CFD study of diesel oil hydrotreating process in the non-isothermal trickle bed reactor

The liquid phase maldistribution factor has been investigated in trickle bed reactor, and the results are compared with the previous measurement data from literature by using the Electrical Resistance Tomography. The simulation results are in agreement with the experimental results to some degree. The flow rates and particle sizes have been simulated with the method of multiphase flow. There are two different particles with average diameters of 3.4 mm and 5.3 mm. The flow rate has been studied ranging from 100 ml/min to 1100 ml/min. It has been found that the changes of the particles and liquid flow rates have a significant impact on the distribution of the liquid volume fraction. The internal liquid holdup is more serious, and the wall-flow phenomenon is more obvious in a bigger flow rate. The prediction of the liquid volume fraction distribution is a key research technique. Regression predictions have also been researched on the section near outlet, which can predict the internal flow state of the trickle bed under the condition of high temperature and high pressure. The average liquid volume fraction is linear with flow rates. The maldistribution factor is the index correlation with the flow rates. The results and main conclusions can be used to predict the distributions and get the properties in a trickle bed reactor.

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“…Mathematical Problems in Engineering calculate the flow state of each phase in the multiphase flow and written as follows [19]:…”

Section: E Eory Of the Numerical Simulationmentioning

confidence: 99%

The Liquid Maldistribution Analysis of the Trickle Bed Reactor with the CFD Method

Liu

Zhao

et al. 2020

Mathematical Problems in Engineering

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“…Regarding the modelling of HDS processes, important developments have been made in recent years with different approaches and assumptions; most contributions usually neglect the hydrodynamic behaviour and consider the solid phase effects, such as the catalyst shape and the distribution of the void phase, using form factors or empirical correlations. [29][30][31] In addition, it is common to find models in literature in which the kinetic behaviour of the TBR is addressed by considering plug flow models, yet overlooking the hydrodynamics behaviour of the reactor and, therefore, neglecting important transport phenomena as radial dispersion and the coupling with the two-phase hydrodynamics. [29,32,33] Furthermore, the effects of the intraparticle mass resistances in catalyst and the mass interchange between fluid-solid and gas-liquid phases are incorporated through effectiveness factors [29,33] and using a volumetric exchange term.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, there have been contributions in the modelling of HDS processes with extended approaches, such as considering 3D simulations that couple the hydrodynamics with the mass transfer. [30,34] In this context, it is important to highlight the work of Silva et al, [34] who developed a 3D CFD simulation that considers simultaneous HDS and hydrodearomatization (HDA), which allows the incorporation of radial dispersion and the coupling of the hydrodynamics. However, no validation for the hydrodynamic was presented and the effects of the bed textural characteristics were incorporated through a porosity distribution expression.…”

Section: Introductionmentioning

confidence: 99%

CFD analysis of bed textural characteristics on TBR behaviour: Kinetics, scaling‐up, multiscale analysis, and wall effects

Uribe¹,

Cordero²,

Zárate³

et al. 2018

Can J Chem Eng

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A simulation of a trickle bed reactor aided by computational fluid dynamics was implemented. With a Eulerian approach, geometrical characteristics were explicitly considered and two simultaneous heterogeneous reactions were included, hydrodesulphurization (HDS) and hydrodenitrogenation (HDN). This was performed in order to achieve the following: (1) attain further insight into a proper scaling‐up procedure to be able to obtain the same hydrodynamics and kinetics behaviour in two reactors of different length and diameter scales; (2) develop a multiscale analysis regarding the communication of information between scales through the construction of a porous microstructure model from which the geometrical information of the microscale is captured by the effective transport coefficients (which affect the overall reactor behaviour); (3) investigate the effect of operation condition variations on hydrodynamics and kinetics; and (4) assess the deviations and further differences observed from average to punctual conversion values and the assumptions from kinetic literature models through a preliminary multiscale analysis. The CFD results were validated against experimental pressure drop data as well as HDS and HDN conversion theoretical data. An excellent agreement was found. The model produces a significant improvement in hydrodynamic parameter prediction, achieving 5 times better accuracy in predicting pressure drops and 50 % improvement in holdup prediction. The fully coupled model predicts HDS conversion with 96 % accuracy and HDN conversion with 94 % accuracy. Results suggest that the best way to obtain similar kinetic and hydrodynamic behaviour in TBRs with different lengths and diameter length scales is by equaling the liquid holdup true(ϵγtrue) or the mass velocities (L‐G).

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“…Our research group has been, for instance, involved with particle‐scale CFD modelling, meso‐scale modelling based on Pore‐Network‐approaches, and macro‐scale Eulerian CFD modelling . When CFD is used to investigate gas‐liquid flow maldistribution, Eulerian approaches are still the most relevant, since those can be used to simulate the flow inside a large range of column diameters, but in return closure laws for fluid‐fluid and fluid‐solid interactions have to be provided. Since Eulerian models are based on the use of several physical sub‐models to account for the different forces applied between the phases.…”

Section: Introductionmentioning

confidence: 99%

Characterization and modelling of a maldistributed Trickle Bed Reactor

2016

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A Trickle Bed Reactor equipped with a non‐ideal distribution tray is investigated. First, a non‐ideal co‐current trickling flow of nitrogen and heptane, induced by a partially plugged tray, is characterized experimentally using the γ‐tomography technique. Resulting liquid saturation data are used to validate the Euler‐Euler CFD model developed in previous work of Solomenko et al.[16] on a 3D realistic flow. The resulting 3D CFD model is then coupled with simple isothermal kinetics of heteroatom removal of heavy petroleum cuts, and the effect of maldistribution on reactor performance is discussed. The problem of CFD model reduction to a 1D reactor model is finally addressed based on transport of internal ages distribution theory. Different 1D models are compared based on reactor effluent throughput. It is shown that a 1D‐Multi Exit reactor model that respects both the age variance at the system outlet as well as the degree of mixing inside the reactor gives the best prediction of the reactor performance.

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CFD study of diesel oil hydrotreating process in the non-isothermal trickle bed reactor

Cited by 11 publications

References 90 publications

The Liquid Maldistribution Analysis of the Trickle Bed Reactor with the CFD Method

The Liquid Maldistribution Analysis of the Trickle Bed Reactor with the CFD Method

CFD analysis of bed textural characteristics on TBR behaviour: Kinetics, scaling‐up, multiscale analysis, and wall effects

Characterization and modelling of a maldistributed Trickle Bed Reactor

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