The power particle-in-cell method

Qu, Ziyin; Li, Minchen; Goes, Fernando de; Jiang, Chenfanfu

doi:10.1145/3528223.3530066

Cited by 11 publications

(6 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fu et al [FGG*17] expand upon the APIC method by generalising the local function on each particle. Qu et al [QLDJ22] compute weights for particle‐grid transfers using the power particle method, which ensures uniform particle distributions and volume preservation.…”

Section: Related Workmentioning

confidence: 99%

Monte Carlo Vortical Smoothed Particle Hydrodynamics for Simulating Turbulent Flows

Ye,

Wang,

et al. 2024

Computer Graphics Forum

View full text Add to dashboard Cite

For vortex particle methods relying on SPH‐based simulations, the direct approach of iterating all fluid particles to capture velocity from vorticity can lead to a significant computational overhead during the Biot‐Savart summation process. To address this challenge, we present a Monte Carlo vortical smoothed particle hydrodynamics (MCVSPH) method for efficiently simulating turbulent flows within an SPH framework. Our approach harnesses a Monte Carlo estimator and operates exclusively within a pre‐sampled particle subset, thus eliminating the need for costly global iterations over all fluid particles. Our algorithm is decoupled from various projection loops which enforce incompressibility, independently handles the recovery of turbulent details, and seamlessly integrates with state‐of‐the‐art SPH‐based incompressibility solvers. Our approach rectifies the velocity of all fluid particles based on vorticity loss to respect the evolution of vorticity, effectively enforcing vortex motions. We demonstrate, by several experiments, that our MCVSPH method effectively preserves vorticity and creates visually prominent vortical motions.

show abstract

Section: Related Workmentioning

confidence: 99%

Monte Carlo Vortical Smoothed Particle Hydrodynamics for Simulating Turbulent Flows

Ye,

Wang,

et al. 2024

Computer Graphics Forum

View full text Add to dashboard Cite

show abstract

“…When there is a velocity difference between point i and point i + 1, it can be inferred that particle A undergoes deformation. The formula for calculating the deformation gradient of particle A is as follows [26]:…”

Section: (I) Deformation Calculationmentioning

confidence: 99%

Applicability Study of Euler–Lagrange Integration Scheme in Constructing Small-Scale Atmospheric Dynamics Models

Wei,

Liu,

Guo

et al. 2024

Atmosphere

View full text Add to dashboard Cite

The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler background field approach to construct a small-scale atmospheric flow field model. The model streamlines the modeling process by combining the benefits of the Lagrangian dynamics model and the Eulerian integration scheme. To verify the effectiveness of the Euler–Lagrange hybrid model, experiments using the Fluent wind field model were conducted for comparison. The results show that both models have their advantages in handling terrain-induced wind fields. The Fluent model excels in simulating the general characteristics of wind fields under specific terrain, while the Euler–Lagrange hybrid model is better at capturing the upstream and downstream disturbances of the terrain on the atmospheric flow field. These findings provide powerful tools for in-depth diagnostic analysis of atmospheric flow simulation and convective precipitation processes. Notably, the Euler–Lagrange hybrid model demonstrates excellent computational efficiency, with an average computation time of approximately 2 s per time step in a Python environment, enabling rapid simulation of 40 time steps within approximately 90 s.

show abstract

“…After years of development, the PIC method has evolved to possess a well-established framework. Comprehensive details regarding the theory and implementation procedures are found in recent research (Snider, 2001;Qu et al, 2022;Yu et al, 2023).…”

Section: Brief Formulationmentioning

confidence: 99%

An Overview of Coupled Lagrangian–Eulerian Methods for Ocean Engineering

Qian,

Yang,

Liu

2024

J. Marine. Sci. Appl.

View full text Add to dashboard Cite

Combining the strengths of Lagrangian and Eulerian descriptions, the coupled Lagrangian–Eulerian methods play an increasingly important role in various subjects. This work reviews their development and application in ocean engineering. Initially, we briefly outline the advantages and disadvantages of the Lagrangian and Eulerian descriptions and the main characteristics of the coupled Lagrangian–Eulerian approach. Then, following the developmental trajectory of these methods, the fundamental formulations and the frameworks of various approaches, including the arbitrary Lagrangian–Eulerian finite element method, the particle-in-cell method, the material point method, and the recently developed Lagrangian–Eulerian stabilized collocation method, are detailedly reviewed. In addition, the article reviews the research progress of these methods with applications in ocean hydrodynamics, focusing on free surface flows, numerical wave generation, wave overturning and breaking, interactions between waves and coastal structures, fluid-rigid body interactions, fluid–elastic body interactions, multiphase flow problems and visualization of ocean flows, etc. Furthermore, the latest research advancements in the numerical stability, accuracy, efficiency, and consistency of the coupled Lagrangian–Eulerian particle methods are reviewed; these advancements enable efficient and highly accurate simulation of complicated multiphysics problems in ocean and coastal engineering. By building on these works, the current challenges and future directions of the hybrid Lagrangian–Eulerian particle methods are summarized.

show abstract

The power particle-in-cell method

Cited by 11 publications

References 52 publications

Monte Carlo Vortical Smoothed Particle Hydrodynamics for Simulating Turbulent Flows

Monte Carlo Vortical Smoothed Particle Hydrodynamics for Simulating Turbulent Flows

Applicability Study of Euler–Lagrange Integration Scheme in Constructing Small-Scale Atmospheric Dynamics Models

An Overview of Coupled Lagrangian–Eulerian Methods for Ocean Engineering

Contact Info

Product

Resources

About