Trickle-bed Reactor Model Research Articles

Modelling of transient kinetics in trickle bed reactors: Ethylene oxide production via hydrogen peroxide

Stationary kinetic methods are not sufficient for studying chemical processes in which solid heterogeneous catalysts and several phases (gas-liquid-solid) are involved, therefore transient experimental techniques are applied to reveal the molecular processes on the catalyst surfaces. Dynamic methods were used to study the kinetics of a heterogeneously catalyzed reaction i.e. the epoxidation of ethylene with hydrogen peroxide as the oxidizing agent and titanium silicalite (TS-1) as the heterogeneous catalyst. No detailed reaction mechanism and kinetic model has ever been proposed for this process. For the kinetic investigation, step response experiments were carried out in a laboratory-scale trickle bed reactor (TBR).A dynamic isothermal model for the TBR was presented together with a dynamic kinetic model based on a proposed surface reaction mechanism, where the key step is the reaction between adsorbed hydrogen peroxide and dissolved ethylene from the liquid phase. The TBR model consisted of dynamic mass balance equations for the components present in the gas and liquid bulk phases as well as adsorbed species on the catalyst surface. The model formed a coupled system of parabolic partial differential equations (gas and liquid phases) and ordinary differential equations (catalyst surface phase). The coupled system of differential equations, describing the concentration profiles from the step response experiments were solved numerically by the method of lines by discretizing the reactor length coordinate with finite differences and solving the large system of ordinary differential equations by a backward difference algorithm suitable for stiff ordinary differential equations. The parameters for surface kinetics, mass transfer and fluid dynamics were determined by non-linear regression analysis using the maximum likelihood approach. The model was able to predict the transient and stationary behavior of the system.

Scaling Up the Performance of a Reactor Model for Hydrotreating Vegetable Oil from Bench-Scale to Pilot-Scale Reactors

Scaling up and validation of a trickle-bed reactor model were performed with the experimental information obtained during the hydrotreatment of vegetable oil in a pilot-scale reactor. The scale-up ...

Three-phase trickle-bed reactor model for industrial hydrotreating processes: CFD and experimental verification

Catalytic hydrotreating (HDT) is a process used to remove impurities from refinery streams, reacting a given feed with hydrogen at high temperature and pressure in a trickle-bed reactor. In order to optimize the operation of such reactors, one needs information about the detailed performance of the reactor. However, mathematical models of such reactors have not received due attention in last decades. Therefore, this work aimed at revisiting a plug flow HDT model to predict the performance of industrial diesel hydrotreating reactor, which considers most of the HDT reactions, gas-liquid and liquid-solid mass transfer, as well as the influence of catalyst deactivation and quenches injection on model predictions. A fourteen pseudo-component reactional network was proposed and successfully used. Computational fluid dynamics (CFD) predictions verified the plug flow behavior of the industrial HDT reactor. Both the CFD and plug flow models were verified using real process plant data, inspecting residual sulfur content and temperature profiles, with maximum relative error of 14%. Pressure and species concentration profiles as well as the effect of inlet pressure and temperature on final sulfur content were predicted and discussed. Catalyst deactivation is an important factor for accurate prediction of industrial HDT over time of campaign.

Simulation of bench-scale hydrotreating of vegetable oil reactor under non-isothermal conditions

A dynamic non-isothermal trickle-bed reactor model was developed to predict the temperature and concentration profiles of vegetable oil catalytic hydrotreating for the production of renewable fuel. A 5-lump kinetic model was implemented to predict the partial pressure and concentration profiles of products in the liquid phase. The simulated results with the proposed reactor model were compared with experimental information reported in the literature presenting good agreement.

Kinetic parameter estimation and reactor simulation of full-range low temperature coal tar during hydrodeasphaltenization over Ni–Mo/γ-Al2O3

In this study, the whole fraction low temperature coal tar (LTCT) was used as raw material, a series of hydrodeasphaltenization (HDAs) experiments were conducted in an isothermal trickle bed reactor, then the kinetic equation of the reaction was established in gPROMS software and the parameters were estimated. The trickle bed reactor model was established and the effects of operating conditions on HDAs reaction and catalyst effective factors were analyzed. The reactor temperature was varied from 623 to 683 K, the hydrogen pressure from 6 to 12 MPa, keeping constant hydrogen-to-oil volume ratio at 1000:1, liquid hourly space velocity at 0.5 h−1. The results showed that the relative error between the experimental and the simulated results were less than ± 5%, which proved that the model had good applicability; the activation energy was 149.8 kJ mol−1, the pre-exponential factor was 633,832, the reaction order was 1.347, and the order of hydrogen was 2.33. The higher activation energy indicated that the HDAs was difficult to occur compared with the reaction in crude oil. And the high hydrogen order indicated that the pressure had a significant influence on the reaction rate. However, the high temperature and low pressure would reduce the effective factor of the catalyst. The reason may be that the large diffusion limitation and reaction heat of asphaltenes lead to a large difference in reaction rates between the catalyst surface and the tunnel of pores under high temperature. This study could contribute to a more in-depth understanding of the features and rules of LTCT HDAs, and also provide a useful model for reactor design, operation and control.

Modeling of a bench-scale fixed-bed reactor for catalytic hydrotreating of vegetable oil

A dynamic trickle-bed reactor model was developed to predict the behavior of reactive species and products during the catalytic hydrotreating of vegetable oil. The prediction capability of the model was verified with experimental information obtained during the hydrotreating of a jatropha oil at temperature of 420 °C, hydrogen pressure of 80 bar, 1500 Nl/l of H2/oil ratio and WHSV of 1–12 h−1 using a NiW/SiO2–Al2O3 catalyst. The proposed model allows to predict the partial pressure and concentration profiles along the catalytic bed as a function of the time-on-stream. The dynamic simulation results agree with experimental data reported at steady-state conditions. A comparison of experimental data and calculated results provides a correlation coefficient of 0.988.

Analyzing the impact of implementing different approaches of the approximation of the catalyst effectiveness factor on the prediction of the performance of trickle bed reactors

Abstract A steady-state diffusion model comprising of diffusion and reaction in a catalyst pellet was used to study and understand the effect of the approximation of the catalyst effectiveness factor in the modeling of trickle bed reactors. The hydrogenation of alpha-methylstyrene was chosen as the case study reaction from literature for liquid-limited reaction conditions. The effectiveness factor values in this study were sensitive to reactor scale equations during the prediction of reactor performance. The approximation of accounting for the overall catalyst effectiveness factor in the reactor scale model equations from different models and solving the reactor scale model equations by different modeling approaches was assessed. It was observed that evaluating the overall effectiveness factor from pellet scale model equations and integrating the parameter in the reactor scale axial dispersion model at every local axial collocation point to simulate the reactor performance showed better agreement to the experimental data. This approach evaluates the effectiveness factor locally with the variation of the reactant concentration at different axial points across the reactor rather than using one value for the entire reactor. The approach of using a single effectiveness factor for the whole bed and using the effectiveness factor approximated as a fitted polynomial to the reactant concentrations did not properly predict the reactor performance.

Mathematical modeling and simulation of an industrial adiabatic trickle-bed reactor for upgrading heavy crude oil by hydrotreatment process

The mathematical modeling of a trickle-bed reactor at particle and catalytic bed levels for the hydrodesulfurization and hydrodemetallization of heavy crude oil was carried out. The kinetic model parameters were estimated from experimental data. Thermodynamic and transport properties were calculated based on existing correlations and equations of state. Simulations of isothermal small scale and large scale adiabatic reactor were carried out and concentration and temperature profiles were obtained. It was demonstrated that temperature affects the catalyst utilization as the effectiveness factor is diminished at higher temperatures. Effectiveness factors undergo changes as reaction mixtures passes through catalytic bed describing different profiles for HDM and HDS.

Molecular-level kinetic modelling of fluid catalytic cracking slurry oil hydrotreating

In this study, a molecular-level kinetic model of fluid catalytic cracking (FCC) slurry oil (SLO) hydrotreating in a trickle-bed reactor was developed. The physical and chemical properties of SLO were measured, and the data were used as input to tune the composition model parameters. A series of reaction rules were collected and established in terms of the reaction family according to the hydrotreating reaction mechanism. After applying the reaction rules on all the SLO molecules, a reaction network was generated containing 5,753 molecules and 15,830 reactions. The kinetic model was then built employing the Langmuir−Hinshelwood−Hougen−Watson (LHHW) formalism. The kinetic model parameters were reduced using the linear free energy relationship (LFER) and quantitative structure-reactivity correlations (QSRCs). The kinetic model was delivered to the trickle-bed reactor model, and the model parameters were tuned using experimental data obtained from a pilot hydrotreating unit. The obtained SLO hydrotreating model showed good agreement between the predicted and experimental product properties and composition under various processing conditions. The model was able to predict the concentration distribution of each species along the reactor. In addition, the influence of reaction temperature on the aromatic content and thiophene compound content was also evaluated.

A carbon-number lump based model for simulation of industrial hydrotreaters: Vacuum gas oil (VGO)

A detailed, molecule-based trickle bed reactor model has been developed to simulate industrial vacuum gas oil (VGO) hydrotreaters. A feed characterization module is used to calculate the composition of the feed without any detailed experimental component analysis. Feed VGO is represented by a pre-defined set of 120 pure molecules, from carbon numbers C14 to C33, and the proportion of these components is calculated using an optimization algorithm so as to match the physico-chemical properties of the mixture with those of VGO, as measured in the laboratory. This molecular composition is used as an input to model the reactions occurring in a hydrotreating reactor. The main reactions occurring in the hydrotreater such as hydro desulfurization, hydro denitrogenation and aromatic saturation reactions, are modeled. The kinetic parameters for these reactions have been estimated from a comprehensive set of experimental pilot plant data spanning a wide range of process conditions. Simulation results showed that the model reproduces the product distribution by boiling range, composition and the temperature rise in the catalyst bed for a range of operating conditions for industrial refinery units.

Acetophenone hydrogenation on Rh/Al2O3 catalyst: Flow regime effect and trickle bed reactor modeling

Flow regime effect and reactor modeling studies in a gas-liquid downward flow fixed bed reactor were conducted for acetophenone hydrogenation on 1% Rh/Al2O3 catalyst, a relatively complex reaction scheme typical of pharmaceutical applications, using a 7.1mm ID stainless steel reactor with 0.5mm catalyst spheres at elevated pressures. A flow regime transition map for trickle and bubbly flows was determined visually in a transparent reactor surrogate and confirmed by monitoring pressure drop fluctuations for different gas/liquid systems, tube/particle materials, and operating pressure and temperature. The flow regime at each operating condition for the opaque stainless steel reactor was identified solely using pressure drop fluctuations. The beneficial effect of bubbly flow on reaction rate was confirmed experimentally at gas and liquid superficial velocity ranges of 0.02–0.19m/s and 2.5–12mm/s, respectively, under 80–100°C, 11–26bar and 0.04–0.6M initial substrate concentration. Gas flow rate, temperature, and pressure variations were used to study the effects on reaction performance of partial wetting of the catalyst and of liquid-solid diffusion limited reaction. A reactor model including external/internal mass transfer and flow regime effects was developed using an adjustable parameter to account for partial wetting and flow regime effects. The parameter was fitted using a subset of the experiments, and the model provided good prediction (R2>95%) of all remaining experiments.

Acetophenone hydrogenation on Rh/Al2O3 catalyst: Intrinsic reaction kinetics and effects of internal diffusion

Acetophenone hydrogenation on 1% Rh/Al2O3 catalyst was conducted using various support sizes to study intrinsic kinetics and internal diffusion effects. In the first part of this work, results from different noble metals and supports were compared, and the 1% Rh/Al2O3 was selected. From experiments at 60–100°C, 1.1–4.1MPa PH2 and 0.04–0.4M CAP.o using powder catalysts, intrinsic reaction kinetic modeling with the Langmuir–Hinshelwood mechanism was conducted. The selected kinetic model included dissociative and non-competitive hydrogen adsorption, along with saturated active sites for organic species, and surface reaction as the rate determining step. With the obtained intrinsic reaction kinetics, internal diffusion effects were investigated using two catalyst particle sizes and diffusion–reaction models. The properties of the egg-shell type catalyst particles, including metal dispersion, were characterized and utilized in the models. The concentration–time profiles calculated from models developed in this work correspond well with the experimental results, explaining the effects of internal diffusion inside catalyst particles on reaction rates and selectivity, and are suitable for future use in trickle-bed reactor modeling studies.

Applying reactor model parameters to estimate pygas selective hydrogenation catalyst activity during operation cycle

The trickle-bed reactor model proposed by Mostoufi et al. was rebuilt for use in commercial software, Aspen Plus®. Coupling with thirty hydrogenation rate equations, the process model could simulate a pyrolysis gasoline hydrogenation unit. With an optimization procedure, the thirty rate constants were obtained after minimizing the relative-concentration-based objective function. In this work, the hydrodynamic parameters including physical properties were simultaneously calculated from the software platform according to the reactor conditions, such as temperature, concentration, etc. Therefore, the effect of parameter variation can be avoided not only along the catalyst bed, but also at the start of run and end of run. This semi-empirical method can be applied to highly exothermic hydrogenation reactor models, and then used it to estimate residue catalyst activity much more theoretically than the weighted average bed temperature method and interpret plant data more in practice, for example, bed temperature profile and its deviation, the relationship between the throughput and pressure drop.

Pore-network modeling of trickle bed reactors: Pressure drop analysis

A pore network model (PNM) has been developed to simulate gas–liquid trickle flows inside fixed beds of spherical particles. The geometry has been previously built from X-ray micro-tomography experiments, and the flow in the throats between pores is modeled as a pure viscous Poiseuille two-phase flow. The flow distribution between pores and throats is obtained by solving mass and momentum balance equations. As a first application of this simple but powerful meso-scale model, a focus is proposed on the ability of PNM to estimate pressure drop and liquid saturation in co-current gas–liquid flows. PNM results arecompared to the classical 1D pressure drop models of Attou et al. (1999), Holub et al. (1992) and Larachi et al. (1991). Agreement and discrepancies are discussed, and, finally, it has been found that the actual PNM approach produces realistic pressure drops as far as inertial contributions to friction are negligible. Concerning liquid saturation, the PNM only estimates its value in the throats between pores. As a consequence, liquid saturations are overestimated, but they can be easily corrected by an ad hoc empirical model.

Dynamic modeling and simulation of hydrotreating of gas oil obtained from heavy crude oil

This paper describes a dynamic heterogeneous one-dimensional model of trickle-bed reactor used for catalytic hydrotreating of oil fractions. The model takes into consideration the main reactions occurring in the hydrotreating process: hydrodesulfurization, hydrodenitrogenation, hydrodearomatization (mono-, di-, and polyaroamatics), olefins hydrogenation, and mild hydrocracking (gas oil, naphtha, and gases). Kinetic parameters were determined from experimental data obtained in an isothermal bench-scale reactor during hydrotreating of atmospheric gas oil coming from a heavy crude oil over a commercial CoMo catalyst. The developed model was used to predict the dynamic behavior of an industrial hydrotreating reactor within a wide range of reaction conditions. Changes in concentration, partial pressure, and temperature profiles are simulated and discussed as a function of reactor axial position and time. The simulation results obtained with the proposed dynamic model showed good agreement with experimental data.

Computational Modeling of Trickle Bed Reactors

In this study, a three-dimensional Eulerian computational fluid dynamics (CFD) reactive flow model is developed for the trickle flow regime in a packed bed. The experimental study of porosity distribution in a bed of extrudates has been performed and then used to implement the local porosity values in the CFD computational grid. The reactive flow study addressed gas and liquid reactant limited systems. For each case a closed form approach of coupling the bed and particle scale solution within the CFD framework is presented. Model predictions achieved satisfactory agreement with experimental data for liquid holdup, wetting efficiency, and reactant conversion.

Whole Crude Oil Hydrotreating from Small-Scale Laboratory Pilot Plant to Large-Scale trickle-Bed Reactor: Analysis of Operational Issues through Modeling

Catalytic hydrotreating (HDT) is a mature process technology practiced in the petroleum refining industries and used to treat the oil fractions from a crude oil distillation (CDU) unit for the removal of contaminants such as sulfur, nitrogen, etc. Hydrotreating of the whole crude oil before it goes to a CDU unit is a new technology and is regarded as one of the more difficult tasks that have not been reported widely in the public domain. Our recent study using a laboratory small-scale pilot plant shows significant improvement in middle distillate yields and quality of crude oil in terms of contaminants present. Recently, we also determined best kinetic parameters for several hydrotreating reactions using experimental data from the small-scale trickle-bed reactor (TBR), using parameter estimation techniques. With these parameters, we were able to develop a process model of TBR that was validated using the experimental data from the pilot plant. In this study, we scale up the pilot-scale TBR where the throughput of crude oil changes from 45 × 10–6 m3/h to 66.243 m3/h (10 000 bpd), the reactor height increases from 65 cm to 1061 cm, and the diameter changes from 2 cm to 399 cm. While isothermal conditions could be easily maintained in the small-scale TBR (an isothermal steady state model mentioned above was sufficient for the reactor), it is not the case for a large-scale reactor. Hence, a detailed model with energy balance was considered for the analysis of the large-scale reactor, and the temperature control issues are discussed. The ratio of reactor length to reactor diameter (LR/DR) is chosen in such a way so that radial variation could be neglected and it was obtained using an optimization technique. All the main simultaneously occurring hydrotreating reactions are considered. These reactions are hydrodesulfurization (HDS), hydrodenitrogentaion (HDN), hydrodeasphaltenization (HDAs), and hydrodemetallization (HDM), which includes hydrodevanadization (HDV), hydrodenickelation (HDNi). In addition, the chemical reactions responsible for converting part of the crude oil to middle distillate are also considered. The gPROMS modeling software is used for modeling and simulation of the scaled-up TBR process.

Numerical assessment of diffusion–convection–reaction model for the catalytic abatement of phenolic wastewaters in packed-bed reactors under trickling flow conditions

Computational fluid dynamics (CFD) modeling of trickle-bed reactors with detailed interstitial flow solvers has remained elusive mostly due to the extreme CPU and memory intensive constraints. Here, we developed a comprehensible and scalable CFD model based on the conservative unstructured finite volume methodology to bring new insights from the perspective of catalytic reactor engineering to gas–liquid–solid catalytic wet oxidation. First, the heterogeneous flow constitutive equations of the trickle bed system have been derived by means of diffusion–convection–reaction model coupled within a Volume-of-Fluid framework. The multiphase model was investigated to gain further evidence on how the effect of process variables such as liquid velocity, surface tension and wetting phenomena affect the overall performance of high-pressure trickle-bed reactor. Second, as long as the application of under-relaxation parameters, mesh density, and time stepping strategy play a major role on the final corroboration, several computational runs on the detoxification of liquid pollutants were validated accordingly and evaluated in terms of convergence and stability criteria. Finally, the analysis of spatial mappings for the reaction properties enables us to identify the existence of relevant dry zones and unveil the channeling phenomena within in the trickle-bed reactor.

Accounting for Vapor−Liquid Equilibrium in the Modeling and Simulation of a Commercial Hydrotreating Reactor

A one-dimensional, plug-flow, trickle-bed reactor model was developed to simulate a steady-state, adiabatic hydrotreating reactor with consideration of vapor−liquid equilibrium (VLE) effects. VLE calculations were simultaneously performed at each integration step of the model simulation. The thermophysical properties and mass flow rates of each fluid phase were updated as functions of local variables along the catalyst bed. Substantial differences in hydrodearomatization (HDA) and hydrodesulfurization (HDS) conversions were observed when the simulation was conducted with and without accounting for VLE, indicating the significance of VLE in the hydrotreater simulation. It was found that an increased inlet temperature increases HDS conversion but reduces HDA conversion. Increased pressure increases the reactor temperature and HDS and HDA conversions. Increased gas/oil ratio increases HDA conversion slightly, but does not change HDS conversion significantly. Polyaromatics are the most reactive for hydrogenat...

Assessment of CFD−VOF Method for Trickle-Bed Reactor Modeling in the Catalytic Wet Oxidation of Phenolic Wastewaters

A multiphase volume of fluid (VOF) model was developed to provide a more detailed understanding of the transient behavior of a laboratory-scale trickle-bed reactor. The gas-liquid flow through a catalytic bed of spherical particles was used to compute velocity field and liquid volume fraction distributions considering interfacial phenomena as well as surface tension effects. The computational model was used to simulate the catalytic wet air oxidation of a phenolic model solution in the multiphase reactor. Several runs were carried out under unsteady-state operation to evaluate the dynamic performance addressing the total organic carbon concentration and temperature profiles. In all runs, some level of backmixing was predicted, being lower at high operating temperatures. These axial concentration profiles were then correlated with the radial ones revealing a poor radial mixing for the simulated flow regime, namely, at the hot spots. The influence of the operating temperature on the thermal profiles illustrated the existence of such hot spots located in the first quarter of the axial coordinate with an intensity about 6% higher than the inlet and wall temperatures. The transient radial temperature profiles corresponding to the hot spot showed the same intensity as was found for the axial thermal profiles, indicating the existence of considerable radial gradients that sustained the poor radial mixing in downflow operating mode. Despite the qualitative differences attained for the shapes of the thermal profiles, one should bear in mind that the maximum difference between the computed results and experimental data was lower than 1.5%, which reinforces the validation of the computational fluid dynamics (CFD) approach at reacting flow conditions.