Multi-GPUs parallel computation of dendrite growth in forced convection using the phase-field-lattice Boltzmann model

Sakane, Shinji; Takaki, Tomohiro; Rojas, Roberto; Ohno, Munekazu; Shibuta, Yasushi; Shimokawabe, Takashi; Aoki, Takayuki

doi:10.1016/j.jcrysgro.2016.11.103

Cited by 85 publications

(39 citation statements)

References 57 publications

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“…1 dq dp PFLBM and PFM correspond to the simulations shown in Fig. 4(a) and (b), respectively [14]. Fig.…”

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confidence: 74%

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Phase-Field Analysis of Dendrite Growth with Melt Flow

Takaki¹

2018

JAPANESE JOURNAL OF MULTIPHASE FLOW

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Dendrite morphology is drastically changed due to the liquid flow, such as forced and natural convections, during the solidification of metallic alloys. We have developed a phase-field lattice Boltzmann method to simulate the dendrite growth during the alloy solidification in the presence of the liquid flow. Here, we have employed the phase-field and lattice Boltzmann methods to express the dendrite growth and liquid flow, respectively. In addition, a parallel computation using multiple graphical processing units in a supercomputer has been enabled to accelerate the phase-field lattice Boltzmann simulation. In this report, the phase-field lattice Boltzmann model is briefly explained, and some dendrite growth simulations using the model are introduced.

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“…1 dq dp PFLBM and PFM correspond to the simulations shown in Fig. 4(a) and (b), respectively [14]. Fig.…”

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confidence: 74%

“…Dendrite morphological changes during growth of an equiaxed dendrite (a) with and (b) without forced convection[14].…”

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confidence: 99%

Phase-Field Analysis of Dendrite Growth with Melt Flow

Takaki¹

2018

JAPANESE JOURNAL OF MULTIPHASE FLOW

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“…However, it requires large computational cost. Therefore, we have developed a parallel GPU scheme for a coupling model of phase‐field and lattice Boltzmann methods to accelerate the dendrite growth simulation in the presence of the liquid flow . Here, we employed the lattice Boltzmann method for solving the liquid flow because it has a great advantage in parallel computing due to the easily implemented method.…”

Section: Large‐scale Phase‐field Simulation Of Solidification and Gramentioning

confidence: 99%

Advent of Cross‐Scale Modeling: High‐Performance Computing of Solidification and Grain Growth

Shibuta

Ohno

Takaki

2018

Advcd Theory and Sims

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The application range of computational metallurgy is rapidly expanding thanks to the recent progress in high-performance computing. In this Progress Report, state-of-the-art collections of large-scale simulations of solidification and grain growth, performed on the GPU supercomputer, are introduced. One of the notable achievements in this direction is a billion-atom molecular dynamics simulation for nucleation and solidification, which revealed the heterogeneity in homogeneous nucleation. Moreover, a series of large-scale phase-field simulations shed light on the topics at issue including competitive growth of dendrites during the directional solidification, the effect of forced and natural convections on the solidification, and so on. Based on simulation results bridging the gap between atomistic and continuum-based simulations, a new criterion of multi-scale modeling is proposed in the age to come. We are now standing at the new era of cross-scale modeling, in which the overlap between atomistic and continuum simulations creates new research concepts and fields.

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“…Spatial locality, a linear advection term, no Poisson solver for pressure, and relative ease of imposing complex boundaries and coupling with other numerical solvers are some of the LBM advantages over conventional computational fluid dynamics methods and are the reason for its use in many applications 4-6 . Because of the locality property, the method can be massively parallelized for speed‐up on modern computing architectures 7-11 …”

Section: Introductionmentioning

confidence: 99%

“…The most popular one is the bounce‐back scheme, where particles collide with the wall and reverse their momentum. It is widely and effectively used in applications with complex geometries 7-11,17-19 due to its efficiency, simplicity, and second‐order accuracy when the boundary is placed midway between gridpoints, and first‐order otherwise. However, it has some drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Moment‐based boundary conditions for straight on‐grid boundaries in three‐dimensional lattice Boltzmann simulations

Krastiņš

Kao

Pericleous

et al. 2020

Numerical Methods in Fluids

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Summary In this article, moment‐based boundary conditions for the lattice Boltzmann method are extended to three dimensions. Boundary conditions for velocity and pressure are explicitly derived for straight on‐grid boundaries for the D3Q19 lattice. The method is compared against the bounce‐back scheme using both single and two relaxation time collision schemes. The method is verified using classical benchmark test cases. The results show very good agreement with the data found in the literature. It is confirmed from the results that the derived moment‐based boundary scheme is of second‐order accuracy in grid spacing and does not produce numerical slip, and therefore offers a transparent way of accurately prescribing velocity and pressure boundaries that are aligned with grid points in three‐dimensional.

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Multi-GPUs parallel computation of dendrite growth in forced convection using the phase-field-lattice Boltzmann model

Cited by 85 publications

References 57 publications

Phase-Field Analysis of Dendrite Growth with Melt Flow

Phase-Field Analysis of Dendrite Growth with Melt Flow

Advent of Cross‐Scale Modeling: High‐Performance Computing of Solidification and Grain Growth

Moment‐based boundary conditions for straight on‐grid boundaries in three‐dimensional lattice Boltzmann simulations

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