Implicit propagation of directly addressed grids in lattice Boltzmann methods

Kummerländer, Adrian; Dorn, Márcio; Frank, Martin; Krause, Mathias J.

doi:10.1002/cpe.7509

Cited by 11 publications

(3 citation statements)

References 37 publications

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“…through the space-time cylinder. The computing steps implemented in one collision are summarized in Algorithm 1 and the streaming is realized as a mere pointer shift [21]. The present work illustrates only the bulk solver.…”

Section: 3mentioning

confidence: 99%

Binary fluid flow simulations with free energy lattice Boltzmann methods

Simonis¹,

Nguyen²,

Avis³

et al. 2024

DCDS-S

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We use free energy lattice Boltzmann methods to simulate shear and extensional flows of a binary fluid in two and three dimensions. To this end, two classical configurations are digitally twinned, namely a parallel-band device for binary shear flow and a four-roller apparatus for binary extensional flow. The free energy lattice Boltzmann method and the test cases are implemented in the open-source parallel C++ framework OpenLB and evaluated for several non-dimensional numbers. Characteristic deformations are captured, where breakup mechanisms occur for critical capillary regimes. Though the known mass leakage for small droplet-domain ratios and large Cahn numbers is observed, suitable mesh sizes show good agreement to analytical predictions and reference results.

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Section: 3mentioning

confidence: 99%

Binary fluid flow simulations with free energy lattice Boltzmann methods

Simonis¹,

Nguyen²,

Avis³

et al. 2024

DCDS-S

Self Cite

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show abstract

“…While the underlying LBM library OpenLB supports various parallelization modes both on CPU and GPU targets [18,25], paint2sim explicitly only uses single-threaded, single-precision, non-vectorized execution for maximum device portability and as a heatmanagement trade-off. While OpenMP-based shared memory parallelization was possible, core heterogeneity and thread binding caused issues across the diverse set of test devices.…”

Section: Performancementioning

confidence: 99%

Just-in-Time Fluid Flow Simulation on Mobile Devices Using OpenVisFlow and OpenLB

Teutscher,

Kummerländer,

Bukreev

et al. 2024

Applied Sciences

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The present state of research in computational fluid dynamics (CFD) is marked by an ongoing process of refining numerical methods and algorithms with the goal of achieving accurate modeling and analysis of fluid flow and heat transfer phenomena. Remarkable progress has been achieved in the domains of turbulence modeling, parallel computing, and mesh generation, resulting in heightened simulation precision when it comes to capturing complex flow behaviors. Nevertheless, CFD faces a significant challenge due to the time and expertise needed for a meticulous simulation setup and intricate numerical techniques. To surmount this challenge, we introduce paint2sim—an innovative mobile application designed to enable on-the-fly 2D fluid simulations using a device’s camera. Seamlessly integrated with OpenLB, a high-performance Lattice Boltzmann-based library, paint2sim offers accurate simulations. The application leverages the capabilities of the Lattice Boltzmann Method (LBM) to model fluid behaviors accurately. Through a symbiotic interaction with the open-source OpenCV library, paint2sim can scan and extract hand-drawn simulation domains, affording the capability for instant simulation and visualization. Notably, paint2sim can also be regarded as a digital twin, facilitating just-in-time representation and analysis of 2D fluid systems. The implications of this technology extend significantly to both fluid dynamics education and industrial applications, effectively lowering barriers and rendering fluid simulations more accessible. Encouragingly, the outcomes of simulations conducted with paint2sim showcase promising qualitative and quantitative results. Overall, paint2sim offers a groundbreaking approach to mobile 2D fluid simulations, providing users with just-in-time visualization and accurate results, while simultaneously serving as a digital twin for fluid systems.

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“…The successful implementation of the constructed algorithm depends on the memory access pattern. This topic is widely discussed in LBM implementations [9,53,54,[59][60][61]. The goal is not only the locality of data that are accessed in one sub-task, but also data alignment and coalescing.…”

Section: Data Structurementioning

confidence: 99%

Heterogeneous LBM Simulation Code with LRnLA Algorithms

null¹,

Perepelkina²

2023

CICP

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A design of a new heterogeneous code for LBM simulations is proposed. By heterogeneous computing we mean a collaborative computation on CPU and GPU, which is characterized by the following features: the data is distributed between CPU and GPU memory spaces taking advantage of both parallel hierarchies; the capabilities of both SIMT GPU and SIMD GPU parallelization are used for calculations; the algorithms in use efficiently conceal the CPU-GPU data exchange; the subdivision of the computing task is performed with an account for the strong points of both processing units: high performance of GPU, low latency, and advanced memory hierarchy of CPU. This code is a continuation of our work in the development of LRnLA codes for LBM. Previous LRnLA codes had good efficiency both for CPU and GPU computing, and allowed GPU simulation performed on data stored in CPU RAM without performance loss on CPU-GPU data transfer. In the new code, we use methods and instruments that can be flexibly adapted to GPU and CPU instruction sets. We present the theoretical study of the performance of the proposed code and suggest implementation techniques. The bottlenecks are identified. As a result, we conclude that larger problems can be simulated with higher efficiency in the heterogeneous system.

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Implicit propagation of directly addressed grids in lattice Boltzmann methods

Cited by 11 publications

References 37 publications

Binary fluid flow simulations with free energy lattice Boltzmann methods

Binary fluid flow simulations with free energy lattice Boltzmann methods

Just-in-Time Fluid Flow Simulation on Mobile Devices Using OpenVisFlow and OpenLB

Heterogeneous LBM Simulation Code with LRnLA Algorithms

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