In this paper, we investigate the coupling of reduced models for the simulation of structures involving localized geometrical details. Herein, we use the Arlequin method, originally designed to deal with multimodel and multiscale analyses of mechanical problems, to mix reduced models built using the proper generalized decomposition. Instead of solving the global coupled problem in a monolithic way, the LATIN strategy is used to propose a decoupled algorithm. The numerical examples demonstrate the feasibility of the approach and in particular its potentiality in terms of flexibility. [ABSTRACT FROM AUTHOR]
In this paper, we present a dynamic refinement algorithm for the smoothed particle Hydrodynamics (SPH) method. An SPH particle is refined by replacing it with smaller daughter particles, which positions are calculated by using a square pattern centered at the position of the refined particle. We determine both the optimal separation and the smoothing distance of the new particles such that the error produced by the refinement in the gradient of the kernel is small and possible numerical instabilities are reduced. We implemented the dynamic refinement procedure into two different models: one for free surface flows, and one for post-failure flow of non-cohesive soil. The results obtained for the test problems indicate that using the dynamic refinement procedure provides a good trade-off between the accuracy and the cost of the simulations. [ABSTRACT FROM AUTHOR]