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Jonas Latt

Publications and source records attributed to Jonas Latt.

At least 19 recordsLinked to original sources

Modelling platelet dynamics in blood flow: an unresolved DEM approach

Computational models of blood flow are caught between fully resolved cell-based methods, which faithfully reproduce the dynamics of individual cells but are computationally prohibitive at vessel scale, and continuum models, scalable yet blind to particle motion. We present an unresolved, mesoscale computational fluid dynamics-discrete element method (CFD-DEM) model of platelet dynamics that bridges this gap and, coupled with an existing unresolved description of deformable red blood cells, moves closer to a scalable model of whole blood. Within this framework, implemented on the open source OpenFOAM-LIGGGHTS coupling, platelets are represented as rigid oblate particles advanced by orientation dependent drag, lift and hydrodynamic torque closures. The model is first validated against resolved simulations and experiments in cylindrical microvessels of diameter $100-200\,\mu m$, across wall shear rates $\dot{\gamma}=150-1650\,s^{-1}$ and hematocrit Ht $=10-20\%$ then used to characterize platelet margination. The model quantifies diffusion coefficient, CFL formation and their dependence on shear rate, Ht and channel size. In particular, platelet diffusivity grows with vessel size and shear rate, while remaining insensitive to Ht, whereas CFL thickens with shear rate and thins with Ht. We further show that even at this mesoscale level, the model remains sensitive to platelet shape: oblate platelets marginate faster and diffuse nearly an order of magnitude more than their spherical surrogates, reaching a comparable steady state distribution but along markedly different temporal paths. Together these results demonstrate that shape driven platelet dynamics can be recovered at a fraction of the cost of fully resolved methods.

physics.comp-ph

LEDDS: Portable LBM-DEM simulations on GPUs

Algorithmic formulations of GPU programs provide a high-level alternative to device-specific code by expressing computations as compositions of well-defined parallel primitives (e.g., map, sort, reduce), rather than through handcrafted GPU kernels. In this work, we demonstrate that this paradigm can be extended to complex and challenging problems in computational physics: the simulation of granular flows and fluid-particle interactions. LEDDS, our open-source framework, performs fully coupled Lattice Boltzmann -- Discrete Element Method (LBM-DEM) simulations using only algorithmic primitives, and runs efficiently on single-GPU platforms. The entire workflow, including neighbor search, collision detection, and fluid-particle coupling, is expressed as a sequence of portable primitives. While the current implementation illustrates these principles primarily through algorithms from the C++ Standard Library, with selective use of Thrust primitives for performance, the underlying concept is compatible with any HPC environment offering a rich set of parallel algorithms and is therefore applicable across a wide range of modern GPU systems and future accelerators. LEDDS is validated through benchmarks spanning both DEM and LBM-DEM configurations, including sphere and ellipsoid collisions, wall friction tests, single-particle settling, Jeffery's orbits, and particle-laden shear flows. Despite its high level of abstraction, LEDDS achieves performances comparable to those of hand-tuned CUDA solvers, while maintaining portability and code clarity. These results show that high-performance LBM-DEM coupling can be achieved without sacrificing generality or readability, establishing LEDDS as a blueprint for portable multiphysics frameworks based on algorithmic primitives.

physics.comp-ph

Multi-GPU Acceleration of PALABOS Fluid Solver using C++ Standard Parallelism

This article presents the principles, software architecture, and performance analysis of the GPU port of the lattice Boltzmann software library Palabos (J. Latt et al., "Palabos: Parallel lattice Boltzmann solver", Comput. Math. Appl. 81, 334-350, (2021)). A hybrid CPU-GPU execution model is adopted, in which numerical components are selectively assigned to either the CPU or the GPU, depending on considerations of performance or convenience. This design enables a progressive porting strategy, allowing most features of the original CPU-based codebase to be gradually and seamlessly adapted to GPU execution. The new architecture builds upon two complementary paradigms: a classical object-oriented structure for CPU execution, and a data-oriented counterpart for GPUs, which reproduces the modularity of the original code while eliminating object-oriented overhead detrimental to GPU performance. Central to this approach is the use of modern C++, including standard parallel algorithms and template metaprogramming techniques, which permit the generation of hardware-agnostic computational kernels. This facilitates the development of user-defined, GPU-accelerated components such as collision operators or boundary conditions, while preserving compatibility with the existing codebase and avoiding the need for external libraries or non-standard language extensions. The correctness and performance of the GPU-enabled Palabos are demonstrated through a series of three-dimensional multiphysics benchmarks, including the laminar-turbulent transition in a Taylor-Green vortex, lid-driven cavity flow, and pore-scale flow in Berea sandstone. Despite the high-level abstraction of the implementation, the single-GPU performance is similar to CUDA-native solvers, and multi-GPU tests exhibit good weak and strong scaling across all test cases.

cs.DC

GPU-based compressible lattice Boltzmann simulations on non-uniform grids using standard C++ parallelism: From best practices to aerodynamics, aeroacoustics and supersonic flow simulations

Despite decades of research, creating accurate, robust, and efficient lattice Boltzmann methods (LBM) on non-uniform grids with seamless GPU acceleration remains challenging. This work introduces a novel strategy to address this challenge by integrating simple yet effective components: (1) parallel algorithms in modern C++, (2) conservative cell-centered grid refinement, (3) local boundary conditions, and (4) robust collision models. Our framework supports multiple lattices (D2Q9, D2Q13, D2Q21, D2Q37, D3Q27, etc) tailored to various flow conditions. It includes collision models with polynomial and numerical equilibria, a second distribution for polyatomic behavior, a Jameson-like shock sensor, and generalizes Rohde's refinement strategy. The framework's accuracy and robustness is validated across diverse benchmarks, including lid-driven cavity flows, Aeolian noise, 30P30N airfoil aerodynamics, inviscid Riemann problems, and viscous flows past a NACA airfoil in transonic and supersonic regimes. Modern C++ further enables our framework to reach GPU-native performance, while ensuring high portability, modularity, and ease of implementation. Notably, weakly compressible LBMs achieve state-of-the-art GPU efficiency on non-uniform grids, while fully compressible LBMs benefit from acceleration equivalent to thousands of CPU cores in the most compute-intensive cases. Our advanced performance models incorporate neighbor-list and asynchronous time-stepping effects, providing new insights into the performance decomposition of LB simulations on non-uniform grids. Overall, this study sets a new standard for portable, tree-based LBMs, demonstrating that a combination of well-chosen components can achieve high performance, accuracy, and robustness across various flow conditions. As a final proof-of-concept, adaptive mesh refinement is proposed for subsonic and supersonic applications.

physics.comp-ph

Palabos Turret: A Particle-Resolved Numerical Framework for Settling Dynamics of Arbitrary-Shaped Particles

Particles transported in fluids are everywhere, occurring for example in indoor air, the atmosphere, the oceans, and engineering applications. In this study, a novel three-dimensional numerical framework -- the Palabos Turret is presented, which allows fully resolved simulations of the settling dynamics of heavy particles with arbitrary shapes over a wide range of particle Reynolds numbers. The numerical solver is based on the lattice Boltzmann method utilizing immersed-boundary approach and a recursive-regularized collision model to fully resolve the particle-fluid interactions. A predictor-corrector scheme is applied for the robust time integration of the six-degrees-of-freedom (6DOF) rigid-body motion. Finally, the multi-scale nature arising from the long free-fall distances of a particle is addressed through a dynamic memory allocation scheme allowing for a virtually infinite falling distance. This solver allows for the simulation of particles of any arbitrary shape. The proposed framework is validated using the analytical and experimental data of freely-falling spheres, ellipsoids, and an irregular particle in a wide range of Reynolds numbers between $5\times10^{-1}$ and $4\times10^4$. For different Reynolds numbers and particle shapes considered, the Palabos Turret shows excellent agreement compared to theoretical and experimental values with a median relative deviation of $\pm1.5\%$ and a maximum deviation of $\pm5\%$. The Palabos Turret enables an in-depth analysis of the translational and rotational dynamics of particles with complex geometries.

physics.comp-ph

Twist, turn and encounter: the trajectories of small atmospheric particles unravelled

Every solid particle in the atmosphere, from ice crystals and pollen to dust, ash, and microplastics, is non-spherical. These particles play significant roles in Earth's climate system, influencing temperature, weather patterns, natural ecosystems, human health, and pollution levels. However, our understanding of these particles is largely based on the theories for extremely small particles and experiments conducted in liquid mediums. In this study, we used an innovative experimental setup and particle-resolved numerical simulations to investigate the behaviour of sub-millimetre ellipsoids of varying shapes in the air. Our results revealed complex decaying oscillation patterns involving numerous twists and turns in these particles, starkly contrasting their dynamics in liquid mediums. We found that the frequency and decay rate of these oscillations have a strong dependence on the particle shape. Interestingly, disk-shaped particles oscillated at nearly twice the frequency of rod-shaped particles, though their oscillations also decayed more rapidly. During oscillation, even subtly non-spherical particles can drift laterally up to ten times their volume-equivalent spherical diameter. This behaviour enables particles to sweep through four times more air both vertically and laterally compared to a volume-equivalent sphere, significantly increasing their encounter rate and aggregation possibility. Our findings provide an explanation for the long-range transport and naturally occurring aggregate formation of highly non-spherical particles such as snowflakes and volcanic ash.

physics.flu-dyn

Anomalous Platelet Transport & Fat-Tailed Distributions

The transport of platelets in blood is commonly assumed to obey an advection-diffusion equation. Here we propose a disruptive view, by showing that the random part of their velocity is governed by a fat-tailed probability distribution, usually referred to as a Lévy flight. Although for small spatio-temporal scales, it is hard to distinguish it from the generally accepted "red blood cell enhanced" Brownian motion, for larger systems this effect is dramatic as the standard approach may underestimate the flux of platelets by several orders of magnitude, compromising in particular the validity of current platelet function tests.

physics.comp-ph

Modelling Settling-Driven Gravitational Instabilities at the Base of Volcanic Clouds Using the Lattice Boltzmann Method

Field observations and laboratory experiments have shown that ash sedimentation can be significantly affected by collective settling mechanisms that promote premature ash deposition, with important implications for associated impacts. Among these mechanisms, settling-driven gravitational instabilities result from the formation of a gravitationally-unstable particle boundary layer (PBL) that grows between volcanic ash clouds and the underlying atmosphere. The PBL destabilises once it reaches a critical thickness, triggering the formation of rapid, downward-moving ash fingers that remain poorly characterised. We simulate this process by coupling a Lattice Boltzmann model, which solves the Navier-Stokes equations for the fluid phase, with a Weighted Essentially Non Oscillatory (WENO) finite difference scheme which solves the advection-diffusion-settling equation describing particle transport. Since the physical problem is advection dominated, the use of the WENO scheme reduces numerical diffusivity and ensures accurate tracking of the temporal evolution of the interface between the layers. We have validated the new model by showing that the simulated early-time growth rate of the instability is in very good agreement with that predicted by linear stability analysis, whilst the modelled late-stage behaviour also successfully reproduces quantitative results from published laboratory experiments.

physics.flu-dyn

Cross-platform programming model for many-core lattice Boltzmann simulations

We present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based solely on C++17 Parallel Algorithms, our approach does not rely on any language extensions, external libraries, vendor-specific code annotations, or pre-compilation steps. Thanks in particular to a recently proposed GPU back-end to C++17 Parallel Algorithms, it is shown that a single code can compile and reach state-of-the-art performance on both many-core CPU and GPU environments for the solution of a given non trivial fluid dynamics problem. The proposed strategy is tested with six different, commonly used implementation schemes to test the performance impact of memory access patterns on different platforms. Nine different LB collision models are included in the tests and exhibit good performance, demonstrating the versatility of our parallel approach. This work shows that it is less than ever necessary to draw a distinction between research and production software, as a concise and generic LB implementation yields performances comparable to those achievable in a hardware specific programming language. The results also highlight the gains of performance achieved by modern many-core CPUs and their apparent capability to narrow the gap with the traditionally massively faster GPU platforms. All code is made available to the community in form of the open-source project "stlbm", which serves both as a stand-alone simulation software and as a collection of reusable patterns for the acceleration of pre-existing LB codes.

physics.comp-ph

PalaCell2D: A framework for detailed tissue morphogenesis

In silico, cell based approaches for modeling biological morphogenesis are used to test and validate our understanding of the biological and mechanical process that are at work during the growth and the organization of multi-cell tissues. As compared to in vivo experiments, computer based frameworks dedicated to tissue modeling allow us to easily test different hypotheses, and to quantify the impact of various biophysically relevant parameters. Here, we propose a formalism based on a detailed, yet simple, description of cells that accounts for intra-, inter- and extra-cellular mechanisms. More precisely, the cell growth and division is described through the space and time evolution of the membrane vertices. These vertices follow a Newtonian dynamics, meaning that their evolution is controlled by different types of forces: a membrane force (spring and bending), an adherence force (inter cellular spring), external and internal pressure forces. In addition to the cells dynamics, our formalism further relies on a lattice Boltzmann method, using the Palabos library, to simulate the diffusion of chemical signals. The latter aims at driving the growth and migration of a tissue by simply changing the state of the cells. All of this leads to an accurate description of the growth and division of cells, with realistic cell shapes and where membranes can have different properties. While this work is of methodological nature, we also propose to validate our framework through simple, yet biologically relevant benchmark tests at both single-cell and full tissue scales. This includes free and chemically controlled cell tissue growth in an unbounded domain. The ability of our framework to simulate cell migration, cell compression and morphogenesis under external constraints is also investigated in a qualitative manner.

physics.bio-ph

Palabos-npFEM: Software for the Simulation of Cellular Blood Flow (Digital Blood)

Palabos-npFEM is a computational framework for the simulation of blood flow with fully resolved constituents. The software resolves the trajectories and deformed state of blood cells, such as red blood cells and platelets, and the complex interaction between them. The tool combines the lattice Boltzmann solver Palabos for the simulation of blood plasma (fluid phase), a finite element method (FEM) solver for the resolution of blood cells (solid phase), and an immersed boundary method (IBM) for the coupling of the two phases. Palabos-npFEM provides, on top of a CPU-only version, the option to simulate the deformable bodies on GPUs, thus the code is tailored for the fastest supercomputers. The software is integrated in the Palabos core library, and is available on the Git repository https://gitlab.com/unigespc/palabos. It offers the possibility to simulate various setups, e.g. several geometries and blood parameters, and due to its modular design, it allows external solvers to readily replace the provided ones.

physics.comp-ph

Enhanced single-node boundary condition for the Lattice Boltzmann Method

We propose a new way to implement Dirichlet boundary conditions for complex shapes using data from a single node only, in the context of the lattice Boltzmann method. The resulting novel method exhibits second-order convergence for the velocity field and shows similar or better accuracy than the well established Bouzidi, Firdaouss, and Lallemand (2001) boundary condition for curved walls, despite its local nature. The method also proves to be suitable to simulate moving rigid objects or immersed surfaces either with or without prescribed motion. The core idea of the new approach is to generalize the description of boundary conditions that combine bounce-back rule with interpolations and to enhance them by limiting the information involved in the interpolation to a close proximity of the boundary.

physics.comp-ph

Efficient supersonic flows through high-order guided equilibrium with lattice Boltzmann

A double-distribution-function based lattice Boltzmann method (DDF-LBM) is proposed for the simulation of polyatomic gases in the supersonic regime. The model relies on an extended equilibrium state that is constructed to reproduce the first 13 moments of the Maxwell-Boltzmann distribution exactly. This extends the validity of the standard 5-constraint (mass, momentum and energy) approach and leads to the correct simulation of thermal, compressible flows with only 39 discrete velocities in 3D. The stability of this BGK-LBM is reinforced by relying on Knudsen-number-dependent relaxation times that are computed analytically. Hence, high-Reynolds number, supersonic flows can be simulated in an efficient and elegant manner. While the 1D Riemann problem shows the ability of the proposed approach to handle discontinuities in the zero-viscosity limit, the simulation of the flow past a NACA0012 airfoil (Mach number $\mathrm{Ma}=1.5$, Reynolds number $\mathrm{Re=10^4}$) confirms the excellent behavior of this model in a low-viscosity and supersonic regime. The proposed model is substantially more efficient than the previous 5-moment D3Q343 DDF-LBM and opens up a whole new world of compressible flow applications that can be realistically tackled with a purely LB approach.

physics.comp-ph

Digital Blood in Massively Parallel CPU/GPU Systems for the Study of Platelet Transport

We propose a highly versatile computational framework for the simulation of cellular blood flow focusing on extreme performance without compromising accuracy or complexity. The tool couples the lattice Boltzmann solver Palabos for the simulation of the blood plasma, a novel finite element method (FEM) solver for the resolution of the deformable blood cells, and an immersed boundary method for the coupling of the two phases. The design of the tool supports hybrid CPU-GPU executions (fluid, fluid-solid interaction on CPUs, the FEM solver on GPUs), and is non-intrusive, as each of the three components can be replaced in a modular way. The FEM-based kernel for solid dynamics outperforms other FEM solvers and its performance is comparable to the state-of-the-art mass-spring systems. We perform an exhaustive performance analysis on Piz Daint at the Swiss National Supercomputing Centre and provide case studies focused on platelet transport. The tests show that this versatile framework combines unprecedented accuracy with massive performance, rendering it suitable for the upcoming exascale architectures.

physics.comp-ph

Bridging the computational gap between mesoscopic and continuum modeling of red blood cells for fully resolved blood flow

We present a computational framework for the simulation of blood flow with fully resolved red blood cells (RBCs) using a modular approach that consists of a lattice Boltzmann solver for the blood plasma, a novel finite element based solver for the deformable bodies and an immersed boundary method for the fluid-solid interaction. For the RBCs, we propose a nodal projective FEM (npFEM) solver which has theoretical advantages over the more commonly used mass-spring systems (mesoscopic modeling), such as an unconditional stability, versatile material expressivity, and one set of parameters to fully describe the behavior of the body at any mesh resolution. At the same time, the method is substantially faster than other FEM solvers proposed in this field, and has an efficiency that is comparable to the one of mesoscopic models. At its core, the solver uses specially defined potential energies, and builds upon them a fast iterative procedure based on quasi-Newton techniques. For a known material, our solver has only one free parameter that demands tuning, related to the body viscoelasticity. In contrast, state-of-the-art solvers for deformable bodies have more free parameters, and the calibration of the models demands special assumptions regarding the mesh topology, which restrict their generality and mesh independence. We propose as well a modification to the potential energy proposed by Skalak et al. 1973 for the red blood cell membrane, which enhances the strain hardening behavior at higher deformations. Our viscoelastic model for the red blood cell, while simple enough and applicable to any kind of solver as a post-convergence step, can capture accurately the characteristic recovery time and tank-treading frequencies. The framework is validated using experimental data, and it proves to be scalable for multiple deformable bodies.

physics.comp-ph

Efficient LBM on GPUs for dense moving objects using immersed boundary condition

There exists an increasing interest for using immersed boundary methods (IBMs) (Peskin 2000) to model moving objects in computational fluid dynamics. Indeed, this approach is particularly efficient, because the fluid mesh does not require to be body-fitted or to adjust dynamically to the motion of the body. Frequently, IBMs are implemented in combination with the lattice Boltzmann methods (LBM) (Krüger 2016). They fit elegantly into the framework of this method, and yield impressive parallel performances. It has also become quite common to accelerate LBM simulations with the use of Graphics Processing Units (GPUs) (Tölke 2010), as the underlying algorithm adjusts naturally to the architecture of such platforms. It is not uncommon that speedups of an order of magnitude, or more, at equal financial cost or energy consumption are observed, as compared to classical CPUs. IBM algorithms are however more difficult to adapt to GPUs, because their complex memory access pattern conflicts with a GPU's strategy of broadcasting data to a large number of GPU cores in single memory accesses. In the existing literature, GPU implementations of LBM-IBM codes are therefore restricted to situations in which the immersed surfaces are very small compared to the total number of fluid cells (Valero-Lara 2014), as is often the case in exterior flow simulations around an obstacle. This assumption is however not valid in many other cases of interest. We propose a new method for the implementation of a LBM-IBM on GPUs in the CUDA language, which allows to handle a substantially larger immersed surfaces with acceptable performance than previous implementations.

physics.comp-ph

A physical description of the adhesion and aggregation of platelets

The early stages of clot formation in blood vessels involve platelets adhesion-aggregation. Although these mechanisms have been extensively studied, gaps in their understanding still persist. We have performed detailed in-vitro experiments and developed a numerical model to better describe and understand this phenomenon. Unlike previous studies, we took into account both activated and non-activated platelets, as well as the 3D nature of the aggregation process. Our investigation reveals that blood albumin is a major parameter limiting platelet adhesion and aggregation. Our results also show that the well accepted Zydney-Colton shear-induced diffusivity is much too low to explain the observed deposition rate. Simulations are in very good agreement with observations and provide quantitative estimates of the adhesion and aggregation rates that are hard to measure experimentally.

physics.bio-ph

Local mesh refinement sensor for the lattice Boltzmann method

A novel mesh refinement sensor is proposed for lattice Boltzmann methods (LBMs) applicable to either static or dynamic mesh refinement algorithms. The sensor exploits the kinetic nature of LBMs by evaluating the departure of distribution functions from their local equilibrium state. This sensor is first compared, in a qualitative manner, to three state-of-the-art sensors: (1) the vorticity norm, (2) the Q-criterion, and (3) spatial derivatives of the vorticity. This comparison shows that our kinetic sensor is the most adequate candidate to propose tailored mesh structures across a wide range of physical phenomena: incompressible, compressible subsonic/supersonic single phase, and weakly compressible multiphase flows. As a more quantitative validation, the sensor is then used to produce the computational mesh for two existing open-source LB solvers based on inhomogeneous, block-structured meshes with static and dynamic refinement algorithms, implemented in the Palabos and AMROC-LBM software, respectively. The sensor is first used to generate a static mesh to simulate the turbulent 3D lid-driven cavity flow using Palabos. AMROC-LBM is then adopted to confirm the ability of our sensor to dynamically adapt the mesh to reach the steady state of the 2D lid-driven cavity flow. Both configurations show that our sensor successfully produces meshes of high quality and allows to save computational time.

physics.flu-dyn