A multiscale simulation method for catalytic reaction processes

Abstract

The application provides a multi-scale simulation method of a catalytic reaction process, comprising the following steps: (1) constructing a micro-element structure; (2) establishing a calculation model of a physical and chemical reaction system in the micro-element structure; (3) simulating and obtaining reaction kinetics parameters of the micro-element structure; (4) constructing a representative unit structure; (5) establishing a calculation model of a physical and chemical reaction system in the representative unit structure; (6) simulating and obtaining reaction kinetics parameters of the representative unit structure; (7) establishing and solving diffusion-reaction equations of a single catalyst particle; (8) establishing a reactor model and realizing real-time coupling calculation of reaction-diffusion-flow on the single catalyst particle; and (9) obtaining target performance parameters. The multi-scale simulation method accurately describes the internal structure of the catalyst and the space-time distribution of gas phase components in the catalyst and the space-time distribution of a flow field in a reactor bed layer, and effectively serves catalyst optimization design and reactor scale-up design.

Description

Technical Field

[0001] This invention belongs to the field of computational simulation technology, and relates to a method for simulating reaction processes, particularly a multi-scale simulation method for catalytic reaction processes. Background Technology

[0002] In catalytic reactions, the mixture of reactants and products flows and diffuses into the catalyst particles within the reactor. Reactants reaching the catalyst surface first diffuse into the active sites within the pores. Through adsorption, reaction, and desorption, the product components diffuse out of the catalyst's pore structure again, forming a highly complex dynamic behavior involving coupled flow, diffusion, and reaction. While most research on catalyst optimization and reactor scale-up is conducted at the macroscopic scale, the primary site of the reaction is within the catalyst's micropores. Therefore, the overall catalytic reaction process involves coordinating reaction and diffusion across the multi-level pores of the catalyst particles and coordinating flow and diffusion across the multi-level flow channels of the reactor, requiring the transmission of information at both the microscopic and macroscopic scales.

[0003] In macroscopic computational models and methods, the internal structural features of catalyst particles are generally ignored. Computational fluid dynamics methods are used, employing experimental fitting or empirical reaction kinetics to describe the reaction process. However, the reaction kinetics used in macroscopic calculations do not consider the catalyst pore structure and the spatiotemporal distribution of components within the pores, lacking theoretical support for the reaction mechanism and only applicable to specific reaction operating conditions. During reactor scale-up design, changes in spatiotemporal scale bring complex and variable reaction operating conditions, leading to significant errors in macroscopic calculations. At the microscopic spatiotemporal scale, methods such as molecular dynamics can be used to simulate the reaction and diffusion processes of reactants and products within the catalyst grain pores. However, the coordination of this intragranular reaction and diffusion process is affected by the mesopores and macropores present in the intergranular spaces, and even the flow field of the particles. Only in a sufficiently large volumetric unit containing a complete pore size distribution can the coordination of reaction and diffusion exhibit stable statistical properties. However, due to computational limitations, single-scale microscopic models and methods cannot simulate the entire catalytic reaction process, from the reaction within the micropores to the flow within the reactor.

[0004] Therefore, it is evident that engineers need to achieve cross-level coupled simulation of the entire catalytic reaction process, from the reaction within the channels to the flow within the reactor, ensuring the self-consistency of each model and the entire simulation method chain, and improving the accuracy of the models. Only in this way can the internal structure of the catalyst and the spatiotemporal distribution of its gaseous components and the flow field within the reactor bed be accurately described, thereby gaining a deeper understanding of the formation mechanism of these spatiotemporal distributions. This will serve to support catalyst optimization design and reactor scale-up design, and ultimately support the research and application of highly efficient and stable reactors. This has become an urgent problem for those skilled in the art to solve. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-scale simulation method for catalytic reaction processes. This multi-scale simulation method realizes cross-level multi-scale simulation of the reaction and transport processes within microscopic channels and the macroscopic flow processes during catalytic reactions. It accurately describes the internal structure of the catalyst and the spatiotemporal distribution of its gaseous components, as well as the spatiotemporal distribution of the flow field within the reactor bed. It provides a deeper understanding of the formation mechanism of these spatiotemporal distributions, thereby effectively serving the optimization design of catalysts and the scale-up design of reactors, and ultimately supporting the research and development and application of high-efficiency and stable reactors.

[0006] To achieve this objective, the present invention adopts the following technical solution:

[0007] This invention provides a multi-scale simulation method for catalytic reaction processes, the multi-scale simulation method comprising the following steps:

[0008] (1) Construct microstructures based on the structural characteristics of porous catalysts used in the catalytic reaction process;

[0009] (2) Establish a first computational model of the physical and chemical reaction system based on the microstructure;

[0010] (3) Based on the first calculation model, the reaction kinetics of the micro-structure is described by parameters and simulation calculation is carried out to obtain the first reaction kinetic parameters corresponding to the micro-structure.

[0011] (4) Construct representative unit structures by combining the reaction kinetics of the microstructures and the structural characteristics of porous catalysts;

[0012] (5) Establish a second computational model of the physical and chemical reaction system based on the representative unit structure described above;

[0013] (6) Based on the second calculation model, the reaction kinetics of the representative unit structure are parametrically described and simulation calculations are performed to obtain the second reaction kinetic parameters corresponding to the representative unit structure;

[0014] (7) Based on the continuous medium theory, establish the diffusion-reaction equation of a single catalyst particle, divide the computational grid in the region of a single catalyst particle, use the reaction kinetics of the representative unit structure as the kinetics of the catalytic reaction in each computational grid, and solve the third reaction kinetic parameters corresponding to each component in a single catalyst particle.

[0015] (8) Establish a reactor model containing a large number of catalyst particles according to the reactor type, and use fluid dynamics methods to calculate the flow process in the reactor. Combined with the third reaction kinetic parameters, realize real-time coupled calculation of reaction-diffusion-flow on a single catalyst particle.

[0016] (9) Based on the simulation results obtained in steps (1)-(8), obtain the target performance parameters of the overall catalytic reaction process and save them as a data file.

[0017] The multi-scale simulation method provided by this invention can conduct multi-level simulations from reaction to reactor for various catalytic reaction processes using porous catalyst particles. The obtained reaction kinetic parameters and target performance parameters are stable and can be used for subsequent catalyst performance optimization simulations and reactor scale-up simulation design. In addition, according to changes in actual operating conditions, the multi-scale simulation method can also easily redesign and adjust the catalyst pore structure, reaction operating conditions, etc., to obtain results under new operating conditions.

[0018] Preferably, the porous catalyst in step (1) has a hierarchical pore structure.

[0019] In this invention, the porous catalyst may have a partially non-functional matrix or may be entirely functional.

[0020] Preferably, the structural features of the porous catalyst in step (1) include porosity, pore diameter, pore size distribution, pore connection structure, content and distribution of functional sites, and pore opening and closing.

[0021] Preferably, the microstructure in step (1) includes a channel geometry or a particle packing structure.

[0022] Preferably, the microstructure described in step (1) contains microporous structures and reactive sites.

[0023] Preferably, the physical and chemical reaction system in step (2) includes diffusion process, adsorption process, desorption process, reaction mechanism and network and reaction conditions.

[0024] In this invention, the physical and chemical reaction system can be a real physical and chemical reaction system or a simplified physical and chemical reaction system.

[0025] Preferably, the parameter description in step (3) includes a description of the material and energy transfer and conversion processes occurring on the surface and / or inside the pores of the catalyst particles, and the parameters include reaction rate constant, reaction rate, reaction order, diffusion coefficient, reaction frequency, change in concentration of each component, carbon deposition rate and carbon deposition amount.

[0026] Preferably, the parameter description in step (3) is in the form of discrete data or functional relation.

[0027] In this invention, the functional relationship can be a functional relationship obtained by fitting a post-processing function, or a functional relationship obtained by machine learning.

[0028] Preferably, the representative unit structure in step (4) comprises a solid and a pore structure formed by the gaps between the solids, and the minimum pore size is not less than the maximum pore size in the micro-element structure.

[0029] Preferably, the physical and chemical reaction system in step (5) includes diffusion process, adsorption process, desorption process, reaction mechanism and network and reaction conditions.

[0030] In this invention, the physical and chemical reaction system can be a real physical and chemical reaction system or a simplified physical and chemical reaction system.

[0031] Preferably, the parameter description in step (6) includes a description of the material and energy transfer and conversion processes occurring on the surface and / or inside the pores of the catalyst particles, and the parameters include reaction rate constant, reaction rate, reaction order, diffusion coefficient, reaction frequency, change in concentration of each component, carbon deposition rate, and carbon deposition amount.

[0032] Preferably, the parameter description in step (6) is in the form of discrete data or functional relation.

[0033] In this invention, the functional relationship can be a functional relationship obtained by fitting a post-processing function, or a functional relationship obtained by machine learning.

[0034] Preferably, the diffusion-reaction equation in step (7) includes a diffusion-reaction equation with a reaction source term described based on Fick's diffusion law.

[0035] Preferably, the coordinate system form of the diffusion-reaction equation in step (7) includes a rectangular coordinate system or a spherical coordinate system.

[0036] Preferably, the dimension of the diffusion-reaction equation in step (7) is any one-dimensional, two-dimensional, or three-dimensional.

[0037] Preferably, the solution method for the diffusion-reaction equation in step (7) includes any one of the following: finite difference method, finite element method, finite volume method, or discrete element method.

[0038] Preferably, the reactor type in step (8) includes any one of a fixed-bed reactor, a fluidized-bed reactor, or a tubular reactor.

[0039] Preferably, the reactor model in step (8) includes a geometric model and / or a particle packing model.

[0040] Preferably, the equations involved in the fluid dynamics method in step (8) include the Navier-Stokes equation, the mass conservation equation, the energy conservation equation, the momentum conservation equation, and the reaction kinetic equation.

[0041] Preferably, the simulation calculation results in step (9) include the results obtained by simulating, calculating and processing the physical and / or chemical processes occurring on the surface and / or inside the pores of the catalyst particles using a computer.

[0042] Preferably, the target performance parameters in step (9) include conversion rate, space-time yield, selectivity, carbon deposition, reaction rate, adsorption rate, and adsorption amount.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] (1) The multi-scale simulation method provided by the present invention can carry out multi-level simulation from reaction to reactor for various catalytic reaction processes using porous catalyst particles. The obtained reaction kinetic parameters and target performance parameters are stable and can be used for subsequent catalyst performance optimization simulation and reactor scale-up simulation design.

[0045] (2) Based on changes in actual operating conditions, the multi-scale simulation method provided by this invention can easily redesign and adjust the catalyst pore structure, reaction operating conditions, etc., so as to obtain results under new operating conditions. Attached Figure Description

[0046] Figure 1 This is a parameter correspondence diagram of the micro-element structure in the multi-scale simulation method provided in Example 1;

[0047] Figure 2 This is a parameter correspondence diagram of a representative unit structure in the multi-scale simulation method provided in Example 1;

[0048] Figure 3 This is a schematic diagram of the dimensions from macroscopic to microscopic for the multi-scale simulation method provided in Example 1;

[0049] Figure 4This is a diagram showing the mass percentage of each component at the reactor outlet obtained after coupled calculation using the multi-scale simulation method provided in Example 1. Detailed Implementation

[0050] The technical solution of the present invention will be further illustrated below through specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the present invention and should not be construed as limiting the invention in any way.

[0051] This invention provides a multi-scale simulation method for catalytic reaction processes, the multi-scale simulation method comprising the following steps:

[0052] (1) Constructing microstructures

[0053] Based on the pore structure characteristics and parameters (such as porosity, content and distribution of functional sites, pore size distribution, and requirements for the addition of special materials) of the porous catalyst used in the catalytic reaction process, a self-developed program is used to construct a multi-level pore structure that meets the preset parameters. This multi-level pore structure includes, but is not limited to, pore size distribution, the connection between pores of different sizes, the opening and closing of pores, the location of functional sites, and the requirements for the addition of special materials. The overall shape of the constructed multi-level pore structure can be any shape, such as cuboid, cube, sphere, or irregular shape. Combining microscopic simulation software and hardware capabilities, the constructed multi-level pore structure includes the minimum spatial structure for catalytic reactions (such as active sites within micropores), with maximum sizes ranging from nanometers to micrometers and above. The multi-level pore structure constructed by the program is saved in the form of data coordinates, which can be descriptions of spatial points, lines, surfaces, or volumes.

[0054] (2) Establish a computational model for the physical and chemical reaction system in the microstructure.

[0055] Based on the established pore geometry, a computational system model is established, including pore structure, physical / chemical processes, initial conditions, and boundary conditions, according to specific physical processes, chemical reaction mechanisms, or simplified physical and chemical processes. The corresponding simulation parameters are determined, including but not limited to the atomic composition, mass, equivalent diameter of atoms or molecules, concentration distribution, temperature, pressure, initial conditions, boundary conditions, chemical reaction pathways, chemical reaction networks, energy transfer and conversion pathways and magnitudes of each component, thereby generating a computational model that can be used for the next step.

[0056] (3) Simulate and obtain the reaction kinetic parameters of the microstructure.

[0057] A suitable simulation program was used to simulate the micro-elemental structure reaction system constructed above. The reaction and diffusion processes were simulated within the above simulation parameter range, and the reaction kinetic parameters were statistically analyzed, including but not limited to the reaction rate constant, reaction rate, change in concentration of each component, carbon deposition rate, and carbon deposition amount for each reaction within the simulation parameter range.

[0058] (4) Construct representative unit structures

[0059] The aforementioned microstructure is simplified into simple geometric shapes (such as cubes, cuboids, spheres, or other irregular shapes) without internal pore structures, and used as the basic unit structure. A self-developed program is then used to construct a multi-level pore structure conforming to preset parameters, i.e., a representative unit structure. This representative unit structure includes a solid and pore structures formed by the gaps between the solids, with the smallest pore size not less than the largest pore size in the microstructure. The solid is formed by the basic unit structure. The representative unit structure is a sufficiently large volumetric unit containing all typical pore size distributions, with sizes ranging from micrometers to millimeters or larger. The pore structure constructed by the program is saved in the form of data coordinates, which can be descriptions of spatial points, lines, surfaces, or volumes.

[0060] (5) Establish computational models of physical and chemical reaction systems in representative unit structures.

[0061] For the basic unit structure simplified from the above-mentioned micro-structure, its outer surface has reactivity, and the reaction kinetic parameters when reactants react on its outer surface (including chemical reactions, adsorption, desorption, etc.) are equivalent to the overall reaction kinetic parameters of the micro-structure before simplification (the parameters are equal in the sense of time and space statistical averages). Thus, the reaction kinetic parameters corresponding to the unit outer surface area and / or unit volume of the basic unit structure are obtained, and used as the kinetic parameters for the reaction of each component on the pore wall surface of the representative unit structure established above. Based on the specific physical process, chemical reaction mechanism or simplified physical and chemical process, a computational system model including pore structure, physical / chemical process, initial conditions and boundary conditions is established and the corresponding simulation parameters are determined, thereby generating a computational model that can be used for the next step.

[0062] (6) Simulate and obtain the reaction kinetic parameters of representative unit structures.

[0063] Using a suitable simulation program, the representative unit structure reaction system constructed above is simulated; the reaction and diffusion processes are simulated within the simulation parameter range, and the reaction kinetic parameters are statistically analyzed, including but not limited to the reaction rate constant, reaction rate, change in concentration of each component, carbon deposition rate, and carbon deposition amount for each reaction within the simulation parameter range.

[0064] (7) Establish and solve the diffusion-reaction equation for a single catalyst particle.

[0065] Assuming the pore structure within a single catalyst particle is isotropic, diffusion reaction equations for each component are established based on Fick's diffusion law. These equations can be in Cartesian or spherical coordinates, and can be one-dimensional, two-dimensional, or three-dimensional. The equations can be solved using methods such as the finite difference method, finite element method, finite volume method, and discrete element method. Each catalyst particle is divided into discrete grid cells, each with the same reaction kinetic parameters as the representative cells. These parameters can vary with time, space, and component concentration, and can be in the form of discrete data or functional relationships obtained through post-processing function fitting, machine learning, etc. Based on the specific physical process, chemical reaction mechanism, or simplified physical and chemical process, a computational system model including initial and boundary conditions is established, and corresponding computational parameters are determined. This allows for the solution of the diffusion reaction equations, thereby obtaining the reaction kinetic parameters and target performance parameters at the individual catalyst particle scale. The initial and boundary conditions can be given separately or derived from other computational methods during the calculation process. The obtained reaction kinetic parameters and target performance parameters can be output separately or passed to other computational methods.

[0066] (8) Establish a reactor model and perform real-time coupled calculations of reaction-diffusion-flow on a single catalyst particle.

[0067] According to the reactor type (such as fixed bed, fluidized bed, tubular reactor, etc.), a suitable method (such as discrete element method, multiphase flow particle grid method, etc.) is used to establish a reactor model (such as geometric structure model and / or particle packing model) and solve it. The parameter information obtained by solving in the reactor, including but not limited to the concentration distribution of each component, flow field distribution, heat flow, etc., can be used as the input information of a single catalyst particle in the above step (7). The reaction kinetic parameters calculated by a single catalyst particle in step (7) are used as the input information for the catalyst reaction kinetic calculation in the reactor, thereby realizing the real-time coupling calculation of the two at the scale of a single catalyst particle.

[0068] (9) Obtain target performance parameters

[0069] The target performance parameters obtained from the simulation calculations in the above steps are saved as data files by the program. The file format can be set according to the needs of subsequent processing.

[0070] Example 1

[0071] This embodiment provides a multi-scale simulation method for the catalytic cracking process of olefins, from the reaction to the reactor. Specifically, the multi-scale simulation method is as follows:

[0072] A self-developed program was used to construct a multi-level porous micro-element structure with a porosity ε1 and a given pore size distribution, such as... Figure 1 As shown, the parameters describing the microstructure include the pore diameter d of each channel and its corresponding pore volume percentage n. Figure 3 As shown, the channel structure is a cubic structure with dimensions of (40.1 × 39.84 × 40.26) nm. 3 Where d and n are found Figure 1 ε1 = 0.194. The functional sites within the pores are chemically reactive sites, accounting for 1 / 200 of the total atoms and randomly distributed on the inner surface. Reaction processes can occur at these sites, and these processes proceed as described below, where each letter represents a component, and the value in parentheses is the energy barrier that needs to be overcome for the reaction to occur:

[0073]

[0074] In the above formula, C is the reactant, A and B are the target products, and the rest are intermediate components and by-products, each of which has its own mass, radius and other properties.

[0075] A self-developed program was used to simulate the reaction and diffusion processes in the microstructure, where the concentrations of each component ranged from 0 to 50 mol / m³. 3 The reaction rate R was calculated based on the temperature variation between 853 K and 853 K. mi With respect to the concentration of component i [C i The relationship between ] and the corresponding reaction rate constant k mi The following (in the same order as the reaction processes listed above):

[0076] R m1 =k m1 [C] 1.63 ,k m1 =46168.50

[0077] R m2 =k m2 [C] 1.63 ,k m2 =4638.70

[0078] R m3 =k m3 [D],k m3 =3793.78

[0079] R m4 =k m4 [E],k m4 =8089.92

[0080] R m5 =km5 [E],k m5 =16.21

[0081] The infinitesimal structure is simplified to infinitesimal cubes of the same volume. The parameter describing the reaction of the infinitesimal cube is the probability P of component i reacting on the surface. mi， and the frequency f of collisions between components and the surface mi Under the same component concentration, the reaction rate of each component on the surface of the cube is statistically equal to the reaction rate of the entire micro-structure. Therefore, the simulation yields the following relationship between the probability of reaction on the surface of the micro-cube and the collision frequency (listed in the same order as above):

[0082] P m1 =3.33×10 -5 ×f m1 0.63

[0083] P m2 =3.35×10 -6 ×f m2 0.63

[0084] P m3 =1.64×10 -7

[0085] P m4 =3.83×10 -7

[0086] P m5 =7.68×10 -10

[0087] A representative unit structure with a porosity ε² and a given pore size distribution was constructed using a self-developed program, such as... Figure 2 As shown, the parameters describing the representative unit structure include the pore diameter d of each channel and its corresponding pore volume percentage n. For example... Figure 3 As shown, the representative unit structure is a cubic structure composed of infinitesimal cubes, with dimensions of (1.035 × 1.035 × 1.035) μm. 3 Where d and n are found Figure 2 ε2 = 0.534. The functional sites within the channels are chemically reactive sites, uniformly distributed on the inner surface, where reaction processes can occur. The probability of each component reacting on the surface is calculated from the probability of reaction occurring on the surface of the micro-cube.

[0088] A self-developed program was used to simulate the reaction and diffusion processes in a representative unit structure, where the concentrations of each component ranged from 0 to 50 mol / m³. 3The reaction rate R was calculated based on the temperature variation between 853 K and 853 K. Mi With respect to the concentration of component i [C i The relationship between ] and the corresponding reaction rate constant k Mi The following (in the same order as the reaction processes listed above):

[0089] R M1 =k M1 [C] 1.62 ,k M1 =18631.43

[0090] R M2 =k M2 [C] 1.62 ,k M2 =1871.96

[0091] R M3 =k M3 [D],k M3 =1679.96

[0092]

[0093]

[0094] Simultaneously, the average diffusion coefficient D of each component in the representative unit structure was obtained through simulation as follows:

[0095] D A 3.161×10 -6 m 2 / s

[0096] D B 2.492×10 -6 m 2 / s

[0097] D C 2.116×10 -6 m 2 / s

[0098] D D 1.875×10 -6 m 2 / s

[0099] D E 1.688×10 -6 m 2 / s

[0100] A fixed-bed reactor model was constructed, with the reactor interior consisting of catalyst particle packing structures. The catalyst particle diameter was 3.6 mm, the reactor diameter was 180 mm, and the catalyst packing height was 750 mm. A self-developed computational fluid dynamics method was used to simulate the gas flow process within the reactor, where the inlet gas was reaction component C. The characterization parameters for the catalyst particles and the gas are as follows:

[0101] Catalyst particle characterization parameters:

[0102] Diameter (mm), d 3.6

[0103] Density (kg / m³) 3 ),ρ s 1500

[0104] Young's modulus (Pa), Y 10 9

[0105] Poisson's ratio (–), ν 0.3

[0106] Coefficient of recovery (–), e 0.1

[0107] Rolling friction coefficient (–), μ r 0.1

[0108] Friction coefficient (–), μ s 0.3

[0109] Time step (s) 10 -5

[0110] Gas characterization parameters

[0111] Density (kg / m³) 3 ),ρ g 0.882

[0112] Gas viscosity (Pa·s), μ g 6.37×10 -6

[0113] Gas diffusion coefficient (m) 2 / s),D g 2.77×10 -5

[0114] Gas inlet velocity (m / s), U g 0.9, 1.35, 1.8

[0115] 100% C4 gas at the inlet

[0116] Time step 10 -4

[0117] The gas governing equations described by computational fluid dynamics at the reactor scale are as follows:

[0118]

[0119]

[0120] In the above formula, ε g ρ g and u g These respectively represent volume fraction, density, and gas flow velocity; τ g t and p represent the viscosity stress tensor, time, and pressure, respectively; β is the drag coefficient.

[0121] The lumped reaction of solid particles is described as follows:

[0122]

[0123] In the above formula, Y i and J i R represents the mass fraction and mass diffusion coefficient of component i, respectively; i Let be the reaction rate of component i, which is the reaction rate calculated from a single catalyst particle during the solution process.

[0124] Assuming the pore structure inside a single catalyst particle is isotropic and exists within a spherically symmetric component concentration atmosphere, the changes in the concentration of each component over time and space can be described by the following one-dimensional diffusion-reaction equation:

[0125]

[0126] In the above formula, t is time; r is the radial coordinate; C i D i and R Mi These respectively represent component concentration, diffusion coefficient, and reaction rate; reaction rate R Mi This refers to the results calculated from the simulation of a representative unit structure.

[0127] The diffusion-reaction equation was solved using the finite difference method, with a particle diameter of 3.6 mm and a time step of 10. -4 The internal structure is divided into concentric circular grids with a radial dimension of 0.012 mm. The particle surface concentration at each time step is calculated at the macroscopic reactor scale, and the calculated reaction rates of each component are used as input information R for the macroscopic reactor simulation. i This enables reaction-diffusion-flow coupling simulation at the scale of a single catalyst particle. Figure 4 This represents the mass percentage of each component at the reactor outlet obtained after coupled calculation.

[0128] Therefore, the multi-scale simulation method provided by this invention can carry out multi-level simulations from reaction to reactor for various catalytic reaction processes using porous catalyst particles. The obtained reaction kinetic parameters and target performance parameters are stable and can be used for subsequent catalyst performance optimization simulation and reactor scale-up simulation design.

[0129] Furthermore, based on changes in actual operating conditions, the multi-scale simulation method provided by this invention can easily redesign and adjust the catalyst pore structure, reaction operating conditions, etc., to obtain results under new operating conditions.

[0130] The applicant declares that the above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the protection and disclosure scope of the present invention.

Claims

1. A method of multiscale simulation of a catalytic reaction process, characterized in that, The multi-scale simulation method includes the following steps: (1) Construct microstructures based on the structural characteristics of the porous catalyst used in the catalytic reaction process; (2) Establish a first computational model of the physical and chemical reaction system based on the aforementioned microstructure; (3) Based on the first calculation model, the reaction kinetics of the micro-structure is described by parameters and simulation calculation is carried out to obtain the first reaction kinetic parameters corresponding to the micro-structure; (4) Construct a representative unit structure by combining the reaction kinetics of the micro-structure and the structural characteristics of the porous catalyst; specifically, this includes: simplifying the micro-structure into micro-cubes of the same volume, and under the same component concentration, the reaction rate of each component on the surface of the cube is statistically equal to the reaction rate of the micro-structure as a whole, and then calculating the probability of reaction on the surface of the micro-cube and the collision frequency; wherein, the representative unit structure is a cube structure composed of micro-cubes, and the probability of reaction of the representative unit structure is calculated from the probability of reaction on the surface of the micro-cube; construct a representative unit structure based on the first reaction kinetic parameters corresponding to the micro-structure and the structural characteristics of the porous catalyst; (5) Establish a second computational model of the physical and chemical reaction system based on the representative unit structure described above; (6) Based on the second calculation model, the reaction kinetics of the representative unit structure are parametrically described and simulation calculations are performed to obtain the second reaction kinetic parameters corresponding to the representative unit structure; (7) Based on the continuous medium theory, establish the diffusion-reaction equation of a single catalyst particle, and divide the computational grid in the region of a single catalyst particle. Use the reaction kinetics of the representative unit structure as the kinetics of the catalytic reaction in each computational grid, and solve for the third reaction kinetic parameters corresponding to each component in a single catalyst particle. Specifically, this includes: assuming that the pore structure inside a single catalyst particle is isotropic, establishing the diffusion-reaction equation of each component according to Fick's diffusion law; dividing the single catalyst particle into discrete grid units, each unit structure having the same reaction kinetic parameters as the above representative unit structure; solving the diffusion reaction equation to obtain the reaction kinetic parameters at the scale of a single catalyst particle. (8) Establish a reactor model containing a large number of catalyst particles according to the reactor type, and use fluid dynamics methods to calculate the flow process in the reactor. Combined with the third reaction kinetic parameters, realize the real-time coupled calculation of reaction-diffusion-flow on a single catalyst particle. Specifically, this includes: using the reaction kinetic parameters calculated by a single catalyst particle in step (7) as input information for the calculation of catalyst reaction kinetics in the reactor, thereby realizing the real-time coupled calculation of the two at the scale of a single catalyst particle; using the calculated reaction rates of each component as input information for the macroscopic reactor simulation, thereby realizing the coupled simulation of reaction-diffusion-flow at the scale of a single catalyst particle. (9) Based on the simulation results obtained in steps (1)-(8), obtain the target performance parameters of the overall catalytic reaction process and save them as a data file.

2. The multiscale simulation method of claim 1, wherein, The porous catalyst in step (1) has a multi-level pore structure.

3. The multi-scale simulation method of claim 1, wherein, The structural features of the porous catalyst in step (1) include porosity, pore diameter, pore size distribution, pore connection structure, content and distribution of functional sites, and pore opening and closing.

4. The multi-scale simulation method according to claim 1, characterized in that, The microstructure described in step (1) includes a channel geometry or a particle packing structure.

5. The multi-scale simulation method according to claim 1, characterized in that, The microstructure described in step (1) contains microporous structures and reactive sites.

6. The multi-scale simulation method according to claim 1, characterized in that, The physical and chemical reaction system described in step (2) includes diffusion process, adsorption process, desorption process, reaction mechanism and network and reaction conditions.

7. The multi-scale simulation method of claim 1, wherein, The parameter description in step (3) includes a description of the material and energy transfer and conversion processes occurring on the surface and / or inside the pores of the catalyst particles, and the parameters include the reaction rate constant, reaction rate, reaction order, diffusion coefficient, reaction frequency, change in concentration of each component, carbon deposition rate and carbon deposition amount.

8. The multi-scale simulation method according to claim 1, characterized in that, The parameter description in step (3) can be in the form of discrete data or functional relational expressions.

9. The multi-scale simulation method according to claim 1, characterized in that, The representative unit structure in step (4) includes a solid and a pore structure formed by the gaps between the solids, and the minimum pore size is not less than the maximum pore size in the micro-element structure.

10. The multi-scale simulation method according to claim 1, characterized in that, The physical and chemical reaction system described in step (5) includes diffusion process, adsorption process, desorption process, reaction mechanism and network and reaction conditions.

11. The multi-scale simulation method of claim 1, wherein, The parameter description in step (6) includes a description of the material and energy transfer and transformation processes occurring on the surface and / or inside the pores of the catalyst particles, and the parameters include the reaction rate constant, reaction rate, reaction order, diffusion coefficient, reaction frequency, change in concentration of each component, carbon deposition rate and carbon deposition amount.

12. The multi-scale simulation method of claim 1, wherein, The parameter description in step (6) can be in the form of discrete data or functional relationships.

13. The multi-scale simulation method of claim 1, wherein, The diffusion-reaction equation in step (7) includes a diffusion-reaction equation with a reaction source term described based on Fick's diffusion law.

14. The multi-scale simulation method according to claim 1, characterized in that, The coordinate system form of the diffusion-reaction equation in step (7) includes a rectangular coordinate system or a spherical coordinate system.

15. The multi-scale simulation method of claim 1, wherein, The dimension of the diffusion-reaction equation in step (7) can be any one-dimensional, two-dimensional, or three-dimensional.

16. The multi-scale simulation method according to claim 1, characterized in that, The solution method for the diffusion-reaction equation in step (7) includes any one of the following: finite difference method, finite element method, finite volume method, or discrete element method.

17. The multi-scale simulation method according to claim 1, characterized in that, The reactor type mentioned in step (8) includes any one of a fixed-bed reactor, a fluidized-bed reactor, or a tubular reactor.

18. The multi-scale simulation method of claim 1, wherein, The reactor model in step (8) includes a geometric model and / or a particle packing model.

19. The multi-scale simulation method of claim 1, wherein, The equations involved in the fluid dynamics method described in step (8) include the Navier-Stokes equation, the mass conservation equation, the energy conservation equation, the momentum conservation equation, and the reaction kinetic equation.

20. The multi-scale simulation method of claim 1, wherein, The simulation results in step (9) include the results obtained by simulating, calculating and processing the physical and / or chemical processes occurring on the surface and / or inside the pores of the catalyst particles using a computer.

21. The multi-scale simulation method of claim 1, wherein, The target performance parameters mentioned in step (9) include conversion rate, space-time yield, selectivity, carbon deposition, reaction rate, adsorption rate, and adsorption amount.

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