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Benyahia, Sofiane

Publications and source records attributed to Benyahia, Sofiane.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Chapter 2: Advances in Coarse Discrete Particle Methods with Industrial Applications

This chapter provides the full description of a coarse-grained discrete particle method based on a novel hard-sphere contact model for the simulation of industrial-scale fluidized bed reactors. This method is based on simple models that are easy to understand and implement in numerical codes. This technique is verified and validated for several small-scale fluidized systems where numerical data based on finer methods as well as experimental data are available. The speed of execution of this method is increased several orders of magnitudes compared to particle-based discrete methods, which allows for thousands of seconds of flow, heat, and mass transfer simulations of industrial reactors such as fluidized catalytic cracking regenerator, Methanol to Olefins reactor, and Rare Earth Elements leaching reactor, achieved in just few days using commonly available computer resources. It is now possible for the common engineer to conduct simulations of large-scale fluid–particle reactors to understand, design, and troubleshoot, as well as optimize the performance of these complex multiphase flow systems.

Lu, Liqiang↗
DOE OSTI2018

Method to estimate uncertainty associated with parcel size in coarse discrete particle simulation

Coarse grained particle methods significantly reduce the computation cost of large‐scale fluidized bed simulation by lumping many real particles into a computation parcel. This research provides a method to estimate the errors associated with parcel size in large‐scale fluidized bed simulations. This uncertainty is first quantified in small scale domains by comparing results of discrete particle method with that employing coarse parcels of different sizes. Then, this uncertainty is correlated with parcel size and simulation domains consisting of a simple homogeneous cooling system and more complex bubbling and circulating fluidized beds. These correlations allow us to accurately estimate the uncertainty in large‐scale fluidized beds based solely on data obtained in smaller systems. The ability to estimate model‐related uncertainty in larger systems makes this method relevant for industrial applications. © 2018 American Institute of Chemical Engineers AIChE J , 64: 2340–2350, 2018

Lu, Liqiang↗
DOE OSTI2018

Assessment of different coarse graining strategies to simulate polydisperse gas-solids flow

Continuum methods require the additional development of solids stress closures for polydisperse powders based on complex kinetic theories that are non-trivial to develop, code, and numerically converge for the wide range of fluidization regimes from very dilute to dense/frictional flow limit. On the other hand, it is straightforward to model the flow of polydisperse granular materials by treating particles as discrete rigid bodies that are tracked following simple physical laws of motion. The coarsening of these discrete methods by lumping several particles in a parcel alleviates the significant computational cost associated with these discrete methods while introducing some inaccuracies in the numerical results. In this research, we explore two different coarse graining methods that can be applied to polydisperse powders, namely the same statistic weight method (SSW) and the same size parcel method (SSP), and assess their accuracy by comparison with the finest simulation results obtained with a discrete element method (DEM). For Geldart group B powders fluidized at a relative low superficial velocity, the numerical results indicate that the SSW is more accurate than the SSP method. For type A powders fluidized at relatively high velocity, these two methods predict similar results. Interestingly, up to four times increase in the speed of simulation of the SSP method was obtained because the original polydisperse powder is scaled to a mono-disperse system in terms of particle-particle collision. Lastly, these results suggest that the SSP method is more favorable for the simulation of fluidized beds due to its accuracy and efficiency while the SSW method may be used for granular flow and dense fluidized bed systems where capturing the size segregation of particles due to collision is important.

42 ENGINEERING↗
DOE OSTI2017

Numerical Investigation of the Ability of Salt Tracers to Represent the Residence Time Distribution of Fluidized Catalytic Cracking Particles

For a long time, salt tracers have been used to measure the residence time distribution (RTD) of fluidized catalytic cracking (FCC) particles. However, due to limitations in experimental measurements and simulation methods, the ability of salt tracers to faithfully represent RTDs has never been directly investigated. Our current simulation results using coarse-grained computational fluid dynamic coupled with discrete element method (CFD-DEM) with filtered drag models show that the residence time of salt tracers with the same terminal velocity as FCC particles is slightly larger than that of FCC particles. This research also demonstrates the ability of filtered drag models to predict the correct RTD curve for FCC particles while the homogeneous drag model may only be used in the dilute riser flow of Geldart type B particles. The RTD of large-scale reactors can then be efficiently investigated with our proposed numerical method as well as by using the old-fashioned salt tracer technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Assessing the capability of continuum and discrete particle methods to simulate gas-solids flow using DNS predictions as a benchmark

For this study, gas–solids flow in a three-dimension periodic domain was numerically investigated by direct numerical simulation (DNS), computational fluid dynamic-discrete element method (CFD-DEM) and two-fluid model (TFM). DNS data obtained by finely resolving the flow around every particle are used as a benchmark to assess the validity of coarser DEM and TFM approaches. The CFD-DEM predicts the correct cluster size distribution and under-predicts the macro-scale slip velocity even with a grid size as small as twice the particle diameter. The TFM approach predicts larger cluster size and lower slip velocity with a homogeneous drag correlation. Although the slip velocity can be matched by a simple modification to the drag model, the predicted voidage distribution is still different from DNS: Both CFD-DEM and TFM over-predict the fraction of particles in dense regions and under-predict the fraction of particles in regions of intermediate void fractions. Also, the cluster aspect ratio of DNS is smaller than CFD-DEM and TFM. Since a simple correction to the drag model can predict a correct slip velocity, it is hopeful that drag corrections based on more elaborate theories that consider voidage gradient and particle fluctuations may be able to improve the current predictions of cluster distribution.

42 ENGINEERING↗
DOE OSTI2017

Quantifying the uncertainty introduced by discretization and time-averaging in two-fluid model predictions

The two-fluid model (TFM) has become a tool for the design and troubleshooting of industrial fluidized bed reactors. To use TFM for scale up with confidence, the uncertainty in its predictions must be quantified. Here, we study two sources of uncertainty: discretization and time-averaging. First, we show that successive grid refinement may not yield grid-independent transient quantities, including cross-section–averaged quantities. Successive grid refinement would yield grid-independent time-averaged quantities on sufficiently fine grids. A Richardson extrapolation can then be used to estimate the discretization error, and the grid convergence index gives an estimate of the uncertainty. Richardson extrapolation may not work for industrial-scale simulations that use coarse grids. We present an alternative method for coarse grids and assess its ability to estimate the discretization error. Second, we assess two methods (autocorrelation and binning) and find that the autocorrelation method is more reliable for estimating the uncertainty introduced by time-averaging TFM data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Assessment of Different Discrete Particle Methods Ability To Predict Gas-Particle Flow in a Small-Scale Fluidized Bed

Several discrete particle methods exist in the open literature to simulate fluidized bed systems, such as discrete element method (DEM), time driven hard sphere (TDHS), coarse-grained particle method (CGPM), coarse grained hard sphere (CGHS), and multi-phase particle-in-cell (MP-PIC). These different approaches usually solve the fluid phase in a Eulerian fixed frame of reference and the particle phase using the Lagrangian method. The first difference between these models lies in tracking either real particles or lumped parcels. The second difference is in the treatment of particle-particle interactions: by calculating collision forces (DEM and CGPM), using momentum conservation laws (TDHS and CGHS), or based on particle stress model (MP-PIC). These major model differences lead to a wide range of results accuracy and computation speed. However, these models have never been compared directly using the same experimental dataset. In this research, a small-scale fluidized bed is simulated with these methods using the same open-source code MFIX. The results indicate that modeling the particle-particle collision by TDHS increases the computation speed while maintaining good accuracy. Also, lumping few particles in a parcel increases the computation speed with little loss in accuracy. However, modeling particle-particle interactions with solids stress leads to a big loss in accuracy with a little increase in computation speed. The MP-PIC method predicts an unphysical particle-particle overlap, which results in incorrect voidage distribution and incorrect overall bed hydrodynamics. Based on this study, we recommend using the CGHS method for fluidized bed simulations due to its computational speed that rivals that of MPPIC while maintaining a much better accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

An efficient and reliable predictive method for fluidized bed simulation

In past decades, the continuum approach was the only practical technique to simulate large-scale fluidized bed reactors because discrete approaches suffer from the cost of tracking huge numbers of particles and their collisions. This study significantly improved the computation speed of discrete particle methods in two steps: First, the time-driven hard-sphere (TDHS) algorithm with a larger time-step is proposed allowing a speedup of 20-60 times; second, the number of tracked particles is reduced by adopting the coarse-graining technique gaining an additional 2-3 orders of magnitude speedup of the simulations. A new velocity correction term was introduced and validated in TDHS to solve the over-packing issue in dense granular flow. The TDHS was then coupled with the coarse-graining technique to simulate a pilot-scale riser. The simulation results compared well with experiment data and proved that this new approach can be used for efficient and reliable simulations of large-scale fluidized bed systems.

42 ENGINEERING↗
DOE OSTI2017

Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation

Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneous drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Extension of a coarse grained particle method to simulate heat transfer in fluidized beds

The heat transfer in a gas-solids fluidized bed is simulated with computational fluid dynamic-discrete element method (CFD-DEM) and coarse grained particle method (CGPM). In CGPM fewer numerical particles and their collisions are tracked by lumping several real particles into a computational parcel. Here, the assumption is that the real particles inside a coarse grained particle (CGP) are made from same species and share identical physical properties including density, diameter and temperature. The parcel-fluid convection term in CGPM is calculated using the same method as in DEM. For all other heat transfer mechanisms, we derive in this study mathematical expressions that relate the new heat transfer terms for CGPM to those traditionally derived in DEM. This newly derived CGPM model is verified and validated by comparing the results with CFD-DEM simulation results and experiment data. The numerical results compare well with experimental data for both hydrodynamics and temperature profiles. Finally, the proposed CGPM model can be used for fast and accurate simulations of heat transfer in large scale gas-solids fluidized beds.

01 COAL, LIGNITE, AND PEAT↗