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Influence of 3D Aggregate Shape on the Meso-Structure of 2D Cross-Sectional Concrete by the Numerical Slicing Method

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Abstract

Aggregate shape is essential for evaluating concrete properties. Most of the existing literature utilizes X-ray computed tomography (X-CT) to assess the morphological characteristics of 2D/3D aggregates. However, the obtainment of a large number of aggregates by X-CT is a tedious, time-consuming and costly task. In this study, a framework combined concrete modeling and the numerical slicing method was developed, which simulated the process for obtaining 3D models of concrete and the corresponding 2D cross-sectional concrete models in the laboratory using X-CT. This was simpler, more efficient, and less costly than the X-CT method. Based on this framework, 3D concrete models with four different aggregate shape types and corresponding 2D cross-sectional concrete models were generated. The influences of 3D aggregate shape types on the roundness, aspect ratio, packing density, and grading curves of 2D cross-sectional aggregates were statistically analyzed and the correlation between the morphological descriptors of 2D/3D aggregates was investigated. The differences between 2D meso-concrete models generated based on the numerical slicing and the random placement methods were compared. The results showed that the 3D aggregate shape type had significant effects on the meso-structure of 2D sectional concrete. Unlike the projection image method, the morphological descriptors of 2D cross-sectional aggregates obtained based on the slicing method were poorly correlated with the morphological characteristics of 3D aggregates. This study laid the foundation for the study of the qualitative and quantitative relationships between the shape index and mechanical properties of aggregates.

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References

  1. Zhou, X.; Xie, Y.J.; Zeng, X.H.; Long, G.C.; Wu, J.Q.; Ma, G.; Wang, F.; Zhao, H.; Yao, L.: Meso-scale numerical simulation of the effect of aggregate strength on damage and fracture of high-strength concrete under dynamic tensile loading. Theor. Appl. Fract. Mech. 122, 103551 (2022). https://doi.org/10.1016/j.tafmec.2022.103551

    Article  Google Scholar 

  2. Nitka, M.; Tejchman, J.: Modelling of concrete behaviour in uniaxial compression and tension with DEM. Granul. Matter. 17, 145–164 (2015). https://doi.org/10.1007/s10035-015-0546-4

    Article  Google Scholar 

  3. Cao, G.D.; Liu, Y.; Long, S.G.; Deng, D.Q.; Jiang, S.Q.; Su, H.W.; Tan, T.: Influence of aggregate shape on the flow properties of fresh concrete. Powder Technol. 415, 118186 (2023). https://doi.org/10.1016/j.powtec.2022.118186

    Article  Google Scholar 

  4. Deng, P.; Xu, K.; Guo, S.C.: Effects of coarse aggregate morphology on concrete mechanical properties. J. Build. Eng. 63, 105408 (2023). https://doi.org/10.1016/j.jobe.2022.105408

    Article  Google Scholar 

  5. Jiang, S.; Shen, L.M.; Li, W.G.: An experimental study of aggregate shape effect on dynamic compressive behaviours of cementitious mortar. Constr. Build. Mater. 303, 124443 (2021). https://doi.org/10.1016/j.conbuildmat.2021.124443

    Article  Google Scholar 

  6. Sun, Y.R.; Zhang, Z.; Wei, X.; Du, C.; Gong, M.Y.; Chen, J.Y.; Gong, H.R.: Mesomechanical prediction of viscoelastic behavior of asphalt concrete considering effect of aggregate shape. Constr. Build. Mater. 274, 122096 (2021). https://doi.org/10.1016/j.conbuildmat.2020.122096

    Article  Google Scholar 

  7. Nitka, M.; Tejchman, J.: Comparative DEM calculations of fracture process in concrete considering real angular and artificial spherical aggregates. Eng. Fract. Mech. 239, 107309 (2020). https://doi.org/10.1016/j.engfracmech.2020.107309

    Article  Google Scholar 

  8. Zheng, B.; Li, T.C.; Qi, H.J.; Gao, L.G.; Liu, X.Q.; Yuan, L.: 3D meso-scale simulation of chloride ion transportation in cracked concrete considering aggregate morphology. Constr. Build. Mater. 326, 126632 (2022). https://doi.org/10.1016/j.conbuildmat.2022.126632

    Article  Google Scholar 

  9. Jiang, Z.L.; Qian, Z.W.; Gu, X.L.; Zhu, J.H.; Long, W.J.; Xing, F.: Statistical analysis of chloride concentration distribution in concrete by a meso-scale model considering irregular shape aggregates. Constr. Build. Mater. 319, 126143 (2022). https://doi.org/10.1016/j.conbuildmat.2021.126143

    Article  Google Scholar 

  10. Naderi, S.; Zhang, M.Z.: Meso-scale modelling of static and dynamic tensile fracture of concrete accounting for real-shape aggregates. Cem. Concr. Compos. 116, 103889 (2021). https://doi.org/10.1016/j.cemconcomp.2020.103889

    Article  Google Scholar 

  11. Yu, Y.; Zheng, Y.; Xu, J.J.; Wang, X.L.: Modeling and predicting the mechanical behavior of concrete under uniaxial loading. Constr. Build. Mater. 273, 121694 (2021). https://doi.org/10.1016/j.conbuildmat.2020.121694

    Article  Google Scholar 

  12. Naija, A.; Miled, K.: Numerical study of the influence of W/C ratio and aggregate shape and size on the ITZ volume fraction in concrete. Constr. Build. Mater. 351, 128950 (2022). https://doi.org/10.1016/j.conbuildmat.2022.128950

    Article  Google Scholar 

  13. Ghosh, S.; Dhang, N.; Deb, A.: Influence of aggregate geometry and material fabric on tensile cracking in concrete. Eng. Fract. Mech. 239, 107321 (2020). https://doi.org/10.1016/j.engfracmech.2020.107321

    Article  Google Scholar 

  14. Chen, H.B.; Xu, B.; Mo, Y.L.; Zhou, T.M.: Behavior of meso-scale heterogeneous concrete under uniaxial tensile and compressive loadings. Constr. Build. Mater. 178, 418–431 (2018). https://doi.org/10.1016/j.conbuildmat.2018.05.052

    Article  Google Scholar 

  15. Ma, H.F.; Xu, W.X.; Li, Y.C.: Random aggregate model for mesoscopic structures and mechanical analysis of fully-graded concrete. Comput. Struct. 177, 103–113 (2016). https://doi.org/10.1016/j.compstruc.2016.09.005

    Article  Google Scholar 

  16. Zheng, Y.X.; Zhang, Y.; Zhuo, J.B.; Zhang, P.; Hu, S.W.: Mesoscale synergistic effect mechanism of aggregate grading and specimen size on compressive strength of concrete with large aggregate size. Constr. Build. Mater. 367, 130346 (2023). https://doi.org/10.1016/j.conbuildmat.2023.130346

    Article  Google Scholar 

  17. Sun, Y.R.; Wei, X.; Gong, H.R.; Du, C.; Wang, W.Y.; Chen, J.Y.: A two-dimensional random aggregate structure generation method: Determining effective thermo-mechanical properties of asphalt concrete. Mech. Mater. 148, 103510 (2020). https://doi.org/10.1016/j.mechmat.2020.103510

    Article  Google Scholar 

  18. Zhou, Y.L.; Jin, H.; Wang, B.L.: Modeling and mechanical influence of meso-scale concrete considering actual aggregate shapes. Constr. Build. Mater. 228, 116785 (2019). https://doi.org/10.1016/j.conbuildmat.2019.116785

    Article  Google Scholar 

  19. Huang, Y.J.; Yan, D.M.; Yang, Z.J.; Liu, G.H.: 2D and 3D homogenization and fracture analysis of concrete based on in-situ X-ray Computed Tomography images and Monte Carlo simulations. Eng. Fract. Mech. 163, 37–54 (2016). https://doi.org/10.1016/j.engfracmech.2016.06.018

    Article  Google Scholar 

  20. Fang, K.; Zhang, J.F.; Tang, H.M.; Hu, X.L.; Yuan, H.H.; Wang, X.T.; An, P.J.; Ding, B.D.: A quick and low-cost smartphone photogrammetry method for obtaining 3D particle size and shape. Eng. Geol. 322, 107170 (2023). https://doi.org/10.1016/j.enggeo.2023.107170

    Article  Google Scholar 

  21. Su, D.; Yan, W.M.: Prediction of 3D size and shape descriptors of irregular granular particles from projected 2D images. Acta Geotech. 15, 1533–1555 (2020). https://doi.org/10.1007/s11440-019-00845-3

    Article  Google Scholar 

  22. Bagheri, G.H.; Bonadonna, C.; Manzella, I.; Vonlanthen, P.: On the characterization of size and shape of irregular particles. Powder Technol. 270, 141–153 (2015). https://doi.org/10.1016/j.powtec.2014.10.015

    Article  Google Scholar 

  23. Zheng, W.B.; Hu, X.L.; Tannant, D.D.; Zhang, K.; Xu, C.: Characterization of two-and three-dimensional morphological properties of fragmented sand grains. Eng. Geol. 263, 105358 (2019). https://doi.org/10.1016/j.enggeo.2019.105358

    Article  Google Scholar 

  24. An, P.J.; Tang, H.M.; Li, C.D.; Fang, K.; Lu, S.; Zhang, J.F.: A fast and practical method for determining particle size and shape by using smartphone photogrammetry. Measurement 193, 110943 (2022). https://doi.org/10.1016/j.measurement.2022.110943

    Article  Google Scholar 

  25. Dong, Q.; Zheng, D.B.; Zhao, X.K.; Chen, X.Q.; Chen, Y.F.: Mesoscale numerical simulation of fracture of cement treated base material during semi circular bending test with discrete element model. Constr. Build. Mater. 261, 119981 (2020). https://doi.org/10.1016/j.conbuildmat.2020.119981

    Article  Google Scholar 

  26. Ying, J.W.; Tian, J.S.; Xiao, J.Z.; Tan, Z.Y.: Identification and reconstruction of concrete mesostructure based on deep learning in artificial intelligence. Constr. Build. Mater. 352, 129018 (2022). https://doi.org/10.1016/j.conbuildmat.2022.129018

    Article  Google Scholar 

  27. Hu, X.L.; Zhang, H.; Boldini, D.; Liu, C.; He, C.C.; Wu, S.S.: 3D modelling of soil-rock mixtures considering the morphology and fracture characteristics of breakable blocks. Comput. Geotech. 132, 103985 (2021). https://doi.org/10.1016/j.compgeo.2020.103985

    Article  Google Scholar 

  28. Wei, D.H.; Wang, J.F.; Nie, J.Y.; Zhou, B.: Generation of realistic sand particles with fractal nature using an improved spherical harmonic analysis. Comput. Geotech. 104, 1–12 (2018). https://doi.org/10.1016/j.compgeo.2018.08.002

    Article  Google Scholar 

  29. Wang, X.; Yin, Z.Y.; Zhang, J.Q.; Xiong, H.; Su, D.: Three-dimensional reconstruction of realistic stone-based materials with control -able stone inclusion geometries. Constr. Build. Mater. 305, 124240 (2021). https://doi.org/10.1016/j.conbuildmat.2021.124240

    Article  Google Scholar 

  30. Zingg, T.: Beitrag zur schotteranalyse. Schweiz. Mineral. Petrogr. Mitt. 15, 52–56 (1935). https://doi.org/10.3929/ethz-a-000103455

    Article  Google Scholar 

  31. Blott, S.; Pye, K.: Particle shape: a review and new methods of characterization and classification. Sedimentology 55(1), 31–63 (2008). https://doi.org/10.1111/j.1365-3091.2007.00892.x

    Article  Google Scholar 

  32. Orosz, Á.; Angelidakis, V.; Bagi, K.: Surface orientation tensor to predict preferred contact orientation and characterise the form of individual particles. Powder Technol. 394, 312–325 (2021). https://doi.org/10.1016/j.powtec.2021.08.054

    Article  Google Scholar 

  33. Zhao, L.H.; Zhang, S.H.; Deng, M.; Wang, X.: Statistical analysis and comparative study of multi-scale 2D and 3D shape features for unbound granular geomaterials. Transp. Geotech. 26, 100377 (2021). https://doi.org/10.1016/j.trgeo.2020.100377

    Article  Google Scholar 

  34. Huang, Y.J.; Guo, F.Q.; Zhang, H.; Yang, Z.J.: An efficient computational framework for generating realistic 3D mesoscale concrete models using micro X-ray computed tomography images and dynamic physics engine. Cem. Concr. Compos. 126, 104347 (2022). https://doi.org/10.1016/j.cemconcomp.2021.104347

    Article  Google Scholar 

  35. Xie, H.; Feng, J.L.: Implementation of numerical mesostructure concrete material models: A dot matrix method. Materials 12(23), 3835 (2019). https://doi.org/10.3390/ma12233835

    Article  Google Scholar 

  36. Zheng, J.J.; Li, C.Q.: Three-dimensional aggregate density in concrete with wall effect. ACI Mater. J. 99, 568–575 (2002). https://doi.org/10.14359/12366

    Article  Google Scholar 

  37. Huang, Q.H.; Li, C.Z.; Song, X.B.: Spatial distribution characteristics of ellipsoidal coarse aggregates in concrete considering wall effect. Constr. Build. Mater. 327, 126922 (2022). https://doi.org/10.1016/j.conbuildmat.2022.126922

    Article  Google Scholar 

  38. Xu, W.X.; Lv, Z.; Chen, H.S.: Effects of particle size distribution, shape and volume fraction of aggregates on the wall effect of concrete via random sequential packing of polydispersed ellipsoidal particles. Phys. A 392(3), 416–426 (2013). https://doi.org/10.1016/j.physa.2012.09.014

    Article  Google Scholar 

  39. Lin, J.J.; Chen, H.S.; Zhang, R.L.; Liu, L.: Characterization of the wall effect of concrete via random packing of polydispersed superball-shaped aggregates. Mater. Charact. 154, 335–343 (2019). https://doi.org/10.1016/j.matchar.2019.06.024

    Article  Google Scholar 

  40. Chen, Y.W.; Feng, J.L.; Li, H.; Meng, Z.F.: Effect of coarse aggregate volume fraction on mode II fracture toughness of concrete. Eng. Fract. Mech. 242, 107472 (2021). https://doi.org/10.1016/j.engfracmech.2020.107472

    Article  Google Scholar 

  41. Zhang, X.P.; Xie, W.Q.; Cai, K.Y.; Liu, Q.S.; Wu, J.; Li, W.W.: Evaluation of rock muck using image analysis and its application in the TBM tunneling. Tunn. Undergr. Space Technol. 113, 103974 (2021). https://doi.org/10.1016/j.tust.2021.103974

    Article  Google Scholar 

  42. Xie, W.Q.; Zhang, X.P.; Yang, X.M.; Liu, Q.S.; Tang, S.H.; Tu, X.B.: 3D size and shape characterization of natural sand particles using 2D image analysis. Eng. Geol. 279, 105915 (2020). https://doi.org/10.1016/j.enggeo.2020.105915

    Article  Google Scholar 

  43. Maroof, M.A.; Mahboubi, A.; Noorzad, A.; Safi, Y.: A new approach to particle shape classification of granular materials. Transp. Geotech. 22, 100296 (2020). https://doi.org/10.1016/j.trgeo.2019.100296

    Article  Google Scholar 

  44. Zhao, X.K.; Dong, Q.; Chen, X.Q.; Ni, F.J.: Meso-cracking characteristics of rubberized cement-stabilized aggregate by discrete element method. J. Clean Prod. 316, 128374 (2021). https://doi.org/10.1016/j.jclepro.2021.128374

    Article  Google Scholar 

  45. Yu, K.L.; Yang, Z.J.; Li, H.; Ooi, T.E.; Li, S.M.; Liu, G.H.: A mesoscale modelling approach coupling SBFEM, continuous damage phase-field model and discrete cohesive crack model for concrete fracture. Eng. Fract. Mech. 278, 109030 (2023). https://doi.org/10.1016/j.engfracmech.2022.109030

    Article  Google Scholar 

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Funding

The study was funded by the National Key R&D Program of China (No. 2017YFC1503103), and the National Natural Science Foundation of China (No. 52074292).

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Correspondence to Lingfei Zhang.

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Zhu, T., Chen, Z., Nian, G. et al. Influence of 3D Aggregate Shape on the Meso-Structure of 2D Cross-Sectional Concrete by the Numerical Slicing Method. Arab J Sci Eng 49, 4655–4673 (2024). https://doi.org/10.1007/s13369-023-08196-8

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