Abstract

The aim of this work is to carry out numerical simulations in the time domain of seakeeping problems taking into account internal flow in tanks, including sloshing. To this aim, a Smooth Particle Hydrodynamics (SPH) solver for simulating internal flows in tanks is coupled in the time domain to a Finite Element Method (FEM) diffraction-radiation solver developed for seakeeping problems. Validations are carried out comparing against available experimental data. Good agreement between obtained numerical results and experimental data is found.

Abstract

An advancing front space‐filling technique for arbitrary objects has been developed. The input required consists of the specification of the desired mean point distance in space and an initial triangulation of the surface. One object at a time is removed from the active front, and, if possible, surrounded by admissible new objects. This operation is repeated until no active objects are left. Two techniques to obtain maximum packing are discussed: closest object placement (during generation) and move/enlarge (after generation). Different deposition or layering patterns can be achieved by selecting the order in which objects are eliminated from the active front. Timings show that for simple objects like spheres the scheme is considerably faster than volume mesh generators based on the advancing front technique, making it possible to generate large (> 106) yet optimal clouds of points in a matter of minutes on a PC. For more general objects, the performance may degrade depending on the complexity of the penetration checks. Several examples are included that demonstrate the capabilities of the technique. 

Abstract

A review is given of advancing front techniques for filling space with arbitrary separated objects. Over the last decade, these techniques have reached a considerable degree of maturity and are being used to generate clouds of points for SPH and FPM simulations, as well as spheres, ellipsoids, objects defined by a collection of spheres or polyhedral objects for DEM simulations. Algorithmic as well as implementational aspects are discussed. Techniques to obtain maximum packing, such as closest object placement (during generation) and move/enlarge (after generation) are also considered. Several examples are included that demonstrate the capabilities developed.

Abstract

This paper proposes a methodology for the continuous blending of the finite element method and smooth particle hydrodynamics. The coupled approximation with finite elements and particles, and the discretization of the boundary value problem with a coupled integration, are described. An integration correction is also proposed to stabilize the solution. Some numerical examples demonstrate the applicability of the method.

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Abstract

A modular computational framework for the identification of friction parameters in metal machining applications is presented. Numerical simulation of such processes using mesh-based techniques (usually) necessitates the re-meshing procedure, which is time-consuming and hard to parallelize. Therefore, the present framework synthesizes the advantages of mesh-free methods with GPU parallel computing, offering an efficient tool for the optimization procedures in thermomechanical modeling of cutting problems. The proposed approach employs an inverse method to determine the unknown coefficients of a temperature-dependent friction model in high-speed metal cutting. We found good agreement between the numerical results and experimental data through a quantitative-qualitative comparison.

Abstract

The study of tumoral cells behaviour through computational models is arising. The movement of these cells is governed by physical laws; therefore, the different forces exerted between them need to be implemented. Nevertheless, biological criteria should be also considered since other factors, as oxygen level or cellular density, are decisive in the real movement. These phenomena are captured by probabilistic models such as the Agent Based Model (ABM). Following this research line, the present paper outlines a numerical model that tries to join both criteria with the aim of reproducing the behaviour of the cells that are part of a brain tumor: Glioblastoma Multiforme (GBM). The study has been carried out by the implementation of the different force equations in a Smoothed-Particle Hydrodynamic (SPH) framework. The SPH method is a meshfree lagrangian method based on the discretization of the study domain into finite particles which carry their own information, as tumoral cells do. Cohesive, viscous and pressure forces have been taking into account. Also, the possible attraction or repulsiveness between cells is considered through the implementation of a mechanical force formulation that combines the Maxwell and KelvinVoigt viscoelastic models. In addition to this forces approach, an energetic model is proposed to consider the results provided by an ABM. It evaluates the energy consumption and the associated extra-force that the cell needs to reach the ABM position, which is considered the biologically optimal one. The model has been tested under different sets of parameters, getting the logical outcome. Successful results have also been found in the evaluation of the energy consumption and, therefore, of the extra-force, finding a formulation that joins both criteria.

Abstract

This work is part of the ProTechTion project funded by MSCA - EU Horizon 2020, and consists of an Incremental Updated Lagrangian Smooth Particle Hydrodynamics (SPH) framework, aimed at applications in the field of fast solid dynamics, with the following highlights: - Mixed-based system of first-order conservation laws - Incremental ULF (multiplicative decomposition of the deformation) - Anisotropic updated kernel function - Entropy-stable Riemann-based stabilisation scheme.

Abstract

Debris flows are characterized as mixtures of solid particles and pore fluids, in which coupling between phases plays a paramount role in the dynamic behaviour. Due to the strong coupling between phases, pore pressures can be generated if the fluidized mass contains solid particles with low permeability. As such, a two-phase propagationconsolidation model should be applied to take into account the motion of each constituent and the time-space evolution of pore-water pressure. In this regard, the capability of a depth-integrated two-phase model, recently developed by the authors, to study the coupled behaviour of solid and fluid in a fluidized geomaterial is evaluated. The developed model is based on the mixture theory in which balance of mass and linear momentum are established for each phase. The computational framework is based on the mesh-free smoothed particle hydrodynamics (SPH), incorporating a 1D finite-difference mesh describing pore pressure's evolution along the vertical distribution of flowing mass. The model is applied to simulate the Johnsons Landing debris avalanche in order to reproduce its complex behaviours, including bifurcation occurred at the mid-channel. The developed two-phase depth-integrated SPH-FD model is also applied to assess the structural countermeasure of the bottom drainage screen, used to reduce the impact of debris flows. The analysis of the results indicates the adequacy of the method to model large deformation of the two-phase materials over an impermeable and permeable bottom boundary. This suggests that the proposed particle-based method is a promising approach for future studies of coupled geophysical problems.