F. Xavier Trias

Conservation Properties of Unstructured Finite-Volume Mesh Schemes for the Navier-Stokes Equations

The Navier-Stokes equations describe fluid flow by conserving mass and momentum. There are two main mesh discretizations for the computation of these equations, the collocated and staggered schemes. Collocated schemes locate the velocity field at the same grid points as the pressure one, while staggered discretizations locate variables at different points within the mesh. One of the most important characteristic of the discretization schemes, aside from accuracy, is their capacity to discretely conserve kinetic energy, specially when solving turbulent flow. Hence, this work analyzes the accuracy and conservation properties of two particular collocated and staggered schemes by solving various problems.

Particulate Immersed Boundary Method for complex fluid-particle interaction problems with heat transfer

In our recent work (Zhang et?al., 2015), a Particulate Immersed Boundary Method (PIBM) for simulating fluid-particle multiphase flow was proposed and assessed in both two- and three-dimensional applications. In this study, the PIBM was extended to solve thermal interaction problems between spherical particles and fluid. The Lattice Boltzmann Method (LBM) was adopted to solve the fluid flow and temperature fields, the PIBM was responsible for the no-slip velocity and temperature boundary conditions at the particle surface, and the kinematics and trajectory of the solid particles were evaluated by the Discrete Element Method (DEM). Four case studies were implemented to demonstrate the capability of the current coupling scheme. Firstly, numerical simulation of natural convection in a two-dimensional square cavity with an isothermal concentric annulus was carried out for verification purpose. The current results were found to have good agreement with previous references. Then, sedimentation of two-and three-dimensional isothermal particles in fluid was numerically studied, respectively. The instantaneous temperature distribution in the cavity was captured. The effect of the thermal buoyancy on particle behaviors was discussed. Finally, sedimentation of three-dimensional thermosensitive particles in fluid was numerically investigated. Our results revealed that the LBM-PIBM-DEM is a promising scheme for the solution of complex fluid-particle interaction problems with heat transfer.

Memory Aware Poisson Solver for Peta-Scale Simulations with one FFT Diagonalizable Direction

Problems with some sort of divergence constraint are found in many disciplines: computational fluid dynamics, linear elasticity and electrostatics are examples thereof. Such a constraint leads to a Poisson equation which usually is one of the most computationally intensive parts of scientific simulation codes. In this work, we present a memory aware Poisson solver for problems with one Fourier diagonalizable direction. This diagonalization decomposes the original 3D system into a set of independent 2D subsystems. The proposed algorithm focuses on optimizing the memory allocations and transactions by taking into account redundancies on such 2D subsystems. Moreover, we also take advantage of the uniformity of the solver through the periodic direction for its vectorization. Additionally, our novel approach automatically optimizes the choice of the preconditioner used for the solution of each frequency subsystem and dynamically balances its parallel distribution. Altogether constitutes a highly efficient and robust HPC Poisson solver that has been successfully attested up to 16384 CPU-cores.Problems with some sort of divergence constraint are found in many disciplines: computational fluid dynamics, linear elasticity and electrostatics are examples thereof. Such a constraint leads to a Poisson equation which usually is one of the most computationally intensive parts of scientific simulation codes. In this work, we present a memory aware Poisson solver for problems with one Fourier diagonalizable direction. This diagonalization decomposes the original 3D system into a set of independent 2D subsystems. The proposed algorithm focuses on optimizing the memory allocations and transactions by taking into account redundancies on such 2D subsystems. Moreover, we also take advantage of the uniformity of the solver through the periodic direction for its vectorization. Additionally, our novel approach automatically optimizes the choice of the preconditioner used for the solution of each frequency subsystem and dynamically balances its parallel distribution. Altogether constitutes a highly efficient and robust HPC Poisson solver that has been successfully attested up to 16384 CPU-cores.

Spectrally-consistent regularization modeling of turbulent natural convection flows

The incompressible Navier-Stokes equations constitute an excellent mathematical modelization of turbulence. Unfortunately, attempts at performing direct simulations are limited to relatively low-Reynolds numbers because of the almost numberless small scales produced by the non-linear convective term. Alternatively, a dynamically less complex formulation is proposed here. Namely, regularizations of the Navier-Stokes equations that preserve the symmetry and conservation properties exactly. To do so, both convective and diffusive terms are altered in the same vein. In this way, the convective production of small scales is effectively restrained whereas the modified diffusive term introduces a hyperviscosity effect and consequently enhances the destruction of small scales. In practice, the only additional ingredient is a self-adjoint linear filter whose local filter length is determined from the requirement that vortex-stretching must stop at the smallest grid scale. In the present work, the performance of the above-mentioned recent improvements is assessed through application to turbulent natural convection flows by means of comparison with DNS reference data.