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Nonlinear numerical simulation of bond performance between recycled concrete and corroded steel bars

  • Zhenfang Li , Dong Gao , Chuanji Wu , Guoqing Lv , Xin Liu , Haoran Zhai EMAIL logo and Zhanfang Huang EMAIL logo
Published/Copyright: April 4, 2023
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Abstract

In this article, the bond performance between recycled concrete and corroded steel bars is analyzed by the nonlinear numerical simulation. The result shows that the maximum bond strength between recycled concrete and steel bar decreases with the increase in steel bar corrosion rate; when the recycled concrete strength is large, the simulated maximum bond strength is in good agreement with the experimental maximum bond strength; when the recycled concrete strength is small, the simulated maximum bond strength is in relatively poor agreement with the experimental maximum bond strength, but there is still an error within the allowable range; the slip between recycled concrete and steel bar increases with the increase in steel bar corrosion rate; when the steel bar corrosion rate exceeded 5%, the bond strength decreases more rapidly; the maximum bond strength increases with the increase in specimen sizes under the same steel bar corrosion rate; the maximum bond strength decreases with the increase in steel bar diameter under the same steel bar corrosion rate.

1 Introduction

Recycled concrete technology is the application of recycled aggregate produced by crushing waste concrete to concrete [1]. Recycled concrete can not only effectively protect natural aggregate resources [2], but also effectively improve the environmental problems caused by construction waste emissions [3]. If recycled concrete technology is widely used in practical engineering, the performance of recycled concrete needs to meet the engineering technical requirements [4]. The bond performance of concrete and steel bars is the basis to ensure the cooperative stress of the two materials [5], and the good bond performance is the key to ensuring the normal work of concrete structures [6]. Therefore, the bond performance between recycled concrete and reinforcement has gradually attracted the attention of scholars [7].

In practical engineering, improper construction and durability degradation make steel bar corrosion become one of the important reasons for the destruction of concrete structures [8]. Steel bar corrosion in concrete leads to the deterioration of mechanical properties of steel bar and expansion of concrete cover [9]. In addition, the steel bar corrosion will also lead to the degradation of the bond performance between concrete and steel bar [10]. The volume expansion of the corrosion products of steel bars will destroy the surrounding recycled concrete and weaken the protection of concrete to steel bars, thereby accelerating the corrosion of steel bars [11]. It can be seen that steel corrosion seriously threatens the safety of concrete structures [12]. Therefore, it is of great significance to study the bond performance between recycled concrete and corroded steel bar for the wide application of recycled concrete technology [13].

When the steel bar corrosion rate was low, the bond performance between concrete and steel bars would not decrease [14] and even increase slightly [15]. This was because when the steel bar corrosion rate was small, the micro-corrosion products were generated and filled with the pores of the bond interface between recycled concrete and steel bar, and the corrosion products increased the surface roughness of the steel bar, thereby increasing the friction between the steel bar and the recycled concrete [16]. Due to the volume expansion of corrosion products, the expansion force squeezed the surrounding core confined concrete, resulting in an increase in the bond force of concrete to the steel bar, which directly led to an increase in the bond strength [17]. When the steel bar corrosion rate was large, the bond performance between concrete and steel bar gradually deteriorated, and the bond strength between steel bar and concrete decreased [18]. Factors such as steel bar corrosion rate [19], recycled aggregate replacement rate [16], water–cement ratio, steel diameter, and relative protective layer thickness [20] have different degrees of influence on the bond performance between recycled concrete and corroded steel bars. In addition, scholars have established the bond-slip constitutive model of recycled concrete and corroded steel bar based on experiments [21]. Combining the experimental method with the numerical simulation method, the bond performance of recycled concrete and corroded steel bars can be investigated more deeply, so as to obtain more valuable data.

The numerical simulation method can save time and resources, and at the same time, it can also achieve an effect similar to experimental research [22]. Scholars have investigated the corroded reinforced concrete flexural members [23], the bearing capacity of corroded reinforced concrete members [24], and the failure mode of reinforced concrete beams with different corrosion rates by the finite element analysis method [25]. Zhang [26] also proposed a simulation method using a temperature expansion ring instead of corrosion products. The volume expansion of corrosion products was simulated by temperature expansion, and the nonuniform corrosion of steel bar in concrete was simulated by changing the shape of expansion ring. Wu et al. [27] and Kang [28] investigated the bond performance of concrete and steel bar using the finite element analysis software ANSYS and the finite element analysis software FEAPpv, which could better simulate the bond performance of steel bar and concrete. The contact surface model introduced by Mou et al. [29] could better simulate the bond-slip between steel bars and concrete. Sun [30] analyzed the influence of protective layer and stirrup spacing on the bond performance by the finite element software ABAQUS. Chen [31] and Xu [32] used the finite element software ANSYS to simulate the influence of steel corrosion on the bond performance between steel bar and concrete, and verified the rationality of the finite element simulation by comparing with the experimental results. However, there are relatively few numerical analyses on the bond performance between recycled concrete and corroded steel bar. In this article, the bond performance of recycled concrete and corroded steel bar was analyzed by the finite element software ABAQUS and compared with the experimental results. The influence of steel bar corrosion rate, specimen size, and steel bar diameter on the bond strength between recycled concrete and corroded steel bar was considered, which could provide a theoretical basis for bond performance analysis of recycled concrete and steel bar. The model established in this article considers the influence of steel bar diameter, concrete strength, steel bar corrosion rate, and specimen size on the bond strength between recycled concrete and corroded steel bar more comprehensively. The bond strength between recycled concrete and steel bar under various working conditions can be calculated, which provides convenience for engineers in practical engineering.

2 Establishment of the finite element model

2.1 Element types

SOLID elements are used for both concrete and steel bars. SOLID element is suitable for nonuniform material elements. The eight nodes of the element have three translational degrees of freedom, which can consider the nonlinear properties of materials [33]. The separate model was used in the bonding interface between steel bar and concrete, that is, setting bond unit at the interface.

2.2 Modeling

2.2.1 Concrete model

The cube compressive strength ( f cu ) of the recycled concrete can be obtained from the experimental data in the literature [16], and the elastic modulus, the uniaxial compressive strength, and the uniaxial tensile strength can be calculated [34] as follows:

Uniaxial compressive strength:

(1) f c = 0.76 f cu .

Uniaxial tensile strength:

(2) f sp = 0.24 f cu 0.65 .

Elastic modulus:

(3) E c = 10 5 2.8 + 40.1 / f cu .

The recycled concrete parameters are shown in Table 1.

Table 1

Performance parameters of recycled concrete

Cube compressive strength/MPa Uniaxial compressive strength/MPa Uniaxial tensile strength/MPa Elastic modulus/GPa
52.6 39.98 3.15 28.07
32.0 24.32 2.28 24.67

The damage plasticity model in the ABAQUS analysis software is used to define the inelastic behavior of concrete. The constitutive equation of dimensionless isotropic material is as follows [35]:

(4) σ = ( 1 d ) D 0 el : ( ε ε pl ) = D el : ( ε ε pl ) ,

where σ is the stress tensor; d is the damage factor, dimensionless stiffness degradation variable; ε is the strain tensor; D 0 el is the initial (undamaged) material elastic stiffness; and ( 1 d ) D 0 el is the elastic stiffness after damage.

The damage states under tension and compression are characterized by two sets of independent hardening constants ε ¯ c pl ε ¯ t pl , which relate to the equivalent plastic strain under tension and compression, respectively. The tensile hardening and compressive hardening can be further written as:

(5) ε ¯ pl = ε ¯ c pl ε ¯ t pl ,

(6) ε ¯ pl = h ( σ ¯ , ε ¯ t pl ) ε pl .

2.2.2 Rebar model

The HRB335 steel bar with a diameter of 20 mm was used as the pull-out steel bar, the yield strength of the steel bar was 358.3 MPa, the ultimate strength was 539.8 MPa, the elastic modulus was 200 GPa, and the Poisson’s ratio was 0.3.

Assuming that the steel bar was corroded uniformly, the cross-sectional area of the steel bar before and after corrosion was unchanged, and the yield strength of the steel bar was replaced by the nominal yield strength, the relationship between the corrosion rate of the steel bar ( ρ ) and the material parameters was as follows [36]:

Yield strength:

(7) f y = ( 1 0.029 ρ ) f y , 0 % < ρ 5 % ,

(8) f y = ( 1.175 0.064 ρ ) f y , ρ > 5 % .

Elastic modulus:

(9) E = ( 1 0.052 ρ ) E , 0 % < ρ 5 % ,

(10) E = ( 0.895 0.031 ρ ) E , ρ > 5 % .

2.2.3 Model assembly and model loading

The recycled concrete model and the steel bar model were established according to the pull-out specimen in the literature [16], as shown in Figures 1 and 2, and then, the recycled concrete model and the steel bar model were assembled, as shown in Figure 3. The meshed finite element model of the recycled concrete specimen is shown in Figure 4. A three-dimensional two-node translator connector element was used to simulate the bond-slip of steel bar and recycled concrete, and the translator connector element was set as nonlinear. To be closer to the test loading state, the displacement-controlled loading method was selected, and the boundary conditions at the loading end of the specimen are set to be completely fixed during the simulation.

Figure 1 
                     Recycled concrete model.
Figure 1

Recycled concrete model.

Figure 2 
                     Steel bar model.
Figure 2

Steel bar model.

Figure 3 
                     Recycled concrete specimen model.
Figure 3

Recycled concrete specimen model.

Figure 4 
                     Finite element model meshing.
Figure 4

Finite element model meshing.

3 Results and discussion

3.1 Comparison of simulation bond strength and experiment bond strength

The simulation maximum bond strength of recycled concrete specimens under different steel corrosion rates is shown in Figure 5. It can be found that the maximum bond strength of recycled concrete specimens decreased with the increase in steel bar corrosion rate. The maximum bond strength of recycled concrete specimens with 52.6 MPa was higher than that of recycled concrete specimens with 32.0 MPa under the same steel bar corrosion rate.

Figure 5 
                  Bond strength and steel bar corrosion rate.
Figure 5

Bond strength and steel bar corrosion rate.

Comparison of simulation maximum bond strength and experiment maximum bond strength in the literature [16] is shown in Table 2. It can be found that for the recycled concrete specimens with 52.6 MPa, the mean value of the ratio of the simulation maximum bond strength and experiment maximum bond strength is 1.116, and the standard deviation is 0.020; for the recycled concrete specimens with 32.0 MPa, the mean value of the ratio of the simulation maximum bond strength and experiment maximum bond strength is 1.239, and the standard deviation is 0.167. The simulation maximum bond strength is in good agreement with the experiment maximum bond strength when the recycled concrete strength is 52.6 MPa.

Table 2

Comparison of simulation bond strength ( τ ) and experiment bond strength ( τ )

Concrete strength/MPa Corrosion rate/% τ /MPa τ /MPa
52.6 0 14.30 15.79
52.6 0.5 12.22 13.67
52.6 1.5 9.87 10.81
52.6 2.5 7.63 8.75
32.0 0 11.61 12.13
32.0 0.5 5.75 8.26
32.0 1.5 5.02 6.87
32.0 2.5 4.49 4.97

The finite element model was adjusted according to the parameters in the literature [37], and the simulation results are compared with the test results, as shown in Table 3. It can be found that the mean value of the ratio of the simulation maximum bond strength and experiment maximum bond strength is 1.299.

Table 3

Comparison of simulation bond strength ( τ ) and experiment bond strength ( τ ) in the literature [37]

Concrete strength/MPa Corrosion rate/% τ /MPa τ /MPa
36.0 0.52 11.29 12.67
36.0 1.07 5.65 8.32
36.0 2.26 3.35 5.04
36.0 3.47 2.61 2.87

3.2 Comparison of simulation slip and experiment slip

The simulation slip corresponding to the maximum bond strength of recycled concrete specimens under different steel bar corrosion rates is shown in Figure 6. It can be found that the slip of recycled concrete specimens increased with the increase in steel bar corrosion rate. The slip of recycled concrete specimens with 52.6 MPa was lower than that of recycled concrete specimens with 32.0 MPa under the same steel bar corrosion rate.

Figure 6 
                  Slip and steel bar corrosion rate.
Figure 6

Slip and steel bar corrosion rate.

Comparison of simulation slip and experiment slip in the literature [16] is shown in Table 4. It can be found that the mean value of the ratio of the simulation maximum bond strength and experiment maximum bond strength is 0.739 when the recycled concrete strength is 52.6 MPa, while that is 0.953 when the recycled concrete strength is 32.0 MPa. The simulation slip is in poor agreement with the experimental slip. In summary, the numerical calculation method can better predict the bond strength between recycled concrete and reinforcement after steel bar corrosion, but the prediction effect on the bond-slip is poor.

Table 4

Comparison of simulation slip (S) and experiment slip ( S )

Concrete strength/MPa Corrosion rate/% S/mm S /mm
52.6 0 0.0429 0.0275
52.6 0.5 0.1525 0.1012
52.6 1.5 0.1575 0.1172
52.6 2.5 0.1600 0.1452
32.0 0 0.0677 0.0412
32.0 0.5 0.2528 0.1547
32.0 1.5 0.2272 0.1865
32.0 2.5 0.1107 0.1958

3.3 Bond strength prediction of specimens with different steel bar corrosion rates

Table 5 shows the simulation maximum bond strength of recycled concrete specimens when the steel corrosion rates are 3.0, 3.5, and 4.0%, respectively. The maximum bond strength of recycled concrete specimens under different steel corrosion rates is shown in Figure 6. It can be found that the maximum bond strength of recycled concrete specimens decreased with the increase in steel bar corrosion rate. When the steel bar corrosion rate exceeded 5%, the bond strength decreased more rapidly. The relationship between the corrosion rate of steel bars and the maximum bond strength is obtained by data fitting (as shown in Figure 7).

(11) σ = 2.0694 ρ + 14.637 .

Table 5

Simulation maximum bond strength after steel bar corrosion

Concrete strength/MPa Corrosion rate/% τ /MPa
52.6 3.0 7.95
52.6 3.5 7.31
52.6 4.0 6.18
52.6 5.5 4.22
Figure 7 
                  Relationship between bond strength and steel corrosion rate.
Figure 7

Relationship between bond strength and steel corrosion rate.

3.4 Bond strength prediction of specimens with different sizes

Table 6 shows the simulation maximum bond strength of recycled concrete specimens of different sizes. The maximum bond strength increased with the increase in specimen sizes under the same steel bar corrosion rate. The reason for this is that as the size of the specimen increases, the concrete cover thickness increases, and the restraint forces on the steel bar increase, thereby increasing the bond strength of the specimen.

Table 6

Maximum bond strength of specimens with different sizes after steel bar corrosion

Sizes/mm Concrete strength/MPa Corrosion rate/% τ /MPa
100 × 100 × 100 52.6 3.0 7.61
150 × 150 × 150 52.6 3.0 7.95
200 × 200 × 200 52.6 3.0 8.18
100 × 100 × 150 52.6 5.5 4.02
150 × 150 × 150 52.6 5.5 4.13
200 × 200 × 200 52.6 5.5 4.87

3.5 Bond strength prediction of specimens with different steel bar diameter

Table 7 shows the simulation maximum bond strength of recycled concrete specimens of different steel bar diameters. The maximum bond strength decreased with the increase in steel bar diameter under the same steel bar corrosion rate. The reason for this is that as the steel bar diameter increases, the number of steel ribs decreases within the same length of the steel bar, resulting in a decrease in the mechanical bite force between the steel bar and the concrete, which leads to a decrease in the bond strength.

Table 7

Maximum bond strength of specimens with steel bar diameter

Steel bar diameter/mm Concrete strength/MPa Corrosion rate/% τ /MPa
16 52.6 3.0 8.18
18 52.6 3.0 8.11
20 52.6 3.0 7.95
22 52.6 3.0 7.84
16 32.0 3.0 5.21
18 32.0 3.0 5.11
20 32.0 3.0 4.97
22 32.0 3.0 4.87

4 Conclusions

  1. The maximum bond strength of recycled concrete specimens decreased with the increase in steel bar corrosion rate.

  2. The simulation maximum bond strength is in good agreement with the experiment maximum bond strength when the recycled concrete strength is 52.6 MPa.

  3. The slip of recycled concrete specimens increased with the increase in steel bar corrosion rate.

  4. When the steel bar corrosion rate exceeded 5%, the bond strength decreased more rapidly.

  5. The maximum bond strength increased with the increase in specimen sizes under the same steel bar corrosion rate.

  6. The maximum bond strength decreased with the increase in steel bar diameter under the same steel bar corrosion rate.

  1. Funding information: This study was funded by the Science and Technology Research and Development Fund of Shandong Hi-speed Group (2022-CXFZJT-CPYF-002).

  2. Author contributions: Zhenfang Li: investigation, Project Manager; Dong Gao: check original draft; Chuanji Wu: writing; Chuanji Wu: investigation; Guoqing Lv: visualization; Xin Liu: check original draft; Haoran Zhai: writing – review and editing; Zhanfang Huang: finite element analysis, writing – review and editing.

  3. Conflict of interest: The authors state no conflict of interest.

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Received: 2022-06-28
Revised: 2022-11-01
Accepted: 2023-01-02
Published Online: 2023-04-04

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  71. A versatile dynamic noise control framework based on computer simulation and modeling
  72. A novel hybrid ensemble convolutional neural network for face recognition by optimizing hyperparameters
  73. Numerical analysis of uneven settlement of highway subgrade based on nonlinear algorithm
  74. Experimental design and data analysis and optimization of mechanical condition diagnosis for transformer sets
  75. Special Issue: Reliable and Robust Fuzzy Logic Control System for Industry 4.0
  76. Framework for identifying network attacks through packet inspection using machine learning
  77. Convolutional neural network for UAV image processing and navigation in tree plantations based on deep learning
  78. Analysis of multimedia technology and mobile learning in English teaching in colleges and universities
  79. A deep learning-based mathematical modeling strategy for classifying musical genres in musical industry
  80. An effective framework to improve the managerial activities in global software development
  81. Simulation of three-dimensional temperature field in high-frequency welding based on nonlinear finite element method
  82. Multi-objective optimization model of transmission error of nonlinear dynamic load of double helical gears
  83. Fault diagnosis of electrical equipment based on virtual simulation technology
  84. Application of fractional-order nonlinear equations in coordinated control of multi-agent systems
  85. Research on railroad locomotive driving safety assistance technology based on electromechanical coupling analysis
  86. Risk assessment of computer network information using a proposed approach: Fuzzy hierarchical reasoning model based on scientific inversion parallel programming
  87. Special Issue: Dynamic Engineering and Control Methods for the Nonlinear Systems - Part I
  88. The application of iterative hard threshold algorithm based on nonlinear optimal compression sensing and electronic information technology in the field of automatic control
  89. Equilibrium stability of dynamic duopoly Cournot game under heterogeneous strategies, asymmetric information, and one-way R&D spillovers
  90. Mathematical prediction model construction of network packet loss rate and nonlinear mapping user experience under the Internet of Things
  91. Target recognition and detection system based on sensor and nonlinear machine vision fusion
  92. Risk analysis of bridge ship collision based on AIS data model and nonlinear finite element
  93. Video face target detection and tracking algorithm based on nonlinear sequence Monte Carlo filtering technique
  94. Adaptive fuzzy extended state observer for a class of nonlinear systems with output constraint
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