Multiscale CFD modelling and analysis of TBR behavior for an HDS process: Deviations from ideal behaviors

Uribe, Sebastián; Cordero, Mario E.; Peralta-Reyes, Ever; Regalado-Méndez, Alejandro; Zárate, Luis Gonzaga Alonso

doi:10.1016/j.fuel.2018.11.104

Cited by 9 publications

(4 citation statements)

References 35 publications

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“…However, nowadays, the modeling of these systems requires simplifications, such as model order reduction, since the purely theoretical (mechanistic) models are still too computationally expensive, require an unpractical level of detail in the geometrical representation [29], or result in ill-posed or highly stiff equations [30]. In order to avoid such complexity, the common approach is to insert on the transport equations closure sub-models that capture, to a certain extent, complex phenomena, such as the microscale multiphase interactions [31]. The drawback in relying on coupled sub-model lays is the fact that these closure terms are usually a set of empirical or semi-empirical expressions, which lack a mechanistic development and can, hence, constrain the applicability of the main mathematical model.…”

Section: Introductionmentioning

confidence: 99%

Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview

Uribe

Al‐Dahhan

2021

Processes

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Modeling of gas-solid fluidized systems has been a prevailing challenge over the last few decades. With different approaches and implementing different sub-models to capture the essential multiphase and multiscale phenomena in these systems, major advances have been achieved, even though most models are only subject to a practical validation of macroscopic parameters. The current description of fluidized beds through mathematical models relies on the inclusion of vast sub-models, leading to an unquantifiable degree of uncertainty on the models’ applicability for extrapolation studies. Furthermore, each closure and fitting parameter in the model represents a possible source of deviation, and their optimization, hence, becomes another major challenge. The recent advances in measurement techniques can enable us to troubleshoot and optimize the implemented models and sub-models based on local scale measurements. Local multiphase hydrodynamic information obtained by advanced measurement techniques can enable the validation of local predictions and optimization of the coupled sub-models, leading to the development of simplified and highly predictive models. Thus, pairing advanced experimental studies on these systems with insightful modeling approaches is required to advance the shortcoming and enhance the predictive quality of the models. In this work, an overview of the status of modeling and experimental measurement techniques for gas-solid fluidized beds is presented; then, an overview on pairing both experimental and modeling studies to improve the models’ local predictions for fluidized beds is presented.

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Section: Introductionmentioning

confidence: 99%

Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview

Uribe

Al‐Dahhan

2021

Processes

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“…Hohne et al (2019) [36] combined a generalized two-phase flow boiling model with CFD to predict the breakup, coalescence, condensation, and evaporation mechanisms in a heated pipe. Uribe et al (2019) [37] compared three different CFD models (heterogeneous micropores model, pseudo-homogenous catalyst particle model, and single-scale reactor model) in a trickle bed reactor (TBR) to show its multiphysics and multiscale nature.…”

Section: Introductionmentioning

confidence: 99%

Multiscale Eulerian CFD of Chemical Processes: A Review

Ngo

Lim

2020

ChemEngineering

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This review covers the scope of multiscale computational fluid dynamics (CFD), laying the framework for studying hydrodynamics with and without chemical reactions in single and multiple phases regarded as continuum fluids. The molecular, coarse-grained particle, and meso-scale dynamics at the individual scale are excluded in this review. Scoping single-scale Eulerian CFD approaches, the necessity of multiscale CFD is highlighted. First, the Eulerian CFD theory, including the governing and turbulence equations, is described for single and multiple phases. The Reynolds-averaged Navier–Stokes (RANS)-based turbulence model such as the standard k-ε equation is briefly presented, which is commonly used for industrial flow conditions. Following the general CFD theories based on the first-principle laws, a multiscale CFD strategy interacting between micro- and macroscale domains is introduced. Next, the applications of single-scale CFD are presented for chemical and biological processes such as gas distributors, combustors, gas storage tanks, bioreactors, fuel cells, random- and structured-packing columns, gas-liquid bubble columns, and gas-solid and gas-liquid-solid fluidized beds. Several multiscale simulations coupled with Eulerian CFD are reported, focusing on the coupling strategy between two scales. Finally, challenges to multiscale CFD simulations are discussed. The need for experimental validation of CFD results is also presented to lay the groundwork for digital twins supported by CFD. This review culminates in conclusions and perspectives of multiscale CFD.

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“…Over the past several decades, there have been vast contributions in the study of trickle bed reactors (TBR) hydrodynamics [ 2‐8 ] and mass transfer [ 9‐14 ] phenomena in the literature. In these contributions, it has been recognized that the hydrodynamics of TBR, and therefore the multiphase interactions, play a determining role in the mass and heat transfer phenomena, kinetics, and performance throughput of these systems.…”

Section: Introductionmentioning

confidence: 99%

Development of a hybrid pressure drop and liquid holdup phenomenological model for trickle bed reactors based on two‐phase volume averaged equations

Uribe

Farid

et al. 2020

Can J Chem Eng

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A model with a high predictive quality to estimate pressure drops and liquid holdups in trickle bed reactors (TBR) is yet necessary to assist in design, up scaling, and the implementation of new processes tasks. The currently available models to estimate pressure drops and liquid holdups on TBRs exhibit important deviations, which lead to uncertainties in their applicability. To overcome the limitations in prediction deviations in the currently available models, a new model is developed based on the volume averaged two‐phase transport equations in a porous media, as developed by Whitaker. In order to develop a model that could simultaneously predict pressure drops and liquid holdup with a high accuracy, the developed model was coupled with a modification of the extended slit model reported in the literature, leading to a new hybrid model with enhanced predictability. Experimentally determined pressure drops and liquid holdup in a column with a 0.14 m internal diameter and a height of 2 m, packed with different extrudate geometries, cylinders, trilobes, and quadlobes, were used to determine the model parameters and to verify the quality of the proposed hybrid model predictions. The developed model, when compared with the experimentally determined data of pressure drops showed mean squared errors (MSE) of 0.89%, 2.31%, and 1.22% for the cylinders, trilobes, and quadlobes particles, respectively, while the liquid holdups were predicted with MSEs of 0.03%, 0.16%, and 0.01% for the cylinders, trilobes, and quadlobes particles, respectively.

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Multiscale CFD modelling and analysis of TBR behavior for an HDS process: Deviations from ideal behaviors

Cited by 9 publications

References 35 publications

Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview

Pairing Experimental and Mathematical Modeling Studies on Fluidized Beds for Enhancement of Models Predictive Quality: A Current Status Overview

Multiscale Eulerian CFD of Chemical Processes: A Review

Development of a hybrid pressure drop and liquid holdup phenomenological model for trickle bed reactors based on two‐phase volume averaged equations

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