In present study, BP neural network model was proposed for the prediction of ultimate compressive strength of Al2O3-ZrO2 ceramic foam filter prepared by centrifugal slip casting. The inputs of the BP neural network mo...In present study, BP neural network model was proposed for the prediction of ultimate compressive strength of Al2O3-ZrO2 ceramic foam filter prepared by centrifugal slip casting. The inputs of the BP neural network model were the applied load on the epispastic polystyrene template （F）, centrifugal acceleration （v） and sintering temperature （T）, while the only output was the ultimate compressive strength （（7）. According to the registered BP model, the effects of F, v, T on 0 were analyzed. The predicted results agree with the actual data within reasonable experimental error, indicating that the BP model is practically a very useful tool in property prediction and process parameter design of the Al2O3-ZrO2 ceramic foam filter prepared by centrifugal slip casting.展开更多
The aim of this paper is to develop computational models for the ultimate compressive strength analysis of stiffened plate panels with nonuniform thickness.Modeling welding-induced initial deformations and residual st...The aim of this paper is to develop computational models for the ultimate compressive strength analysis of stiffened plate panels with nonuniform thickness.Modeling welding-induced initial deformations and residual stresses was presented with the measured data.Three methods,i.e.,ANSYS finite element method,ALPS/SPINE incremental Galerkin method,and ALPS/ULSAP analytical method,were employed together with existing test database obtained from a full-scale collapse testing of steel-stiffened plate structures.Sensitivity study was conducted with varying the difference in plate thickness to define a representative(equivalent)thickness for plate panels with nonuniform thickness.Guidelines are provided for structural modeling to compute the ultimate compressive strength of plate panels with variable thickness.展开更多
基金financially supported by the Innovation Research Team Program of the Ministry of Education(IRT0713)the Key Laboratory of New Materials in Automobile of Liaoning Province(grant No.201016201)Doctoral Initiating Project of Liaoning Province Foundation for Natural Sciences,China
文摘In present study, BP neural network model was proposed for the prediction of ultimate compressive strength of Al2O3-ZrO2 ceramic foam filter prepared by centrifugal slip casting. The inputs of the BP neural network model were the applied load on the epispastic polystyrene template （F）, centrifugal acceleration （v） and sintering temperature （T）, while the only output was the ultimate compressive strength （（7）. According to the registered BP model, the effects of F, v, T on 0 were analyzed. The predicted results agree with the actual data within reasonable experimental error, indicating that the BP model is practically a very useful tool in property prediction and process parameter design of the Al2O3-ZrO2 ceramic foam filter prepared by centrifugal slip casting.
文摘The aim of this paper is to develop computational models for the ultimate compressive strength analysis of stiffened plate panels with nonuniform thickness.Modeling welding-induced initial deformations and residual stresses was presented with the measured data.Three methods,i.e.,ANSYS finite element method,ALPS/SPINE incremental Galerkin method,and ALPS/ULSAP analytical method,were employed together with existing test database obtained from a full-scale collapse testing of steel-stiffened plate structures.Sensitivity study was conducted with varying the difference in plate thickness to define a representative(equivalent)thickness for plate panels with nonuniform thickness.Guidelines are provided for structural modeling to compute the ultimate compressive strength of plate panels with variable thickness.
