Numerical Simulation of Concrete Mix Structure and Detection of its Elastic Stiffness

Document Type: Original Article

Authors

1 Department of Mechanical Engineering, College of Engineering, King Faisal University, Al Hofoof, KSA

2 Department of Civil Engineering, Faculty of Engineering, Hashemite University, Zarqa, Jordan

Abstract

Concrete mix stiffness (CM) primarily relies on its ingredients, which mainly consists of stone aggregate and mortar. To analyse the role of the components of CM on its properties a numerical simulation of CM structure is conducted. Within the scope of this study, the structure and the properties of CM are simulated using ANSYS code to apply the finite element method (FEM). The size of aggregate is modelled using direct random nodes and elements and the problem is approximated as two-dimensional plane one. Different ratios of aggregate and mortar were considered to determine their influence on the stiffness of CM. The CM is treated as bi-composite and subjected to compressive loading. For determining the influence of the proportion of stone aggregate on the stiffness of CM, the used specimens only differ in the amount of stone aggregate and their shapes. Although the stone aggregates are assumed to be of cylindrical shapes (plane conditions), the compressive stiffness of CM works well with the mixture rule.

Highlights

Google Scholar

Keywords

Main Subjects


[1]       Persson B. A comparison between mechanical properties of self-compacting concrete and the corresponding properties of normal concrete. Cem Concr Res 2001;31:193–8. doi:10.1016/S0008-8846(00)00497-X.

[2]       Bahari A, Berenjian J, Sadeghi-Nik A. Modification of Portland Cement with Nano SiC. Proc Natl Acad Sci India Sect A Phys Sci 2016;86:323–31. doi:10.1007/s40010-015-0244-y.

[3]       Sadeghi-Nik A, Berenjian J, Bahari A, Safaei AS, Dehestani M. Modification of microstructure and mechanical properties of cement by nanoparticles through a sustainable development approach. Constr Build Mater 2017;155:880–91. doi:10.1016/j.conbuildmat.2017.08.107.

[4]       Bahari A, Sadeghi Nik A, Roodbari M, Mirshafiei E, Amiri B. Effect of Silicon Carbide Nano Dispersion on the Mechanical and Nano Structural Properties of Cement. Natl Acad Sci Lett 2015;38:361–4. doi:10.1007/s40009-014-0316-6.

[5]       Wu K-R, Chen B, Yao W, Zhang D. Effect of coarse aggregate type on mechanical properties of high-performance concrete. Cem Concr Res 2001;31:1421–5. doi:10.1016/S0008-8846(01)00588-9.

[6]       Rao GA, Prasad BKR. Influence of the roughness of aggregate surface on the interface bond strength. Cem Concr Res 2002;32:253–7. doi:10.1016/S0008-8846(01)00668-8.

[7]       González-Peña R, Martı́-López L, Cibrián-Ortiz de Anda RM, Molina-Jiménez T, Piqueres-Ayela C. Measurement of Young’s modulus of cementitious materials using an electro-optic holographic technique. Opt Lasers Eng 2001;36:527–35. doi:10.1016/S0143-8166(01)00080-X.

[8]       Grote DL, Park SW, Zhou M. Dynamic behavior of concrete at high strain rates and pressures: I. experimental characterization. Int J Impact Eng 2001;25:869–86. doi:10.1016/S0734-743X(01)00020-3.

[9]       Wong YL, Lam L, Poon CS, Zhou FP. Properties of fly ash-modified cement mortar-aggregate interfaces. Cem Concr Res 1999;29:1905–13. doi:10.1016/S0008-8846(99)00189-1.

[10]     Wang ZM, Kwan AKH, Chan HC. Mesoscopic study of concrete I: generation of random aggregate structure and finite element mesh. Comput Struct 1999;70:533–44. doi:10.1016/S0045-7949(98)00177-1.

[11]     Willam K, Rhee I, Beylkin G. No Title. Meccanica 2001;36:131–50. doi:10.1023/A:1011905201001.

[12]     Lai S, Serra M. Concrete strength prediction by means of neural network. Constr Build Mater 1997;11:93–8. doi:10.1016/S0950-0618(97)00007-X.

[13]     Zhao X-H, Chen WF. Effective elastic moduli of concrete with interface layer. Comput Struct 1998;66:275–88. doi:10.1016/S0045-7949(97)00056-4.

[14]     Hashin Z, Monteiro PJM. An inverse method to determine the elastic properties of the interphase between the aggregate and the cement paste. Cem Concr Res 2002;32:1291–300. doi:10.1016/S0008-8846(02)00792-5.

[15]     Park SW, Xia Q, Zhou M. Dynamic behavior of concrete at high strain rates and pressures: II. numerical simulation. Int J Impact Eng 2001;25:887–910. doi:10.1016/S0734-743X(01)00021-5.

[16]     Kwan AKH, Wang ZM, Chan HC. Mesoscopic study of concrete II: nonlinear finite element analysis. Comput Struct 1999;70:545–56. doi:10.1016/S0045-7949(98)00178-3.

[17]     Li G, Zhao Y, Pang S-S. A three-layer built-in analytical modeling of concrete. Cem Concr Res 1998;28:1057–70. doi:10.1016/S0008-8846(98)00062-3.

[18]     Khademi F, Jamal SM, Deshpande N, Londhe S. Predicting strength of recycled aggregate concrete using Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System and Multiple Linear Regression. Int J Sustain Built Environ 2016;5:355–69. doi:10.1016/j.ijsbe.2016.09.003.

[19]     Khademi F, Akbari M, Jamal SM, Nikoo M. Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete. Front Struct Civ Eng 2017;11:90–9. doi:10.1007/s11709-016-0363-9.

[20]     Boresi AP, Chong K, Lee JD. Elasticity in engineering mechanics. Wiley; 2011.

[21]     Callister WD, Rethwisch DG. Materials Science and Engineering An Introduction Library of Congress Cataloging-in-Publication Data 2003.