LBfoam: An open-source software package for the simulation of foaming using the Lattice Boltzmann Method

Ataei, Mohammadmehdi; Shaayegan, Vahid; Costa, Franco; Han, Sejin; Park, Chul; Bussmann, Markus

doi:10.1016/j.cpc.2020.107698

Cited by 16 publications

(11 citation statements)

References 57 publications

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“…The stabilization scaling τ m is used for our PSPG scaling as well, with an additional scaling by density for consistent units. Finally, numerical diffusion is employed to improve the overall behavior of the solution for both polymerization Equation ( 4) and the moment Equations (10) with values of 10 À5 cm 2 =s and 10 À6 cm 2 =s, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Capturing the evolution of the bubble size and its effect on foam dynamics is often desired, as bubble concentration and size distribution can greatly influence the overall material properties and behavior of the system. Ataei et al 10 created a lattice‐Boltzmann model for polymer foams that incorporated bubbles directly and, by accounting for a multitude of physical interactions, were able to capture complex behavior such as foam drainage. Usually, a simplified approach is chosen in which bubbles are represented by a PBE.…”

Section: Introductionmentioning

confidence: 99%

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Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

et al. 2021

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Polyurethane foams are widely used materials often chosen for their useful characteristics such as low thermal conductivity, ease of application, and high strength-toweight ratios. Computational models are needed to predict the dynamics of the flow and expansion, and the resulting material properties, to improve manufacturing processes. In this paper, a model for PMDI, a water-blown polyurethane foam, is presented. By extending a kinetics-based approach by adding bubble-scale information via a population balance equation (PBE) using the quadrature method of moments, we can track bubble size distributions during foaming. We present results from a three-dimensional computational fluid dynamics model using arbitrary Lagrangian-Eulerian interface tracking implemented in finite element software. The model compares favorably with experimental data, including dynamics, bubble distributions measured by both camera and diffusion wave spectroscopy, and post-test bubble size from scanning electron microscopy and density measurements from x-ray computed tomography.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

et al. 2021

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“…LBfoam (Ataei et al 2021b) is a free surface lattice Boltzmann solver for foaming simulations. In LBfoam, a disjoining pressure Π between two adjacent bubble interfaces is responsible for stabilizing liquid lamellae (the thin layer of liquid separating two bubbles).…”

Section: Implementation In a Cfd Solvermentioning

confidence: 99%

“…To date, many studies have used PLIC for interface reconstruction on structured and unstructured grids, and also for related calculations such as calculating the distance between two interfaces, and have proposed improvements to reduce the implementation complexity and increase its efficiency (López et al 2005;Ataei et al 2021b;Dai and Tong 2019;Ataei et al 2021a;Nahed and Dgheim 2020;Scheufler and Roenby 2019). A simple analytical solution can be used to solve PLIC in 2D for a square cell.…”

Section: Introductionmentioning

confidence: 99%

NPLIC: A machine learning approach to piecewise linear interface construction

et al. 2021

Self Cite

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Piecewise Linear Interface Construction (PLIC) is frequently used to geometrically reconstruct fluid interfaces in Computational Fluid Dynamics (CFD) modeling of two-phase flows. PLIC reconstructs interfaces from a scalar field that represents the volume fraction of each phase in each computational cell. Given the volume fraction and interface normal, the location of a linear interface is uniquely defined. For a cubic computational cell (3D), the position of the planar interface is determined by intersecting the cube with a plane, such that the volume of the resulting truncated polyhedron cell is equal to the volume fraction. Yet it is geometrically complex to find the exact position of the plane, and it involves calculations that can be a computational bottleneck of many CFD models. However, while the forward problem of 3D PLIC is challenging, the inverse problem, of finding the volume of the truncated polyhedron cell given a defined plane, is simple. In this work, we propose a deep learning model for the solution to the forward problem of PLIC by only making use of its inverse problem. The proposed model is up to several orders of magnitude faster than traditional schemes, which significantly reduces the computational bottleneck of PLIC in CFD simulations.

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“…The focus of this paper is on LB models, which have become very popular and attractive in the last two decades, due to their simplicity, efficiency and applicability in different contexts [31,32]. Several open-access LB implementations are available, e.g., Ludwig [33], LB3D [34], LBsoft [35], Palabos [36], and LBfoam [37]. However, an LB software that simulates the dynamics of finite-size droplets stabilised against coalescence and subjected to thermal convection is not available to the best of our knowledge in an open-access version.…”

Section: Introductionmentioning

confidence: 99%

TLBfind: a Thermal Lattice Boltzmann code for concentrated emulsions with FINite-size Droplets

Pelusi,

Lulli,

Sbragaglia

et al. 2021

Preprint

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In this paper, we present TLBfind, a GPU code for simulating the hydrodynamics of droplets along with a dynamic temperature field. TLBfind hinges on a two-dimensional multi-component lattice Boltzmann (LB) model simulating a concentrated emulsion with finite-size droplets evolving in a thermal convective state, just above the transition from conduction to convection. The droplet concentration of the emulsion system is tunable and at the core of the code lies the possibility to measure a large number of physical observables characterising the flow and dropletsFurthermore, TLBfind includes a parallel implementation on GPU of the Delaunay triangulation useful for the detection of droplets' plastic rearrangements, and several types of boundary conditions, supporting simulations of channels with structured rough walls.

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LBfoam: An open-source software package for the simulation of foaming using the Lattice Boltzmann Method

Cited by 16 publications

References 57 publications

Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

NPLIC: A machine learning approach to piecewise linear interface construction

TLBfind: a Thermal Lattice Boltzmann code for concentrated emulsions with FINite-size Droplets

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