CT imaging-enhanced numerical simulation of microscopic structure and resilient safety of asphalt concrete

Lei Bao , Min He , Tianhao Ye , Mengyan Tan , Ruijie Wang , Han Yang

Earthquake Engineering and Resilience ›› 2024, Vol. 3 ›› Issue (3) : 447 -474.

PDF
Earthquake Engineering and Resilience ›› 2024, Vol. 3 ›› Issue (3) : 447 -474. DOI: 10.1002/eer2.92
RESEARCH ARTICLE

CT imaging-enhanced numerical simulation of microscopic structure and resilient safety of asphalt concrete

Author information +
History +
PDF

Abstract

Asphalt concrete is a foundational material in water conservancy projects, serving a critical function in the construction of impermeable structures such as dams. The seismic response characteristics and resilient safety of concrete dams are heavily influenced by the arrangement and evolution of the microscopic structure of the dam material. In this study, a high-precision computed tomography (CT) scanning technique, in conjunction with advanced numerical simulations, was employed to analyze the internal damage and crack extension mechanism of asphalt concrete. Microstructural images of the asphalt concrete specimen were accurately captured by CT scanning, followed by the construction of corresponding numerical models. Presented simulation results show that the displacement deformation of asphalt concrete reaches its maximum value in the top region of the model and subsequently decreases with depth. Material damage was first observed at the interface between aggregate and asphalt matrix, where microcracks emerge and extend to the entire asphalt matrix, resulting in a gradual deterioration of the model performance. The simulation results indicate that the overall strength of asphalt concrete is primarily influenced by the strength characteristics of its aggregates. The stress–strain curves obtained from the numerical simulations exhibit a hyperbolic relationship, which is in high agreement with the physical test results. This study not only enhances our comprehension of the mechanical behavior of concrete but also contributes to the analysis of seismic response and risk assessment in dam engineering through dynamic experimental testing and numerical simulation.

Keywords

asphalt concrete / CT scanning technology / numerical test / resilient safety

Cite this article

Download citation ▾
Lei Bao, Min He, Tianhao Ye, Mengyan Tan, Ruijie Wang, Han Yang. CT imaging-enhanced numerical simulation of microscopic structure and resilient safety of asphalt concrete. Earthquake Engineering and Resilience, 2024, 3(3): 447-474 DOI:10.1002/eer2.92

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Szydtowski C, Smakosz L, Stienss M, Gorski J. Monte Carlo simulations of the fracture resistance degradation of asphalt concrete subjected to environmental factors. Arch Civ Eng. 2023;69:245-257.

[2]

Chang Z, Liu D, Liang J. Relationship between porosity and the modified constitutive model parameters of asphalt concrete core material. KSCE J Civ Eng. 2023;27(10):4250-4262.

[3]

Long A, Sun X, Yu Z, et al. Experimental study and mechanism analysis on the basic mechanical properties of hydraulic basalt fiber asphalt concrete. Mater Struct. 2022;55:161.

[4]

Tan Z, Leng Z, Jelagin D, et al. Numerical modeling of the mechanical response of asphalt concrete in tension and compression. Mech Mater. 2023;187:1.1-1.18.

[5]

Asim M, Khan R. Numerical modeling of nonlinear behavior of asphalt concrete. Adv Civil Eng. 2018;5.

[6]

Niazi S, Najmeddine A, Shakiba M. A coupled thermo-hydro-mechanical framework for simulating the failure response of asphalt concrete under freezing conditions. Cold Reg Sci Technol. 2024;218:104073.

[7]

Khan ZH, Amanul Hasan M, Tarefder RA. Phase field approach to damage and fracture in asphalt concrete using multiscale finite element modeling of an instrumented pavement section. Eng Fract Mech. 2022;272:108686.

[8]

Xia X, Han D, Zhao Y, Xie Y, Zhou Z, Wang J. Investigation of asphalt pavement crack propagation based on micromechanical finite element: a case study. Case Stud Constr Mater. 2023;19:e02247.

[9]

Qian N, Luo W, Ye Y, et al. Effects of the ductility and brittle point of modified asphalt on the freeze-break behavior of asphalt concrete: a 3D-mesoscopic damage FE model. Constr Build Mater. 2023;386:131555.

[10]

Wang M, Yu W, Yang Y, Wang Y. Stochastic CFD Numerical Model, Algorithm, and Simulation on Regular Wave Fields. IOP Publishing Ltd; 2024.

[11]

Fabra-Rodriguez M, Abellán-López D, Simón-Portillo FJ, Campello-Vicente H, Campillo-Davo N, Peral-Orts R. Numerical model for vibro-acoustics analysis of tyre-road noise generation caused by speed bumps. Appl Acoust. 2024;216:109830.

[12]

Carlos TB, Silva VP. CFRP-strengthened RC beams under fire condition: numerical model. Rev IBRACON Estrut Mater. 2023;16.

[13]

Bandyopadhyaya R, Das A, Basu S. Numerical simulation of mechanical behaviour of asphalt mix. Constr Build Mater 2008;22(6):1051-1058.

[14]

Arambula E, Caro S, Masad E. Experimental measurement and numerical simulation of water vapor diffusion through asphalt pavement materials. J Mater Civil Eng. 2010;22(6):588-598.

[15]

Caro S, Masad E, Bhasin A, Little D. Micromechanical modeling of the influence of material properties on moisture-induced damage in asphalt mixtures. Constr Build Mater. 2010;24(7):1184-1192.

[16]

Elseifi MA, Mohammad LN, Ying H, Cooper S. Modeling and evaluation of the cracking resistance of asphalt mixtures using the semi-circular bending test at intermediate temperatures. Road Mater Pavement Des. 2012;13:124-139.

[17]

Kim YR, Aragão FTS. Microstructure modeling of rate-dependent fracture behavior in bituminous paving mixtures. Finite Elem Anal Des. 2013;63:23-32.

[18]

Ren D, Xu J, Su S, et al. Characterization of internal pore size distribution and interconnectivity for asphalt concrete with various porosity using 3D CT scanning images. Constr Build Mater. 2023;400:132751.

[19]

Zhao Y, Wang X, Jiang J, Zhou L. Characterization of interconnectivity, size distribution and uniformity of air voids in porous asphalt concrete using X-ray CT scanning images. Constr Build Mater. 2019;213:182-193.

[20]

Zhang Y, Verwaal W, van de Ven MFC, Molenaar AAA, Wu SP. Using high-resolution industrial CT scan to detect the distribution of rejuvenation products in porous asphalt concrete. Constr Build Mater. 2015;100:1-10.

[21]

Gao L, Liu M, Wang Z, Xie J, Jia S. Correction of texture depth of porous asphalt pavement based on CT scanning technique. Constr Build Mater. 2019;200:514-520.

[22]

Si C, Zhou X, You Z, He Y, Chen E, Zhang R. Micro-mechanical analysis of high modulus asphalt concrete pavement. Constr Build Mater. 2019;220:128-141.

[23]

Underwood BS, Kim YR. Microstructural investigation of asphalt concrete for performing multiscale experimental studies. Int J Pavement Eng. 2013;14(5):498-516.

[24]

Zhong-Zhi L. Research on Comprehensive Assessment on Surface Function of Asphalt Concrete Pavement. Northern Communications; 2016.

[25]

Costa DB, de Medeiros Melo Neto O, de Souza MCR, Rodrigues JKG, Cavalcante FP. Analysis of permanent deformation in asphalt mixtures using Mohr–Coulomb criteria. Mater Struct. 2024;57(6):147.

[26]

Li L, Zhao C, Zhou J, Chai JH, Yu SC, Niu YR. Breakage characteristics of spherical gypsum particles under three-point contact. IOP Conf Ser: Earth Environ Sci. 2021;861:072083.

[27]

Lian-Jie Z, Qing-Jun M. Study on cervical spine stresses based on three-dimensional finite element method. In: International Conference on Computational &Information Sciences. 2010:420-423.

[28]

Alam NMFHNB, Ramli N, Mohd AH. Intuitionistic fuzzy set-based time series forecasting model via delegeration of hesitancy degree to the major grade de-i-fuzzification and arithmetic rules based on centroid defuzzification. J Phys Conf Ser. 2021;1988(1):012014.

[29]

Zadeh LA. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1978;1(1):3-28.

[30]

Fang JY, Li N, Qu F, Dou ZS, Li ST. Quantitative analysis of concrete on the basis of fuzzy set and computerised tomography number. Thermal Sci. 2020;24:3907-3913.

[31]

Fang J, Dang F, Xiao Y, Ding W. Quantitative study on the CT test process of siltstone under triaxial compression. Chin J Rock Mech Eng. 2015.

[32]

Liu S, Huang Z. Analysis of strength property and pore characteristics of Taihang limestone using X-ray computed tomography at high temperatures. Sci Rep. 2021;11:13478.

[33]

Bai X. Assessment of Relationship Between Dynamic and Seismic Moduli of Asphalt Concrete Mixtures. The University of Texas at El Paso;2004.

[34]

Kong XM, Liu YL, Yan PY. Influence of loading rate on mechanical properties of cement asphalt mortars. Jianzhu Cailiao Xuebao/J Build Mater. 2010;13(2):187-192.

[35]

Xing Y, Gomez RB. Hyperspectral image analysis using ENVI (environment for visualizing images). Proc SPIE Int Soc Opt Eng. 2001;15(38):79-86.

[36]

Zgurovsky MZ. System analysis: theory and applications. Springer;2007.

[37]

Xu J, Ma B, Mao W, Si W, Wang X. Review of interfacial adhesion between asphalt and aggregate based on molecular dynamics. Constr Build Mater. 2023;362:129642.

[38]

Mehta PK, Monteiro PJM. Concrete: Microstructure, Properties, and Materials. Prentice-Hall;2013.

[39]

Fugen J. Test and apply elastic modulus of aggregate. J Taiyuan Univ Technol. 2001;35:29-32.

[40]

Jianjun W. Analysis on Pavement Performance of AC-13 Asphalt Mixture Mixed at Normal Temperature. 2019.

[41]

Jianyin F, Faning D, Ping W, Chao Y. Research on numerical method for features of concrete and its CT testing. Chin J Undergr Space Eng. 2014;10:1293-1299.

[42]

Shu X, Huang B. Micromechanics-based dynamic modulus prediction of polymeric asphalt concrete mixtures. Compos Part B Eng. 2008;39(4):704-713.

RIGHTS & PERMISSIONS

2024 Tianjin University and John Wiley & Sons Australia, Ltd.

AI Summary AI Mindmap
PDF

162

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/