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Bond behavior of recycled coarse aggregate concrete with rebar after freeze–thaw cycles: Finite element nonlinear analysis

  • Wei Su , Huibin Sun , Yiyun Wang and Tian Su EMAIL logo
Published/Copyright: July 14, 2022
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Nonlinear Engineering
From the journal Nonlinear Engineering Volume 11 Issue 1

Abstract

In this article, the bond performance of recycled coarse aggregate concrete with rebar after freeze–thaw cycles is analyzed by the ABAQUS finite element method. The result shows that the finite element simulation value of the ultimate bond strength of recycled aggregate concrete specimens is in good agreement with the experimental value, while the agreement between the finite element simulation value of the peak bond slip of recycled aggregate concrete specimens and the experimental value is low; the bond strength between rebar and recycled aggregate concrete increased with the increase of concrete strength and concrete cover depth; the calculation formula for the bond strength between recycled aggregate concrete specimens with different concrete strengths and different concrete cover depth after freeze and thaw cycles are obtained.

Keywords: recycled concrete; finite element; freeze–thaw cycles; concrete cover depth; concrete strength

1 Introduction

Concrete has become the preferred material for modern engineering structures due to the good working performance, and the bond performance between concrete and rebar is the basis for the two materials to work together [1]. Freeze–thaw damage is one of the important reasons for the degradation of frost resistance and mechanical properties of concrete [2]. The mechanical properties of concrete will also change after freeze–thaw cycles, thus affecting the bond performance between concrete and rebar [3]. The bond performance between concrete and rebar deteriorated after freeze–thaw cycles [4], and the maximum bond strength between concrete and rebar decreased gradually with the increase of the number of freeze–thaw cycles [5], while the slip corresponding to the maximum bond strength increased [6].

In recent years, the rapid development of the construction industry has resulted in a large amount of waste concrete [7]. Waste concrete not only occupies land resources but also pollutes the environment [8]. With the enhancement of people’s environmental awareness, the impact of waste concrete on the environment has attracted more and more attention [9]. At the same time, the natural aggregates required to prepare concrete are decreasing [10]. Therefore, it is necessary to find a new production method to solve the current problems in the construction industry [11]. Recycled aggregate concrete is a new type of concrete that is mixed with waste concrete after crushing, cement, sand, water and admixtures [12]. Recycled concrete technology can not only solve the problem of resource shortage but also realize the sustainable use of resources [13]. However, the poor frost resistance of recycled aggregate concrete leads to poor bond performance between recycled aggregate concrete and rebar [14], which will inevitably affect the application of recycled aggregate concrete in engineering [15]. Therefore, it is necessary to study the bond performance between recycled aggregate concrete and rebar under freeze–thaw environment [16].

The bond strength between recycled aggregate concrete and rebar decreased after freeze–thaw damage [17], while the slip increased [18], which was consistent with the degradation law of the performance between ordinary aggregate concrete and rebar. In addition, the recycled aggregate replacement rate, the rebar type and the diameter of the rebar would affect the bond performance between recycled aggregate concrete and rebar under freeze–thaw environment [19]. The bond strength between recycled aggregate concrete and rebar decreased with the increase of the recycled coarse aggregate replacement rate [20]. The bond strength of between recycled aggregate concrete and deformed rebar was greater than that between recycled aggregate concrete and plain rebar after the same numbers of freeze–thaw cycles [21]. The bond strength between recycled aggregate concrete and rebar decreased with the increase of the steel bar diameter [22]. Lu [22] proposed the bond–slip constitutive relationship between recycled aggregate concrete and rebar.

Some scholars have also investigated the performance between ordinary aggregate concrete and rebar under salt-frost cycles [23], and the results show that the degradation degree of bond performance after salt–frost cycles was greater than that after freeze–thaw cycles [24]. Ren et al. [25] and Shang et al. [26] found that the bond strength between recycled aggregate concrete and rebar in seawater after freeze–thaw cycles was lower than that in freshwater, while the bond slip in seawater was larger than that in freshwater. However, the test method would not only consume a lot of materials but also spend a lot of time. Therefore, a new method was needed to study the bond performance of concrete specimens instead of the experimental method.

With the rapid development of computer technology, the method of finite element analysis technology has been widely used in engineering [27]. Scholars have begun to numerically analyze the bond performance between concrete and rebar on the basis of experiments [28]. The rationality of the finite element model could be verified by comparing the finite element simulation results with the experimental results [29]. The three-dimensional nonlinear finite element analysis method and the two-dimensional nonlinear finite element analysis method could better simulate the bond performance between concrete and rebar [30,31]. In recent years, the finite element method was used to investigate the bond performance between recycled aggregate concrete and rebar [32].

However, there are few studies on bond performance between recycled aggregate concrete and rebar after freeze–thaw cycles by the finite element method. Although Fubo [33] investigated the bond performance between recycled aggregate concrete and rebar after freeze–thaw cycles, the important influencing factor of concrete strength was not considered. In addition, the relationship between bar diameter and concrete strength and bond strength could not be established. Therefore, the objective of this study is to investigate the bond performance between recycled aggregate concrete and rebar after freeze–thaw cycles by the finite element method, considering the effects of recycled aggregate concrete strength and concrete cover depth on bond performance, and to establish the calculation formula for the bond strength between recycled aggregate concrete specimens with different concrete strengths and different concrete cover depths after freeze and thaw cycles. This study provides the theoretical basis for the application of recycled aggregate concrete in cold regions.

2 Finite element model

2.1 Recycled aggregate concrete model

SOLID element in finite element ABAQUS could better simulate the performance of recycled aggregate concrete [34]. SOLID element was an eight-node hexahedral solid element. Each node could be divided into three degrees of freedom along the direction of the spatial coordinate system, and the displacement in each direction could bear the tension pressure along this direction. The size of a recycled aggregate concrete model was 150 mm × 150 mm × 150 mm, as shown in Figure 1.

Figure 1 Recycled aggregate concrete model.
Figure 1

Recycled aggregate concrete model.

Uni-axial compressive stress–strain constitutive relation of recycled aggregate concrete after freeze–thaw cycles proposed by Wu et al. [12] is expressed as follows (n is the number of freeze–thaw cycles, ε c is the ultimate stress, σ c is the peak strain and a is the parameter to be determined in the ascending branch of the stress–strain curve):

(1) y = a x + ( 3 − 2 a ) x 2 + ( a − 2 ) x 2 , x ≤ 1 x B ( x − 1 ) + x , x ≥ 1 B = − 9 × 10 − 6 n 3 + 0.0024 n 2 − 0.1689 n + 4.2712 , x = ε ε c , y = σ σ c .

The cube compressive strength f cu of recycled aggregate concrete could be assigned according to the corresponding experimental data. The elastic modulus (E c), the uni-axial compressive strength (f c) and the uni-axial tensile strength (f sp) of recycled aggregate concrete are given as follows [35]:

(2) E c = 10 5 2.8 + 40.1 / f cu ,

(3) f c = 0.76 f cu ,

(4) f sp = 0.24 f cu 0.65 .

The cubic compressive strength in ref. [33] was brought into formulas (2–4), and the basic performance indicators of recycled aggregate concrete were obtained, as presented in Table 1.

Table 1

Basic performance indicators of recycled aggregate concrete

Concrete strength grade (MPa) Freeze–thaw cycles (times) Uni-axial compressive strength (MPa) Uni-axial tensile strength (MPa) Elastic modulus (GPa) Poisson’s ratio
40 0 33.97 2.84 27.05 0.20
50 32.60 2.76 26.78 0.20
100 28.96 2.56 26.00 0.20
150 26.98 2.44 25.45 0.20
200 26.14 2.39 25.22 0.20
30 0 26.37 2.41 25.28 0.20
50 25.00 2.32 24.89 0.20
100 21.36 2.10 23.66 0.20
150 19.38 1.97 22.87 0.20
200 18.54 1.91 22.51 0.20
20 0 18.47 1.91 22.47 0.20
50 14.97 1.67 20.68 0.20
100 10.94 1.36 17.91 0.20

2.2 Rebar model

Considering the setting of the spring element at the interface between the concrete and the rebar, the truss element was selected in the ABAQUS software to simulate the rebar in the concrete, in which the section size of the rebar was set by editing the section in the ABAQUS software. The rebar model is shown in Figure 2.

Figure 2 Rebar finite element model.
Figure 2

Rebar finite element model.

The stress mode of the rebar simulated in this article is a uni-axial stress state, and the constitutive relation was relatively simple. Therefore, the double-line model was selected for analysis, as shown in Figure 3. The material properties of the rebar were assigned based on the experimental data in ref. [34], and the basic performance indicators of rebar are presented in Table 2.

Figure 3 Rebar constitutive relation model.
Figure 3

Rebar constitutive relation model.

Table 2

Basic performance indicators of rebar

Rebar type Diameter (mm) Tensile strength (MPa) Yield strength (MPa) Elastic modulus (GPa) Poisson’s ratio
HRB400 16 550 410 201 0.3

2.3 Model assembly and meshing

After establishing the recycled concrete model and the steel bar model, the two models were assembled to make the rebar located in the center of the specimen, as shown in Figures 4 and 5, respectively. Then, the specimen was meshed, and the same mesh size was selected for the concrete element and the rebar element to ensure that the nodes of the concrete element and the steel element were coincident, as shown in Figure 6.

Figure 4 Pull-out the test specimen.
Figure 4

Pull-out the test specimen.

Figure 5 Finite element model.
Figure 5

Finite element model.

Figure 6 Finite element model meshing.
Figure 6

Finite element model meshing.

To better simulate the bond performance between recycled aggregate concrete and rebar, a double-spring connecting element was set at the interface surface between recycled aggregate concrete and rebar, and the Spring2 element was selected as the connecting element and modified to a nonlinear element [33]:

“*Spring, elset = Springs/Dashpots-1-spring, nonlinear.”

3 Results and discussion

3.1 Comparison of finite element analysis results and test results

3.1.1 Comparison of bond strength

The finite element simulation results of the ultimate bond strength (τ c) of C20 recycled aggregate concrete specimens were compared with the experimental results (τ e) in the literature [33], as presented in Table 3.

Table 3

The comparison of simulation results (τ c) and experiment results (τ e)

Freeze–thaw cycles τ c (MPa) τ e (MPa)
0 16.21 15.22
50 13.77 12.37
100 9.58 7.99

It is presented in Table 3 that the bond strength decreased with the increasing number of freeze–thaw cycles, and the maximum error rate of the finite element simulation value was 18%. It can be seen that the finite element simulation value was in good agreement with the experimental value, which proved the rationality of the finite element simulation in terms of bond strength of recycled aggregate concrete with rebar.

3.1.2 Comparison of peak bond slip (slip corresponding to ultimate bond stress)

The finite element simulation results of the peak bond slip (s c) of C20 recycled aggregate concrete specimens were compared with the experimental results (s e) in the literature [33], as presented in Table 4.

Table 4

The comparison of calculation results (s c) and experiment results (s e)

Freeze–thaw cycles s c (mm) s e (mm)
0 0.928 0.65
50 1.310 0.95
100 1.569 1.12

It is presented in Table 4 that the peak bond slip increased with the increasing number of freeze–thaw cycles, and the maximum error rate of the finite element simulation value was 43%. It can be seen that the agreement between the finite element simulation value and the experimental value was low. The reason may be that the double-spring connecting element cannot reflect the slip between the recycled aggregate concrete and the rebar, so only the bond strength was analyzed in the following analysis.

3.2 Influence of concrete strength on bond strength

The influence of concrete strength on bond strength between the rebar and the recycled aggregate concrete and with different concrete strengths after freeze and thaw cycles is shown in Figure 7. It can be seen that the bond strength between the rebar and the recycled aggregate concrete increased with the increase of the concrete strength. The reason is that the frost resistance of concrete increases with the increase of the concrete strength, and the loss rate of the concrete strength decreases after freeze–thaw cycles, which leads to the decrease of bond damage.

Figure 7 Influence of concrete strength on bond strength.
Figure 7

Influence of concrete strength on bond strength.

The ultimate bond strengths between the rebar and the recycled aggregate concrete and with different concrete strengths after freeze and thaw cycles were fitted as follows:

(5) C 40 : τ u = − 0.0308 n + 17.638 , R 2 = 0.8345 ,

(6) C 30 : τ u = − 0.0318 n + 16.986 , R 2 = 0.9069 ,

(7) C 20 : τ u = − 0.0723 n + 15.475 , R 2 = 0.9853 .

3.3 Influence of concrete cover depth on bond strength

The ultimate bond strength of the recycled aggregate concrete specimens with different concrete cover depths after freeze and thaw cycles, as shown in Figure 8. It can be seen that the bond strength between the rebar and the recycled aggregate concrete increased with the increase of rebar diameter. Su et al. [34] also obtained similar conclusions that the bond strength after salt frost cycles increased with the increase of concrete cover depth.

Figure 8 Influence of concrete cover depth on bond strength.
Figure 8

Influence of concrete cover depth on bond strength.

The ultimate bond strengths of the recycled aggregate concrete specimens with different concrete cover depths after freeze and thaw cycles were fitted as follows:

(8) c = 67 mm: τ u = − 0.0308 n + 17.638 , R 2 = 0.8345 ,

(9) c = 77 mm: τ u = − 0.0227 n + 17.784 , R 2 = 0.7764 ,

(10) c = 87 mm: τ u = − 0.0136 n + 18.002 , R 2 = 0.9547 .

4 Conclusions

  1. The finite element simulation value of the ultimate bond strength of recycled aggregate concrete specimens was in good agreement with the experimental value.

  2. The agreement between the finite element simulation value of the peak bond slip of recycled aggregate concrete specimens and the experimental value was low.

  3. The bond strength between rebar and recycled aggregate concrete increased with the increase of concrete strength and concrete cover depth.

  4. The calculation formula for the bond strength of recycled aggregate concrete specimens with different concrete strengths and different concrete cover depths after freeze and thaw cycles were obtained.

Although this study cannot accurately predict the peak slip of recycled aggregate concrete and rebar after freeze–thaw cycles, it can accurately predict the bond strength of recycled concrete and steel bars after freeze–thaw cycles, which can promote the application of recycled aggregate concrete in engineering.

Acknowledgments

The study was carried out with the support of Key Laboratory for Comprehensive Energy Saving of Cold Regions Architecture of Ministry of Education, Jilin Jianzhu University.

  1. Funding information: The authors state no funding involved.

  2. Author contributions: W.S.: investigation, finite element analysis, writing–review & editing; H.S.: writing; Y.W.: check original draft; T.S.: check original draft.

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

References

[1] Kabir MR, Islam MM. Bond stress behavior between concrete and steel rebar: Critical investigation of pull-out test via finite element modeling. Int J Comput Civ Struct Eng. 2014;5(1):80–90.Search in Google Scholar

[2] Mechtcherine V, Schrfl C, Wyrzykowski M, Gorges M, Weiss J. Effect of superabsorbent polymers (SAP) on the freeze–thaw resistance of concrete: results of a RILEM interlaboratory study. Mater Struct. 2017;50(1):1–19.10.1617/s11527-016-0868-7Search in Google Scholar

[3] Fan YF, Zhang SY, Shah SP. Influence of nanoclay on concrete subjected to freeze–thaw cycles and bond behavior between rebar and concrete. Key Eng Mater. 2016;711:256–62.10.4028/www.scientific.net/KEM.711.256Search in Google Scholar

[4] Zhu F, Ma Z, Zhao T. Influence of freeze–thaw damage on the steel corrosion and bond-slip behavior in the reinforced concrete. Adv Mater Sci Eng. 2016;1(3):1–12.10.1155/2016/9710678Search in Google Scholar

[5] Xu S, Li A, Wang H. Bond properties for deformed steel bar in frost-damaged concrete under monotonic and reversed cyclic loading. Constr Build Mater. 2017;148(9):344–58.10.1016/j.conbuildmat.2017.05.090Search in Google Scholar

[6] Liu Y, Chen YF, Wang W, Li Z. Bond performance of thermal insulation concrete under freeze–thaw cycles. Constr Build Mater. 2016;104(8):116–25.10.1016/j.conbuildmat.2015.12.040Search in Google Scholar

[7] Nuaklong P, Wongsa A, Boonserm K, Ngohpok C, Chindaprasirt P. Enhancement of mechanical properties of fly ash geopolymer containing fine recycled concrete aggregate with micro carbon fiber. J Build Eng. 2021;41:102403.10.1016/j.jobe.2021.102403Search in Google Scholar

[8] Tabyang W, Suksiripattanapong C, Phetchuay C, Laksanakit C, Chusilp N. Evaluation of municipal solid waste incineration fly ash based geopolymer for stabilised recycled concrete aggregate as road material. Road Mater Pavem Des. 2021;8:1–12.10.1080/14680629.2021.1959385Search in Google Scholar

[9] Pandurangan K, Dayanithy A, Prakash S. Influence of treatment methods on the bond strength of recycled aggregate concrete. Constr Build Mater. 2016;120(9):212–21.10.1016/j.conbuildmat.2016.05.093Search in Google Scholar

[10] Sadati S, Arezoumandi M, Khayat KH, Volz JS. Shear performance of reinforced concrete beams incorporating recycled concrete aggregate and high-volume fly ash. J Clean Prod. 2016;115(3):284–93.10.1016/j.jclepro.2015.12.017Search in Google Scholar

[11] Zhang QT, Xiao JZ, Zhang KJ, Duan ZH. Mechanical behavior of seawater sea-sand recycled concrete columns confined by engineered cementitious composite under eccentric compression. J Build Eng. 2022;45:103497.10.1016/j.jobe.2021.103497Search in Google Scholar

[12] Wu J, Jing X, Wang Z. Uni-axial compressive stress-strain relation of recycled coarse aggregate concrete after freezing and thawing cycles. Constr Build Mater. 2017;134(3):210–9.10.1016/j.conbuildmat.2016.12.142Search in Google Scholar

[13] Shi C, Li Y, Zhang J, Li W, Chong L, Xie Z. Performance enhancement of recycled concrete aggregate-A review. J Clean Prod. 2016;112(1):466–72.10.1016/j.jclepro.2015.08.057Search in Google Scholar

[14] Cheng Y, Shang X, Zhang Y. Experimental research on durability of recycled aggregate concrete under freeze–thaw cycles. J Phys Conf Ser. 2017;870(1):1–4.10.1088/1742-6596/870/1/012018Search in Google Scholar

[15] Su T, Wang C, Cao F, Zou Z, Wang C, Wang J, et al. An overview of bond behavior of recycled coarse aggregate concrete with steel bar. Rev Adv Mater Sci. 2021;60(1):127–44.10.1515/rams-2021-0018Search in Google Scholar

[16] Li Y. Experimental study on the basic performance of entraining concrete and the bond behavioue between entraining concrete and reinfored after thawing [dissertation]. Qingdao: Qingdao Technological University; 2015.Search in Google Scholar

[17] Cao F, Tang L, Ding B, Wang C. Study on bond-slip properties between steel bars and recycled concrete after freeze–thaw cycles. Eng Mech. 2017;34(S1):244–51.Search in Google Scholar

[18] Wang C, Tang L, Zhang Z, Wang J, Cao F. Pullout tests research on steel bars and recycled concrete after freeze–thaw cycles. Build Struct. 2018;48(9):97–102.Search in Google Scholar

[19] Li ZH, Deng ZH, Yang HF, Wang HL. Bond behavior between recycled aggregate concrete and deformed rebar after freeze–thaw damage. Constr Build Mater. 2020;250:118805.10.1016/j.conbuildmat.2020.118805Search in Google Scholar

[20] Liu KH, Yan JC, Meng XX, Zou CY. Bond behavior between deformed steel bars and recycled aggregate concrete after freeze–thaw cycles. Constr Build Mater. 2020;232:117236.10.1016/j.conbuildmat.2019.117236Search in Google Scholar

[21] Shang HS, Zhao TJ, Cao WQ. Bond behavior between steel bar and recycled aggregate concrete after freeze–thaw cycles. Cold Reg Sci Technol. 2015;118:38–44.10.1016/j.coldregions.2015.06.008Search in Google Scholar

[22] Lu XM. Experimental study on the bond properties of recycled concrete after freezing and thawing [dissertation]. Qingdao: Qingdao University of Technology; 2014.Search in Google Scholar

[23] Su T, Wu J, Yang GX, Zou Z. Bond behavior between recycled coarse aggregate concrete and steel bar after salt-frost cycles. Constr Build Mater. 2019;226:673–85.10.1016/j.conbuildmat.2019.07.301Search in Google Scholar

[24] Su T, Wang T, Wang CG, Yi HH. The influence of salt-frost cycles on the bond behavior distribution between rebar and recycled coarse aggregate concrete. J Build Eng. 2022;45:103568.10.1016/j.jobe.2021.103568Search in Google Scholar

[25] Ren GS, Shang HS, Zhang P, Zhao T. Bond behaviour of reinforced recycled concrete after rapid freezing-thawing cycles. Cold Reg Sci Technol. 2019;157:133–8.10.1016/j.coldregions.2018.10.005Search in Google Scholar

[26] Shang HS, Wang ZH, Zhang P, Zhao T, Fan G, Ren G. Bond behavior of steel bar in air-entrained RCAC in fresh water and sea water after fast freeze–thaw cycles. Cold Reg Sci Technol. 2017;135(3):90–6.10.1016/j.coldregions.2016.11.005Search in Google Scholar

[27] Sharma D, Kaur R, Sandhir M, Sharma H. Finite element method for stress and strain analysis of FGM hollow cylinder under effect of temperature profiles and inhomogeneity parameter. Nonlinear Eng. 2021;10(1):477–87.10.1515/nleng-2021-0039Search in Google Scholar

[28] Chen Q. Numerical simulation of reinforced concrete bonding properties and beam cracks [dissertation]. Hangzhou: Zhejiang University; 2011.Search in Google Scholar

[29] Reinhardt HW, Blaauwendraad J, Vos E. Prediction of bond between steel and concrete by numerical analysis. Matériaux Constr. 1984;17(4):311–20.10.1007/BF02479089Search in Google Scholar

[30] Xiangling G. Experimental research and numerical simulation of bonding properties between high performance concrete and reinforcement [dissertation]. Shanghai: Tongji University; 2003.Search in Google Scholar

[31] Kang ZF. Research on nonlinear finite element analysis method of reinforced concrete considering bond slip [dissertation]. Chongqing: Chongqing University; 2007.Search in Google Scholar

[32] Fubo C, Zhiming L, Chenxia W, Jianbo S. Finite element analysis of bond behavior between steel bars and recycled concrete after freeze–thaw cycles in the beam-type test. J Shenyang Architect Univ (Nat Sci Ed). 2019;35(6):1099–110.Search in Google Scholar

[33] Fubo C. Experimental study on basic mechanical properties of recycled concrete after freeze–thaw cycles [dissertation]. Nanjing: Nanjing University of Aeronautics and Astronautics; 2017.Search in Google Scholar

[34] Su T, Wang T, Huang Z, Yi H, Zhai H. Finite element analysis on bond behavior of steel bar in salt frost damaged recycled coarse aggregate concrete. Rev Adv Mater Sci. 2021;60(1):853–61.10.1515/rams-2021-0063Search in Google Scholar

[35] Xiao JZ. Recycled concrete [dissertation]. Beijing: China Construction Industry Press; 2008.Search in Google Scholar
Received: 2022-03-24
Revised: 2022-05-20
Accepted: 2022-06-09
Published Online: 2022-07-14

© 2022 Wei Su et al., published by De Gruyter

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

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https://doi.org/10.1515/nleng-2022-0032
Keywords for this article
recycled concrete; finite element; freeze–thaw cycles; concrete cover depth; concrete strength
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  10. Research on facial expression recognition based on an improved fusion algorithm
  11. N-dimensional quintic B-spline functions for solving n-dimensional partial differential equations
  12. Solution of two-dimensional fractional diffusion equation by a novel hybrid D(TQ) method
  13. Investigation of three-dimensional hybrid nanofluid flow affected by nonuniform MHD over exponential stretching/shrinking plate
  14. Solution for a rotational pendulum system by the Rach–Adomian–Meyers decomposition method
  15. Study on the technical parameters model of the functional components of cone crushers
  16. Using Krasnoselskii's theorem to investigate the Cauchy and neutral fractional q-integro-differential equation via numerical technique
  17. Smear character recognition method of side-end power meter based on PCA image enhancement
  18. Significance of adding titanium dioxide nanoparticles to an existing distilled water conveying aluminum oxide and zinc oxide nanoparticles: Scrutinization of chemical reactive ternary-hybrid nanofluid due to bioconvection on a convectively heated surface
  19. An analytical approach for Shehu transform on fractional coupled 1D, 2D and 3D Burgers’ equations
  20. Exploration of the dynamics of hyperbolic tangent fluid through a tapered asymmetric porous channel
  21. Bond behavior of recycled coarse aggregate concrete with rebar after freeze–thaw cycles: Finite element nonlinear analysis
  22. Edge detection using nonlinear structure tensor
  23. Synchronizing a synchronverter to an unbalanced power grid using sequence component decomposition
  24. Distinguishability criteria of conformable hybrid linear systems
  25. A new computational investigation to the new exact solutions of (3 + 1)-dimensional WKdV equations via two novel procedures arising in shallow water magnetohydrodynamics
  26. A passive verses active exposure of mathematical smoking model: A role for optimal and dynamical control
  27. A new analytical method to simulate the mutual impact of space-time memory indices embedded in (1 + 2)-physical models
  28. Exploration of peristaltic pumping of Casson fluid flow through a porous peripheral layer in a channel
  29. Investigation of optimized ELM using Invasive Weed-optimization and Cuckoo-Search optimization
  30. Analytical analysis for non-homogeneous two-layer functionally graded material
  31. Investigation of critical load of structures using modified energy method in nonlinear-geometry solid mechanics problems
  32. Thermal and multi-boiling analysis of a rectangular porous fin: A spectral approach
  33. The path planning of collision avoidance for an unmanned ship navigating in waterways based on an artificial neural network
  34. Shear bond and compressive strength of clay stabilised with lime/cement jet grouting and deep mixing: A case of Norvik, Nynäshamn
  35. Communication
  36. Results for the heat transfer of a fin with exponential-law temperature-dependent thermal conductivity and power-law temperature-dependent heat transfer coefficients
  37. Special Issue: Recent trends and emergence of technology in nonlinear engineering and its applications - Part I
  38. Research on fault detection and identification methods of nonlinear dynamic process based on ICA
  39. Multi-objective optimization design of steel structure building energy consumption simulation based on genetic algorithm
  40. Study on modal parameter identification of engineering structures based on nonlinear characteristics
  41. On-line monitoring of steel ball stamping by mechatronics cold heading equipment based on PVDF polymer sensing material
  42. Vibration signal acquisition and computer simulation detection of mechanical equipment failure
  43. Development of a CPU-GPU heterogeneous platform based on a nonlinear parallel algorithm
  44. A GA-BP neural network for nonlinear time-series forecasting and its application in cigarette sales forecast
  45. Analysis of radiation effects of semiconductor devices based on numerical simulation Fermi–Dirac
  46. Design of motion-assisted training control system based on nonlinear mechanics
  47. Nonlinear discrete system model of tobacco supply chain information
  48. Performance degradation detection method of aeroengine fuel metering device
  49. Research on contour feature extraction method of multiple sports images based on nonlinear mechanics
  50. Design and implementation of Internet-of-Things software monitoring and early warning system based on nonlinear technology
  51. Application of nonlinear adaptive technology in GPS positioning trajectory of ship navigation
  52. Real-time control of laboratory information system based on nonlinear programming
  53. Software engineering defect detection and classification system based on artificial intelligence
  54. Vibration signal collection and analysis of mechanical equipment failure based on computer simulation detection
  55. Fractal analysis of retinal vasculature in relation with retinal diseases – an machine learning approach
  56. Application of programmable logic control in the nonlinear machine automation control using numerical control technology
  57. Application of nonlinear recursion equation in network security risk detection
  58. Study on mechanical maintenance method of ballasted track of high-speed railway based on nonlinear discrete element theory
  59. Optimal control and nonlinear numerical simulation analysis of tunnel rock deformation parameters
  60. Nonlinear reliability of urban rail transit network connectivity based on computer aided design and topology
  61. Optimization of target acquisition and sorting for object-finding multi-manipulator based on open MV vision
  62. Nonlinear numerical simulation of dynamic response of pile site and pile foundation under earthquake
  63. Research on stability of hydraulic system based on nonlinear PID control
  64. Design and simulation of vehicle vibration test based on virtual reality technology
  65. Nonlinear parameter optimization method for high-resolution monitoring of marine environment
  66. Mobile app for COVID-19 patient education – Development process using the analysis, design, development, implementation, and evaluation models
  67. Internet of Things-based smart vehicles design of bio-inspired algorithms using artificial intelligence charging system
  68. Construction vibration risk assessment of engineering projects based on nonlinear feature algorithm
  69. Application of third-order nonlinear optical materials in complex crystalline chemical reactions of borates
  70. Evaluation of LoRa nodes for long-range communication
  71. Secret information security system in computer network based on Bayesian classification and nonlinear algorithm
  72. Experimental and simulation research on the difference in motion technology levels based on nonlinear characteristics
  73. Research on computer 3D image encryption processing based on the nonlinear algorithm
  74. Outage probability for a multiuser NOMA-based network using energy harvesting relays
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