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Prediction of Load Carrying Capacity of Corroded Reinforced Concrete Beam
作者姓名:范颖芳  周晶  冯新
作者单位:[1]StateKeyLaboratoryofCoastalandOffshoreEngineering,DalianUniversityofTechnolgy,Dalian116024,China [2]SchoolofCivilEngineering,TongjiUniversity,Shanghai200092,China
基金项目:ThisresearchwasfinanciallysupportedbytheProvincialFundProjectofLiaoningProvince (GrantNo .2 0 0 2 2 135 )
摘    要:A novel method for prediction of the load carrying capacity of a corroded reinforced concrete beam (CRCB) is presented in the paper. Nine reinforced concrete beams, which had been working in an aggressive environment for more than 10 years, were tested in the laboratory. Comprehensive tests, including flexural test, strength test for corroded concrete and rusty rebar, and pullout test for bond strength between concrete and rebar, were condueted. The flexural test results of CRCBs reveal that the distribution of surface cracks on the beams shows a fractal behavior. The relationship between the fractal dimensions and mechanical properties of CRCBs is then studied. A prediction model based on artificial neural network (ANN) is established by the use of the fractal dimension as the corrosion index, together with the basic intbrmation of the beam. The validity of the prediction model is demonstrated through the experimental data, and satisfactory resuits are achieved.

关 键 词:钢筋混凝土结构    弯曲检验  防腐蚀

Prediction of Load Carrying Capacity of Corroded Reinforced Concrete Beam
FAN Ying-fang a,ZHOU Jing a and FENG Xin b a State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technolgy,Dalian ,China b School of Civil Engineering,Tongji University,Shanghai ,China.Prediction of Load Carrying Capacity of Corroded Reinforced Concrete Beam[J].China Ocean Engineering,2004,18(1):107-118.
Authors:FAN Ying-fang a    ZHOU Jing a and FENG Xin b a State Key Laboratory of Coastal and Offshore Engineering  Dalian University of Technolgy  Dalian  China b School of Civil Engineering  Tongji University  Shanghai  China
Institution:FAN Ying-fang a,1,ZHOU Jing a and FENG Xin b a State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technolgy,Dalian 116024,China b School of Civil Engineering,Tongji University,Shanghai 200092,China
Abstract:A novel method for prediction of the load carrying capacity of a corroded reinforced concrete beam (CRCB) is presented in the paper. Nine reinforced concrete beams, which had been working in an aggressive environment for more than 10 years, were tested in the laboratory. Comprehensive tests, including flexural test, strength test for corroded concrete and rusty rebar, and pullout test for bond strength between concrete and rebar, were conducted. The flexural test results of CRCBs reveal that the distribution of surface cracks on the beams shows a fractal behavior. The relationship between the fractal dimensions and mechanical properties of CRCBs is then studied. A prediction model based on artificial neural network (ANN) is established by the use of the fractal dimension as the corrosion index, together with the basic information of the beam. The validity of the prediction model is demonstrated through the experimental data, and satisfactory results are achieved.
Keywords:corrosion  reinforced concrete beam  load carrying capacity  prediction  fractal  artificial neural network
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