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One of the most important aspects in tsunami studies is the wave behavior when it approaches the coast. Information on physical parameters that characterize waves is often limited because of the diffilculties in achieving accurate measurements at the time of the event. The impact of a tsunami on the coast is governed by nonlinear physics such as turbulence with spatial and temporal variability. The use of the Smoothed Particle Hydrodynamic method (SPH) presents advantages over models based on two-dimensional Shallow Waters Equations (SWE), because the assumed vertical velocity simplifies hydrodynamics in two dimensions. The study presented here reports numerical SPH simulations of the tsunami event occurred in Coquimbo (Chile) on September 16 of 2015. On the basis of the reconstruction of the physical parameters that characterized this event (flow velocities, direction and water elevations), calibrated by a reference rodel, force values on buildings located on the study coast were numerically calculated, and compared with an estimate of the Chilean Structural Design Standard. Finally, discussion and conclusions of the comparison of both methodologies are presented, including an influence analysis of the topographical detail of the model in the estimation of hydrodynamic forces.
We present a three--pronged numerical approach to the dynamo problem at low magnetic Prandtl numbers $P_M$. The difficulty of resolving a large range of scales is circumvented by combining Direct Numerical Simulations, a Lagrangian-averaged model, an
This paper presents an extension of the hybrid scheme proposed by Wang et al. (J. Comput. Phys. 229 (2010) 169-180) for numerical simulation of compressible isotropic turbulence to flows with higher turbulent Mach numbers. The scheme still utilizes a
Corridors of size-selected crescent-shaped dunes, known as barchans, are commonly found in water, air, and other planetary environments. The growth of barchans results from the interplay between a fluid flow and a granular bed, but their size regulat
We propose a super-resolution (SR) simulation system that consists of a physics-based meteorological simulation and an SR method based on a deep convolutional neural network (CNN). The CNN is trained using pairs of high-resolution (HR) and low-resolu
The intent of this paper is to discuss the history and origins of Lagrangian hydrodynamic methods for simulating shock driven flows. The majority of the pioneering research occurred within the Manhattan Project. A range of Lagrangian hydrodynamic sch