearing capacity loss of corroded RC structures. This paper proposes a Bayesian framework to infer the steel weight loss distribution in RC structures based on the observed corrosion-induced crack width. To reduce the dimensions of the Bayesian inference, a Karhunen-Loève transform is applied to extract the principal distribution features of the steel weight loss. The forward model of the Bayesian inference adopts a data-driven sequence-to-sequence transduction approach to predict corrosion-induced crack width from steel weight loss. This model incorporates a novel nonlinear convolution kernel for input encoding and a sparse polynomial chaos expansion for decoding, which proves more accurate and efficient than finite element simulations. The Hamiltonian Markov chain Monte Carlo (HMCMC) sampler is used to efficiently sample from the posterior distribution of the Bayesian inference. The case study of the proposed method demonstrated that Bayesian inference provides robust range estimation for the steel weight loss distribution, with its 95% confidence interval encompassing most observations. Additionally, the method efficiently inferred high-dimensional steel weight loss sequences up to 61 dimensions, taking advantage of the dimension reduction technique and the gradient-informed HMCMC sampler.

Time-dependent reliability assessment and optimal design of corroded reinforced concrete beams

It remains a significant challenge to quantitatively describe the corrosion of reinforced concrete (RC) structures under chloride penetration. Moreover, when considering uncertainties throughout the life cycle of corroded RC structures for assessing their safety, reliability, and optimal design, the complexity of the problem intensifies. To address these issues, this paper studies the time-dependent reliability analysis and optimal design of corroded RC beams. At first, the time-dependent reliability of beams is investigated by considering both the serviceability limit state (SLS), which corresponds to the corrosion initiation of the reinforced steel, and the ultimate limit state (ULS), associated with the bending failure of the beam. This analysis takes into account the time-dependent chloride diffusion coefficient and incorporates a stochastic process. The reliability is evaluated using the Monte Carlo Simulation (MCS) method and the cumulative distribution function (CDF) method. Subsequently, a time-dependent reliability-based design optimization (TRBDO) problem is formulated, and the PSO-MCS, a methodology incorporating a particle swarm optimization (PSO) algorithm and MCS is adopted to solve it. After optimization, the initial cost of the specific RC beam is reduced from 1351.879€ to 1247.075€, while the time-dependent reliability within [0, 100] years is improved from 0.6057 to 0.6508. The effectiveness of the CDF, MCS and PSO-MCS methods are demonstrated through reliability analysis and design examples of corroded RC beams.

A Novel SMFL‐Based Assessment Method for Corrosion Nonuniformity of Rebar and Its Application in Reliability Analysis of Corroded RC Beam

The reliability of corroded reinforced concrete (RC) structures relies on the accurate minimum cross‐sectional area of corroded rebar. In this study, the accurate morphologies and self‐magnetic flux leakage (SMFL) field strengths of twenty‐eight non‐uniformly corroded rebars were obtained using 3D structural light scanning and micromagnetic detection technologies, based on which three indices of the SMFL field variation ratio dH, the corrosion non‐uniformity degree dSn, and the cross‐sectional area ratio K0.25 are proposed. The statistical results show that the probability densities of dSn and K0.25 obey the Weibull distribution and Gamma distribution at the 95% confidence level, respectively, and their distribution parameters are linearly or inversely proportional to dH. The probability density distribution of the minimum cross‐sectional area of corroded rebar can be determined using indices dSn and K0.25, based on which a feasible SMFL‐based reliability assessment method of corroded RC structures is proposed. The case study of a real specific corroded RC beam shows that the reliability assessment error of the SMFL‐based method is only 1.2%, which is much lower than the 20.7% error of the existing method. This SMFL‐based method provides a novel idea that can automatically and accurately assess the effect of rebars’ corrosion non‐uniformity on the reliability of specific in‐serviceRC structures.

Pure shear model for crack width analysis of reinforced concrete members

Reinforcement corrosion in concrete structures with excessive crack width poses a high risk of reducing the structure's service life. The crack width behavior is one of the most complex aspects of the mechanics of reinforced concrete (RC). With most of the models used in practice being semi–empirical or empirical, very few analytical approaches have been proposed. However, the analytical models lack either accuracy or simplicity, or both. This paper presents a new analytical model, termed the Pure Shear Model, that predicts mean crack width by a simple formula. It is based on the partial interaction tension stiffening model considering a short RC tie subjected to short–term loading. The model assumes elastic material properties and neglects shrinkage, internal cracking, and slip at the interface. It presumes that the only deformations that occur in concrete are the shear strains due to shear lag that are taken constant across the cover thickness. Deplanation of concrete section due to shear lag results in crack width linearly increasing from zero at the bar to its maximum value on the surface of the RC member. Despite the simplicity of the proposed model, its accuracy in predicting mean crack width was shown to be comparable to that of the design code methods.

An improved method for predicting the shear strength of corroded reinforced concrete beams with experimental and numerical validation

Shear failure of reinforced concrete (RC) beams is a brittle failure without giving sufficient warning. Steel bar corrosion is one of the main deterioration phenomena for concrete structures in marine environments. However, the effect of steel bar corrosion on the shear-transfer mechanism of RC beams is not yet fully understood, and existing findings are insufficient for reasoned and accurate prediction of shear strength. Thus, the primary objective of this study was to propose and validate a revised fictitious-support-point method for better predicting the shear strength of corroded RC beams. The revised method determines the fictitious support points based on a more transparent mechanical model than previously. Finite element simulation confirms the validity of the revised method from the load-bearing mechanism point of perspective. Validation with copious previously-published test data show that the revised method predicts the shear strength of corroded RC beams more accurately and reasonably than the existing method proposed by other researchers. This study contributes to effective and reasonable maintenance of corroded RC structures.

Service life prediction of reinforced concrete structures subjected to corrosion: a comparative study

PurposeReliable estimations of the extent of corrosion and time required to reach specific safety limits are crucial for assessing the reliability of aging reinforced concrete (RC) bridges. Engineers and decision-makers can use these figures to plan suitable inspection and maintenance operations.Design/methodology/approachAnalytical, empirical and numerical approaches for estimating the service life of corroded RC structures were presented and compared. The concrete cover cracking times, which were predicted by the previously proposed analytical models, were compared with the experimentally obtained cracking times to identify the model/s for RC bridges. The shortcomings and limitations of the existing models are discussed.FindingsThe empirical models typically depend on the rate of corrosion, diameter of steel reinforcement and concrete cover depth and based on basic mathematical formula. In contrast, the analytical and numerical models contain the strength and stiffness properties of concrete as well as type of corrosion products and incorporate more complex mechanical factors. Four existing analytical models were analyzed and their performance was evaluated against existing experimental data in literature. All the considered analytical models were assumed thick-walled cylinder models. The maximum difference between observed cracking time from different test data and calculated cracking time using the developed models is 36.5%. The cracking times extend with increase in concrete cover and decrease with corrosion current density. The development of service life prediction models that considers factors such as heterogeneity of concrete, non-uniform corrosion along rebar, rust production rate and a more accurate representation of the corrosion accommodating region are some of the areas for further research.Research limitations/implicationsOutcome of this paper partially bridge the gap between theory and practice, as it is the basis to estimate the serviceability of corrosion-affected RC structures and to propose maintenance and repair strategies for the structures. For structural design and evaluation, the crack-width criterion is the greatest practical importance, and structural engineers, operators and asset managers should pay close attention to it. Additionally, repair costs for corrosion-induced serviceability failures, particularly concrete cracking and spalling, are significantly higher than those for strength failures. Therefore, to optimize the maintenance cost of RC structures, it is essential to precisely forecast the serviceability of corrosion-affected concrete structures. The lifespan of RC structures may be extended by timely repairs. This helps stake holders to manage the resources.Practical implicationsIn order to improve modeling of corrosion-induced cracking, important areas for future research were identified. Heterogeneity properties of concrete, concept of porous zone (accommodation effect of pores should be quantified), actual corrosion morphology (non-uniform corrosion along the length of rebar), interaction between sustain load and corrosions were not considered in existing models. Therefore, this work suggested for further researches should consider them as input and develop models which have best prediction capacity.Social implicationsThis work has positive impact on society and will not affect the quality of life. Predicting service life of structures is necessary for maintenance and repair strategy plans. Optimizing maintenance strategy is used to extend asset life, reduce asset failures, minimize repair cost, and improve health and safety for society.Originality/valueThe degree of accuracy and applicability of the existing service life prediction models used for RC were assessed by comparing the predicted cracking times with the experimentally obtained times reported in the literature. The shortcomings of the models were identified and areas where further research is required are recommended.

Corrosion-related parameter estimation for RC structures using UKF-based Bayesian nonlinear finite element model updating with seismic data

Model updating based on field measurements (e.g., from ambient vibration) has proven to be an efficient approach for assessing the condition of reinforced concrete (RC) structures. Despite existing studies in the literature, no effort has been devoted to corrosion-related parameter estimation for RC structures based on Bayesian nonlinear finite element model updating (FEMU) with seismic data. To bridge this gap, this research work extends the application of nonlinear FEMU to corroded RC structures and provides a methodology to estimate the corrosion-related parameters from seismic measurement of RC structures with high nonlinearity. The essential idea of this approach is to integrate recursive Bayesian inference (i.e., unscented Kalman filter) with advanced finite element (FE) modeling of corroded RC structures to estimate corrosion-affected properties. The advanced FE modeling approach used in this study is an efficient modeling strategy that accounts for different aspects of the corrosion, particularly corroded bond-slip in RC structures. The capability of the approach in evaluating the corrosion-affected model parameters is examined by 13 case studies using an example RC column with simulated seismic data due to lack of real-word measurements. These study cases consider different corrosion levels, measurement noise levels, corroded features, seismic intensity levels, and types of measurement. The successful estimation of the corrosion-affected properties for the corroded column under various scenarios indicates that the proposed methodology can be employed to identify the unknown corroded properties of RC structures using recorded seismic response data. The updated FE model of a corroded RC structure can potentially be utilized for reliable seismic performance assessment, which assists in future decision-making for repair or retrofit of existing structures.

Investigation of Corroded Bond-Slip Effects for Corroded RC Columns

Steel bar corrosion is one of the most common causes of structural performance degradation for reinforced concrete (RC) columns subjected to extreme loads such as earthquakes. Due to the different characteristics of corrosion effects, a comprehensive and efficient finite element (FE) modeling approach is necessary for the performance assessment of corroded RC columns. To this end, this study provides an effective FE modeling approach using a recently developed geometrically nonlinear fiber-based frame element that considers bond-slip, allowing for explicit representation of corrosion-affected bonding. This aspect necessitates the use of an explicit material model for corroded bond-slip and its associated corroded properties. Since the existing models of corroded bonding properties in the literature were developed based on the highly scattered and limited experimental data, this study develops a new probabilistic model for corroded bonding properties based on more experimental data compiled from the literature and quantifies the prevailing uncertainties. To facilitate its use for modeling corroded RC structures, a cyclic corroded bond-slip model in an open-source FE software framework is implemented. In this paper, the FE modeling approach is first used to model two corroded RC columns tested in the literature, with comparison to the conventional modeling approach (i.e., assuming perfect bonding). The influence of corroded bonding on the static and dynamic behaviors of RC columns is further explored deterministically. Furthermore, the impact of uncertainty in corroded bonding properties on the static and dynamic behavior simulations of RC columns is examined. This work is concluded that (1) the FE modeling approach provided for corroded RC columns proves to be effective in capturing corrosion effects; and (2) corroded bonding plays an important role in simulating the behavior of corroded RC columns, and thus cannot be neglected. This is particularly true considering its associated uncertainty and its impact on the performance assessment of RC columns under severe corrosion conditions.

New semiempirical temporal model to predict chloride profiles considering convection and diffusion zones

Chloride ions are primarily responsible for reinforcement corrosion in concrete structures in the marine environment. Thereby, analyses regarding chloride penetration into concrete are fundamental for service life estimates, in which the chloride concentration profiles provide quantitative information for prediction models. However, the conventional modeling method based on the solution of Fick's second law of diffusion usually only fits the diffusion profile zone and does not represent the convection zone. Therefore, this article shows a new model for complete chloride profile modeling. The semiempirical double exponential model was developed by approximating Fick's second law using the finite difference method and validated with chloride profiles from structures under natural degradation for more than 40 years. The double exponential model proposed can fit in the two profile zones, showing higher efficiency than Fick's model, and stands out for expressing the variation in chloride peak depth over time.

Acoustic emission testing for multi-scale assessment of reinforcement corrosion in concrete structures

Degradation of existing structures poses a serious threat to our built environment. The aim of this paper is to investigate the use of acoustic emission monitoring in degradation assessment of existing structures, focusing specifically on corrosion damage detection in reinforced concrete structures. Reinforcement corrosion is seen as one of the most significant and costly degradation mechanisms that impact the durability and structural safety of our built infrastructure and Modern heritage buildings. The paper presents a multi-scale experimental approach, from material to structure, focusing on two challenges: (i) monitoring the evolution of the corrosion process itself and the consequential concrete cracking during accelerated corrosion, and (ii) identifying the different AE sources in this complex process. The application of AE testing for rebar corrosion monitoring is investigated on various sample types and scales under accelerated conditions in a lab environment, and from on-site monitoring of a concrete girder bridge. Results show that the developed test setups, data filtering and processing procedures substantially improve AE-based corrosion damage monitoring, and provide a valuable contribution towards on-site application.

Influence of various parameters on the current distribution and protection degree of impressed current cathodic protection for reinforced concrete with TiMMO mesh anodes

Impressed current cathodic protection (ICCP) is an effective technique to control reinforcement corrosion in concrete structures. The efficiency and design of an ICCP system with titanium mixed metal oxide (TiMMO) anodes in a mortar overlay is strongly influenced by the current distribution to the different reinforcement layers of a reinforced concrete element. An in-depth experimental study is performed to investigate the effect of various parameters on the current distribution and degree of corrosion protection: (i) chloride content, (ii) cement type, and (iii) reinforcement configuration. 24-hour depolarization measurements (EN ISO 12696:2022) indicate that an increase in chloride concentration in the concrete, related to an increase in the rate of reinforcement corrosion, leads to a general decrease in the degree of protection. The use of a CEM III/A cement leads to a large increase in concrete electrical resistivity compared to concrete with an ordinary Portland cement (CEM I). This causes a lower total current output to the reinforcement and a less uniform distribution of current. Finally, a lower steel reinforcement density resulted in a larger current density, as the total current is distributed over a smaller steel surface area, causing higher depolarization values.

Effects of treated corrosion reinforcement on structural behavior of concrete beams

Structural degradation phenomena like reinforcement corrosion in concrete structures imply a consequent reduction in time of the safety level. Corrosion causes a reduction of the sectional area, ductility and strength of rebars, bond strength between steel and concrete. The subsequent redistribution of internal stresses induces a reduction in ductility at ultimate limit state and a variation of the deformational behavior in serviceability conditions. In this paper, an experimental investigation was carried out to study the effect of treated corrosion reinforcement on structural behavior of concrete beams. In this investigation, phosphoric acid and vinegar solution are used to treat the corroded steel bars and compared the bending strength of concrete beams with treated and untreated corrosion reinforcement. A finite element computer software (ANSYS) has been used to compare the experimental results. From the experimental and analytical results, it was observed that performance of concrete beams with treated corrosion reinforcement is better than the concrete beams with corrosion reinforcement,

Enhancing Sustainability of Corroded RC Structures: Estimating Steel-to-Concrete Bond Strength with ANN and SVM Algorithms

The bond strength between concrete and corroded steel reinforcement bar is one of the main responsible factors that affect the ultimate load-carrying capacity of reinforced concrete (RC) structures. Therefore, the prediction of accurate bond strength has become an important parameter for the safety measurements of RC structures. However, the analytical models are not enough to estimate the bond strength, as they are built using various assumptions and limited datasets. The machine learning (ML) techniques named artificial neural network (ANN) and support vector machine (SVM) have been used to estimate the bond strength between concrete and corroded steel reinforcement bar. The considered input parameters in this research are the surface area of the specimen, concrete cover, type of reinforcement bars, yield strength of reinforcement bars, concrete compressive strength, diameter of reinforcement bars, bond length, water/cement ratio, and corrosion level of reinforcement bars. These parameters were used to build the ANN and SVM models. The reliability of the developed ANN and SVM models have been compared with twenty analytical models. Moreover, the analyzed results revealed that the precision and efficiency of the ANN and SVM models are higher compared with the analytical models. The radar plot and Taylor diagrams have also been utilized to show the graphical representation of the best-fitted model. The proposed ANN model has the best precision and reliability compared with the SVM model, with a correlation coefficient of 0.99, mean absolute error of 1.091 MPa, and root mean square error of 1.495 MPa. Researchers and designers can apply the developed ANN model to precisely estimate the steel-to-concrete bond strength.

Structural performance deterioration of corroding reinforced concrete columns in marine environments

In aggressive marine environments, rebar corrosion caused by chloride ion ingression in concrete is a critical factor leading to premature failure of in-service reinforced concrete (RC) structures. This paper investigated the structural performance deterioration of marine RC structures affected by rebar corrosion, and proposed new analytical models for predicting the residual bearing capacity of the corroded RC columns. By analyzing the performance deterioration mechanisms of the corroded RC structures, the material degradation models and structural strength reduction models were constructed. Then, the analytical models for estimating the residual bearing capacity of the corroded RC columns under various loading conditions were proposed. From the proposed models, the moment-axial force (M-N) interaction diagrams were plotted for analyzing the influence of corrosion damage locations on the residual bearing capacity. Furthermore, the impact of marine environmental factors on the service life of the corroding RC columns under various loading conditions was investigated. Finally, a numerical example for the corroded RC columns was given to demonstrate the effectiveness of the proposed models. The results showed that the residual bearing capacity of the marine RC columns can be significantly affected by the rebar corrosion level, corrosion damage location, load condition and in-service environment.

Steel corrosion damage monitoring in reinforced concrete structures with the acoustic emission technique: A review

• An in‐depth literature review and discussion on AE‐based corrosion monitoring in RC is presented. • Consistency of parameter‐ and signal‐based AE methods for corrosion monitoring is analyzed. • AE‐based condition assessment of corroded RC elements during load testing is discussed. • An overview on availability of AE data sets for corrosion tests in lab and in‐situ is presented. • Research challenges for in‐situ monitoring of corrosion damage in RC structures are discussed. Corrosion is a major issue in construction and infrastructure management, giving rise to high repair costs, safety concerns and structural failures. Especially reinforcement corrosion in concrete structures is a complex issue. As degradation starts internally, visual inspection lacks efficiency in early stages of the corrosion process. Acoustic Emission (AE) monitoring provides major advantages as this technique enables to detect internal damage in an early stage. However, the use of AE monitoring also comes with certain challenges. The aim of this paper is to review appropriate protocols for AE-based reinforced concrete (RC) corrosion monitoring based on an overview of reported lab experiments, highlighting challenges and pitfalls, and to provide a solid basis for extension of the research focus towards on-site AE-based corrosion monitoring in RC structures. Therefore, this paper firstly discusses AE monitoring during (accelerated) corrosion tests, including methods for data analysis and best-practice protocols. Secondly, application of the AE technique for condition assessment of corroded RC elements during load testing is discussed. Thirdly, an overview is presented of reported on-site AE monitoring studies on corroding RC structures. The paper concludes with a discussion and future research challenges, especially towards on-site monitoring of existing RC structures.

Axial behavior of circular seawater sea-sand coral concrete columns reinforced with BFRP bars and spirals

• Axial behavior of BFRP bars reinforced seawater sea-sand coral concrete columns was studied experimentally. • The load bearing capacity of B-SSCC columns declined as the spiral spacing narrowed paradoxically owing to the significant discontinuity of coral concrete internally. • Columns with dense stirrups showed more pronounced ductility in the post-peak stage compared with B-SSCC square columns. • An ultimate bearing capacity prediction model is established. For the sake of solving the problem of steel reinforcement corrosion in concrete structures and reducing the transportation cost of concrete raw materials at sea in the development of South China Sea Islands, a new type of coral reef sand concrete columns reinforced with basalt fiber reinforced polymer (BFRP) bars and spirals was proposed. In this study a total of 18 circular seawater sea-sand coral reef concrete columns reinforced with BFRP bars and spirals (B-SSCC) were tested under concentric axial loads. Parameters of nominal longitudinal bar diameters and spiral spacing were investigated to obtain variations on crack propagation, failure modes, load bearing capacity, strain and ductility properties. The results indicated that no obvious cracks were observed until the curves reached up to 0.95 P max approximately and the columns experienced more brittle and explosive failure modes with the increase of longitudinal bar diameter and spiral spacing. The load bearing capacity of B-SSCC columns increased with longitudinal reinforcement ratio, however, declined as the spiral spacing narrowed paradoxically. It was owing to the significant discontinuity of coral concrete internally. Compared with B-SSCC square columns, the circular columns with dense stirrups showed pronounced ductile behavior in the post-peak stage, remarked by improved average ductile coefficient β of 22.6%. Finally, a numerical prediction of load bearing capacity was suggested.

Lifetime reliability analysis of concrete columns damaged by reinforcement corrosion

Rebar corrosion caused by chloride ion ingression is a critical factor leading to performance deterioration of in-service reinforced concrete (RC) structures exposed to aggressive environments. This paper presents a new method to evaluate the concrete crack growth, the bearing capacity degradation and the lifetime performance deterioration for the corroded RC columns under small eccentric compression. By analyzing the material degradation mechanism of the corroded RC structures, an effective method is proposed to predict the concrete crack growth and to estimate the residual bearing capacity of the corroding eccentrically loaded RC columns. Then, the concrete crack width and the load-bearing capacity deterioration rate are selected as structural performance indicators to assess the lifetime performance of the corroding RC columns. The stochastic gamma process is adopted for simulating the evolution of structural performance indicators and estimating lifetime failure probability and the remaining useful life of the corroding structures. Finally, a numerical example is given to demonstrate the effectiveness of the proposed methods for the lifetime performance assessment of the corroding columns. The obtained results show that the residual bearing capacity and the lifetime performance of the corroding RC columns can be significantly affected by rebar corrosion level, load condition and in-service environments.