The recently developed data-driven approach can establish the material law for nonlinear elastic composite materials(especially newly developed materials)by the generated stress-strain data under different loading pat...The recently developed data-driven approach can establish the material law for nonlinear elastic composite materials(especially newly developed materials)by the generated stress-strain data under different loading paths(Computational Mechanics,2019).Generally,the displacement(or strain)fields can be obtained relatively easier using digital image correlation(DIC)technique experimentally,but the stress field is hard to be measured.This situation limits the applicability of the proposed data-driven approach.In this paper,a method based on artificial neural network(ANN)to identify stress fields and further obtain the material law of nonlinear elastic materials is presented,which can make the proposed data-driven approach more practical.A numerical example is given to prove the validity of the method.The limitations of the proposed approach are also discussed.展开更多
The two one-state-variable, rate- and state-dependent friction laws, i.e., the slip and slowness laws, are com- pared on the basis of dynamical behavior of a one-degree-of-freedom spring-slider model through numerical...The two one-state-variable, rate- and state-dependent friction laws, i.e., the slip and slowness laws, are com- pared on the basis of dynamical behavior of a one-degree-of-freedom spring-slider model through numerical simulations. Results show that two （normalized） model parameters, i.e., A （the normalized characteristic slip distance） and β-α （the difference in two normalized parameters of friction laws）, control the solutions. From given values of △, β, and α, for the slowness laws, the solution exists and the unique non-zero fixed point is stable when △〉（β-α）, yet not when △ 〈（β-α）. For the slip law, the solution exists for large ranges of model parameters and the number and stability of the non-zero fixed points change from one case to another. Results suggest that the slip law is more appropriate for controlling earthquake dynamics than the slowness law.展开更多
基金the support from the National Natural Science Foundation of China (Grant 11872139)the support from the National Natural Science Foundation of China (Grants 11732004 and 11821202)Program for Changjiang Scholars, Innovative Research Team in University (PCSIRT)
文摘The recently developed data-driven approach can establish the material law for nonlinear elastic composite materials(especially newly developed materials)by the generated stress-strain data under different loading paths(Computational Mechanics,2019).Generally,the displacement(or strain)fields can be obtained relatively easier using digital image correlation(DIC)technique experimentally,but the stress field is hard to be measured.This situation limits the applicability of the proposed data-driven approach.In this paper,a method based on artificial neural network(ANN)to identify stress fields and further obtain the material law of nonlinear elastic materials is presented,which can make the proposed data-driven approach more practical.A numerical example is given to prove the validity of the method.The limitations of the proposed approach are also discussed.
基金supported by Academia Sinica (Taipei) and Science Council (Grant NSC96-2116-M-001-012-MY3).
文摘The two one-state-variable, rate- and state-dependent friction laws, i.e., the slip and slowness laws, are com- pared on the basis of dynamical behavior of a one-degree-of-freedom spring-slider model through numerical simulations. Results show that two （normalized） model parameters, i.e., A （the normalized characteristic slip distance） and β-α （the difference in two normalized parameters of friction laws）, control the solutions. From given values of △, β, and α, for the slowness laws, the solution exists and the unique non-zero fixed point is stable when △〉（β-α）, yet not when △ 〈（β-α）. For the slip law, the solution exists for large ranges of model parameters and the number and stability of the non-zero fixed points change from one case to another. Results suggest that the slip law is more appropriate for controlling earthquake dynamics than the slowness law.
