Transient meshless boundary element method for prediction of chloride diffusion in concrete with time dependent nonlinear coefficients

被引:20
|
作者
Guo, Li [1 ,2 ]
Chen, Tang [1 ]
Gao, Xiao-Wei [3 ]
机构
[1] Southeast Univ, Sch Civil Engn, Dept Engn Mech, Nanjing 210096, Peoples R China
[2] Southeast Univ, Jiangsu Key Lab Engn Mech, Nanjing 210096, Peoples R China
[3] Dalian Univ Technol, State Key Lab Struct Anal Ind Equipment, Dalian 116024, Peoples R China
关键词
Meshless boundary element method; Chloride diffusion; Time dependent coefficient; Concentration coupled coefficient; Concrete structural durability; SERVICE LIFE PREDICTION; PENETRATION; INGRESS;
D O I
10.1016/j.enganabound.2011.08.005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Chloride-induced corrosion of steel reinforcements has been identified as one of the main causes of deterioration of concrete structures. A feasible numerical method is required to predict chloride penetration in concrete structures. A transient meshless boundary element method is proposed to predict chloride diffusion in concrete with time dependent nonlinear coefficient. Taking Green's function as the weighted function, the weighted residue method is adopted to transform the diffusion equation into equivalent integral equations. By the coupling of radial integral method and radial basis function approximation, the domain integrals in equivalent control equations are transformed into boundary integrals. Following the general procedure of boundary element meshing and traditional finite difference method, a set of nonlinear algebraic equations are constructed and are eventually solved with the modified Newtonian iterative method. Several numerical examples are provided to demonstrate the effectiveness and efficiency of the developed model. A comparison of the simulated chloride concentration with the corresponding reported experimental data in a real marine structure indicates the high accuracy and advantage of the time dependent coefficient and nonlinear model over the conventional constant coefficient model. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:104 / 111
页数:8
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