Multiphase flow coupling analogue simulation method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of computer numerical simulation, discloses a multiphase flow coupling analogue simulation method and device, computer equipment and a storage medium, and is applied to a process for preparing methanol through CO2 hydrogenation by a liquid phase method. The method comprises the following steps: constructing an initial multiphase flow model of a gas-liquid-solid three-phase system based on a gaseous phase state parameter, a liquid phase state parameter and a particle phase state parameter in an initial reaction stage; combining and correcting the liquid phase state parameters and the particle phase state parameters so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry phase two-phase system; constructing a component transport model based on the equivalent state parameters of the equivalent multiphase flow model; and constructing a coupling simulation model by using the equivalent multiphase flow model, the component transport model and the reaction model, and carrying out iterative solution on the coupling simulation model to obtain an analogue simulation result of multiphase flow coupling. Therefore, high-efficiency and high-precision simulation of the stirring reaction process for preparing methanol through CO2 hydrogenation by the liquid phase method is realized.

Description

Technical Field

[0001] The present application relates to the technical field of computer numerical simulation, and in particular to a simulation method, device, computer equipment and storage medium for multiphase flow coupling. Background Art

[0002] With the rapid development of industry, the demand for efficient chemical conversion technology is growing. In the field of energy and chemical industry, the liquid phase process of dispersing nanocatalysts in high boiling point inert media for chemical reactions is gradually emerging. This process uses the high heat capacity of the liquid phase to achieve rapid dissipation of reaction heat, which can effectively control temperature fluctuations and improve product selectivity. However, although the liquid phase method has advantages, it still has shortcomings in design, observation and optimization. There is an urgent need for a high-efficiency and high-precision simulation method to guide its process optimization. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the present application proposes a simulation method, device, computer equipment and storage medium for multiphase flow coupling. The main technical solutions adopted by the present application include: In the first aspect, an embodiment of the present application provides a simulation method for multiphase flow coupling, which is applied to a liquid phase CO2 hydrogenation to methanol process, the method comprising: constructing an initial multiphase flow model of a gas-liquid-solid three-phase system based on gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction; wherein the initial multiphase flow model is used to describe the flow characteristics, interphase forces and energy transfer process of the gas-liquid-solid three-phases; merging and correcting the liquid phase state parameters and the particle phase state parameters to generate equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry two-phase system; based on the equivalent multiphase flow The component transport model is constructed based on the equivalent state parameters of the model; the component transport model is used to track the mass conservation of each component in the gas phase and the slurry phase, so as to describe the mass change process caused by the convection, diffusion, chemical reaction and interphase mass transfer of each component in different phases; the coupled simulation model is constructed using the equivalent multiphase flow model, the component transport model and the reaction model, and the coupled simulation model is iteratively solved to obtain the simulation results of the multiphase flow coupling; the reaction model is established based on the reaction equation corresponding to the hydrogenation to methanol process, and is used to simulate the CO2 hydrogenation reaction rate; the simulation results are used to quantitatively analyze the stirring reaction process of liquid phase CO2 hydrogenation to methanol.

[0004] Optionally, the coupled simulation model is iteratively solved to obtain simulation results of multiphase flow coupling, including: applying boundary conditions to the coupled simulation model; wherein the boundary conditions are determined based on the operating conditions of the reaction process under actual operating conditions; combining the boundary conditions and the coupled simulation model, and using an adaptive step size method to iteratively solve the coupled simulation model to obtain simulation results.

[0005] Optionally, a component transport model is constructed based on equivalent state parameters of an equivalent multiphase flow model, including: using a population equilibrium model to calculate the interphase mass transfer coefficient based on the equivalent state parameters; wherein the interphase mass transfer coefficient is a physical quantity used to describe the material transfer rate between different phases during the reaction process; the population equilibrium model is established based on the bubble dynamics of the equivalent multiphase flow model, and is used to dynamically track the bubble size distribution to quantify the gas-liquid mass transfer surface area; a component transport model is constructed based on the interphase mass transfer coefficient and the component conservation equation; wherein the component conservation equation is an equation used to describe the mass change, transmission, and transfer process of each component between different phases in space and time during the reaction process.

[0006] Optionally, a component transport model is constructed according to the interphase mass transfer coefficient and the component conservation equation, including: determining the mass flux of the component interphase mass transfer based on the interphase mass transfer coefficient, and embedding it as a source term into the component conservation equation to construct the component transport model.

[0007] Optionally, the component conservation equation is constructed in the following manner: the component conservation equation is established based on the gas phase state parameters and the liquid phase state parameters.

[0008] Optionally, an initial multiphase flow model of the gas-liquid-solid three-phase system is constructed based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction, including: determining the continuity equation, momentum equation and energy equation based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters, and introducing the turbulent diffusion force equation and the initial drag equation; constructing an interphase force model based on the turbulent diffusion force equation and the initial drag equation; constructing an initial multiphase flow model based on the continuity equation, momentum equation, energy equation and interphase force model.

[0009] Optionally, constructing the interphase force model based on the turbulent diffusion force equation and the initial drag equation includes: dynamically correcting the drag coefficient of the initial drag equation according to the flow characteristics to obtain a corrected drag equation; and constructing the interphase force model based on the turbulent diffusion force equation and the corrected drag equation.

[0010] In the second aspect, the embodiment of the present application provides a simulation device for multiphase flow coupling, which is applied to the liquid phase CO2 hydrogenation to methanol process, and the device includes: a multiphase flow model establishment module, which is used to construct an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction; wherein the initial multiphase flow model is used to describe the flow characteristics, interphase forces and energy transfer process of the gas-liquid-solid three-phase; a multiphase flow model equivalent module, which is used to merge and correct the liquid phase state parameters and the particle phase state parameters to generate equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry two-phase system; a component transport model A module is established to construct a component transport model based on the equivalent state parameters of the equivalent multiphase flow model; wherein the component transport model is used to track the mass conservation of each component in the gas phase and the slurry phase, so as to describe the mass change process caused by the convection, diffusion, chemical reaction and interphase mass transfer of each component in different phases; a coupling solution module is used to construct a coupling simulation model using the equivalent multiphase flow model, the component transport model and the reaction model, and iteratively solve the coupling simulation model to obtain the simulation results of the multiphase flow coupling; wherein the reaction model is established based on the reaction equation corresponding to the hydrogenation to methanol process, and is used to simulate the CO2 hydrogenation reaction rate; the simulation results are used to quantitatively analyze the stirring reaction process of liquid phase CO2 hydrogenation to methanol.

[0011] In a third aspect, the present application further provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above methods when executing the computer program.

[0012] In a fourth aspect, the present application also provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when the computer program is executed by a processor.

[0013] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which implements the steps of any of the above methods when executed by a processor.

[0014] In the above embodiment, by merging the gas-liquid-solid three-phase system into a gas-slurry two-phase system and correcting the macroscopic characteristics of the slurry phase based on equivalent state parameters, the model is simplified while correcting the equivalent apparent physical properties that can reflect the effect of particles on the slurry phase, which significantly reduces the dimension and amount of calculation of the multiphase flow model, so that the complex gas-liquid-solid interaction is efficiently characterized, thereby shortening the simulation time while ensuring the accuracy of the multi-physics field coupling simulation. The efficient and high-precision simulation of the stirred reaction process of CO2 hydrogenation to methanol in the liquid phase is achieved, providing strong theoretical support and practical basis for the optimal design and industrial scale-up of the stirred reactor, and effectively solving the deficiencies in the design, observation and optimization of the CO2 hydrogenation process to methanol in the liquid phase. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1a A flowchart of a simulation method for multiphase flow coupling provided according to an embodiment of the present application; Figure 1b A schematic diagram of a grid of a fluid calculation domain provided according to an embodiment of the present application; Figure 1c A gas holdup distribution cloud diagram provided according to an embodiment of the present application; Figure 1d A bubble diameter distribution cloud diagram provided according to an embodiment of the present application; Figure 1e A slurry phase velocity distribution cloud diagram provided according to an embodiment of the present application; Figure 1f A reaction rate distribution cloud diagram provided according to one embodiment of the present application; Figure 1g A methanol concentration distribution cloud diagram provided according to an embodiment of the present application; Figure 1h A temperature distribution cloud diagram provided according to an embodiment of the present application; Figure 2 A flowchart of an iterative solution method provided according to an embodiment of the present application; Figure 3 A flow chart of constructing a component transport model according to one embodiment of the present application; Figure 4 A flowchart of constructing a multiphase flow model according to an embodiment of the present application; Figure 5 A flowchart of constructing an interphase force model according to an embodiment of the present application; Figure 6 A structural block diagram of a multiphase flow coupling simulation device provided according to an embodiment of the present application; Figure 7 The figure is a diagram of the internal structure of a computer device provided according to one embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0018] With the rapid development of industry, the demand for efficient chemical conversion technology is growing. In the field of energy and chemical industry, taking carbon dioxide (CO2) as an example, the rapid advancement of industrialization has led to a continuous increase in the concentration of CO2 in the atmosphere, and the greenhouse effect caused by its excessive emissions has posed a serious threat to global ecological security. In this context, it is urgent to develop efficient CO2 resource technology. Among them, the catalytic hydrogenation of CO2 into high-value-added fuels and chemicals such as methanol can not only achieve carbon recycling, but also alleviate the dependence on fossil energy, with significant environmental and economic benefits. The current mainstream process in industry adopts the gas phase method, in which CO2 and hydrogen are hydrogenated on the surface of a solid catalyst through a fixed bed reactor. However, due to the violent exothermic reaction, this process is prone to cause bed temperature gradient distortion and local hot spots (temperature fluctuations of ±15%), resulting in catalyst sintering and deactivation, and methanol selectivity drops below 60%. For this reason, the liquid phase process of dispersing nanocatalysts in a high-boiling point inert medium for chemical reaction has gradually emerged. This process uses the high heat capacity of the liquid phase to achieve rapid dissipation of reaction heat, which can effectively control temperature fluctuations and improve product selectivity. That is, the liquid phase process disperses the nanocatalyst in a high boiling point inert medium (such as paraffin oil) to form a slurry system, and uses the high heat capacity of the liquid phase (>2.5 kJ / (kg·K)) to achieve rapid dissipation of reaction heat, which can control the temperature fluctuation within ±10°C and increase the methanol selectivity to more than 85%. When using a stirred slurry reactor, the gas-liquid mass transfer coefficient can reach 5×10 -3 m / s, which is 2-3 orders of magnitude higher than that of fixed bed.

[0019] However, despite its advantages, the liquid phase method still has the following shortcomings: 1. The design method is limited. The reactor structural parameters (such as blade configuration and gas distributor aperture) mostly rely on empirical formulas, and lack of systematic modeling of the multiphase flow field-mass transfer-reaction coupling mechanism; 2. The observation method is missing. Under high temperature and high pressure (>200℃, >5MPa) conditions, the gas-liquid-solid three-phase flow behavior, interphase mass transfer, and intraphase reaction details are difficult to capture in real time through experiments; 3. The optimization cycle is lengthy. The traditional trial and error method requires dozens of pilot tests, and the test cost is expensive. Therefore, there is an urgent need for a high-efficiency and high-precision simulation method to guide its process optimization.

[0020] Based on this, according to an embodiment of the present application, a simulation method embodiment of multiphase flow coupling is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0021] In this embodiment, a multiphase flow coupling simulation method is provided, which is applied to the liquid phase CO2 hydrogenation to methanol process. Figure 1a is a flow chart of a simulation method for multiphase flow coupling according to an embodiment of the present application, such as Figure 1a As shown, the process includes the following steps: S110. Construct an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction.

[0022] It should be understood that before constructing the initial multiphase flow model, it is also necessary to establish a geometric model including a reactor body, a stirrer and a gas distributor according to the size structure of the stirred reactor for producing methanol by hydrogenation of CO2 by the liquid phase method, so as to provide an accurate physical space description for the subsequent multiphase flow model and ensure that the model is consistent with the actual reactor. For example, the geometric model of the reactor can be constructed using the three-dimensional modeling software Solidworks. The inner diameter of the reactor body is 380mm, with a built-in concentric biaxial stirrer, an inner paddle is a six-straight blade disc turbine paddle, and an outer paddle is a frame paddle. The annular gas distributor with a diameter of 120mm is located at a height of 125mm from the bottom of the kettle, and it has 24 uniform openings in the downward circumference, with an aperture of 2mm. Further, it is also necessary to mesh the geometric model, that is, to define the fluid domain of the geometric model based on the computational fluid dynamics numerical simulation software and mesh it to decompose it into multiple small calculation units. For example, Fluent Meshing can be used to mesh the geometric model, and the mesh can select the Poly-hexcore hexahedral mesh, and the number of meshes needs to be mesh-independent. Verification. At the same time, in order to accurately simulate the movement of the stirrer, a multiple reference system method can be used to set the areas near the inner and outer stirring paddles as dynamic areas, and the rest of the areas as static areas. Figure 1b As shown in the figure, the grid structure of the reactor geometric model after grid division, including the division of the dynamic area (near the stirring paddle) and the static area.

[0023] Furthermore, after completing the construction and meshing of the reactor geometry model, it is necessary to determine the state parameters of each phase participating in the reaction at the initial stage of the reaction in order to establish an initial multiphase flow model. Among them, the gas phase state parameters, liquid phase state parameters, and particle phase state parameters can all refer to the parameters of the physical properties and state characteristics of the corresponding state phase substances in the reaction system under a specific state. Specifically, the gas phase state parameters may include gas flow rate, ambient temperature, ambient pressure, and gas composition, etc.; the liquid phase state parameters may cover the viscosity, density, initial concentration, etc. of the liquid participating in the reaction; the particle phase state parameters may involve the particle size distribution, concentration, density, etc. of the particles participating in the reaction.

[0024] And, after determining these parameters, these parameters can be combined with the geometric model to establish an initial multiphase flow model. Among them, the initial multiphase flow model is used to describe the flow characteristics, interphase forces and energy transfer process of the gas-liquid-solid three-phase. Specifically, after determining the relevant parameters, the appropriate basic control equations can be selected as the basis for building the multiphase flow model according to the specific conditions of the reactor and the simulation requirements. Exemplarily, the equations under the Euler-Euler system can be used as the basic control equations, in which each phase is regarded as a continuous medium that penetrates each other, and there is an exchange of mass, momentum and energy between the phases. Further, in the selected multiphase flow model, the interphase forces are defined, and the energy equation is enabled, and the thermophysical properties of each phase are set to simulate the heat transfer process. Finally, a comprehensive and accurate initial multiphase flow model is established.

[0025] S120, combining and correcting the liquid phase state parameters and the particle phase state parameters to generate equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry two-phase system.

[0026] Among them, the equivalent state parameters of the slurry phase can be parameters used to describe the macroscopic properties of the liquid and particle phases after mixing. Specifically, the processing method of modifying the empirical formula of physical properties can be used to merge and modify the state parameters of the liquid phase and the particle phase in the initial multiphase flow model of the gas-liquid-solid three-phase system to determine the equivalent state parameters of the slurry phase. It can be understood that this not only retains the key characteristics of the liquid phase and the particle phase, such as viscosity, density, and specific heat capacity, but also reduces the computational complexity and improves the computational efficiency by reducing the number of phases.

[0027] For example, in the initial multiphase flow model of the gas-liquid-solid three-phase system, if the liquid phase is liquid paraffin oil, the solid phase, i.e., the particle phase, is a C307 copper-based catalyst, and the gas phase is a gaseous mixture including CO2, H2, H2O, and CH3OH, then the liquid phase and the particle phase can be processed into a uniformly mixed slurry phase. By correcting the equivalent apparent physical properties of the slurry phase, such as viscosity, density, specific heat capacity, and diffusion coefficient, etc., to reflect the influence of the particles, an equivalent conversion from the gas-liquid-solid three-phase system to the gas phase-slurry phase two-phase system is achieved.

[0028] Specifically, the corrected equivalent viscosity can be expressed as follows: In the formula, is the equivalent viscosity; is the liquid phase viscosity; Is the solid content.

[0029] The corrected equivalent density can be expressed as follows: In the formula, is the equivalent density; is the density of the liquid phase; is the particle phase density; Is the solid content.

[0030] The corrected equivalent specific heat capacity can be expressed as follows: In the formula, is the equivalent specific heat capacity; is the relative heat capacity of liquid; is the relative heat capacity of particles; is the density of the liquid phase; is the particle phase density; Is the solid content.

[0031] The corrected equivalent diffusion coefficient can be expressed as follows: In the formula, is the equivalent diffusion coefficient; is the liquid phase diffusion coefficient; Is the solid content.

[0032] S130. Construct a component transport model based on equivalent state parameters of the equivalent multiphase flow model.

[0033] Among them, the component transport model is used to track the mass conservation of each component in the gas phase and the slurry phase, so as to describe the mass change process caused by convection, diffusion, chemical reaction and interphase mass transfer of each component in different phases. Specifically, using the equivalent state parameters determined in the equivalent multiphase flow model, based on Fick's law, the mass transfer equation of the relationship between the diffusion flux of the components in each phase and the concentration gradient is established. At the same time, considering the effects of convection, diffusion, chemical reaction and interphase mass transfer, combined with the equivalent state parameters, the transport equations of each component in the gas phase and the slurry phase are established. Finally, by combining these equations, the distribution of each substance in different stages is determined, so as to construct a component transport model that fully describes the transport process of each component in the gas phase and the slurry phase.

[0034] S140. Use an equivalent multiphase flow model, a component transport model, and a reaction model to construct a coupled simulation model, and iteratively solve the coupled simulation model to obtain a simulation result of the multiphase flow coupling.

[0035] Among them, the reaction model is established based on the reaction equation corresponding to the hydrogenation methanol process and is used to simulate the CO2 hydrogenation reaction rate. It should be understood that the intrinsic kinetic model is an expression selected by the reaction model to calculate the reaction rate. It is used to describe the relationship between the reaction rate and variables such as reactant concentration and temperature, and can accurately characterize the essential characteristics of the reaction.

[0036] Specifically, according to the reaction equation and the intrinsic kinetic model, a chemical reaction model is established to simulate the reaction process of CO2 hydrogenation. First, the reaction steps need to be determined. The chemical reaction formula for CO2 hydrogenation to methanol is: . During the reaction process, the elementary reaction steps that may be experienced include the adsorption of CO2, the dissociative adsorption of H2, the generation and transformation of intermediate species, and the desorption of CH3OH. After clarifying the reaction mechanism, a suitable intrinsic kinetic model can be selected, and the law of mass action and the principle of adsorption equilibrium can be used to derive the quantitative relationship between the reaction rate and the concentration (or fugacity) of each component. Finally, a kinetic equation that can quantitatively analyze the effect of reaction conditions on the reaction rate is obtained, that is, a reaction model.

[0037] For example, in the methanol synthesis reaction kinetics, the LH model with good extrapolation performance can be used as the intrinsic kinetic model to describe the reaction, and the reaction rate of this reaction process can be described by compiling a user-defined function, which can be specifically expressed as shown in the following formula: In the formula, is the reaction rate; is the reaction rate constant; is the reaction equilibrium constant expressed as fugacity; is the component fugacity of CO2; is the component fugacity of CH3OH; is the component fugacity of H2O; is the component fugacity of H2; is the adsorption constant of CO2; is the adsorption constant of H2O.

[0038] Among them, the reaction rate constant The expression can be shown as follows: In the formula, is the reaction rate constant; is the gas constant; and T is the temperature.

[0039] Adsorption constant of CO2 The expression can be shown as follows: In the formula, is the adsorption constant of CO2; T is the temperature.

[0040] Adsorption constant of H2O The expression can be shown as follows: In the formula, is the adsorption constant of H2O; T is the temperature.

[0041] The reaction equilibrium constant expressed by the fugacity The expression can be shown as follows: In the formula, is the reaction equilibrium constant; T is the temperature.

[0042] The above formula comprehensively considers the effects of factors such as the fugacity of reactants and products, adsorption constants, and reaction equilibrium constants on the reaction rate. It can quantitatively analyze the effects of reaction conditions on the reaction rate and provide a theoretical basis for optimizing the reaction process.

[0043] Furthermore, the equations in the equivalent multiphase flow model, component transport model, and reaction model are combined, and the interaction between the reaction term and the interphase mass transfer term is comprehensively considered, so that each model is related to each other to form an equation group containing multiple variables and equations, namely, a coupled simulation model. Among them, the coupled simulation model can be a model used to comprehensively and accurately simulate and predict the actual reflection system behavior.

[0044] At the same time, after obtaining the coupled simulation model, it can be further solved to obtain the simulation results of multiphase flow coupling.

[0045] It should be noted that before solving, it is necessary to assign initial values ​​to each variable in the model and initialize the internal field parameters. For example, the temperature in the reactor in the internal field parameters can be set to 250°C, the pressure to 5Mpa, the internal stirring paddle speed to 500rpm, and the external stirring paddle speed to 10rpm. In addition, it is necessary to select a suitable solver for iterative solution. Specifically, the SIMPLE algorithm can be used to couple the pressure-velocity field, and the first-order upwind format can be used to discretize the relevant parameters to divide the calculation area into multiple small control volumes. And a transient solver is selected to iteratively solve the variables in each control volume.

[0046] Furthermore, in each iteration, the model can be solved to obtain the reaction rate based on the current physical quantity value (such as flow rate, pressure or temperature, etc.). And the reaction rate obtained is used to update the source term in the component transport model. Then the component transport equation is solved to obtain the concentration distribution of each component. Subsequently, the physical parameters of the fluid (such as density or viscosity, etc.) are updated according to the new component concentration, and then substituted into the equivalent multiphase flow model for solution to obtain new physical quantities such as flow rate and pressure. At the same time, the relative change of the variable less than a preset threshold can be used as a convergence condition. In the iterative process, it is judged whether the change of each variable after each iteration meets the convergence condition, and finally the simulation results of multiphase flow coupling are obtained. Among them, the simulation results can be used to quantitatively analyze the stirring reaction process of liquid phase CO2 hydrogenation to methanol.

[0047] Furthermore, after obtaining the simulation results, the solution results can be processed using post-processing software to obtain multi-physics field distribution information. For example, after the calculation converges, the gas content distribution cloud map can be obtained by post-processing using CFD Post software, such as Figure 1c As shown in the figure, the spatial distribution of gas holdup in the reactor is shown, and the color depth indicates the gas holdup. A cloud diagram of bubble diameter distribution can also be obtained, such as Figure 1d As shown in the figure, the group distribution of bubble diameters in different regions is shown; the slurry phase velocity distribution cloud map can also be obtained, such as Figure 1e As shown in the figure, the color depth indicates the speed, reflecting the mixing effect of the stirring paddle on the flow field; the reaction rate distribution cloud map can also be obtained, such as Figure 1f As shown in the figure, the local reaction rate of CO2 hydrogenation to methanol in the reactor is shown; the methanol concentration distribution cloud map can also be obtained, such as Figure 1g As shown in the figure, the color gradient indicates the concentration, showing the spatial distribution of the methanol mass fraction in the slurry phase; the temperature distribution cloud map can also be obtained, such as Figure 1h As shown, the figure shows the temperature field distribution in the reactor to show the temperature gradient between the high temperature area (such as near the stirring paddle) and the low temperature area.

[0048] Optionally, the obtained simulation results can also be compared with the experimental results under the same conditions. For example, under the same reaction conditions, the gas content of the experimental results is 4.35%, and the gas content of the simulation results is 4.11%, and the prediction error is 0.055; the outlet methanol concentration of the experimental results is 0.1547, and the outlet methanol concentration of the simulation results is 0.1358, and the prediction error is 0.122. It can be seen from the above data that the established simulation model has high accuracy and can be used to predict the stirring reaction process of liquid-phase methanol production. Based on this, the key factors and optimization methods affecting the stirring reaction process of liquid-phase methanol production are further studied to provide data support and theoretical basis for the efficient and scientific design of stirred reactors.

[0049] In the above implementation, by merging the gas-liquid-solid three-phase system into a gas-slurry two-phase system, and correcting the macroscopic characteristics of the slurry phase based on equivalent state parameters, the model is simplified while correcting the equivalent apparent physical properties that can reflect the effect of particles on the slurry phase, significantly reducing the dimension and amount of calculation of the multiphase flow model, so that the complex gas-liquid-solid interaction is efficiently characterized, thereby shortening the simulation time while ensuring the accuracy of the multi-physics field coupling simulation. The efficient and high-precision simulation of the stirred reaction process of CO2 hydrogenation to methanol in the liquid phase is achieved, providing strong theoretical support and practical basis for the optimal design and industrial scale-up of the stirred reactor, and effectively solving the deficiencies in the design, observation and optimization of the CO2 hydrogenation process to methanol in the liquid phase.

[0050] In some embodiments, please refer to the attached Figure 2 , the coupled simulation model is iteratively solved to obtain the simulation results of multiphase flow coupling, including: S210. Apply boundary conditions to the coupled simulation model.

[0051] Among them, the boundary conditions are determined based on the operating conditions of the reaction process under actual operation conditions. Exemplarily, the boundary conditions of the fluid domain may include boundary type, inlet flow, intake composition, and initial bubble diameter distribution. It is understandable that in order to more accurately simulate the real situation, the gas distributor inlet boundary can be set to VelocityInlet, the inlet gas velocity is 8m / s, the intake composition molar ratio is set to CO2 / H2=1:3, the initial bubble diameter distribution is uniformly set to 4.5mm, the outlet boundary is Degassing, and the remaining boundaries are set to Wall.

[0052] S220, the boundary conditions and the coupled simulation model are combined, and the coupled simulation model is iteratively solved using an adaptive step size method to obtain a simulation result.

[0053] Specifically, the above boundary conditions can be substituted into the corresponding equations of the coupled simulation model, so that the boundary conditions become an organic part of the coupled simulation model, ensuring that the model can reflect the external constraints of the actual reaction system.

[0054] Furthermore, during the iterative solution process, if the result does not converge, the time step can be adjusted according to the adaptive step method. For example, the initial time step can be set (e.g. s) and the maximum time step (e.g. s), and determine the truncation error (less than 0.01) used to judge the step size adjustment. If the calculation results change dramatically, the time step will be automatically reduced to improve the calculation accuracy; if the calculation results are relatively stable, the time step will be automatically increased without exceeding the maximum time step to improve the calculation efficiency.

[0055] Optionally, during the simulation, you can also obtain a report file for recording and storing key simulation data to monitor and evaluate the simulation process and results. Exemplarily, the report file may include gas content, reaction rate, and component concentration in the kettle, and output data every 50 time steps during the calculation process. By analyzing the gas content, the distribution of the gas phase in the system and the degree of participation in the reaction can be determined; the reaction rate directly reflects the speed of the reaction; the component concentration in the kettle can show the consumption of reactants and the generation of products, providing support for studying reaction kinetics. Based on the report file, when performing iterative solution, you only need to iterate the calculation repeatedly until the gas content and reaction rate tend to be stable, and the convergence error is less than 10 -5 , you can stop the iteration and output the result.

[0056] In the above implementation, the precise setting of boundary conditions ensures that the model matches the external constraints of the actual reaction system, and accurately simulates the actual reaction process of liquid phase CO2 hydrogenation to methanol. The use of the adaptive step size method not only improves the calculation efficiency, but also ensures the accuracy of the results. Ultimately, an efficient and accurate simulation of the stirring reaction process of liquid phase CO2 hydrogenation to methanol is achieved, providing a strong theoretical basis and practical guidance for the optimal design of the reactor and industrial scale-up.

[0057] In some embodiments, please refer to the attached Figure 3 , a component transport model is constructed based on the equivalent state parameters of the equivalent multiphase flow model, including: S310. Calculate the interphase mass transfer coefficient based on equivalent state parameters using a population equilibrium model.

[0058] Among them, the interphase mass transfer coefficient is a physical quantity used to describe the material transfer rate between different phases during the reaction process. The population balance model is established based on the bubble dynamics of the equivalent multiphase flow model and is used to dynamically track the bubble size distribution to quantify the gas-liquid mass transfer surface area.

[0059] It should be understood that due to the significant differences in bubble size distribution in multiphase reactors such as stirred tanks (such as coalescence and fragmentation dynamics), the model assuming a single bubble diameter cannot reflect the impact of this heterogeneity on mass transfer and reaction, resulting in inaccurate simulation results. The use of a population equilibrium model to describe the particle size distribution and its evolution of the dispersed phase (such as bubbles, droplets, etc.) can improve the accuracy of the simulation results by statistically analyzing the bubble size distribution and quantifying the contribution of bubbles of different sizes. At the same time, in the reaction, the bubble surface area is also directly related to the interphase mass transfer coefficient, and the bubble size distribution determines the total mass transfer area. Using the population equilibrium model, the group behavior can be converted into macroscopic parameters, so that the calculation results of the interphase mass transfer coefficient are more consistent with the actual reaction situation. Specifically, the slurry phase can be set as the main phase, the gas phase can be set as the secondary phase, and a population equilibrium model reflecting the bubble size characteristics can be established. Bubble diameter groups are set, and the fragmentation model and coalescence model are defined. For example, the discrete method can be used to solve the population balance model, the bubble size is divided into multiple size sub-intervals, and the population balance equation is integrated and solved in each size sub-interval to obtain the number density function of all sub-intervals. The population balance equation can be specifically expressed as: In the formula, is the bubble density; is the volume fraction of the i-th size subinterval; is the speed of the i-th size subinterval; is the size of the i-th size subinterval; represents the breakup and generation of bubbles in the i-th size subinterval; Represents the breakup and extinction of bubbles in the i-th size subinterval; represents the coalescence and generation of bubbles in the i-th size subinterval; Represents the coalescence of bubbles in the i-th size subinterval.

[0060] Optionally, to meet the bubble size distribution in actual production, the bubble diameter range in the flow process can be set to 0.5-10 mm, divided into 20 groups, among which the coalescence-breakup model can be described by Luo-Luo model.

[0061] Furthermore, by solving the population equilibrium model, the bubble size distribution can be obtained, and the interphase contact area between the gas phase and the slurry phase can be calculated. Then, based on the selected mass transfer model, the interphase contact area and the diffusion coefficient determined based on the equivalent state parameters are substituted into it to calculate the interphase mass transfer coefficient.

[0062] It should be understood that in the stirring reaction process of CO2 hydrogenation to methanol in the liquid phase, a total of four components, CO2, H2, CH3OH and H2O, are involved in the interphase mass transfer, and their diffusion coefficients are 3.2624×10 -8 4.1075×10 -8 , 2.8411×10 -8 4.4605×10 -8 .

[0063] Furthermore, the expression of this process can be shown as follows: In the formula, is the mass transfer coefficient of the slurry phase; D slurry is the diffusion coefficient of the slurry phase; is the turbulent dissipation rate of the slurry phase; is the viscosity of the slurry phase.

[0064] This formula quantifies the effects of diffusion capacity, turbulence intensity and fluid resistance on mass transfer, and establishes a mass transfer coefficient calculation model based on slurry phase diffusion coefficient, turbulent dissipation rate and viscosity, which is used to accurately reflect the comprehensive action mechanism of various physical quantities in the interphase mass transfer process.

[0065] S320. Construct a component transport model based on the interphase mass transfer coefficient and the component conservation equation.

[0066] Among them, the component conservation equation is an equation used to describe the mass change, transmission, and transfer process between different phases of each component in space and time during the reaction process.

[0067] It can be understood that the component conservation equation follows the principle of mass conservation and is used to describe the mass change of components in time and space. Furthermore, after determining the component conservation equation, the interphase mass transfer coefficient can be used as a link to integrate mass transfer related parameters to finally construct a complete component transport model. That is, in the liquid phase hydrogenation reaction, the bubble characteristics are first obtained through the population equilibrium model to calculate the interphase mass transfer coefficient, and then the interphase mass transfer coefficient is substituted into the component conservation equation, which can finally achieve an accurate simulation of the temporal and spatial distribution of each component in the reaction system.

[0068] In the above implementation, by using the population balance model to calculate the interphase mass transfer coefficient, the mass change, transmission and interphase transfer process of each component in the multiphase reaction system can be accurately described. According to the interphase mass transfer coefficient and the component conservation equation, the component transport model can be constructed to fully consider the influence of processes such as convection, diffusion, chemical reaction and interphase mass transfer, so as to achieve accurate simulation and connect the microscopic particle behavior, mass transfer process and macroscopic component transport of the spatiotemporal distribution of each component in the reaction system.

[0069] In some embodiments, a component transport model is constructed based on the interphase mass transfer coefficient and the component conservation equation, including: determining the mass flux of the component interphase mass transfer based on the interphase mass transfer coefficient, and embedding it as a source term into the component conservation equation to construct the component transport model.

[0070] Specifically, the component conservation equation is an equation used to describe the mass change of components in time and space, which may include the convection of fluid flow carrying components and the natural migration and diffusion of components from high concentration areas to low concentration areas, as well as the reaction of components generated or consumed by chemical reactions and the mass transfer of components between different phases (such as gas phase and slurry phase). In order to accurately describe the transfer of components between different phases, the mass flux of component interphase mass transfer is determined based on the interphase mass transfer coefficient, and it is embedded as a source term in the component conservation equation. The interphase mass transfer coefficient is used to calculate the mass transfer source term (such as the transfer rate of components at the phase interface), which can be combined with parameters that affect the transfer rate such as the interphase contact area and the component concentration difference to form the mass transfer source term in the component conservation equation. Exemplarily, in a gas phase-slurry phase two-phase system, the interphase mass transfer coefficient is first used to calculate the mass flux of the component from the gas phase to the slurry phase or from the slurry phase to the gas phase. This flux is related to factors such as the interphase contact area and the component concentration difference. Then, the calculated mass flux is embedded as a source term into the component conservation equations of the gas phase and the slurry phase, respectively. When the component is transferred from the gas phase to the slurry phase, the source term in the component conservation equation of the gas phase is negative (indicating the loss of the component), while the source term in the component conservation equation of the slurry phase is positive (indicating the increase of the component), and vice versa, thereby quantifying the impact of interphase material transfer on the component distribution.

[0071] In the above implementation, the component transport model constructed by the interphase mass transfer coefficient and the component conservation equation can comprehensively and accurately describe the mass change, transmission and interphase transfer process of each component in the multiphase reaction system. By combining the interphase mass transfer coefficient with parameters such as the interphase contact area and the component concentration difference, the mass flux of the component interphase mass transfer is determined, and it is embedded as a source term in the component conservation equation. This model can not only describe the convection, diffusion and reaction process of the components in the gas phase and slurry phase, but also quantify the effect of interphase material transfer on the component distribution. It not only improves the accuracy of the simulation results, but also provides strong theoretical support for optimizing reaction conditions and reactor design.

[0072] In some embodiments, the component conservation equation is constructed in the following manner: the component conservation equation is established based on the gas phase state parameters and the liquid phase state parameters.

[0073] Specifically, when establishing the component conservation equation, it is necessary to consider the influence of the flow, diffusion and chemical reaction within each phase on each component, so the constructed component conservation equation can be expressed as: In the formula, i=l represents the liquid phase, i=g represents the gas phase; represents the mass fraction of component j in phase i; represents the diffusion coefficient of component j in phase i; It represents the mass generated or consumed due to interphase mass transfer; Indicates the creation or consumption of mass caused by a chemical reaction.

[0074] The component conservation equation describes the mass conservation of component j in phase i in a multiphase flow system, taking into account the mass change rate of component j in phase i, convective transport, diffusion transport, and mass changes caused by interphase mass transfer and chemical reactions.

[0075] In the above implementation, the constructed component conservation equation can accurately describe the mass change law of each component in the multiphase flow system, comprehensively consider the influence of the internal flow, diffusion and chemical reaction of each phase on the components, provide a theoretical basis for the accurate modeling and simulation of complex multiphase flow systems, and improve the reliability and accuracy of the simulation results.

[0076] In some embodiments, please refer to the attached Figure 4 , based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction, the initial multiphase flow model of the gas-liquid-solid three-phase system is constructed, including: S410, determining the continuity equation, momentum equation and energy equation based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters, and introducing the turbulent diffusion force equation and initial drag force equation.

[0077] Similarly, the equations under the Euler-Euler system can be used to determine the basic control equations such as the continuity equation, the momentum equation and the energy equation based on the gas phase state parameters, the liquid phase state parameters and the particle phase state parameters. For example, the continuity equation can be expressed as: In the formula, i=l represents the liquid phase, i=g represents the gas phase; is the volume fraction of phase i; is the velocity of phase i; is the density of phase i; t is the time.

[0078] This continuity equation is used to describe the conservation of mass of each phase. Its significance lies in that at any time during the reaction, the sum of the mass change rate of a phase per unit volume and the mass flux of the phase through the surface of the control body is zero, ensuring that the mass of each phase in the reaction system will not be created or disappeared out of thin air.

[0079] The momentum equation can be expressed as: In the formula, i=l represents the liquid phase, i=g represents the gas phase; is the volume fraction of phase i; is the velocity of phase i; is the density of phase i; t is the time; g is the acceleration due to gravity; P is the pressure in the reactor; is the force between gas and liquid phases, Stress-strain tensor terms.

[0080] The momentum equation is used to describe the conservation of momentum of each phase, taking into account factors such as gravity, pressure gradient, and interphase forces. It shows that the rate of change of momentum of a phase in a unit volume over time is equal to the resultant force generated by factors such as pressure gradient, gravity, and interphase forces, reflecting the change in the motion state of each phase under the action of multiple forces.

[0081] The energy equation can be expressed as: In the formula, i=l represents the liquid phase, i=g represents the gas phase; represents the temperature of phase i; represents the thermal conductivity of phase i; represents the constant-pressure specific heat capacity of phase i.

[0082] Furthermore, in order to improve the accuracy and reliability of the multiphase flow model, it is also necessary to introduce the turbulent diffusion force equation and the initial drag force equation into the multiphase flow model.

[0083] For example, the turbulent diffusion force equation can be expressed as: In the formula, represents the turbulent diffusion force; To adjust the turbulent diffusion coefficient, its value is 1.0, which is used to control the intensity of turbulent diffusion. As a preset parameter, it directly affects the overall level of turbulent diffusion in the calculation; The intrinsic turbulent diffusion coefficient is used to characterize the diffusion properties of turbulence itself and reflects the essential ability of material diffusion under turbulent conditions. It is the gas-liquid coupled turbulent diffusion coefficient, which focuses on the coupling effect between the gas and liquid phases and reflects the specific correlation characteristics of turbulent diffusion between the gas and liquid phases in the model; is the turbulent Prandtl number, which is 0.9; is the volume fraction of gas phase; is the volume fraction of liquid phase.

[0084] The turbulent diffusion force equation can describe the diffusion effect between the gas phase and the liquid phase under turbulent state, and can quantify the enhancement of turbulent effect on the mass, momentum and energy transfer between phases, thereby accurately describing the interphase mixing and dispersion behavior under complex flow fields.

[0085] The initial drag equation can be expressed as: In the formula, is the drag force; is the drag coefficient; is the characteristic diameter of the bubble; is the volume fraction of gas phase; is the density of the liquid phase; is the velocity of the gas phase; is the velocity of the liquid phase.

[0086] The initial drag equation is used to capture the resistance effect caused by the relative motion between phases. It indicates that the turbulent diffusion force is related to factors such as the velocity difference between the two phases, the turbulent characteristics, and the volume fraction of the phases, reflecting the influence of turbulence on the diffusion of substances between the gas and liquid phases.

[0087] S420. Construct an interphase force model based on the turbulent diffusion force equation and the initial drag force equation.

[0088] Among them, the interphase force model can be used to characterize the mutual mechanical interaction between different phases in a multiphase flow system. Its core is to describe the forces generated by each phase during the flow process due to turbulent diffusion or relative motion, so as to analyze the dynamic characteristics of multiphase flow. Specifically, the turbulent diffusion force equation and the initial drag force equation can be selected as the basis and combined with the two. Through the parameters in the equation, the influence of the diffusion force caused by turbulence on the gas phase distribution is considered, and the constraints of the drag force on the relative motion of gas and liquid are incorporated. Finally, a unified interphase force model is formed to comprehensively calculate the total interphase force.

[0089] S430, constructing an initial multiphase flow model based on the continuity equation, momentum equation, energy equation and interphase force model.

[0090] It is understandable that the construction of the initial multiphase flow model requires the integration of the continuity equation, momentum equation, energy equation and interphase force model to systematically describe the flow, mass transfer and energy transfer process of the multiphase system. Specifically, the interphase interaction mechanism can be integrated into the established basic conservation equations, that is, the interphase force model can be embedded into the basic continuity equation, momentum equation and energy equation, so as to form a complete multiphase flow model and realize the systematic simulation of complex processes such as flow, mass transfer and heat transfer of the multiphase flow system.

[0091] In the above implementation, by integrating the continuity equation, momentum equation, energy equation and interphase force model, the flow, mass transfer and energy transfer processes of the multiphase system are systematically described, and the complex interactions of the phases in the multiphase flow system are accurately simulated, thereby improving the accuracy and reliability of the simulation and providing a powerful tool for the research and application of multiphase flow systems.

[0092] In some embodiments, please refer to the attached Figure 5 , based on the turbulent diffusion force equation and the initial drag force equation, the interphase force model is constructed, including: S510, dynamically correcting the drag coefficient of the initial drag equation according to the flow characteristics to obtain a corrected drag equation.

[0093] It should be understood that in the real reaction process, due to factors such as changes in local turbulence intensity, particle agglomeration or dispersion, bubble deformation, droplet breakup, particle-particle collision, and momentum exchange enhanced by turbulent pulsation, there are significant non-uniformity, dynamic evolution of multiphase interfaces, and nonlinear interactions in the real flow. These flow characteristics will cause the drag coefficient of the initial drag equation to deviate from the preset value in the simulation, thereby affecting the calculation accuracy of the interphase momentum transfer in the simulation calculation. Therefore, the drag coefficient of the initial drag equation can be dynamically corrected. Exemplarily, its expression can be shown as follows: In the formula, is the corrected drag coefficient; is the terminal velocity of the bubble in a stationary fluid; is the Froude number, which is the ratio of gravity to inertial force; This expression can be used to reflect the change of the drag coefficient in a turbulent environment compared to a static situation. This formula can be used to correct the drag coefficient of the initial drag equation, more accurately calculate the drag between the gas and liquid phases, and thus more accurately describe the flow characteristics of the multiphase flow. Furthermore, after obtaining the corrected drag coefficient, it can be substituted into the initial drag equation to obtain the corrected drag equation.

[0094] S520. Construct an interphase force model based on the turbulent diffusion force equation and the modified drag force equation.

[0095] Similarly, the turbulent diffusion force equation is used to describe the diffusion driving force of the turbulent effect on the gas phase distribution, and the modified drag equation is used to quantify the resistance generated by the relative motion of gas and liquid. That is, by integrating the equations, a unified interphase force model can be formed, thereby comprehensively calculating the total interphase force.

[0096] In the above implementation, by taking into account the influence of turbulence and dynamically correcting the drag coefficient of the initial drag equation, the drag between the gas and liquid phases can be calculated more accurately, thereby more accurately describing the flow characteristics of the multiphase flow. The interphase force model finally formed can fully calculate the total interphase force, thereby improving the accuracy and reliability of the multiphase flow model.

[0097] It should be understood that, although the various steps in the above flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above flowchart may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0098] The embodiment of this specification also provides a multiphase flow coupling simulation device 600, such as Figure 6 As shown, it includes: a multiphase flow model building module 610, a multiphase flow model equivalent module 620, a component transport model building module 630 and a coupling solution module 640, wherein: The multiphase flow model establishment module 610 is used to construct an initial multiphase flow model of the gas-liquid-solid three-phase system based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction; wherein the initial multiphase flow model is used to describe the flow characteristics, interphase forces and energy transfer process of the gas-liquid-solid three-phase system.

[0099] The multiphase flow model equivalent module 620 is used to merge and modify the liquid phase state parameters and the particle phase state parameters to generate equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry two-phase system.

[0100] The component transport model establishment module 630 is used to construct a component transport model based on the equivalent state parameters of the equivalent multiphase flow model; wherein the component transport model is used to track the mass conservation of each component in the gas phase and the slurry phase, so as to describe the mass change process caused by convection, diffusion, chemical reaction and interphase mass transfer of each component in different phases.

[0101] The coupling solution module 640 is used to construct a coupling simulation model using an equivalent multiphase flow model, a component transport model and a reaction model, and iteratively solve the coupling simulation model to obtain simulation results of multiphase flow coupling; wherein the reaction model is established based on the reaction equation corresponding to the hydrogenation to methanol process, and is used to simulate the CO2 hydrogenation reaction rate; the simulation results are used to quantitatively analyze the stirring reaction process of liquid phase CO2 hydrogenation to methanol.

[0102] In some embodiments, the coupling solution module 640 is also used to impose boundary conditions on the coupled simulation model; wherein the boundary conditions are determined based on the operating conditions of the reaction process under actual operating conditions; the boundary conditions and the coupled simulation model are combined, and the coupled simulation model is iteratively solved using an adaptive step size method to obtain simulation results.

[0103] In some embodiments, the component transport model establishment module 630 is also used to calculate the interphase mass transfer coefficient based on the equivalent state parameters using the population equilibrium model; wherein the interphase mass transfer coefficient is a physical quantity used to describe the material transfer rate between different phases during the reaction process; the population equilibrium model is established based on the bubble dynamics characteristics of the equivalent multiphase flow model, and is used to dynamically track the bubble size distribution to quantify the gas-liquid mass transfer surface area; a component transport model is constructed based on the interphase mass transfer coefficient and the component conservation equation; wherein the component conservation equation is an equation used to describe the mass change, transmission, and transfer process between different phases of each component in space and time during the reaction process.

[0104] In some embodiments, the component transport model building module 630 is further used to determine the mass flux of component interphase mass transfer based on the interphase mass transfer coefficient, and embed it into the component conservation equation as a source term to construct a component transport model.

[0105] In some embodiments, the multiphase flow coupled simulation device 600 further includes a component conservation equation establishing module for establishing a component conservation equation based on gas phase state parameters and liquid phase state parameters.

[0106] In some embodiments, the multiphase flow model establishment module 610 is also used to determine the continuity equation, momentum equation and energy equation based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters, and introduce the turbulent diffusion force equation and the initial drag equation; construct an interphase force model based on the turbulent diffusion force equation and the initial drag equation; and construct a multiphase flow model based on the continuity equation, momentum equation, energy equation and interphase force model.

[0107] In some embodiments, the multiphase flow coupling simulation device 600 also includes an interphase force model establishment module, which is used to dynamically correct the drag coefficient of the initial drag equation according to the flow characteristics to obtain a corrected drag equation; and construct an interphase force model based on the turbulent diffusion force equation and the corrected drag equation.

[0108] For the specific definition of a multiphase flow coupling simulation device, please refer to the definition of a multiphase flow coupling simulation method mentioned above, which will not be repeated here. Each module in the above-mentioned multiphase flow coupling simulation device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0109] The multiphase flow coupling simulation device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0110] The embodiment of the present application also provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a simulation method for multiphase flow coupling is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0111] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0112] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0113] The embodiment of the present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method of any embodiment of the present application.

[0114] The above embodiments illustrate a method, device, computer equipment and storage medium for simulating multiphase flow coupling, which can be implemented by a computer chip or entity, or by a product with a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices. For the convenience of description, the above devices are described in various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same one or more software and / or hardware.

[0115] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0116] The present application is described with reference to the flowchart and / or block diagram of the method, device (system), and computer program product according to the embodiment of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the process and / or box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the function specified in one or more processes of the flowchart and / or one or more boxes of the block diagram. These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the function specified in one or more processes of the flowchart and / or one or more boxes of the block diagram. These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0117] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0118] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. It should also be noted that the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements. The various embodiments in this specification are described in a progressive manner, and the same and similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. Since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0119] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0120] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A simulation method for multiphase flow coupling, characterized in that: Applied to the process of producing methanol by CO2 hydrogenation in liquid phase, the method comprises: An initial multiphase flow model of a gas-liquid-solid three-phase system is constructed based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction; wherein the initial multiphase flow model is used to describe the flow characteristics, interphase forces and energy transfer process of the gas-liquid-solid three-phase system; The liquid phase state parameters and the particle phase state parameters are combined and corrected to generate equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry phase two-phase system; A component transport model is constructed based on the equivalent state parameters of the equivalent multiphase flow model; wherein the component transport model is used to track the mass conservation of each component in the gas phase and the slurry phase, so as to describe the mass change process caused by convection, diffusion, chemical reaction and interphase mass transfer of each component in different phases; A coupled simulation model is constructed using the equivalent multiphase flow model, the component transport model and the reaction model, and the coupled simulation model is iteratively solved to obtain simulation results of multiphase flow coupling; wherein the reaction model is established based on the reaction equation corresponding to the hydrogenation to methanol process, and is used to simulate the CO2 hydrogenation reaction rate; the simulation results are used to quantitatively analyze the stirring reaction process of liquid phase CO2 hydrogenation to methanol.

2. The method according to claim 1, characterized in that: The iterative solution of the coupled simulation model to obtain a simulation result of multiphase flow coupling includes: Applying boundary conditions to the coupled simulation model; wherein the boundary conditions are determined based on the operating conditions of the reaction process under actual operation conditions; The boundary condition and the coupled simulation model are combined, and the coupled simulation model is iteratively solved using an adaptive step method to obtain the simulation result.

3. The method according to claim 1, characterized in that The constructing of a component transport model based on equivalent state parameters of the equivalent multiphase flow model comprises: The interphase mass transfer coefficient is calculated based on the equivalent state parameter using a population balance model; wherein the interphase mass transfer coefficient is a physical quantity used to describe the material transfer rate between different phases during a reaction process; the population balance model is established based on the bubble dynamics characteristics of the equivalent multiphase flow model, and is used to dynamically track the bubble size distribution to quantify the gas-liquid mass transfer surface area; The component transport model is constructed according to the interphase mass transfer coefficient and the component conservation equation; wherein the component conservation equation is an equation for describing the mass change, transmission and transfer process of each component in space and time during the reaction process between different phases.

4. The method according to claim 3, characterized in that The component transport model is constructed according to the interphase mass transfer coefficient and the component conservation equation, including: Based on the interphase mass transfer coefficient, the mass flux of the interphase mass transfer of the components is determined, and is embedded as a source term into the component conservation equation to construct the component transport model.

5. The method according to claim 3, characterized in that: The component conservation equation is constructed in the following way: The component conservation equation is established based on the gas phase state parameter and the liquid phase state parameter.

6. The method according to claim 1, characterized in that The initial multiphase flow model of the gas-liquid-solid three-phase system is constructed based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction, including: Determining the continuity equation, momentum equation and energy equation based on the gas phase state parameters, the liquid phase state parameters and the particle phase state parameters, and introducing the turbulent diffusion force equation and the initial drag force equation; Constructing an interphase force model based on the turbulent diffusion force equation and the initial drag force equation; The initial multiphase flow model is constructed based on the continuity equation, the momentum equation, the energy equation and the interphase force model.

7. The method according to claim 6, characterized in that The constructing of the interphase force model based on the turbulent diffusion force equation and the initial drag force equation includes: Dynamically correcting the drag coefficient of the initial drag equation according to the flow characteristics to obtain a corrected drag equation; The interphase force model is constructed based on the turbulent diffusion force equation and the modified drag force equation.

8. A multiphase flow coupling simulation device, characterized in that: Applied to the process of producing methanol by CO2 hydrogenation in liquid phase, the device comprises: A multiphase flow model building module is used to build an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gas phase state parameters, liquid phase state parameters and particle phase state parameters in the initial stage of the reaction; wherein the initial multiphase flow model is used to describe the flow characteristics, interphase forces and energy transfer process of the gas-liquid-solid three-phase system; A multiphase flow model equivalent module, used for combining and correcting the liquid phase state parameters and the particle phase state parameters to generate equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of a gas-slurry phase two-phase system; A component transport model building module is used to build a component transport model based on the equivalent state parameters of the equivalent multiphase flow model; wherein the component transport model is used to track the mass conservation of each component in the gas phase and the slurry phase to describe the mass change process caused by convection, diffusion, chemical reaction and interphase mass transfer of each component in different phases; A coupling solution module is used to construct a coupling simulation model using the equivalent multiphase flow model, the component transport model and the reaction model, and iteratively solve the coupling simulation model to obtain a simulation result of multiphase flow coupling; wherein the reaction model is established based on the reaction equation corresponding to the hydrogenation to methanol process, and is used to simulate the CO2 hydrogenation reaction rate; the simulation result is used to quantitatively analyze the stirring reaction process of liquid phase CO2 hydrogenation to methanol.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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