考虑骨料体积含量影响的混凝土准脆性断裂预测模型及应用

Translated title of the contribution: Quasi-brittle fracture model and application on concrete considering aggregate volume content effect

Ping Xu, Xiao Zhi Hu, Min Xia Zhang, Jin Yi Ma

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Based on the analysis of parameters in a Boundary Effect Model,the average aggregate size d ave has been introduced into the model. Whereafter, the quasi-brittle fracture prediction model on concrete considering aggregate volume content and size effect has been proposed. The ratio of effective notch length to characteristic crack length in this model can clarify the fracture failure criterion of the specimens as the variation of the dimension and initial notch length for single edge notched beams (SENB) in three-point-bending tests. The fictitious crack length in critical crack growth region at P max will be determined by the d ave and dispersion coefficient β ave in this model. Based on the stress analysis of the SENB at P max , the relationship between critical nominal strength σ n and effective notch length ae and tensile strength f t and fracture toughness K IC has been obtained. According to the experiment results performed by Amparano, the tensile strength and fracture toughness could be predicted well by the fracture model with the average fictitious crack length Δa fic =(0.8~1.4)d ave . The reliability and applicability of the fracture model proposed have been confirmed by the comparison of the prediction curves derived by the fracture model at Δa fic =1.2 d ave with the experiment results. According to the three-point-bending tests with SENB proposed by RILEM, tensile strength and fracture toughness can be predicted by the quasi-brittle fracture prediction model on concrete considering aggregate volume content effect.

Original languageChinese
Pages (from-to)75-84
Number of pages10
JournalGongcheng Lixue/Engineering Mechanics
Volume35
Issue number10
DOIs
Publication statusPublished - 1 Oct 2018

    Fingerprint

Cite this