Concrete Spalling Research Articles

Heat-induced explosive spalling of self-prestressing, self-compacting concrete slabs

A novel concrete mix has been developed that can achieve high levels of self-prestressing through the controlled expansion of the concrete sample with cast-in carbon fibre reinforced polymer (CFRP) bars. Experiments have shown that the mechanical properties and durability of the mix are not adversely affected by the mix’s self-expanding nature. However, the behaviour of this mix at elevated temperatures is largely unknown, raising legitimate concerns regarding the fire performance of the resulting self-prestressed concrete elements. The research presented in this paper investigates the behaviour of concrete elements manufactured from self-prestressed, self-compacting concrete (SPSCC) when exposed to severe heating – such as would likely be experienced during a building fire. Nine specimens, with dimensions (600 mm × 200 mm × 45 mm) were tested under one-sided exposure to an experimentally simulated ISO 834 standard heating regime. The results showed that the SPSCC samples were acutely prone to explosive spalling under these conditions. The results also suggest that the comparatively higher moisture content of SPSCC samples, as compared with conventional concrete mixes of similar composition and mechanical properties, appeared to be the most critical factor for heat-induced concrete cover spalling. Higher prestress (compressive) forces also appeared to exacerbate the spalling likelihood of SPSCC samples. The addition of 2 kg/m3 of polypropylene (PP) fibres led to the complete elimination of spalling in SPSCC samples. The self-prestress levels in samples with PP fibres were 30 % less than those without PP fibres, for reasons which require additional investigation. Differential thermal expansion between the internal CFRP bars and the concrete was observed to restrain the elongation and thermal curvature of the samples during heating, up until the point where the bars debonded from the surrounding concrete due to elevated temperature and (presumed) increased tensile stress in the tendon anchorage zones. The results provide compelling evidence supporting the need to include PP fibres within high-performance, self-prestressing, self-compacting concrete slabs.

Insights and theoretical model of thermal conductivity of thermally damaged hybrid steel-fine polypropylene fiber-reinforced concrete

The use of hybrid steel-fine polypropylene fiber-reinforced concrete (HFRC) may be an effective strategy for avoiding concrete thermal spalling under fire loading. The thermal conductivity of HFRC is one key parameter for the fire resistance assessing. In this research, the thermal conduction behavior of HFRC is experimentally and numerically studied to obtain a thorough understanding on its thermal degradations and their mechanisms after high-temperature exposure. New mechanisms are discovered to explain the remarkable reduction of thermal conductivity. In addition to the effect of moisture loss and porosity increase, the combined effect of heat bridge and interfacial thermal resistance (ITR) is found to be the dominant mechanisms. Moreover, the evaporation of polypropylene fibers adhering to the coarse aggregates enhances the ITR effect. Based on these mechanisms, a multi-scale homogenization method is also proposed to evaluate the thermal conductivity of thermally damaged HFRC, whose accuracy are demonstrated by the excellent agreements between the experimental data and the numerical results.

Utilizing Advanced Modelling for Fire Damage Assessment of Reinforced Concrete Tunnel Linings

Fire hazards can cause severe and irrecoverable damage to reinforced concrete (RC) tunnel linings. Historically, major fire events have led to months of downtime and millions of dollars of losses owing to repair costs and affected operations. The potential threat to the serviceability of transportation networks emphasizes the need to establish a standardized and effective post-fire damage assessment method to guide repairs and restore functionality. This paper proposes a fire damage assessment framework for RC tunnel linings that integrates advanced modeling with visual inspections, non-destructive testing and material sampling. The framework quantifies fire damage to RC tunnel linings in terms of surface discoloration, crack width, concrete spalling, sectional temperatures, strength loss of materials and residual displacement. A damage classification system is proposed based on a collection of international guidelines and feedback from industry experts to map damage metrics and repair strategies. A case study, using data from recent experiments, is conducted to demonstrate the applicability of the proposed framework and the benefits of the information obtained from numerical modeling. This framework can also be integrated with risk-assessment methods to optimize the fire design of tunnels with associated active and/or passive fire protection.

Fire resistance tests on polypropylene-fiber-reinforced prestressed concrete box bridge girders

This paper presents an experimental study on fire behavior of polypropylene fiber prestressed concrete (PFPC) bridge girders subjected to localized hydrocarbon-fuel fire (mixed diesel oil and natural gas) and applied structural loading. The thermal responses, including temperature inside chamber, temperature within concrete and prestressing strands, were measured and analyzed throughout entire fire exposure duration. Further, structural responses, embracing mid-span deflection, effective prestress, polypropylene (PP) fiber concrete spalling, fire resistance, damage evolution and failure modes, attained from test were investigated in detail. The experimental results show that PP fiber can significantly release pressure of water vapor generated within high-strength concrete used in PFPC bridge girders, thus effectively enhancing spalling resistance of concrete in PFPC girders at elevated temperatures. The diaphragm can keep temperature inside chamber and also within top flange of PFPC box bridge girders steady for a period of time when temperature reaches 100 °C. However, the diaphragm has little effect on structural response of PFPC box bridge girders. The mid-span deflection increases sharply at final stage of fire exposure. Meanwhile, fracture of prestressing strands occurs and the effective prestress decreases suddenly towards final stage of fire exposure. Thereafter, PFPC bridge girders rapidly get to limit state dependent on rate of deflection, thus exhibiting a brittle failure characteristic. This failure of PFPC bridge girders can be prevented using reserved prestressing strands. PFPC bridge girders, designed as per under-reinforced girder at room temperature, vulnerably present failure characteristics of rare-reinforced girder under fuel fire exposure conditions.

Optimizing choice of polypropylene fiber geometry for preventing spalling of high performance concrete due to fire

This article presents a work on optimization of choice of polypropylene fiber dosage and geometry to ensure thermal stability of high performance concrete subjected to fire. Three cementitious materials with different granular skeletons containing polypropylene fibers are studied. Experimental campaign of fire tests is conducted on uniaxially compressed concrete prisms via mobile gas furnace. Then, thermo-mechanical simulations are accomplished to validate experimental findings. Results show that an optimal PP fiber length should be selected in accordance with aggregate size. PP fiber diameter has shown to have no significant influence on spalling prevention.

Mechanistic understanding of precast UHPC segmental beams with external tendons and epoxy joints subject to combined bending and shear

Precast ultra-high-performance concrete (UHPC) segmental bridges (PUSBs) have become a competitive bridge type in modern civil engineering. To establish a thorough mechanistic understanding of PUSBs, seven specimens were fabricated and experimentally investigated. These specimens were designed to have different longitudinal reinforcements, construction methods, joint types, shear span-to-depth ratios (λ), stirrup ratios, and numbers of shear keys. Two failure modes were observed in the tests: flexural failure with crushing of the UHPC at the joints, and shear failure with shear tension sliding and concrete spalling of the web. Additionally, it was found that although the ultimate capacity, stiffness, and cracking load of the segmental beams were slightly lower than those of the monolithic beams, the segmental beams tended to exhibit better ductility and deformation capacity. As λ increased, the ultimate capacity and stiffness of the segmental beams decreased, whereas the growth rates of the deflection and tendon stress increased. Moreover, the stirrups showed a positive effect on the cracking control ability and shear strength of the beams. The three-keyed specimen exhibited better structural behavior than the single-keyed specimen. Finally, calculation methods were proposed to predict the cracking strength and ultimate capacity of PUSBs.

Lightweight semantic segmentation of complex structural damage recognition for actual bridges

Although structural damage recognition has been extensively investigated using deep learning and computer vision (CV) techniques, the following limitations exist for real-world applications: (1) the accuracy heavily relies on a large volume of network parameters; (2) the sensitivity to tiny cracks is limited due to low contrast between microcrack and background pixels; (3) the robustness on complex cracks with various morphological features and surface disturbances is inadequate. To address these issues, this study proposes a lightweight, accurate, and robust semantic segmentation method of complex structural damage recognition for actual bridges. Firstly, a modified DeepLabv3+ model is established using the lightweight MobileNetV2 backbone and transposed convolutions to reduce parameter volume and enhance the recognition capability of local minor damages. Secondly, the depthwise separable convolution is utilized instead of the standard convolution to decouple the spatial and channel interactions of feature maps. Thirdly, a refined atrous spatial pyramid pooling (ASPP) module is constructed at the backbone end using multilevel dilated convolutions to expand the receptive fields. Finally, a piecewise synthetical loss function based on focal and dice losses is designed for different training stages. A total of 3226 actual crack images in different scales, resolutions, and scenes are utilized to verify the proposed method. The results show that the mean intersection-over-union for complex cracks in various real-world scenarios reaches 0.776 with significant reductions of 91.5% in parameter volume and 38.9% in recognition time. Comparative studies demonstrate the superiority of the proposed method over existing lightweight crack segmentation models based on SegNet and DenseNet. In addition, ablation experiments demonstrate the necessity and effectiveness of the MobileNetV2 backbone, refined ASPP module, and piecewise synthetical loss function. Moreover, the robustness and expandability of the proposed method on new structural damage categories (including concrete spalling, rebar exposure, and cable corrosion) are also verified.

Experimental Study on Impact Behavior of Concrete Panel with and without Polypropylene Macrofibers

Macrofibers have often been used to increase the tensile strength, durability, crack resistance, spalling, impact resistance, and toughness of concrete. However, the impact behavior of fiber-reinforced concrete (FRC) structures is quite different from their static behavior, and the effectiveness of macrofibers in improving impact resistance should be carefully evaluated. In this study, the impact behavior of FRC with polypropylene (PP) macrofibers was studied through a series of drop-weight impact tests. First, the material characteristics of the FRC with PP fibers under static conditions were evaluated. Test specimens were constructed and drop-weight impact tests were performed. The main parameters were the presence or absence of PP fibers and the drop height, which is related to the magnitude of the impact energy. From the results, it can be found that the crack width of the FRC specimen was smaller than the normal concrete specimen for a similar residual deflection after the impact test due to the bridging effect of the macrofibers. However, the effect of PP fibers on the impact resistance was not significant, even though there was a considerable increase in tensile and flexural performance under static conditions, since the hardening effect after the sharp reduction in strength shown in the static test of FRC is not effective in the impact test.

Axial compressive behavior of mega steel-reinforced high-strength concrete columns with different steel sections

Steel-reinforced concrete columns are the crucial vertical load-bearing members in the frame composite structures. Previous studies on steel-reinforced concrete columns primarily focus on simple H-shaped and cruciform steel sections; insufficient attention is paid to mega columns, which are frequently designed with complex steel sections and high-strength concrete. In this study, four scaled mega columns, including two open-shaped and two multicell-shaped steel-reinforced high-strength concrete columns with cross-sectional dimensions of 700 × 700 mm and different concrete strengths, were subjected to one-way repeated compression tests. The aforementioned tests were conducted to examine the damage evolution, load-axial deformation response, bearing capacity, strain development, stiffness degradation, ductility, and restoration capacity of the columns. The test results indicate that the multicell steel section effectively alleviates crack widening and concrete spalling, and improves the post-peak stiffness and ductility. With increasing concrete strength, the peak load, initial stiffness, and restoration capacity are improved, while the ductility is impaired, and more abrupt damage is recorded. Three existing codes were examined to calculate the bearing capacity with a conservative estimation, particularly the ACI 318-11, with a mean predicted result to test result ratio of 0.76. Hence, an analytical model considering the confinement provided by stirrups and steel sections was proposed to predict the load-axial displacement curve with desirable accuracy. Furthermore, a finite element model based on the division of different confined concrete was established to further explore the damage evolution and to conduct a parametric study.

High-resolution concrete damage image synthesis using conditional generative adversarial network

Concrete damage images are essential for training deep learning-based damage detection networks. Considering the manual collection of concrete damage images is time-consuming and labor-intensive, this study proposes a synthesis method for high-resolution concrete damage images using a conditional generative adversarial network (CGAN). To this end, pix2pix, CycleGAN, OASIS, and pix2pixHD with various hyperparameters were trained and tested on 500 concrete crack and spalling images. The test results show that the trained pix2pixHD with λpix2pixHD = 15 is the best CGAN for concrete damage image synthesis. Concrete damage images were synthesized by the best CGAN according to hand-painted damage maps and used to train deep learning networks. The results show that the synthesized images have excellent authenticity and can be used to train and test deep learning-based concrete damage detection networks. The proposed method can be enhanced by adding damage images to the existing database or employing a better CGAN generator.

Flexural test for steel-concrete composite walls (aspect ratio 2.0) with steel U-Section boundary element

For high structural performance and constructability, a steel–concrete composite wall with boundary elements of steel U-section was developed. In the present study, cyclic lateral loading tests were performed to investigate the flexural performance of the proposed walls. Test parameters were the type of boundary element, area of steel U-section, and type of web reinforcement. The boundary steel U-section not only provided high flexural strength, but also provided lateral confinement to the boundary concrete and restrained shear sliding of the web concrete. Thus, the flexural strength, deformation capacity, and energy dissipation were significantly greater than those of the counterpart RC wall with conventional boundary reinforcement. Such advantages were pronounced when steel U-section with larger area was used. Further, the use of steel plate beams restrained diagonal cracking and spalling of the web concrete, thus improving the deformation capacity. As strain hardening stress after yielding was developed in the boundary steel section, the strength of the test specimens exceeded the nominal flexural strength based on plastic stress distribution.

Avaliação de danos e inovação de solução eficiente de reabilitação de lajes de concreto armado expostas a explosão de contato

abstract: Under contact explosions, the reinforced concrete structures can behave in a brittle manner with highly localized damage like concrete cratering, spalling, and reinforcement rupturing. High-speed fragmentation resulting from concrete spall may cause severe casualties and injuries. It is therefore important to restrained concrete fragments and improve collapse resistance of the slab. A new retrofitting technique is proposed in this paper which completely prevents fragmentation. To mitigate blast effects on civil structures, a new kind of concrete material named Ultra-High-Performance-Concrete (UHPC) is now widely studied and applied. UHPC material is known for its high compressive and tensile strength, large energy absorption capacity as well as good workability and anti-abrasion ability compared to normal strength concrete(NRC). All of recent experimental published work concerning blast performance of UHPC slabs under far or near explosion effect, on the other side, the contact explosion tests are relatively limited experimentally and nearly impossible because of security restrictions and costly in terms of both preparation and measurements. So, the real and accurate finite element models are needed to address this gap and understanding the real contact-explosion behavior of both NRC and UHPC slabs. The numerical analyses allow gaining insight into the complex failure mechanisms occurring in the slab and not directly observable. In this study, coupled smoothed particle hydrodynamics (SPH) method and finite element method is utilized to simulate the contact blast tests. Numerical results are compared with the experimental observations, and the feasibility and accuracy of the numerical model are validated. The validated numerical model provided a useful tool for designing potential blast-retrofitting solutions which can prevent the local material damage and fragmentations in both NRC & UHPC slabs subjected to contact explosion. This study introduced adequate and very efficient protection solution for both NRC & UHPC slabs exposed to contact explosion (1 kg of TNT) by utilizing the composite action generated between slabs & bonded steel plates. The 2 mm and 1 mm bonded steel plates at both faces of the NRC and UHPC slabs respectively attained a superior resistance to contact explosion.

Finite element analysis of bond behavior in corroded reinforced concrete beams: State-of-the-art

The article conducts a comprehensive examination of various aspects related to rebar corrosion, encompassing the corrosion mechanism, its implications on design criteria, the modeling of bond interfaces under both corroded and non-corroded conditions, and the modeling of reinforced concrete (RC) beams affected by corrosion, employing both empirical and analytical methodologies. The initial stages of corrosion instigate a gradual transformation of rebar into rust. One notable consequence of reinforcement corrosion is the generation of expansive pressure, leading to concrete cracking, spalling, and detachment of the concrete cover. Additionally, it diminishes the effective cross sectional area of the rebar, ultimately resulting in a decline in the concrete's bond strength and gradual structural deterioration. Ultimately, continuous corrosion can lead to a complete loss of bond between the concrete and rebar, representing the most severe form of damage attributable to corrosion. This poses a critical threat, particularly in cases where the beam functions as an unreinforced structure, potentially culminating in sudden structural failure. This paper primarily underscores the utilization of the Finite Element Method (FEM) for evaluating the impact of bond deterioration between concrete and reinforcement caused by corrosion. The paper effectively employs this technique to predict and analyze the structural damage in corroded RC beam specimens.

Synergies between Heat- and Stress-Induced Spalling Theory Applied to Rock and Concrete in Tunnel Applications

Fire-induced and stress-driven catastrophic failures in rock and concrete are commonly known as spalling (or rockburst in its severe form) that have jeopardised the safety of personnel, seriously damaged rock structures, and shut down operations for months or even permanently in certain circumstances. Particularly in Australia, spalling and rockburst in deep excavations results in a heavy toll on mine safety and have become a constraint to the economic viability of several Australian deep mines since the early 1950s. The prevailing industry approach is to treat such unwanted failures and associated microseismic events as a result of insufficient energy absorption by the spalling-prone rock/concrete at the post-peak stage. However, this approach does not allow efficient handling of heat- or stress-induced failures as it requires an in-depth understanding of their mechanics. Prediction of these events based on the available failure criteria does not help either due to the numerous criteria involved and the difficulty in determining their parameters at the excavation scale. A proper understanding of the fracture growth in such failures is needed to understand the behaviour of rock or concrete structures resulting in a sudden release of energy at deep excavations. This paper investigates the similarities and differences between heat-induced concrete spalling and stress-driven rockburst and further examines the effect(s) of material, geometrical, geological properties, and the applied deviatoric stresses on these failure modes.

Experimental research on fire resistance of the reduced scale immersed tunnel with fire in both traffic tubes

In order to investigate the fire performance of concrete immersed tunnels, a large-scale model of an immersed tunnel was constructed, loading devices and two fire test furnaces were built at the same time. The fire test considered an extreme fire condition. Without fire protection, the fire test was carried out in both tubes of the tunnel at the same time. In the tunnel, the maximum temperature of fire exceeded 1300 °C. Under the service load, the tunnel was heated by fire for 245 min, and then the tunnel was cooled by ventilation for 360 min. During the fire test, the temperatures, deformations, cracking, spalling, and other behaviors of the tunnel were recorded. The test data provided the record of the structural damage and structural deformations of the tunnel under fire. The concrete spalling of the tunnel under fire was almost 100 %, and the maximum depth of the concrete spalling reached 142.2 mm. The inner rebars of the tunnel were exposed to fire, and some rebars melted. The mid wall suffered the severest damage, and it was the most dangerous of the tunnel under fire. However, the deformation of the tunnel was mainly caused by the axial deformation of each component, and it was very small. The test results showed that the bearing capacity of the tunnel under fire was sufficient, but the concrete cracking of the tunnel was very severe. During the fire test, affected by the thermal expansion and contraction of concrete, the unheated side and heated side of the tunnel alternately cracked, and the crack positions overlapped, which might cause through cracks inside the tunnel. In the case of sufficient bearing capacity of immersed tunnels under fire, concrete cracking can still cause disaster or reduce the durability of immersed tunnels. In the fire resistance design of immersed tunnels, measures should be taken to restrain the concrete cracking and improve the flexural bearing capacity of the mid wall under fire.

Analysis and prediction methods for the static properties of reinforced concrete beams under fire

In order to study the thermal properties and static performance of reinforced concrete (RC) beams exposed to fire and reveal the relationship between fire exposure time, concrete spalling, bond slip and mechanical properties, the numerical simulation, theoretical analysis and machine learning methods were adopted to study the effects of high temperature on thermal and static mechanical properties of RC beams and the prediction methods of residual bearing capacity were proposed in this paper. Fire tests and static load tests after natural cooling were carried out on 4 RC simply supported beams. The refined numerical analysis model of RC beam was established and its validity was verified by the fire test. The effects of fire exposure time and characteristic parameters of concrete spalling on temperature fields and interfacial bond properties were simulated and analyzed. The residual flexural capacity were calculated and compared with measured and simplified theoretical values. Finally fire exposure time, concrete spalling depth and local spalling area ratio were selected as variables to design 250 groups of sample data, and sample database was established based on the refined numerical analysis model. Several methods for predicting residual flexural capacity after fire were proposed. Their accuracy and reliability were compared and analyzed, which can provide a method reference for safety estimation and analysis of post-disaster engineering.

Convolutional neural networks (CNNs)-based multi-category damage detection and recognition of high-speed rail (HSR) reinforced concrete (RC) bridges using test images

The fast networking of high-speed rail (HSR) may cause in-service fatigue and ultimate load damage to bridges. This paper investigates the application of deep convolutional neural networks (CNNs) for multi-category damage image classification recognition of HSR-reinforced concrete (RC) bridges. The present study establishes a deep learning (DL) system based on a large amount of HSR bridge test data. When to begin, the damage done to HSR bridge piers may be broken down into three primary categories: concrete cracks, concrete spalling, and reinforcement exposure. These categories are determined by the statistics of HSR bridge pier testing. Secondly, in order to develop an automated recognition model for the damage of HSR piers, AlexNet CNNs were taught a transfer learning approach and then used to train themselves. The correct recognition rate of the three damaged pictures in the actual application of the model is 86% for cracks, 82% for reinforcement exposure, and 70% for concrete spalling, all of which have good recognition rates. The study's accuracy and precision enhance detection efficiency and may be utilized to identify HSR pier deterioration quickly. The research comprises a random selection from the training and validation sets. It also assesses the training model's generalization to out-of-sample pictures for engineering applications. This aspect of the work sets it apart from previous research in the same study area.

Seismic performance of earthquake-damaged corroded reinforced concrete beam-column joints retrofitted with basalt fiber-reinforced polymer sheets

This present research conducted an experimental study on the influence of different earthquake damages on the seismic performances of aged reinforced concrete (RC) beam-column joints retrofitted with basalt fiber-reinforced polymer (BFRP) sheets under cyclic loadings. Six beam-column joints included one benchmark specimen, one uncorroded specimen retrofitted with BFRP sheets, and four earthquake-damaged corroded specimens with the corrosion rates of 0% and 9% retrofitted with BFRP sheets. Test results demonstrated that the seismic performances of earthquake-damaged corroded specimens effectually improved after retrofitting with BFRP sheets, and the retrofitting effectiveness was significantly affected by the earthquake-damaged levels. The bucking of stirrups, spalling and crushing of concrete of retrofitted specimens were effectually postponed, while the ductility of corroded and uncorroded specimens under the earthquake damages increased after retrofitting with BFRP sheets. The total cumulative energy dissipation and final stiffness of retrofitted specimens considerably improved with the maximum increase of 22.3% and 14.3% comparing to those of benchmark specimen, respectively. Besides, the models for predicting the shear strength of RC beam-column joint cores considering the influences of earthquake damage, reinforcement corrosion, and FRP retrofitting were proposed.

Performance Comparison of Multiple Convolutional Neural Networks for Concrete Defects Classification.

Periodical vision-based inspection is a principal form of structural health monitoring (SHM) technique. Over the last decades, vision-based artificial intelligence (AI) has successfully facilitated an effortless inspection system owing to its exceptional ability of accuracy of defects' pattern recognition. However, most deep learning (DL)-based methods detect one specific type of defect, whereas DL has a high proficiency in multiple object detection. This study developed a dataset of two types of defects, i.e., concrete crack and spalling, and applied various pre-built convolutional neural network (CNN) models, i.e., VGG-19, ResNet-50, InceptionV3, Xception, and MobileNetV2 to classify these concrete defects. The dataset developed for this study has one of the largest collections of original images of concrete crack and spalling and avoided the augmentation process to replicate a more real-world condition, which makes the dataset one of a kind. Moreover, a detailed sensitivity analysis of hyper-parameters (i.e., optimizers, learning rate) was conducted to compare the classification models' performance and identify the optimal image classification condition for the best-performed CNN model. After analyzing all the models, InceptionV3 outperformed all the other models with an accuracy of 91%, precision of 83%, and recall of 100%. The InceptionV3 model performed best with optimizer stochastic gradient descent (SGD) and a learning rate of 0.001.

Study on Mechanical Properties and Constitutive Relationship of Concrete Corroded by Hydrochloric Acid under Cyclic Load

Most of the existing studies on acid corrosion of concrete have focused on the mechanical behavior of concrete structures under monotonic load or without load. To investigate the mechanical properties of in-service concrete components under cyclic load in an acid corrosion environment, six groups of concrete prism specimens with different acid corrosion degrees (corrosion duration) were designed and prepared by the accelerated corrosion test method. The monotonic and cyclic axial compression load tests on these specimens were conducted to investigate the effects of corrosion degree on the mechanical properties of concrete specimens. The experimental results indicated that hydrochloric acid corrosion has obvious effects on the failure characteristics and mechanical properties of concrete. The surface of corroded concrete was easier to crack and spall under load, and the concrete spalling area enlarged as the acid corrosion duration increased. The compressive capacity of concrete specimens reduced rapidly with the increase in corrosion duration. The stress–strain envelope curves for concrete with different corrosion duration under cyclic load were essentially similar to that of concrete under monotonic load. The degradation rate of the descending section for the stress–strain curves of corroded concrete under cyclic load was much larger than that under the monotonic load due to the accumulation of internal damage in concrete. The peak strain and ultimate strain of corroded concrete increased significantly with the increase in corrosion duration and enhanced by 55.7% and 77.9%, respectively, compared with the uncorroded concrete, whereas the peak stress and elastic modulus rapidly decreased and reduced by 53.3% and 74.1%, respectively. Moreover, based on the strength degradation depth, the concept of effective bearing cross-sectional area ratio was proposed to characterize the corrosion degree of concrete, and the correction coefficient of descending section for the effective bearing cross-sectional area ratio was introduced to establish the constitutive model of corroded concrete under cyclic load, and the results calculated by this model matched well with the experimental values. The research in this paper can provide the experimental and theoretical basis for seismic life cycle and fatigue redesign of concrete structures in acid corrosion environments or coastal areas.