In order to improve the strength and stiffness of shield cutterhead, the method of fuzzy mathematics theory in combination with the finite element analysis is adopted. An optimal design model of structural parameters ...In order to improve the strength and stiffness of shield cutterhead, the method of fuzzy mathematics theory in combination with the finite element analysis is adopted. An optimal design model of structural parameters for shield cutterhead is formulated,based on the complex engineering technical requirements. In the model, as the objective function of the model is a composite function of the strength and stiffness, the response surface method is applied to formulate the approximate function of objective function in order to reduce the solution scale of optimal problem. A multi-objective genetic algorithm is used to solve the cutterhead structure design problem and the change rule of the stress-strain with various structural parameters as well as their optimal values were researched under specific geological conditions. The results show that compared with original cutterhead structure scheme, the obtained optimal scheme of the cutterhead structure can greatly improve the strength and stiffness of the cutterhead, which can be seen from the reduction of its maximum equivalent stress by 21.2%, that of its maximum deformation by 0.75%, and that of its mass by 1.04%.展开更多
Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ri...Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.展开更多
To determine the onset and duration of contraflow evacuation, a multi-objective optimization(MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algor...To determine the onset and duration of contraflow evacuation, a multi-objective optimization(MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.展开更多
基金Project(51074180) supported by the National Natural Science Foundation of ChinaProject(2012AA041801) supported by the National High Technology Research and Development Program of China+2 种基金Project(2007CB714002) supported by the National Basic Research Program of ChinaProject(2013GK3003) supported by the Technology Support Plan of Hunan Province,ChinaProject(2010FJ1002) supported by Hunan Science and Technology Major Program,China
文摘In order to improve the strength and stiffness of shield cutterhead, the method of fuzzy mathematics theory in combination with the finite element analysis is adopted. An optimal design model of structural parameters for shield cutterhead is formulated,based on the complex engineering technical requirements. In the model, as the objective function of the model is a composite function of the strength and stiffness, the response surface method is applied to formulate the approximate function of objective function in order to reduce the solution scale of optimal problem. A multi-objective genetic algorithm is used to solve the cutterhead structure design problem and the change rule of the stress-strain with various structural parameters as well as their optimal values were researched under specific geological conditions. The results show that compared with original cutterhead structure scheme, the obtained optimal scheme of the cutterhead structure can greatly improve the strength and stiffness of the cutterhead, which can be seen from the reduction of its maximum equivalent stress by 21.2%, that of its maximum deformation by 0.75%, and that of its mass by 1.04%.
基金Project(51205299)supported by the National Natural Science Foundation of ChinaProject(2015M582643)supported by the China Postdoctoral Science Foundation+2 种基金Project(2014BAA008)supported by the Science and Technology Support Program of Hubei Province,ChinaProject(2014-IV-144)supported by the Fundamental Research Funds for the Central Universities of ChinaProject(2012AAA07-01)supported by the Major Science and Technology Achievements Transformation&Industrialization Program of Hubei Province,China
文摘Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.
基金Project(ADLT 930-809R)supported by the Alabama Department of Transportation,USA
文摘To determine the onset and duration of contraflow evacuation, a multi-objective optimization(MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.
