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

For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The application of developed models for predictive simulations has however been strongly limited by the available computational power and the capability o...

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Vydáno v:Powder technology Ročník 366; s. 906 - 924
Hlavní autoři: Neau, Hervé, Pigou, Maxime, Fede, Pascal, Ansart, Renaud, Baudry, Cyril, Mérigoux, Nicolas, Laviéville, Jérome, Fournier, Yvan, Renon, Nicolas, Simonin, Olivier
Médium: Journal Article
Jazyk:angličtina
Vydáno: Lausanne Elsevier B.V 15.04.2020
Elsevier BV
Elsevier
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ISSN:0032-5910, 1873-328X
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Abstract For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The application of developed models for predictive simulations has however been strongly limited by the available computational power and the capability of computational fluid dynamics software to handle large enough simulations. In recent years, both aspects have made significant advances and we thus now demonstrate the feasibility of a massively parallel simulation, on whole supercomputers using NEPTUNE_CFD, of an industrial-scale polydispersed fluidized-bed reactor. This simulation of an olefin polymerization reactor makes use of an unsteady Eulerian multi-fluid approach and relies on a billion cells meshing. This is a worldwide premiere as the obtained accuracy is yet unmatched for such a large-scale system. The interest of this work is two-fold. In terms of High Performance Computation (HPC), all steps of setting-up the simulation, running it with NEPTUNE_CFD, and post-processing results induce multiple challenges due to the scale of the simulation. The simulation ran using 1260 up to 36,000 cores on supercomputers, used 15 millions of CPU hours and generated 200 TB of raw data for a simulated physical time of 25s. This article details the methodology applied to handle this simulation, and also focuses on computation performances in terms of profiling, code efficiency and partitioning method suitability. Though being by itself interesting, the HPC challenge is not the only goal of this work as performing this highly-resolved simulation will benefit chemical engineering and CFD communities. Indeed, this computation enables the possibility to account, in a realistic way, for complex flows in an industrial-scale reactor. The predicted behavior is described, and results are post-processed to develop sub-grid models. These will allow for lower-cost simulations with coarser meshes while still encompassing local phenomenon. [Display omitted] •An industrial-scale reactive polydispersed gas-solid fluidized bed is simulated.•The mesh reaches a size of a billion cells; the simulation ran on 36,000 CPU cores.•Focus is made on HPC challenges at all steps: simulation setup, run, post-processing.•Massively parallel performances of NEPTUNE_CFD are evaluated on two supercomputers.•Sub-grid models are developed from the highly resolved simulation.
AbstractList For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The application of developed models for predictive simulations has however been strongly limited by the available computational power and the capability of computational fluid dynamics software to handle large enough simulations. In recent years, both aspects have made significant advances and we thus now demonstrate the feasibility of a massively parallel simulation, on whole supercomputers using NEPTUNE_CFD, of an industrial-scale polydispersed fluidized-bed reactor. This simulation of an olefin polymerization reactor makes use of an unsteady Eulerianmulti-fluid approach and relies on a billion cellsmeshing. This is a worldwide premiere as the obtained accuracy is yet unmatched for such a large-scale system. The interest of this work is two-fold. In terms of High Performance Computation (HPC), all steps of setting-up the simulation, running it with NEPTUNE_CFD, and post-processing results induce multiple challenges due to the scale of the simulation. The simulation ran using 1260 up to 36,000 cores on supercomputers, used 15 millions of CPU hours and generated 200 TB of rawdata for a simulated physical time of 25s. This article details the methodology applied to handle this simulation, and also focuses on computation performances in terms of profiling, code efficiency and partitioning method suitability. Though being by itself interesting, the HPC challenge is not the only goal of this work as performing this highly-resolved simulation will benefit chemical engineering and CFD communities.Indeed, this computation enables the possibility to account, in a realistic way, for complex flows in an industrial-scale reactor. The predicted behavior is described, and results are post-processed to develop sub-grid models. These will allow for lower-cost simulations with coarser meshes while still encompassing local phenomenon.
For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The application of developed models for predictive simulations has however been strongly limited by the available computational power and the capability of computational fluid dynamics software to handle large enough simulations. In recent years, both aspects have made significant advances and we thus now demonstrate the feasibility of a massively parallel simulation, on whole supercomputers using NEPTUNE_CFD, of an industrial-scale polydispersed fluidized-bed reactor. This simulation of an olefin polymerization reactor makes use of an unsteady Eulerian multi-fluid approach and relies on a billion cells meshing. This is a worldwide premiere as the obtained accuracy is yet unmatched for such a large-scale system. The interest of this work is two-fold. In terms of High Performance Computation (HPC), all steps of setting-up the simulation, running it with NEPTUNE_CFD, and post-processing results induce multiple challenges due to the scale of the simulation. The simulation ran using 1260 up to 36,000 cores on supercomputers, used 15 millions of CPU hours and generated 200 TB of raw data for a simulated physical time of 25s. This article details the methodology applied to handle this simulation, and also focuses on computation performances in terms of profiling, code efficiency and partitioning method suitability. Though being by itself interesting, the HPC challenge is not the only goal of this work as performing this highly-resolved simulation will benefit chemical engineering and CFD communities. Indeed, this computation enables the possibility to account, in a realistic way, for complex flows in an industrial-scale reactor. The predicted behavior is described, and results are post-processed to develop sub-grid models. These will allow for lower-cost simulations with coarser meshes while still encompassing local phenomenon.
For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The application of developed models for predictive simulations has however been strongly limited by the available computational power and the capability of computational fluid dynamics software to handle large enough simulations. In recent years, both aspects have made significant advances and we thus now demonstrate the feasibility of a massively parallel simulation, on whole supercomputers using NEPTUNE_CFD, of an industrial-scale polydispersed fluidized-bed reactor. This simulation of an olefin polymerization reactor makes use of an unsteady Eulerian multi-fluid approach and relies on a billion cells meshing. This is a worldwide premiere as the obtained accuracy is yet unmatched for such a large-scale system. The interest of this work is two-fold. In terms of High Performance Computation (HPC), all steps of setting-up the simulation, running it with NEPTUNE_CFD, and post-processing results induce multiple challenges due to the scale of the simulation. The simulation ran using 1260 up to 36,000 cores on supercomputers, used 15 millions of CPU hours and generated 200 TB of raw data for a simulated physical time of 25s. This article details the methodology applied to handle this simulation, and also focuses on computation performances in terms of profiling, code efficiency and partitioning method suitability. Though being by itself interesting, the HPC challenge is not the only goal of this work as performing this highly-resolved simulation will benefit chemical engineering and CFD communities. Indeed, this computation enables the possibility to account, in a realistic way, for complex flows in an industrial-scale reactor. The predicted behavior is described, and results are post-processed to develop sub-grid models. These will allow for lower-cost simulations with coarser meshes while still encompassing local phenomenon. [Display omitted] •An industrial-scale reactive polydispersed gas-solid fluidized bed is simulated.•The mesh reaches a size of a billion cells; the simulation ran on 36,000 CPU cores.•Focus is made on HPC challenges at all steps: simulation setup, run, post-processing.•Massively parallel performances of NEPTUNE_CFD are evaluated on two supercomputers.•Sub-grid models are developed from the highly resolved simulation.
For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The application of developed models for predictive simulations has however been strongly limited by the available computational power and the capability of computational fluid dynamics software to handle large enough simulations. In recent years, both aspects have made significant advances and we thus now demonstrate the feasibility of a massively parallel simulation, on whole supercomputers using NEPTUNE_CFD, of an industrial-scale polydispersed fluidized-bed reactor. This simulation of an olefin polymerization reactor makes use of an unsteady Eulerian multi-fluid approach and relies on a billion cells meshing. This is a worldwide premiere as the obtained accuracy is yet unmatched for such a large-scale system. The interest of this work is two-fold. In terms of High Performance Computation (HPC), all steps of setting-up the simulation, running it with NEPTUNE_CFD, and post-processing results induce multiple challenges due to the scale of the simulation. The simulation ran using 1260 up to 36,000 cores on supercomputers, used 15 millions of CPU hours and generated 200 TB of raw data for a simulated physical time of 25 s. This article details the methodology applied to handle this simulation, and also focuses on computation performances in terms of profiling, code efficiency and partitioning method suitability. Though being by itself interesting, the HPC challenge is not the only goal of this work as performing this highly-resolved simulation will benefit chemical engineering and CFD communities. Indeed, this computation enables the possibility to account, in a realistic way, for complex flows in an industrial-scale reactor. The predicted behavior is described, and results are post-processed to develop sub-grid models. These will allow for lower-cost simulations with coarser meshes while still encompassing local phenomenon.
Author Fournier, Yvan
Pigou, Maxime
Ansart, Renaud
Renon, Nicolas
Simonin, Olivier
Fede, Pascal
Neau, Hervé
Baudry, Cyril
Mérigoux, Nicolas
Laviéville, Jérome
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  organization: Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
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  organization: Fluid Mechanics, Energy and Environment Dpt., EDF R&D, Chatou, France
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  fullname: Laviéville, Jérome
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  organization: Fluid Mechanics, Energy and Environment Dpt., EDF R&D, Chatou, France
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  givenname: Olivier
  surname: Simonin
  fullname: Simonin, Olivier
  organization: Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
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Keywords Computation fluid dynamics
Sub-grid model
High performance computing
Polydispersed
MPI
Industrial scale
HPC
Olefin polymerization reactor
Massively parallel
Heat transfer
Fluidized bed
Language English
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Snippet For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The...
For the last 30 years, experimental and modeling studies have been carried out on fluidized bed reactors from laboratory up to industrial scales. The...
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SubjectTerms Chemical and Process Engineering
Chemical engineering
Chemical Sciences
Computation fluid dynamics
Computational fluid dynamics
Computer applications
Computer simulation
computer software
computers
Cores
Engineering Sciences
Finite element method
Fluid dynamics
fluid mechanics
Fluidized bed
Fluidized bed reactors
Fluidized beds
Fluids mechanics
Heat transfer
High performance computing
HPC
Hydrodynamics
Industrial scale
Massively parallel
Mathematical models
Mechanics
MPI
olefin
Olefin polymerization reactor
Polydispersed
polymerization
porous media
Post-production processing
Reactors
Simulation
Sub-grid model
Supercomputers
Title 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
URI https://dx.doi.org/10.1016/j.powtec.2020.03.010
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https://www.proquest.com/docview/2431852394
https://hal.science/hal-02735376
Volume 366
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