NEPTUNE_CFD High Parallel Computing Performances for Particle-Laden Reactive Flows

This paper presents high performance computing of NEPTUNE_CFD V1.07@Tlse. NEPTUNE_CFD is an unstructured parallelized code (MPI) using unsteady Eulerian multi-fluid approach for dilute and dense particle-laden reactive flows. Three-dimensional numerical simulations of two test cases have been carried out. The first one, a uniform granular shear flow exhibits an excellent scalability of NEPTUNE_CFD up to 1024 cores, and demonstrates the good agreement between the parallel simulation results and the analytical solutions. Strong scaling and weak scaling benchmarks have been performed. The second test case, a realistic dense fluidized bed shows the code computing performances on an industrial geometry

Comparative study of pressure-correction and Godunov-type schemes on unsteady compressible cases

International audienceTwo pressure-correction algorithms are studied and compared to an approximate Godunov scheme on unsteady compressible cases. The first pressure-correction algorithm sequentially solves the equations for momentum, mass and enthalpy, with sub-iterations which ensure conservativity. The algorithm also conserves the total enthalpy along a streamline, in a steady flow. The second pressure-correction algorithm sequentially solves the equations for mass, momentum and energy without sub-iteration. This scheme is conservative and ensures the discrete positivity of the density. Total enthalpy is conserved along a streamline, in a steady flow. It is numerically verified that both pressure-correction algorithms converge towards the exact solution of Riemann problems, including shock waves, rarefaction waves and contact discontinuities. To achieve this, conservativity is compulsory. The two pressure-correction algorithms and the approximate Godunov scheme are finally compared on cases with heat source terms: all schemes converge towards the same solution as the mesh is refined

Strongly coupled fluid-particle flows in vertical channels. II. Turbulence modeling

In Part I, simulations of strongly coupled fluid-particle flow in a vertical channel were performed with the purpose of understanding, in general, the fundamental physics of wall-bounded multiphase turbulence and, in particular, the roles of the spatially correlated and uncorrelated components of the particle velocity.The exact Reynolds-averaged (RA) equations for high-mass-loading suspensions were presented, and the unclosed terms that are retained in the context of fully developed channel flow were evaluated in an Eulerian–Lagrangian (EL) framework. Here, data from the EL simulations are used to validate a multiphase Reynolds-stress model (RSM) that predicts the wall-normal distribution of the two-phase, one-point turbulence statistics up to second order. It is shown that the anisotropy of the Reynolds stresses both near the wall and far away is a crucial component for predicting the distribution of the RA particle-phase volume fraction. Moreover, the decomposition of the phase-average (PA) particle-phase fluctuating energy into the spatially correlated and uncorrelated components is necessary to account for the boundary conditions at the wall. When these factors are properly accounted for in the RSM, the agreement with the EL turbulence statistics is satisfactory at first order (e.g., PA velocities) but less so at second order (e.g., PA turbulent kinetic energy). Finally, an algebraic stress model for the PA particle-phase pressure tensor and the Reynolds stresses is derived from the RSM using the weak-equilibrium assumption

High performance computing (HPC) for the fluidization of particle-laden reactive flows

The present paper shows the parallel computing performance (up to 4,096 cores) of a numerical solver for simulation of dense reactive multiphase reactive flow such as fluidized bed reactor. NEPTUNE_CFD V1.08 is a parallelized unstructured code solving unsteady Eulerian multi-fluid approach. The meshes have up to 38,000,000 cells. The simulations show an excellent scalability up to 2,536 cores

Computational study of dense granular flows in stirred reactors

In chemical engineering applications, reactors featuring rotating parts are common practice. As these rotating parts are present in order to enhance chemical reactions, it is essential to take them into account when performing predictive numerical simulations. This aspect can be particularly challenging, even more so when complex industrial geometries are to be treated. In this communication the rotating mesh numerical methodology of NEPTUNE_CFD V3.0 (an Eulerian n-fluid multiphase flow CFD code) is presented. The method is based on splitting the domain into static and rotating parts. The information between rotating and static parts is passed thanks to a non-conformal mesh matching technique. The methodology is first validated, both numerically and experimentally using the classical rotating drum case. The high degree of compaction of the flow is taken into account thanks to a frictional stress tensor. The method is then pushed further and used to investigate the hydrodynamics of dry granular beds in stirred vessels. The results show that the rotating mesh method can effectively treat such configurations, hence offering interesting insight concerning the dynamics of the flow

Numerical simulation of unsteady dense granular flows with rotating geometries.

In chemical engineering applications, it is not uncommon to encounter reactors featuring rotating parts. As these rotating parts are present in order to enhance processes such as chemical reactions and/or ensure homogeneity, it is essential to take them into account to perform predictive numerical simulations. This aspect can be particularly challenging, even more so when complex industrial geometries are to be treated.In this paper a numerical methodology for simulating unsteady granular flow in rotating geometries is presented. The method is based on splitting the domain into static and rotating parts. The information between rotating and static parts is passed by a non-conformal mesh matching technique. The presented methodology is validated numerically by comparing its results with other conventional methods. The method is then applied to an industrial scale problem. The applicability of the method and the way it may be used to investigate complex flow is demonstrated. Therefore this approach enables to consider the full geometry of complex reactors. It opens the door to further investigation, optimization and design of industrial scale chemical processes

A CMOS silicon spin qubit

Silicon, the main constituent of microprocessor chips, is emerging as a promising material for the realization of future quantum processors. Leveraging its well-established complementary metal-oxide-semiconductor (CMOS) technology would be a clear asset to the development of scalable quantum computing architectures and to their co-integration with classical control hardware. Here we report a silicon quantum bit (qubit) device made with an industry-standard fabrication process. The device consists of a two-gate, p-type transistor with an undoped channel. At low temperature, the first gate defines a quantum dot (QD) encoding a hole spin qubit, the second one a QD used for the qubit readout. All electrical, two-axis control of the spin qubit is achieved by applying a phase-tunable microwave modulation to the first gate. Our result opens a viable path to qubit up-scaling through a readily exploitable CMOS platform.Comment: 12 pages, 4 figure

A penalization method for the simulation of bubbly flows

This work is devoted to the development of a penalization method for the simulation of bubbly flows. Spherical bubbles are considered as moving penalized obstacles interacting with the fluid and a numerical method for ensuring the shear free condition at the liquid– bubble interface is proposed. Three test-cases (curved channel, inclined channel and 3D translating bubble) are used to validate the accuracy of the discretization ensuring the slip condition at the interface. Numerical simulations of a rising bubble in a quiescent liquid are performed for moderate Reynolds numbers. Considering bubble terminal velocities, initial accelerations and wake decay, the effect of the penalization viscosity used to ensure a uniform velocity in the penalized object is discussed. Finally, simulations of bubble swarms have been carried out in a fully periodic box with a large range of void fractions from 1% to 15%. The statistics provided by the simulations characterizing the bubble-induced agitation are found in remarkable agreement with the experiments

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 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