arXiv subjects

Ulrich Rüde

Publications and source records attributed to Ulrich Rüde.

At least 37 records · Page 2Linked to original sources

arXiv2022

Comparison of refilling schemes in the free-surface lattice Boltzmann method

Simulating mobile liquid-gas interfaces with the free-surface lattice Boltzmann method (FSLBM) requires frequent re-initialization of fluid flow information in computational cells that convert from gas to liquid. The corresponding algorithm, here referred to as the refilling scheme, is crucial for the successful application of the FSLBM in terms of accuracy and numerical stability. This study compares five refilling schemes that extract information from the surrounding liquid and interface cells by averaging, extrapolating, or assuming one of the three different equilibrium states. Six numerical experiments were performed, covering a broad spectrum of possible scenarios. These include a standing gravity wave, a rectangular and cylindrical dam break, a Taylor bubble, a drop impact into liquid, and a bubbly plane Poiseuille flow. In some simulations, the averaging, extrapolation, and one equilibrium-based scheme were numerically unstable. Overall, the results have shown that the simplest equilibrium-based scheme should be preferred in terms of numerical stability, computational cost, accuracy, and ease of implementation.

physics.flu-dyn↗

arXiv2022

Advanced Automatic Code Generation for Multiple Relaxation-Time Lattice Boltzmann Methods

The scientific code generation package lbmpy supports the automated design and the efficient implementation of lattice Boltzmann methods (LBMs) through metaprogramming. It is based on a new, concise calculus for describing multiple relaxation-time LBMs, including techniques that enable the numerically advantageous subtraction of the constant background component from the populations. These techniques are generalized to a wide range of collision spaces and equilibrium distributions. The article contains an overview of lbmpy's front-end and its code generation pipeline, which implements the new LBM calculus by means of symbolic formula manipulation tools and object-oriented programming. The generated codes have only a minimal number of arithmetic operations. Their automatic derivation rests on two novel Chimera transforms that have been specifically developed for efficiently computing raw and central moments. Information contained in the symbolic representation of the methods is further exploited in a customized sequence of algebraic simplifications, further reducing computational cost. When combined, these algebraic transformations lead to concise and compact numerical kernels. Specifically, with these optimizations, the advanced central moment- and cumulant-based methods can be realized with only little additional cost as when compared with the simple BGK method. The effectiveness and flexibility of the new lbmpy code generation system is demonstrated in simulating Taylor-Green vortex decay and the automatic derivation of an LBM algorithm to solve the shallow water equations.

cs.MS↗

arXiv2022

Effect of Sediment Form and Form Distribution on Porosity: A Simulation Study Based on the Discrete Element Method

Porosity is one of the key properties of dense particle packings like sediment deposits and is influenced by a multitude of grain characteristics such as their size distribution and shape. In the present work, we focus on the form, a specific aspect of the overall shape, of sedimentary grains in order to investigate and quantify its effect on porosity, ultimately deriving novel porosity-prediction models. To this end, we develop a robust and accurate simulation tool based on the discrete element method which we validate against laboratory experiments. Utilizing digital representations of actual sediment from the Rhine river, we first study packings that are composed of particles with a single form. There, the porosity is found to be mainly determined by the inverse equancy, i.e., the ratio of the longest to the smallest form-defining axis. Only for small ratios, additional shape-related properties become relevant, as revealed by a direct comparison to packings of form-equivalent ellipsoids. Since sediment naturally features form mixtures, we extend our simulation tool to study sediment packings with normally-distributed forms. In agreement with our single form studies, the porosity depends primarily on the inverse of the mean equancy. By supplying additional information about a second form factor and the standard deviations, we derive an accurate model for porosity prediction. Due to its simplicity, it can be readily applied to sediment packings for which some measurements of flatness and elongation, the two most common form factors, are available.

physics.geo-ph↗

arXiv2021

A decoupled numerical method for two-phase flows of different densities and viscosities in superposed fluid and porous layers

In this article we consider the numerical modeling and simulation via the phase field approach of two-phase flows of different densities and viscosities in superposed fluid and porous layers. The model consists of the Cahn-Hilliard-Navier-Stokes equations in the free flow region and the Cahn-Hilliard-Darcy equations in porous media that are coupled by seven domain interface boundary conditions. We show that the coupled model satisfies an energy law. Based on the ideas of pressure stabilization and artificial compressibility, we propose an unconditionally stable time stepping method that decouples the computation of the phase field variable, the velocity and pressure of free flow, the velocity and pressure of porous media, hence significantly reduces the computational cost. The energy stability of the scheme effected with the finite element spatial discretization is rigorously established. We verify numerically that our schemes are convergent and energy-law preserving. Ample numerical experiments are performed to illustrate the features of two-phase flows in the coupled free flow and porous media setting.

math.NA↗

arXiv2021

Rheology of mobile sediment beds in laminar shear flow: effects of creep and polydispersity

Classical scaling relationships for rheological quantities such as the $μ(J)$-rheology have become increasingly popular for closures of two-phase flow modeling. However, these frameworks have been derived for monodisperse particles. We aim to extend these considerations to sediment transport modeling by using a more realistic sediment composition. We investigate the rheological behavior of sheared sediment beds composed of polydisperse spherical particles in a laminar Couette-type shear flow. The sediment beds consist of particles with a diameter size ratio of up to ten, which corresponds to grains ranging from fine to coarse sand. The data was generated using fully coupled, grain resolved direct numerical simulations using a combined lattice Boltzmann - discrete element method. These highly-resolved data yield detailed depth-resolved profiles of the relevant physical quantities that determine the rheology, i.e., the local shear rate of the fluid, particle volume fraction, total shear, and granular pressure. A comparison against experimental data shows excellent agreement for the monodisperse case. We improve upon the parameterization of the $μ(J)$-rheology by expressing its empirically derived parameters as a function of the maximum particle volume fraction. Furthermore, we extend these considerations by exploring the creeping regime for viscous numbers much lower than used by previous studies to calibrate these correlations. Considering the low viscous numbers of our data, we found that the friction coefficient governing the quasi-static state in the creeping regime tends to a finite value for vanishing shear, which decreases the critical friction coefficient by a factor of three for all cases investigated.

physics.flu-dyn↗

arXiv2021

Coupling fully resolved light particles with the Lattice Boltzmann method on adaptively refined grids

The simulation of geometrically resolved rigid particles in a fluid relies on coupling algorithms to transfer momentum both ways between the particles and the fluid. In this article, the fluid flow is modeled with a parallel Lattice Boltzmann method using adaptive grid refinement to improve numerical efficiency. The coupling with the particles is realized with the momentum exchange method. When implemented in plain form, instabilities may arise in the coupling when the particles are lighter than the fluid. The algorithm can be stabilized with a virtual mass correction specifically developed for the Lattice Boltzmann method. The method is analyzed for a wide set of physically relevant regimes, varying independently the body-to-fluid density ratio and the relative magnitude of inertial and viscous effects. These studies of a single rising particle exhibit periodic regimes of particle motion as well as chaotic behavior, as previously reported in the literature. The new method is carefully compared with available experimental and numerical results. This serves to validate the presented new coupled Lattice Boltzmann method and additionally it leads to new physical insight for some of the parameter settings.

physics.flu-dyn↗

arXiv2021

A massively parallel Eulerian-Lagrangian method for advection-dominated transport in viscous fluids

Motivated by challenges in Earth mantle convection, we present a massively parallel implementation of an Eulerian-Lagrangian method for the advection-diffusion equation in the advection-dominated regime. The advection term is treated by a particle-based, characteristics method coupled to a block-structured finite-element framework. Its numerical and computational performance is evaluated in multiple, two- and three-dimensional benchmarks, including curved geometries, discontinuous solutions, pure advection, and it is applied to a coupled non-linear system modeling buoyancy-driven convection in Stokes flow. We demonstrate the parallel performance in a strong and weak scaling experiment, with scalability to up to $147,456$ parallel processes, solving for more than $5.2 \times 10^{10}$ (52 billion) degrees of freedom per time-step.

cs.CE↗

arXiv2020

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

A high-performance implementation of a multiphase lattice Boltzmann method based on the conservative Allen-Cahn model supporting high-density ratios and high Reynolds numbers is presented. Metaprogramming techniques are used to generate optimized code for CPUs and GPUs automatically. The coupled model is specified in a high-level symbolic description and optimized through automatic transformations. The memory footprint of the resulting algorithm is reduced through the fusion of compute kernels. A roofline analysis demonstrates the excellent efficiency of the generated code on a single GPU. The resulting single GPU code has been integrated into the multiphysics framework waLBerla to run massively parallel simulations on large domains. Communication hiding and GPUDirect-enabled MPI yield near-perfect scaling behaviour. Scaling experiments are conducted on the Piz Daint supercomputer with up to 2048 GPUs, simulating several hundred fully resolved bubbles. Further, validation of the implementation is shown in a physically relevant scenario-a three-dimensional rising air bubble in water.

physics.flu-dyn↗

arXiv2020

Textbook efficiency: massively parallel matrix-free multigrid for the Stokes system

We employ textbook multigrid efficiency (TME), as introduced by Achi Brandt, to construct an asymptotically optimal monolithic multigrid solver for the Stokes system. The geometric multigrid solver builds upon the concept of hierarchical hybrid grids (HHG), which is extended to higher-order finite-element discretizations, and a corresponding matrix-free implementation. The computational cost of the full multigrid (FMG) iteration is quantified, and the solver is applied to multiple benchmark problems. Through a parameter study, we suggest configurations that achieve TME for both, stabilized equal-order, and Taylor-Hood discretizations. The excellent node-level performance of the relevant compute kernels is presented via a roofline analysis. Finally, we demonstrate the weak and strong scalability to up to $147,456$ parallel processes and solve Stokes systems with more than $3.6 \times 10^{12}$ (trillion) unknowns.

cs.CE↗

arXiv2020

Densification of Single-Walled Carbon Nanotube Films: Mesoscopic Distinct Element Method Simulations and Experimental Validation

Nanometer thin single-walled carbon nanotube (CNT) films collected from the aerosol chemical deposition reactors have gathered attention for their promising applications. Densification of these pristine films provides an important way to manipulate the mechanical, electronic, and optical properties. To elucidate the underlying microstructural level restructuring, which is ultimately responsible for the change in properties, we perform large scale vector-based mesoscopic distinct element method simulations in conjunction with electron microscopy and spectroscopic ellipsometry characterization of pristine and densified films by drop-cast volatile liquid processing. Matching the microscopy observations, pristine CNT films with finite thickness are modeled as self-assembled CNT networks comprising entangled dendritic bundles with branches extending down to individual CNTs. Simulations of the film under uniaxial compression uncover an ultra-soft densification regime extending to a ~75% strain, which is likely accessible with the surface tensional forces arising from liquid surface tension during the evaporation. When removing the loads, the pre-compressed samples evolve into homogeneously densified films with thickness values depending on both the pre-compression level and the sample microstructure. The significant reduction in thickness, confirmed by our spectroscopic ellipsometry, is attributed to the underlying structural changes occurring at the 100 nm scale, including the zipping of the thinnest dendritic branches.

cond-mat.mtrl-sci↗

arXiv2020

lbmpy: Automatic code generation for efficient parallel lattice Boltzmann methods

Lattice Boltzmann methods are a popular mesoscopic alternative to macroscopic computational fluid dynamics solvers. Many variants have been developed that vary in complexity, accuracy, and computational cost. Extensions are available to simulate multi-phase, multi-component, turbulent, or non-Newtonian flows. In this work we present lbmpy, a code generation package that supports a wide variety of different methods and provides a generic development environment for new schemes as well. A high-level domain-specific language allows the user to formulate, extend and test various lattice Boltzmann schemes. The method specification is represented in a symbolic intermediate representation. Transformations that operate on this intermediate representation optimize and parallelize the method, yielding highly efficient lattice Boltzmann compute kernels not only for single- and two-relaxation-time schemes but also for multi-relaxation-time, cumulant, and entropically stabilized methods. An integration into the HPC framework waLBerla makes massively parallel, distributed simulations possible, which is demonstrated through scaling experiments on the SuperMUC-NG supercomputing system

cs.MS↗

arXiv2020

Stencil scaling for vector-valued PDEs on hybrid grids with applications to generalized Newtonian fluids

Matrix-free finite element implementations for large applications provide an attractive alternative to standard sparse matrix data formats due to the significantly reduced memory consumption. Here, we show that they are also competitive with respect to the run time in the low order case if combined with suitable stencil scaling techniques. We focus on variable coefficient vector-valued partial differential equations as they arise in many physical applications. The presented method is based on scaling constant reference stencils originating from a linear finite element discretization instead of evaluating the bilinear forms on-the-fly. This method assumes the usage of hierarchical hybrid grids, and it may be applied to vector-valued second-order elliptic partial differential equations directly or as a part of more complicated problems. We provide theoretical and experimental performance estimates showing the advantages of this new approach compared to the traditional on-the-fly integration and stored matrix approaches. In our numerical experiments, we consider two specific mathematical models. Namely, linear elastostatics and incompressible Stokes flow. The final example considers a non-linear shear-thinning generalized Newtonian fluid. For this type of non-linearity, we present an efficient approach to compute a regularized strain rate which is then used to define the node-wise viscosity. Depending on the compute architecture, we could observe maximum speedups of 64% and 122% compared to the on-the-fly integration. The largest considered example involved solving a Stokes problem with 12288 compute cores on the state of the art supercomputer SuperMUC-NG.

cs.CE↗

arXiv2020

An efficient four-way coupled lattice Boltzmann - discrete element method for fully resolved simulations of particle-laden flows

A four-way coupling scheme for the direct numerical simulation of particle-laden flows is developed and analyzed. It employs a novel adaptive multi-relaxation time lattice Boltzmann method to simulate the fluid phase efficiently. The momentum exchange method is used to couple the fluid and the particulate phase. The particle interactions in normal and tangential direction are accounted for by a discrete element method using linear contact forces. All parameters of the scheme are studied and evaluated in detail and precise guidelines for their choice are developed. The development is based on several carefully selected calibration and validation tests of increasing physical complexity. It is found that a well-calibrated lubrication model is crucial to obtain the correct trajectories of a sphere colliding with a plane wall in a viscous fluid. For adequately resolving the collision dynamics it is found that the collision time must be stretched appropriately. The complete set of tests establishes a validation pipeline that can be universally applied to other fluid-particle coupling schemes providing a systematic methodology that can guide future developments.

physics.comp-ph↗

arXiv2019

Computational Study of Ultrathin CNT Films with the Scalable Mesoscopic Distinct Element Method

In this work we present a computational study of the small strain mechanics of freestanding ultrathin CNT films under in-plane loading. The numerical modeling of the mechanics of representatively large specimens with realistic micro- and nanostructure is presented. Our simulations utilize the scalable implementation of the mesoscopic distinct element method of the waLBerla multi-physics framework. Within our modeling approach, CNTs are represented as chains of interacting rigid segments. Neighboring segments in the chain are connected with elastic bonds, resolving tension, bending, shear and torsional deformations. These bonds represent a covalent bonding within CNT surface and utilize Enhanced Vector Model (EVM) formalism. Segments of the neighboring CNTs interact with realistic coarse-grained anisotropic vdW potential, enabling relative slip of CNTs in contact. The advanced simulation technique allowed us to gain useful insights on the behavior of CNT materials. In particular, it was established that the energy dissipation during CNT sliding leads to extended load transfer that conditions material-like mechanical response of the weakly bonded assemblies of CNTs.

cond-mat.mes-hall↗

arXiv2019

waLBerla: A block-structured high-performance framework for multiphysics simulations

Programming current supercomputers efficiently is a challenging task. Multiple levels of parallelism on the core, on the compute node, and between nodes need to be exploited to make full use of the system. Heterogeneous hardware architectures with accelerators further complicate the development process. waLBerla addresses these challenges by providing the user with highly efficient building blocks for developing simulations on block-structured grids. The block-structured domain partitioning is flexible enough to handle complex geometries, while the structured grid within each block allows for highly efficient implementations of stencil-based algorithms. We present several example applications realized with waLBerla, ranging from lattice Boltzmann methods to rigid particle simulations. Most importantly, these methods can be coupled together, enabling multiphysics simulations. The framework uses meta-programming techniques to generate highly efficient code for CPUs and GPUs from a symbolic method formulation. To ensure software quality and performance portability, a continuous integration toolchain automatically runs an extensive test suite encompassing multiple compilers, hardware architectures, and software configurations.

cs.DC↗

arXiv2019

A Systematic Comparison of Dynamic Load Balancing Algorithms for Massively Parallel Rigid Particle Dynamics

As compute power increases with time, more involved and larger simulations become possible. However, it gets increasingly difficult to efficiently use the provided computational resources. Especially in particle-based simulations with a spatial domain partitioning large load imbalances can occur due to the simulation being dynamic. Then a static domain partitioning may not be suitable. This can deteriorate the overall runtime of the simulation significantly. Sophisticated load balancing strategies must be designed to alleviate this problem. In this paper we conduct a systematic evaluation of the performance of six different load balancing algorithms. Our tests cover a wide range of simulation sizes, and employ one of the largest supercomputers available. In particular we study the runtime and memory complexity of all components of the simulation carefully. When progressing to extreme scale simulations it is essential to identify bottlenecks and to predict the scaling behaviour. Scaling experiments are shown for up to over one million processes. The performance of each algorithm is analyzed with respect to the quality of the load balancing and its runtime costs. For all tests, the waLBerla multiphysics framework is employed.

cs.DC↗

arXiv2019

Validation and calibration of coupled porous-medium and free-flow problems using pore-scale resolved models

The correct choice of interface conditions and effective parameters for coupled macroscale free-flow and porous-medium models is crucial for a complete mathematical description of the problem under consideration and for accurate numerical simulation of applications. We consider single-fluid-phase systems described by the Stokes-Darcy model. Different sets of coupling conditions for this model are available. However, the choice of these conditions and effective model parameters is often arbitrary. We use large scale lattice Boltzmann simulations to validate coupling conditions by comparison of the macroscale simulations against pore-scale resolved models. We analyse two settings (lid driven cavity over a porous bed and infiltration problem) with different geometrical configurations (channelised and staggered distributions of solid grains) and different sets of interface conditions. Effective parameters for the macroscale models are computed numerically for each geometrical configuration. Numerical simulation results demonstrate the sensitivity of the coupled Stokes-Darcy problem to the location of the sharp fluid-porous interface, the effective model parameters and the interface conditions.

math.NA↗

arXiv2019

A Modular and Extensible Software Architecture for Particle Dynamics

Creating a highly parallel and flexible discrete element software requires an interdisciplinary approach, where expertise from different disciplines is combined. On the one hand domain specialists provide interaction models between particles. On the other hand high-performance computing specialists optimize the code to achieve good performance on different hardware architectures. In particular, the software must be carefully crafted to achieve good scaling on massively parallel supercomputers. Combining all this in a flexible and extensible, widely usable software is a challenging task. In this article we outline the design decisions and concepts of a newly developed particle dynamics code MESA-PD that is implemented as part of the waLBerla multi-physics framework. Extensibility, flexibility, but also performance and scalability are primary design goals for the new software framework. In particular, the new modular architecture is designed such that physical models can be modified and extended by domain scientists without understanding all details of the parallel computing functionality and the underlying distributed data structures that are needed to achieve good performance on current supercomputer architectures. This goal is achieved by combining the high performance simulation framework waLBerla with code generation techniques. All code and the code generator are released as open source under GPLv3 within the publicly available waLBerla framework (www.walberla.net).

cs.SE↗