The finite_element_displacement_perturbation method (FEDPM)for the geometric nonlinear behaviors of shells of revolution subjected to pure bending moments or lateral forces in one of their meridional planes (Ⅰ) was e...The finite_element_displacement_perturbation method (FEDPM)for the geometric nonlinear behaviors of shells of revolution subjected to pure bending moments or lateral forces in one of their meridional planes (Ⅰ) was employed to calculate the stress distributions and the stiffness of the bellows. Firstly, by applying the first_order perturbation solution (the linear solution)of the FEDPM to the bellows, the obtained results were compared with those of the general solution and the initial parameter integration solution proposed by the present authors earlier, as well as of the experiments and the FEA by others.It is shown that the FEDPM is with good precision and reliability, and as it was pointed out in (Ⅰ) the abrupt changes of the meridian curvature of bellows would not affect the use of the usual straight element. Then the nonlinear behaviors of the bellows were discussed. As expected, the nonlinear effects mainly come from the bellows ring plate,and the wider the ring plate is, the stronger the nonlinear effects are. Contrarily, the vanishing of the ring plate, like the C_shaped bellows, the nonlinear effects almost vanish. In addition, when the pure bending moments act on the bellows, each convolution has the same stress distributions calculated by the linear solution and other linear theories, but by the present nonlinear solution they vary with respect to the convolutions of the bellows. Yet for most bellows, the linear solutions are valid in practice.展开更多
In order to analyze bellows effectively and practically, the finite_element_displacement_perturbation method (FEDPM) is proposed for the geometric nonlinear behaviors of shells of revolution subjected to pure bending ...In order to analyze bellows effectively and practically, the finite_element_displacement_perturbation method (FEDPM) is proposed for the geometric nonlinear behaviors of shells of revolution subjected to pure bending moments or lateral forces in one of their meridional planes. The formulations are mainly based upon the idea of perturba_ tion that the nodal displacement vector and the nodal force vector of each finite element are expanded by taking root_mean_square value of circumferential strains of the shells as a perturbation parameter. The load steps and the iteration times are not as arbitrary and unpredictable as in usual nonlinear analysis. Instead, there are certain relations between the load steps and the displacement increments, and no need of iteration for each load step. Besides, in the formulations, the shell is idealized into a series of conical frusta for the convenience of practice, Sander's nonlinear geometric equations of moderate small rotation are used, and the shell made of more than one material ply is also considered.展开更多
Machine learning methods have advantages in predicting excavation-induced lateral wall displacements.Due to lack of sufficient field data,training data for prediction models were often derived from the results of nume...Machine learning methods have advantages in predicting excavation-induced lateral wall displacements.Due to lack of sufficient field data,training data for prediction models were often derived from the results of numerical simulations,leading to poor prediction accuracy.Based on a specific quantity of data,a multivariate adaptive regression splines method(MARS)was introduced to predict lateral wall deflections caused by deep excavations in thick water-rich sands.Sensitivity of lateral wall deflections to affecting factors was analyzed.It is disclosed that dewatering mode has the most significant influence on lateral wall deflections,while the soil cohesion has the least influence.Using crossvalidation analysis,weights were introduced to modify the MARS method to optimize the prediction model.Comparison of the predicted and measured deflections shows that the prediction based on the modified multivariate adaptive regression splines method(MMARS)is more accurate than that based on the traditional MARS method.The prediction model established in this paper can help engineers make predictions for wall displacement,and the proposed methodology can also serve as a reference for researchers to develop prediction models.展开更多
文摘The finite_element_displacement_perturbation method (FEDPM)for the geometric nonlinear behaviors of shells of revolution subjected to pure bending moments or lateral forces in one of their meridional planes (Ⅰ) was employed to calculate the stress distributions and the stiffness of the bellows. Firstly, by applying the first_order perturbation solution (the linear solution)of the FEDPM to the bellows, the obtained results were compared with those of the general solution and the initial parameter integration solution proposed by the present authors earlier, as well as of the experiments and the FEA by others.It is shown that the FEDPM is with good precision and reliability, and as it was pointed out in (Ⅰ) the abrupt changes of the meridian curvature of bellows would not affect the use of the usual straight element. Then the nonlinear behaviors of the bellows were discussed. As expected, the nonlinear effects mainly come from the bellows ring plate,and the wider the ring plate is, the stronger the nonlinear effects are. Contrarily, the vanishing of the ring plate, like the C_shaped bellows, the nonlinear effects almost vanish. In addition, when the pure bending moments act on the bellows, each convolution has the same stress distributions calculated by the linear solution and other linear theories, but by the present nonlinear solution they vary with respect to the convolutions of the bellows. Yet for most bellows, the linear solutions are valid in practice.
文摘In order to analyze bellows effectively and practically, the finite_element_displacement_perturbation method (FEDPM) is proposed for the geometric nonlinear behaviors of shells of revolution subjected to pure bending moments or lateral forces in one of their meridional planes. The formulations are mainly based upon the idea of perturba_ tion that the nodal displacement vector and the nodal force vector of each finite element are expanded by taking root_mean_square value of circumferential strains of the shells as a perturbation parameter. The load steps and the iteration times are not as arbitrary and unpredictable as in usual nonlinear analysis. Instead, there are certain relations between the load steps and the displacement increments, and no need of iteration for each load step. Besides, in the formulations, the shell is idealized into a series of conical frusta for the convenience of practice, Sander's nonlinear geometric equations of moderate small rotation are used, and the shell made of more than one material ply is also considered.
基金Financial support from the National Natural Science Foundation of China(Grant No.42177179)is gratefully acknowledged.
文摘Machine learning methods have advantages in predicting excavation-induced lateral wall displacements.Due to lack of sufficient field data,training data for prediction models were often derived from the results of numerical simulations,leading to poor prediction accuracy.Based on a specific quantity of data,a multivariate adaptive regression splines method(MARS)was introduced to predict lateral wall deflections caused by deep excavations in thick water-rich sands.Sensitivity of lateral wall deflections to affecting factors was analyzed.It is disclosed that dewatering mode has the most significant influence on lateral wall deflections,while the soil cohesion has the least influence.Using crossvalidation analysis,weights were introduced to modify the MARS method to optimize the prediction model.Comparison of the predicted and measured deflections shows that the prediction based on the modified multivariate adaptive regression splines method(MMARS)is more accurate than that based on the traditional MARS method.The prediction model established in this paper can help engineers make predictions for wall displacement,and the proposed methodology can also serve as a reference for researchers to develop prediction models.
