Ship collision on bridge is a dynamic process featured by high nonlinearity and instantaneity. Calculating ship-bridge collision force typically involves either the use of design-specification-stipulated equivalent st...Ship collision on bridge is a dynamic process featured by high nonlinearity and instantaneity. Calculating ship-bridge collision force typically involves either the use of design-specification-stipulated equivalent static load, or the use of finite element method (FEM) which is more time-consuming and requires supercomputing resources. In this paper, we proposed an alternative approach that combines FEM with artificial neural network (ANN). The radial basis function neural network (RBFNN) employed for calculating the impact force in consideration of ship-bridge collision mechanics. With ship velocity and mass as the input vectors and ship collision force as the output vector, the neural networks for different network parameters are trained by the learning samples obtained from finite element simulation results. The error analyses of the learning and testing samples show that the proposed RBFNN is accurate enough to calculate ship-bridge collision force. The input-output relationship obtained by the RBFNN is essentially consistent with the typical empirical formulae. Finally, a special toolbox is developed for calculation efficiency in application using MATLAB software.展开更多
For the dynamic demand assessment of bridge structures under ship impact loading,it may be prudent to adopt analytical models which permit rapid analysis with reasonable accuracy.Herein,a nonlinear dynamic macro-eleme...For the dynamic demand assessment of bridge structures under ship impact loading,it may be prudent to adopt analytical models which permit rapid analysis with reasonable accuracy.Herein,a nonlinear dynamic macro-element is proposed and implemented to quantify the demand of bridge substructures subjected to ship collisions.In the proposed nonlinear macro-element,a combination of an elastic-plastic spring and a dashpot in parallel is employed to describe the mechanical behavior of ship-bows with strain rate effects.Based on the analytical model using the proposed macro-element,a typical substructure under 5000 deadweight tonnage(DWT) ship collision is discussed.Our analyses indicate that the responses of the structure using the nonlinear macro-element agree with the results from the high resolution model,but the efficiency and feasibility of the proposed method increase significantly in practical applications.Furthermore,comparisons between some current design codes(AASHTO,JTGD60-2004,and TB10002.1-2005) and the developed dynamic analysis method suggest that these design codes may be improved,at least to consider the effect of dynamic amplification on structural demand.展开更多
基金the National Natural Science Foundation of China (No. 50778131)the National key Technology R&D Pro-gram, Ministry of Science and Technology (No. 2006BAG04B01), China
文摘Ship collision on bridge is a dynamic process featured by high nonlinearity and instantaneity. Calculating ship-bridge collision force typically involves either the use of design-specification-stipulated equivalent static load, or the use of finite element method (FEM) which is more time-consuming and requires supercomputing resources. In this paper, we proposed an alternative approach that combines FEM with artificial neural network (ANN). The radial basis function neural network (RBFNN) employed for calculating the impact force in consideration of ship-bridge collision mechanics. With ship velocity and mass as the input vectors and ship collision force as the output vector, the neural networks for different network parameters are trained by the learning samples obtained from finite element simulation results. The error analyses of the learning and testing samples show that the proposed RBFNN is accurate enough to calculate ship-bridge collision force. The input-output relationship obtained by the RBFNN is essentially consistent with the typical empirical formulae. Finally, a special toolbox is developed for calculation efficiency in application using MATLAB software.
基金supported by the Ministry of Science and Technology of China (No. SLDRCE 09-B-08)the National Natural Science Foundation of China (Nos. 50978194 and 90915011)+1 种基金the Kwang-Hua Fund for College of Civil Engineering,Tongji Universitythe Fund of National Engineering and Research Center for Highways in Mountain Area (No. gsgzj-2010-01),China
文摘For the dynamic demand assessment of bridge structures under ship impact loading,it may be prudent to adopt analytical models which permit rapid analysis with reasonable accuracy.Herein,a nonlinear dynamic macro-element is proposed and implemented to quantify the demand of bridge substructures subjected to ship collisions.In the proposed nonlinear macro-element,a combination of an elastic-plastic spring and a dashpot in parallel is employed to describe the mechanical behavior of ship-bows with strain rate effects.Based on the analytical model using the proposed macro-element,a typical substructure under 5000 deadweight tonnage(DWT) ship collision is discussed.Our analyses indicate that the responses of the structure using the nonlinear macro-element agree with the results from the high resolution model,but the efficiency and feasibility of the proposed method increase significantly in practical applications.Furthermore,comparisons between some current design codes(AASHTO,JTGD60-2004,and TB10002.1-2005) and the developed dynamic analysis method suggest that these design codes may be improved,at least to consider the effect of dynamic amplification on structural demand.
