Massively parallel numerical simulation using up to 36,000 CPU cores of an industrial-scale polydispersed reactive pressurized fluidized bed with a mesh of one billion cells

Neau, Hervé; Pigou, Maxime; Fede, Pascal; Ansart, Renaud; Baudry, C.; Mérigoux, Nicolas; Laviéville, Jérôme; Fournier, Yvan; Renon, Nicolas; Simonin, Olivier

doi:10.1016/j.powtec.2020.03.010

Cited by 35 publications

(13 citation statements)

References 39 publications

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“…Numerical modeling of processes at laboratory, pilot and industrial scales by N-Euler CFD modeling approaches (such as NEPTUNE_CFD) are becoming powerful tools to support optimization or scaling-up of polymerization processes [133]- [136] and the development of new processes based on innovative concepts. [137] Despite the usefulness of such models, there are clear limitations with respect to the correct description of the hydrodynamics (mixing and segregation of solids) of multiphase flows, and the proper modeling of reactor hydrodynamics is still in its infancy. A recent review on modeling of gas phase reactors for ethylene polymerization made it clear that the models that one finds in the literature are necessarily simplified because otherwise they cannot be solved in a reasonable timeframe.…”

Section: Reactor Fluid Dynamicsmentioning

confidence: 99%

A conceptual multilevel approach to polyolefin reaction engineering

Soares

McKenna

2022

Can J Chem Eng

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This article gives a wide overview of different types of mathematical models that can be used to describe the polymerization of linear olefins with coordination catalysts. We expanded the conventional classification of mathematical models into micro-, meso-, and macroscale, to include seven modelling levels: catalysis, polymerization kinetics, thermodynamic equilibrium, particle transport phenomena, particle interactions, reactor fluid dynamics, and reactor residence time distribution. Some of these levels may coexist at the same scale, but they are better treated separately because they make use of distinct modelling approaches. How complex the models in each level need to be, as well as how many modelling levels should be implicitly included, depends on the type of application intended for the simulations. In this paper, we will argue that the proposed levels of mathematical modelling not only bring to our attention the complexity behind the simulation of laboratory-and industrial-scale olefin polymerization reactors but are also useful conceptual tools to assist us to decide which levels to include and which ones to exclude when we develop simulation packages to describe olefin polymerization processes.

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Section: Reactor Fluid Dynamicsmentioning

confidence: 99%

A conceptual multilevel approach to polyolefin reaction engineering

Soares

McKenna

2022

Can J Chem Eng

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“…Just for curiosity, up to authors’ best knowledge the biggest computational effort for CFD applied to a fluidized bed reactor was recently reported by Neau et al., [ 141 ] who employed 36 000 CPU cores, a mesh composed of a billion element and 15 millions of CPU hours to simulate an industrial scale FBR with a 3D geometry. Even though the calculation produced 200 TB of data, the simulated physical time was no longer than 25 s.…”

Section: Macroscale Modeling With Computational Fluid Dynamicsmentioning

confidence: 99%

Gas‐Phase Polyethylene Reactors—A Critical Review of Modeling Approaches

Alves

Casalini

Storti

et al. 2021

Macro Reaction Engineering

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Different approaches to modeling the gas phase polymerization of ethylene that have been considered in the literature are reviewed. It is shown that while simple, well‐mixed models can give an adequate representation of the average performance of a given polymerization reactor, they do not allow one to analyze certain modeling problems such as the existence of temperature gradients or particle segregation, nor can they be used to treat operational modes such as condensed cooling where there can be up to three different phases in different parts of the reactor. For this, more complex models are required. These can take the form of compartmentalized models or even models based on computation fluid dynamics. However, long computational times can be required to fully exploit these models. Furthermore, significant progress needs to be made if one needs to address important phenomena such as agglomeration or particle attrition during polymerization.

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“…This software is a multiphase flow solver developed in the framework of the NEPTUNE project, financially supported by CEA, EDF, IRSN and Framatome. The numerical solver has been developed for High Performance Computing [24][25][26]. The transport equations are derived by phase ensemble averaging for the continuous phase and in the framework of the kinetic theory of granular flows [27] for the dispersed phase but extended in order to take into account the interstitial fluid effects and particles-turbulence interactions [28,29].…”

Section: Numerical Simulation Overviewmentioning

confidence: 99%

Eulerian modelling of the powder discharge of a silo: Attempting to shed some light on the origin of jet expansion

Audard

Fede

Belut³

et al. 2021

Powder Technology

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Powder discharging from a silo provokes an emission of dust. To understand and prevent this source of danger, 3D simulations of a silo discharge were performed using an Euler-Euler approach. The impact of the coupling between the flow inside the silo and the granular jet in free-fall is analyzed. Results show that the solid mass flow rate is correctly predicted and that gas back-flowing at the hopper exhaust appears responsible for the formation of a fluctuating and radially expanding jet. However, the radial expansion of the free-falling jet is underestimated. Stochastic fluctuations of the particles velocity at the hopper exhaust are introduced to evaluate their effect on the downstream development of the free-falling jet. These fluctuations are found capable of generating a development of the jet similar to that observed experimentally. This suggests that the granular flow conditions at the hopper exhaust are responsible for the further dispersion of powder.

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Massively parallel numerical simulation using up to 36,000 CPU cores of an industrial-scale polydispersed reactive pressurized fluidized bed with a mesh of one billion cells

Abstract: Massively parallel numerical simulation using up to 36,000 CPU cores of an industrial-scale polydispersed reactive pressurized fluidized bed with a mesh of one billion cells. (2020) Powder Technology, 366. 906-924. ISSN 00325910 .

Cited by 35 publications

References 39 publications

A conceptual multilevel approach to polyolefin reaction engineering

A conceptual multilevel approach to polyolefin reaction engineering

Gas‐Phase Polyethylene Reactors—A Critical Review of Modeling Approaches

Eulerian modelling of the powder discharge of a silo: Attempting to shed some light on the origin of jet expansion

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