Safety Of Concrete Structures Research Articles

A deep transfer learning-based algorithm for concrete surface defect detection

The integrity and safety of concrete structures are crucial in modern civil engineering. Traditional image-defect detection methods are significantly affected by light and noise. Methods based on deep learning, particularly convolutional neural networks (CNNs), offer new solutions for automated defect detection. This paper introduces a concrete surface defect detection algorithm based on deep transfer learning. Our model utilizes the ResNet50 architecture as its backbone and incorporates Atrous Spatial Pyramid Pooling (ASPP) to adapt to the diversity of defects and enhance recognition accuracy. In addition, the use of a self-attention mechanism effectively enhances the model’s focus on and analysis of key defect areas, improving its ability to perceive and select features for defects of various sizes, aiding precise localization and classification under complex conditions. Image preprocessing techniques such as resizing, conversion to grayscale, histogram equalization, and noise addition further enhance the robustness of the model in diverse real-world scenarios. On the publicly available COncrete DEfect BRidge IMage Dataset, our model achieved a mean average precision (mAP@0.5) of 0.90, showing a 3.4% improvement over the current best baseline method. Through transfer learning, it reached 0.92 on our custom dataset, significantly outperforming existing methods. These results demonstrate the effectiveness and superiority of the proposed model for detecting concrete defects. Additionally, we evaluated the impact of different architectures on model performance. Compared to traditional models using the VGG16 as the backbone, the ResNet50 architecture used in this study reduces parameter count by 5.41 times while improving performance by 6.1%.

Theoretical modeling of concrete friction-impact deterioration using water-borne sand abrasion experiment

To explore the influence of impact angle on concrete abrasion deterioration under water-borne sand, a theoretical model for friction-impact deterioration was developed. This model innovatively proposes the inhibition effect of the normal impact action on the tangential friction mass loss and the facilitation effect of the tangential friction action on the normal impact mass loss to rationally explain the effect of impact angle on concrete mass loss. Simultaneously, a water-borne sand accelerated abrasion experiment was conducted to initiate a comprehensive discussion on surface abrasion deterioration indicators, including mass loss, number of holes, aperture, hole area, and hole volume. In addition, the concrete abrasion mass loss rate was evaluated based on the friction-impact deterioration model combined with experimental data. Applying this model facilitates a reliable prediction of concrete's mass loss caused by abrasion. Consequently, this allows for a more accurate assurance of the safety of concrete structures exposed to abrasive conditions throughout their operational life. The results show that the mass loss per unit area, maximum aperture, hole area ratio, and hole volume exhibit a trend of first decreasing, then increasing and finally decreasing with the increase of impact angle. Under 15°, 60°, and 90°, 70 % of the mass loss per unit area of the concrete specimens occurred within the first 6 d of abrasion. When the angles were 30° and 45°, 50 % of the mass loss per unit area of the concrete specimens occurred in the 9–12 d abrasion. It has been revealed that 69° results in the most severe abrasion mass loss. The abrasion deterioration process of concrete can be divided into three primary stages, including surface mortar abrasion, prime aggregate-mortar abrasion, and continuous aggregate-mortar abrasion. Additionally, the friction-impact theoretical model was employed to simulate the abrasion of both single and multiple pier columns, and the simulations provided insights into the non-uniform mass loss rate distribution around the pier columns.

A numerical model for predicting the drying shrinkage behavior of concrete under ultra-low relative humidity

The drying shrinkage caused by rapid water loss will pose a great threat to the safety of concrete structures, especially for those serviced in an extremely dry environment. However, the majority of reported research primarily focuses on drying shrinkage behavior of concrete under relative humidity (RH) ranging from 50% to 100%, and the corresponding drying shrinkage prediction models have poor applicability, leading to an unclear understanding of it under ultra-low RH (RH<40%). In this study, a numerical model, finite element model with cohesive elements, was proposed to better predict the drying shrinkage behavior of concrete, even under the RH of 20%. Initially, geometric models of concrete with varying coarse aggregate size ranges and volume fractions were established. Subsequently, based on the relationship between RH and humidity diffusion coefficient of concrete with different water-cement ratio (w/c), a drying shrinkage model was proposed to examine the corresponding shrinkage strain of concrete even under ultra-low RH conditions, and its validity was verified through comparison with reported experimental research. Utilizing the developed model, the effects of size range and volume fraction of coarse aggregate, and the w/c, on the drying shrinkage of concrete across a wide range of RH levels were systematically investigated. The results indicated that increasing the aggregate size range can only slightly inhibit drying shrinkage, while there is a marked inhibition effect on it (decrease by about 45% at most) for increasing the aggregate vol% or reducing w/c, even under ultra-low RH of 20%. Finally, grey relation analysis was employed to assess the inhibition weight of each parameter on the drying shrinkage, following this sequence in order: RH > w/c > coarse aggregate vol% > coarse aggregate range size. We also envision that the proposed model could provide feasible guidelines for the inhibition of concrete in ultra-dry regions.

Investigation of Load–Displacement Characteristics and Crack Behavior of RC Beam Based on Nonlinear Finite Element Analysis Using Concrete Damage Plasticity

Crack patterns provide critical information about the structural integrity and safety of concrete structures. However, until now, there has been a lack of sufficient studies on using the Finite Element (FE) method to investigate the characteristics of the crack patterns of reinforced concrete (RC) beams. Therefore, this study aims to develop an FE model to analyze the load–displacement and crack characteristics of a beam under a four-point bending test using the concrete damaged plasticity (CDP) model that accounts for the influence of mesh size. The simulation results were validated against experimental results, including mesh convergence analysis, energy balance, load characteristics, and crack patterns. A parametric study was then conducted using this model to investigate the influence of the rebar’s diameter, number, and spacing on the RC beam’s load–displacement characteristics and crack behavior. The findings demonstrate that the FE model accurately simulates the working behavior of the RC beam, with a maximum deviation at a cracking load of 8.7% and crack patterns with a maximum deviation in the mean crack height of 12.1%. In addition, the results of the parametric study suggest that the rebar configuration significantly affects the RC beam’s loading carrying capacity. This study provides deeper insights into the use of FE modeling for analyzing the behavior of RC beams, which can be useful for designing and optimizing structures in civil engineering.

Investigating equivalency of different element models in discrete mesoscale analysis of ASR-damaged concrete

The alkali-silica reaction (ASR) is one of the most serious durability issues affecting the safety of concrete structures. Numerical simulation is useful for monitoring the internal condition of an RC structure with ASR damage and predicting its long-term behavior. A mesoscale three-dimensional rigid body spring model (3D RBSM), a type of discrete analysis model, has previously been developed to simulate ASR expansion by modeling aggregate and mortar separately. The element size in simulations using this model (known as the aggregate model) is 2–3 mm, so the number of elements is huge and computation time correspondingly long. An equivalent model with lower number of elements is required, so in this study a concrete model based on RBSM is proposed. The aggregate is not separately modeled and expansive elements are included to simulate ASR expansion, allowing a larger element size (1–2 cm). The number of elements and computation time are less than 1 % compared with the aggregate model. This proposed model is used to simulate free ASR expansion, ASR expansion under confinement, and the mechanical properties of ASR-damaged concrete, as well as pullout behavior after ASR expansion. The simulation results are compared against previously reported results obtained using the aggregate model, as well as against experimental results. This comparison confirms equivalency between the concrete model and the aggregate model, opening the possibility of simulating ASR damage in RC structures in the future.

Influence of the coarse aggregates size on the frost resistance in normal and polycarboxylate mixed concrete

The durability and safety of concrete structures depend heavily on their frost resistance. Previous studies indicated that the addition of coarse aggregates (CAs) and water reducing admixtures (WRA) can significantly improve the mechanical properties of concrete. However, the role of CAs size proportion on the frost resistance of normal (NC) and WRA mixed concrete (WRC) has not been well understood. In this study, the small (5∼10 mm) and large (10∼20 mm) grading CAs were mixed as the low (small: large = 90 : 10), medium (small: large = 40 : 60) and high (small: large = 10 : 90) mix proportion in NC and WRC. The mass test, ultrasonic measurement, compressive and splitting tests, mercury intrusion porosimetry (MIP) analysis were applied to investigate the variations of mass weight, elastic modulus, compressive and splitting strength, and porosity characteristics of NC and WRC under freezing and thawing (F-T) cycles. Additionally, a damage model was established to analyze the correlation between the macroscopic and microscopic damage of NC and WRC. The results showed that: i) The concrete with medium CAs mix proportion owned the best workability and mechanical properties before F-T cycles, and exhibited the least mechanical loss and porosity evolution after F-T cycles; ii) The incorporation of WRA improved the workability and mechanical properties of concrete, and mitigated the mechanical loss and porosity evolution after F-T cycles, but did not change the influence of CAs mix proportion; iii) The macroscopic changes in the mechanical properties of concrete were found to be related to the microscopic damage on porosity characteristics, which was minimum with the medium CAs mix proportion. Overall, our study emphasized the importance of CAs size proportion in enhancing the mechanical properties and frost resistance of NC and WRC. These findings can serve as valuable reference for field applications.

Influence of moisture on ultrasonic propagation, acoustic emission activity, and failure mechanism in concrete media

Free water in a concrete medium significantly influences its bearing capacity and failure mechanism. In this study, the mechanical properties and failure mechanism in concrete specimens with different moisture contents were investigated with the objective of enhancing the safety of concrete structures. Uniaxial compression tests were employed to study bearing capacity, ultrasonic propagation, acoustic emission activity and failure mechanism of concrete specimens with moisture contents of 0%, 2%, 4%, and 5.5%. The results implied that the crack initiation stress and compressive strength of concrete first increased and then decreased with the increase in moisture content, and the elastic modulus and Poisson’ s ratio first decreased and then increased. The inflection points were observed in the fitting curves for moisture contents within 1.15–1.65%. With the increase in the moisture in the concrete specimens, the ultrasonic propagation velocity in the material increased, the acoustic emission activity decreased, and the proportion of high-frequency acoustic emission signals decreased. The acoustic emission activity in the concrete specimens was observed predominantly in the failure stage under the influence of uniaxial stress. Based on the moment tensor inversion of acoustic emission, the proportion of shear damage in the failure process of concrete increased with the increase in moisture content. The failure mechanism was analyzed by obtaining the ISO and DC values of acoustic emission events, the moment tensor T–k diagram, and the P–T diagram. The geometric orientation of the acoustic emission events was consistent with the macroscopic fracture mode of the specimens. The ultrasonic propagation, acoustic emission characteristics and the deterioration mechanism of bearing capacity in water-saturated concrete were analyzed. The findings of this study can be applied in health monitoring and for the safe operation of concrete structures in water environments.

Analytical bond strength of deformed bars in concrete confined with transverse reinforcement and FRP

To ensure the long-term stability and safety of concrete structures, it is critical to accurately analyze the internal transverse reinforcements and externally bonded fiber-reinforced polymer (FRP) confinement to bond performances of deformed bars in concrete. However, no prediction models are available for bond strength and the bond-slip response with double confinement (transverse reinforcement and FRP). To address these issues, the present study proposes a predictive model to evaluate the bond strength of deformed bars in concrete under double confinement. The focus is on determining the internal pressure at the reinforcement/concrete interface provided by the transverse reinforcement and FRP at various stages of concrete cracking. The integral absolute error (IAE) of 12.0% for the 93 experimental data from the training dataset shows that the proposed model outperforms the other models. A general model for a bond-slip response involving double confinement is proposed and validated, along with a design recommendation to predict the minimum FRP thickness and bond length for seismic reinforcement.

Effects of sulfate and freeze–thaw cycles on the bond behavior of CFRP-concrete interface

The bonding performance of the interface between carbon fiber-reinforced polymer (CFRP) and concrete is crucial for the safety of concrete structures that are strengthened with CFRP. The reinforced structures in Northwest China are often affected by harsh environmental conditions. In this paper, by using the test method of sulfate and freeze–thaw cycles coupling erosion, the actual erosion environment that may be suffered in this area was simulated, and the bonding performance of CFRP reinforced concrete structures in this environment was studied. Combined with macro and micro experiments, the mechanism of coupled erosion was discussed, and the influence of the above environment on the interface failure mode, interface bearing capacity and interface characteristic values were analyzed. The experimental results show that under the coupling erosion, the failure mode of the CFRP-concrete interface has changed. And the bonding performance of the interface has been significantly reduced. The specific performance is that with the increase of erosion times, the interface bearing capacity is continuously reduced, and the maximum bond shear stress position is gradually moved to the free end. Through induction and analysis of the test data, the bond-slip model of the interface under this condition was established, and the accuracy of the model was evaluated by comparing it with the experimental data.

Concrete crack detection using lightweight attention feature fusion single shot multibox detector

As one of the most important defects of concrete, cracks seriously threaten the service life and safety of concrete structures, and various safety incidents caused by the collapse of concrete structures have occurred. Therefore, it is essential to detect concrete cracks as soon as possible. Existing object detection methods have low detection accuracy for cracks, leading to unsatisfactory detection results. In this paper, we propose a variety of feasible modules that improve the accuracy of single shot multibox detection (SSD), which is the most efficient object detection method in terms of both accuracy and speed. First, to improve the neural network’s ability to learn high-level and low-level feature maps, we propose a feature fusion enhancement module (FFEM). Second, to more effectively capture the information between feature map channels, we propose convolutional network attention (CNA). Third, to improve the anchor box fit to the ground truth box, we reset the distribution of the anchor box. Last, we propose a new type of nonmaximum suppression (NMS) named T-Soft NMS to address numerous issues with current NMS and to significantly enhance the performance of the model. We tested our method on a crack dataset, and numerous tests showed that it outperformed competing methods. In addition, we carried out ablation studies to confirm the validity and efficacy of our method.

Forensic-based investigation-optimized extreme gradient boosting system for predicting compressive strength of ready-mixed concrete

Abstract Regulations mandate testing concrete’s compressive strength after the concrete has cured for 28 days. In the ideal situation, cured strength equals the target strength. Advanced estimation of concrete’s compressive strength can facilitate quality management, improve safety, and present economic advantages in sustainable use. Basic statistical methods cannot effectively predict concrete’s strength or its non-linear relationships with the proportions of its constituent materials. In this study, a baseline model for predicting concrete’s compressive strength was constructed using a state-of-the-art machine-learning method. Most related studies have used sets of concrete mix design results concerning concrete specimens for laboratory-produced concrete specimens as training sets and have obtained simple models through regression; however, these models have been unsuitable for onsite prediction of the compressive strength of concrete with the various mix designs. Control over mix proportions is high in laboratories, resulting in low variation; onsite manual operation and environmental factors cause significant variations in assessment data. In this study, machine-learning techniques and a newly developed metaheuristic optimization algorithm were applied to big long-term data from 75 concrete plants to construct the optimal machine-learning model. Our self-developed forensic-based investigation algorithm was employed to fine-tune the hyperparameters of the extreme gradient boosting model and to improve the model’s generalizability. The lowest mean absolute percentage error (MAPE) obtained using this model was 9.29%, which was smaller than the lowest MAPE achieved using the conventional simple regression with the water-to-binder (W/B) ratio (12.73%). The traditional method tends to overestimate the actual compressive strength. Finally, a convenient expert system was developed that facilitates the use of the proposed model by onsite engineers for quality management. This system expedites the judgment of whether a mixed design is reasonable, reducing production costs while maintaining the safety of concrete structures. It can be widely applied in practice and function as an effective decision-making tool.

Time-dependent structural response estimation method for concrete structures using time information and convolutional neural networks

In this study, a structural response estimation method for evaluating the long-term strain, which can serve as the basis of assessing structural safety of concrete structures, is presented. Characteristics of short-term deformation caused by environmental influences and long-term inelastic deformation caused by combination of rheological effects and environmental influences are identified. To reflect these time-dependent short- and long-term deformation characteristics in the proposed method, the strain and corresponding time information collected from a structural health monitoring (SHM) are used. In the proposed method, the relationship between a strain response measured from a concrete structure and the corresponding time information including the year, month, day, and hour is defined by a convolutional neural network (CNN), which is a deep learning technique. The method assumes that the main sources of the strain in the structure are environmental influences, such as temperature and humidity, which have daily and seasonal periodicity, and rheological effects in concrete, such as creep and shrinkage, but it also assumes that the quantitative information on these sources is not available (e.g., environmental temperature and humidity, and rheological strain were not reliably measured). Thus, the CNN method developed in this study is trained only with strain and time data collected over several years, and used to estimate strain values within a specific timeframe, e.g., when the safety evaluation of the concrete structure is required or in case of SHM system failure or data loss. The presented method was developed and validated using SHM data from a real structure instrumented with fiber optic strain sensors. In addition, exploration of the constitution of the input of the CNN identified the type of time information that is the most effective in the long-term strain estimation of the developed method.

FPGA: Field programmable gate array-based four-channel embedded system for ultrasonic imaging of under-water concrete structures.

Non-destructive testing is needed for the evaluation of quality and safety of concrete structures in the field of civil engineering. The imaging of concrete/reinforced cement concrete structures (RCC) is a challenging task due to the non-homogeneous properties of the concrete material. To address this challenge, a novel real-time, re-configurable, four-channel embedded system has been designed and developed to image the internal details of the concrete samples using the water immersion pulse-echo (PE) mode under automation, which needs access from one side of the structure. The system performs data acquisition (DAQ) of the amplified echo signals under the control of the computer via a universal serial bus interface. A graphical user interface (GUI) has been developed using C# in a Visual environment, for image acquisition and control of the DAQ parameters. The performance of the system has been evaluated by acquiring B-Scan images of three types of concrete test blocks having side drilled holes (SDHs) and simulated inclusions embedded in concrete blocks of M20 grade using a linear array of 92kHz water immersion transducers operating in under-water PE mode. The acquired B-Scan images revealed the internal details of the concrete test blocks with sizing of the SDHs and inclusions. Therefore, the developed four-channel ultrasonic imaging system can visualize the internal details of under-water concrete structures, such as bridges and sea links, with the help of corresponding 2-D cross-sectional images, acquired using the developed system.

An improved model for predicting bond strength of deformed rebars in concrete with stirrups

To ensure the long-term stability and safety of concrete structures, it is critical to accurately analyze the stirrup confinement to bond performances of deformed bars in concrete. However, it remains a challenging task. As a result of this study, a bond prediction model incorporating the internal pressure, failure plane characteristics, and stirrup confinement is developed as a solution. The internal pressure of the rebar/concrete interface at various stages of comprehensive concrete cracking is determined with the aid of the SIFs-based crack propagation criterion, where the key parameters are evaluated by weight function theory and finite element model. In a comprehensive comparison, the proposed model accurately predicts both stirrup confinement and failure modes. A validation study is performed on 125 experimental results, with the integral absolute error (IAE) of 12.1% for the proposed model, which is significantly lower than other models.

Effects of elevated temperature and water re-curing on fracture process of hybrid fiber reinforced concretes

Hybrid fiber reinforced concrete has been introduced in constructions due to its superior mechanical performance compared to plain and mono fiber reinforced concrete. However, hybrid fiber reinforced concrete mechanical behavior after exposition at elevated temperature is of considerable importance for the safety of concrete structures and need more in-depth understanding. In this study, the effect of the elevated temperatures and water re-curing on the Mode I fracture performance of two hybrid fiber reinforced concretes was investigated. The Mix S exploited long hooked-end and medium hooked-end steel fiber, as well as high strength short wave-shaped steel fiber, for the hybrid reinforcement. Mix P contained polypropylene fibers substituting the high strength short wave-shaped steel fibers. The damage degree (DD) was estimated using the ultrasonic pulse velocity (UPV) method. The fracture process and development of fracture process zone (FPZ) length was studied by three-point bending tests and measuring the full-field displacement and strain on the surface of the specimen by the digital image correlation (DIC) technique. The results indicated an increasing damage degree with the elevated temperature, and a considerable reduction after water re-curing. The elevated temperatures above 200 °C deteriorate: modulus of rupture (MOR), residual strength, and fracture toughness. The dependency of the deterioration coefficient (DC) and the temperature from 20 °C to 800 °C was predicted by a linear / exponential relationship. Branching crack appeared when the elevated temperature exceeded 200 °C. Water re-curing enhanced the flexural performance of thermally damaged hybrid fiber reinforced concrete, reducing the crack branching and recovering the FPZ length. Mix S had a better flexural performance than Mix P at elevated temperature.

Research on expansion and stability of Friedel’s salt

Friedel’s salt is a common hydrate of cement concrete in chloride environment, and the change of its performance will affect the performance of cement paste and the safety of concrete structure. In order to study the properties and morphological characteristics of Friedel’s salt, Friedel’s salt is prepared by reaction of C3A with chlorine salt and chemical synthesis in this paper. The expansibility and stability of Friedel’s salt are studied by XRD, SEM, TG-DTG and FTIR. The results show that the higher the curing temperature is, the faster the reaction rate is, the expansion degree is 0.3 and the density is 2.087 g/cm3. Friedel’s salt is more stable in alkaline environment, and the greater the pH value is, the more stable the Friedel’s salt is. Under dry heat curing, Friedel’s salt is gradually decomposed with the increase of temperature, and the Friedel’s salt prepared by C3A and chlorine salt is completely decomposed at 500 °C, and the Friedel’s salt prepared by chemical method is completely decomposed at 600 °C. Under damp heat curing, Friedel’s salt is gradually decomposed with the increase of temperature, and it is not completely decomposed at 100 °C.

Experimental investigation of mixed mode I–II fatigue crack propagation in concrete using a digital image correlation method

The propagation of fatigue cracks leads to the degradation of the load-carrying capacity of concrete structures and even fatigue failure. An in-depth investigation of the fatigue crack propagation process is essential to reveal the fracture mechanism and further assess the safety of concrete structures. This paper presents an experimental study of mixed mode I–II fatigue crack propagation in concrete. Fatigue tests are conducted on three-point bending (TPB) beams with an off-center initial crack with different fatigue load levels. The digital image correlation (DIC) method is employed to observe the complete fatigue crack propagation process, and the method is verified to be applicable. The results indicate that the mixed mode I–II fatigue crack propagation process can be divided into three stages, namely, the rapid propagation in the initial stage, a stable propagation stage, and the final fast propagation until unstable failure. The mixed mode I–II crack propagation path under static loading is a good approximation of that under fatigue loading. The results also show that the crack tip opening displacement (CTOD), crack tip sliding displacement (CTSD), mode I stress intensity factor (SIF), and mode II SIF corresponding to the unstable failure of the TPB beam are approximately constant and independent of the fatigue load level. In particular, the negligible CTSD and mode II SIF demonstrate that the mixed mode I–II fatigue failure of concrete is dominated by the mode I component.

A length scale insensitive phase‐field model for fully coupled thermo‐mechanical fracture in concrete at high temperatures

AbstractFracture in concrete at high temperatures involves complex thermo‐mechanical couplings and arbitrary crack evolution, imposing great challenges to its computational modeling. This work addresses a length scale insensitive phase‐field cohesive model for fully coupled thermo‐mechanical fracture in concrete at high temperatures. Both the thermal expansion and transient creep strain are accounted for in the kinematics. Based on the underlying phase‐field cohesive model for fracture in solids at ambient temperature, the temperature‐dependent mechanical properties of concrete, that is, Young's modulus, tensile and compressive strengths and fracture energy, and so forth, are all incorporated. In addition to the cracking‐induced mechanical damage mechanism represented by the crack phase‐field, the thermal deterioration mechanism is also considered by a temperature‐dependent thermal damage variable. The numerical implementation of the proposed model into the multi‐field finite element method is then briefly addressed. Several representative numerical examples, for example, thermally induced cracking in energy storage structures, thermal shock in quenched concrete plates, mode‐I and mixed‐mode failure of notched beams at high temperatures, and so forth, are presented for the validation. The effects of various expressions for the transient creep strain (TCS) on the global behavior of concrete structures are also studied. As in those purely mechanical problems, both the predicted crack pattern and global responses for all examples are insensitive to the incorporated phase‐field length scale. Being able to capture the fully coupled thermo‐mechanical fracture in concrete, the proposed phase‐field cohesive model, combined with a reliable hydro‐chemo‐thermal analysis, is promising in assessing the integrity and safety of concrete structures at high temperatures like fire scenarios.

Reliability analysis of deteriorated post-tensioned concrete bridges: The case study of Ynys-y-Gwas bridge in UK

Concrete structures are exposed to aggressive environmental conditions that lead to corrosion of the embedded reinforcement and pre-stressing steel. Consequently, the safety of concrete structures may be compromised, and this requires a significant budgets to repair and maintain critical infrastructure. Prediction of structural safety can lead to significant reductions in maintenance costs by maximising the impact of investments. The aim of this paper is to establish a framework to assess the reliability of existing post-tensioned concrete bridges. A time-dependent reliability analysis of an existing post-tensioned involving the assessment of Ynys-y-Gwas bridge has been presented in this study. The main cause of failure of this bridge was corrosion of tendons, making it a relevant case study to evaluate the effect of corrosion on bridge safety. Uncertainties associated with material properties, geometry, loads and corrosion parameters are taken into account. The probabilistic models of the uncertainties are combined with a non-linear finite element analysis to study the effect of tendons pitting corrosion on the post-tensioned concrete bridge. The limit state function considered is flexural strength. The Monte-Carlo simulation (MCS) method is used to compute the statistical parameters of the resisting bending moment through a MATLAB code running ABAQUS. It was found that the reliability index for the first year of bridge service life is below the minimum value acceptable for structures. The study confirmed that this bridge was a high risk structure due to its design and location. The proposed framework can be used by engineers and researchers as a tool to support decision for segmental post-tensioned (PT) bridges maintenance since they need for a regular inspection due to their risk to corrosion.

Study of anti-chlorine corrosion of anion exchange resin based superhydrophobic cement mortar in chloride salt environment

Anti-corrosion of reinforced concrete structures in the chloride salt environment is an important issue. Especially the corrosion damage of reinforced concrete by chloride ions seriously affects the safety of concrete structures and quality of the material’s appearance. In this paper, the chlorine corrosion resistance of superhydrophobic anion exchange resin cement mortar in a chloride environment was investigated. The chlorine corrosion resistance of different samples was compared by electrochemical experiments and chloride distribution test. The results show that the as-fabricated mortar has better corrosion resistance to chloride salt attack than the reference sample at a 98.60% increase in corrosion resistance rate. AgNO3 color development experiment and free chloride ion concentration measurements show that the as-fabricated mortar can not only adsorb chloride ions inside the mortar, but also effectively inhibit the penetration of external chloride ions. This internally and externally coordinated anti-corrosion cement mortar is expected to extend the service life of reinforced concrete in chloride salt environments.