Numerical Simulation Study on the Constitutive Model of Fully-Graded Concrete Based on Statistical Damage Theory
Auteur(s): |
Chenyang Yuan
Chunlei Li Hao Huang Weifeng Bai Yunfei Xie |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 10 octobre 2023, n. 10, v. 13 |
Page(s): | 2412 |
DOI: | 10.3390/buildings13102412 |
Abstrait: |
A statistical damage model (SDM) of fully-graded concrete was created using statistical damage theory, based on the mechanical properties of axial tension and axial compression of the material. The SDM considers two damage modes, fracture and yield, and explains the intrinsic connection between the mesoscopic damage evolution mechanism and the macroscopic nonlinear mechanical behavior of fully-graded concrete. The artificial bee colony (ABC) algorithm was used to obtain the optimal parameter combination through an intelligent search of parameters εa, εh, εb and H in the constitutive model by taking the test data as the target value, and the sum of the squares of the differences between the target value and the predicted value as the objective function. The SDM numerical simulation model of fully-graded concrete is proposed by compiling subroutines in FORTRAN by constructing two modules of data model and damage analysis. The numerical results under uniaxial and biaxial forces are in agreement with the experimental results, which verifies the accuracy of the program. The model also analyzes the characteristics of mesoscopic damage evolution and predicts the mechanical properties under triaxial forces. The results show that the proposed numerical simulation model can reflect the salient features for fully-graded concrete under uniaxial, biaxial and triaxial loading conditions, and the evolution law of mesoscopic parameters. Therefore, the proposed model serves as a basis for the refined finite element analysis of hydraulic fully-graded concrete structures and reveals the mesoscopic damage mechanism of concrete under different load environments. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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sur cette fiche - Reference-ID
10744581 - Publié(e) le:
28.10.2023 - Modifié(e) le:
07.02.2024