On parallel scalability aspects of strongly coupled partitioned fluid-structure-acoustics interaction

Multi-physics simulations, such as fluid-structure-acoustics interaction (FSA), require a high performance computing environment in order to perform the simulation in a reasonable amount of computation time. Currently used coupling methods use a staggered execution of the fluid and solid solver [6], which leads to inherent load imbalances. In [12] a new coupling scheme based on a quasi-Newton method is proposed for fluidstructure interaction which coupled the fluid and solid solver in parallel. The quasi- Newton method requires approximately the same number of coupling iterations per time step compared to a staggered coupling approach, resulting in a better load balance when running in a parallel environment. This contribution investigates the scalability limit and load-balancing for a strongly coupled fluid-structure interaction problem, and also for a fluid-structure-acoustics interaction problem. The acoustic far field of the fluid-structure-acoustics interaction problem is loosely coupled with the flow field

An integrated particle model for fluid–particle–structure interaction problems with free-surface flow and structural failure

Discrete Element Method (DEM) and Smoothed Particles Hydrodynamics (SPH) are integrated to investigate the macroscopic dynamics of fluid-particle-structure interaction (FPSI) problems. With SPH the fluid phase is represented by a set of particle elements moving in accordance with the Navier-Stokes equations. The solid phase consists of physical particle(s) and deformable solid structure(s) which are represented by DEM using a linear contact model and a linear parallel contact model to account for the interaction between particle elements, respectively. To couple the fluid phase and solid particles, a local volume fraction and a weighted average algorithm are proposed to reformulate the governing equations and the interaction forces. The structure is coupled with the fluid phase by incorporating the structure's particle elements in SPH algorithm. The interaction forces between the solid particles and the structure are computed using the linear contact model in DEM. The proposed model is capable of simulating simultaneously fluid-structure interaction (FSI), particle-particle interaction and fluid-particle interaction (FPI), with good agreement between complicated hybrid numerical methods and experimental results being achieved. Finally, a specific test is carried out to demonstrate the capability of the integrated particle model for simulating FPSI problems with the occurrence of structural failure

Parallel Overlapping Schwarz Preconditioners for Incompressible Fluid Flow and Fluid-Structure Interaction Problems

Efficient methods for the approximation of solutions to incompressible fluid flow and fluid-structure interaction problems are presented. In particular, partial differential equations (PDEs) are derived from basic conservation principles. First, the incompressible Navier-Stokes equations for Newtonian fluids are introduced. This is followed by a consideration of solid mechanical problems. Both, the fluid equations and the equation for solid problems are then coupled and a fluid-structure interaction problem is constructed. Furthermore, a discretization by the finite element method for weak formulations of these problems is described. This spatial discretization of variables is followed by a discretization of the remaining time-dependent parts. An implementation of the discretizations and problems in a parallel C++ software environment is described. This implementation is based on the software package Trilinos. The parallel execution of a program is the essence of High Performance Computing (HPC). HPC clusters are, in general, machines with several tens of thousands of cores. The fastest current machine, as of the TOP500 list from November 2019, has over 2.4 million cores, while the largest machine possesses over 10 million cores. To achieve sufficient accuracy of the approximate solutions, a fine spatial discretization must be used. In particular, fine spatial discretizations lead to systems with large sparse matrices that have to be solved. Iterative preconditioned Krylov methods are among the most widely used and efficient solution strategies for these systems. Robust and efficient preconditioners which possess good scaling behavior for a parallel execution on several thousand cores are the main component. In this thesis, the focus is on parallel algebraic preconditioners for fluid and fluid-structure interaction problems. Therefore, monolithic overlapping Schwarz preconditioners for saddle point problems of Stokes and Navier-Stokes problems are presented. Monolithic preconditioners for incompressible fluid flow problems can significantly improve the convergence speed compared to preconditioners based on block factorizations. In order to obtain numerically scalable algorithms, coarse spaces obtained from the Generalized Dryja-Smith-Widlund (GDSW) and the Reduced dimension GDSW (RGDSW) approach are used. These coarse spaces can be constructed in an essentially algebraic way. Numerical results of the parallel implementation are presented for various incompressible fluid flow problems. Good scalability for up to 11 979 MPI ranks, which corresponds to the largest problem configuration fitting on the employed supercomputer, were achieved. A comparison of these monolithic approaches and commonly used block preconditioners with respect to time-to-solution is made. Similarly, the most efficient construction of two-level overlapping Schwarz preconditioners with GDSW and RGDSW coarse spaces for solid problems is reported. These techniques are then combined to efficiently solve fully coupled monolithic fluid-strucuture interaction problems

The LifeV library: engineering mathematics beyond the proof of concept

LifeV is a library for the finite element (FE) solution of partial differential equations in one, two, and three dimensions. It is written in C++ and designed to run on diverse parallel architectures, including cloud and high performance computing facilities. In spite of its academic research nature, meaning a library for the development and testing of new methods, one distinguishing feature of LifeV is its use on real world problems and it is intended to provide a tool for many engineering applications. It has been actually used in computational hemodynamics, including cardiac mechanics and fluid-structure interaction problems, in porous media, ice sheets dynamics for both forward and inverse problems. In this paper we give a short overview of the features of LifeV and its coding paradigms on simple problems. The main focus is on the parallel environment which is mainly driven by domain decomposition methods and based on external libraries such as MPI, the Trilinos project, HDF5 and ParMetis. Dedicated to the memory of Fausto Saleri.Comment: Review of the LifeV Finite Element librar

GPUs Based Material Point Method for Compressible Flows

Particle-In-Cell (PIC) methods such as the Material Point Method (MPM) can be cast in formulations suitable to the requirements of data locality and fine-grained parallelism of modern hardware accelerators such as Graphics Processing Units (GPUs). While continuum mechanics simulations have already shown the capabilities of MPM on a wide range of phenomena, the use of the method in compressible gas dynamics is less frequent. This contribution aims to show the potential of a GPU-based MPM parallel implementation for compressible fluid dynamics, as well as to assess the reliability of this approach in reproducing supersonic gas flows against solid obstacles. The results in the paper represent a stepping stone towards a highly parallel, Multi-GPU, MPM-base solver for M ach > 1 Fluid-Structure Interaction problems

Computational Modelling of Fluid-Solid Interaction Problems by Coupling Smoothed Particles Hydrodynamics and the Discrete Element Method

Discrete Element Method (DEM) and Smoothed Particles Hydrodynamics (SPH) are integrated to investigate the macroscopic dynamics of fluid-solid interaction (FSI) problems. This coupled model is originated from two different meshless methods without mesh generation, which can handle fluid-particle-structure interactions with structural deformation/failure. With SPH the fluid phase is represented by a set of SPH particle elements moving in accordance with the Navier-Stokes equations. The solid phase consists of single or multiple solid particle(s) phase and deformable structure(s) phase which are represented by DEM particle elements using a linear contact model and a linear parallel contact model to account for the interaction between particle elements, respectively. To couple the fluid phase and solid particle phase, a local volume fraction and a weighted average algorithm are proposed to reformulate the governing equations and the interaction forces. The structure phase is coupled with the fluid phase by incorporating the structure’s DEM particle elements in SPH algorithm. The interaction forces between the solid particles and the structure phases are computed using the linear contact model in DEM. The proposed model is capable of simulating simultaneously fluid-structure interaction, particleparticle interaction and fluid-particle interaction, with good agreement between complicated hybrid numerical methods and experimental results being achieved. Finally, two engineering problems in injection moulding and 3D printing process are carried out to demonstrate the capability of the integrated particle model for simulating fluid-solid interaction problems with the occurrence of structural failure

Uintah hybrid task-based parallelism algorithm

pre-printAbstract-Uintah is a software framework that provides an environment for solving large-scale science and engineering problems involving the solution of partial differential equations. Uintah uses a combination of fluid-flow solvers and particle-based methods for solids, together with adaptive meshing and asynchronous task-based approach with automated load balancing. When applying Uintah to fluid-structure interaction problems, the combination of adaptive meshing and the movement of structures through space present a formidable challenge in terms of achieving scalability on large-scale parallel computers. Adopting a model that uses MPI to communicate between nodes and a shared memory model on-node is one approach to achieve scalability on large-scale systems.This scalability challenge is addressed here for Uintah, by the development of new hybrid runtime and scheduling algorithms combined with novel lock-free data structures, making it possible for Uintah to achieve excellent scalability for a challenging fluid-structure problem with mesh refinement on as many as 256K cores