Simulation method, device, computer equipment and storage medium for multiphase flow coupling

Abstract

The present application relates to the field of computer numerical simulation technology, and discloses a simulation method, device, computer device and storage medium for multiphase flow coupling, which is applied to the liquid-phase CO2 hydrogenation to methanol process. The method includes: constructing an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gaseous phase state parameters, liquid phase state parameters and particle phase state parameters at the initial stage of the reaction; merging and correcting the liquid phase state parameters and particle phase state parameters 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; constructing a coupled simulation model using the equivalent multiphase flow model, component transport model and reaction model, and performing iterative solution on the coupled simulation model to obtain the simulation result of multiphase flow coupling. Thus, the efficient and high-precision simulation of the stirring reaction process of liquid-phase CO2 hydrogenation to methanol 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 device, and storage medium for multiphase flow coupling. Background Art

[0002] With the rapid development of industry, the demand for efficient chemical conversion technologies is increasing day by day. In the fields of energy and chemical engineering, the liquid-phase process of carrying out chemical reactions by dispersing nano-catalysts in high-boiling-point inert media has gradually emerged. This process utilizes the high heat capacity of the liquid phase to achieve rapid dissipation of reaction heat, can effectively control temperature fluctuations, and improve product selectivity. However, although the liquid-phase method has advantages, it still has deficiencies in design, observation, and optimization, and 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 at least solve one of the technical problems in the related art to some extent. For this purpose, the present application provides a simulation method, device, computer device, and storage medium for multiphase flow coupling. The main technical solutions adopted by the present application include:

[0004] In a first aspect, an embodiment of the present application provides a simulation method for multiphase flow coupling, which is applied to the liquid-phase process of hydrogenating CO2 to methanol. The method includes: constructing an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gaseous-phase state parameters, liquid-phase state parameters, and particle-phase state parameters at 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; constructing 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 gaseous 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; constructing a coupled simulation model using the equivalent multiphase flow model, the component transport model, and the reaction model, and performing iterative solution on the coupled 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 process of methanol, and is used to simulate the CO2 hydrogenation reaction rate; the simulation result is used to quantitatively analyze the stirring reaction process of the liquid-phase hydrogenation of CO2 to methanol.

[0005] 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.

[0006] 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.

[0007] 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.

[0008] 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.

[0009] 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.

[0010] 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.

[0011] In a second aspect, an 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. The device includes: a multiphase flow model establishment module, configured to construct an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gaseous phase state parameters, liquid phase state parameters, and particle phase state parameters at 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; a multiphase flow model equivalence module, configured to merge and correct the liquid phase state parameters and 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 establishment module, configured 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 gaseous phase and 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 coupled solution module, configured to construct a coupled simulation model using the equivalent multiphase flow model, component transport model, and reaction model, and perform iterative solution on the coupled 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 the liquid-phase CO2 hydrogenation to methanol.

[0012] In a third aspect, the present application further provides a computer device including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method according to any one of the above are implemented.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method according to any one of the above are implemented.

[0014] In a fifth aspect, the present invention provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of the above are implemented.

[0015] In the above embodiments, by combining the gas-liquid-solid three-phase system into a gas-slurry two-phase system and modifying the macroscopic properties of the slurry phase based on the equivalent state parameters, while simplifying the model, the equivalent apparent physical properties that can reflect the influence of particles on the slurry phase are corrected, significantly reducing the dimension and computational amount of the multiphase flow model, enabling the efficient characterization of the complex gas-liquid-solid interactions, thereby shortening the simulation time on the basis of ensuring the accuracy of the multi-physical field coupling simulation. It realizes the efficient and high-precision simulation of the stirring reaction process of CO2 hydrogenation to methanol by the liquid phase method, provides strong theoretical support and practical basis for the optimized design and industrial scale-up of the stirring reactor, and effectively solves the deficiencies in the design, observation and optimization of the CO2 hydrogenation to methanol process by the liquid phase method. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0017] Figure 1a It is a flowchart of a simulation method for multiphase flow coupling provided according to an embodiment of the present application;

[0018] Figure 1b It is a schematic diagram of the mesh of the fluid calculation domain provided according to an embodiment of the present application;

[0019] Figure 1c It is a cloud map of the gas holdup distribution provided according to an embodiment of the present application;

[0020] Figure 1d It is a cloud map of the bubble diameter distribution provided according to an embodiment of the present application;

[0021] Figure 1e It is a cloud map of the slurry phase velocity distribution provided according to an embodiment of the present application;

[0022] Figure 1f It is a cloud map of the reaction rate distribution provided according to an embodiment of the present application;

[0023] Figure 1g It is a cloud map of the methanol concentration distribution provided according to an embodiment of the present application;

[0024] Figure 1h It is a cloud map of the temperature distribution provided according to an embodiment of the present application;

[0025] Figure 2 It is a flowchart of the iterative solution method provided according to an embodiment of the present application;

[0026] Figure 3 A flowchart for constructing a component transport model provided according to an embodiment of the present application;

[0027] Figure 4 A flowchart for constructing a multiphase flow model provided according to an embodiment of the present application;

[0028] Figure 5 A flowchart for constructing an interfacial force model provided according to an embodiment of the present application;

[0029] Figure 6 A structural block diagram of a simulation device for multiphase flow coupling provided according to an embodiment of the present application;

[0030] Figure 7 An internal structure diagram of a computer device provided according to an embodiment of the present application. Detailed implementation manners

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0032] With the rapid development of industry, the demand for efficient chemical conversion technologies is increasing day by day. In the fields 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. The greenhouse effect caused by its excessive emissions has posed a serious threat to the global ecological security. In this context, it is urgent to develop efficient CO2 resource utilization technologies. Among them, the catalytic hydrogenation of CO2 to high-value-added fuels and chemicals such as methanol can not only achieve carbon cycle utilization but also alleviate the dependence on fossil energy, with significant environmental and economic benefits. Currently, the mainstream industrial process adopts the gas-phase method, in which CO2 and hydrogen undergo a hydrogenation reaction on the surface of a solid catalyst through a fixed-bed reactor. However, this process is prone to cause distortion of the bed temperature gradient and local hot spots (temperature fluctuation ±15%) due to intense exothermic reaction, resulting in sintering inactivation of the catalyst and a methanol selectivity drop below 60%. Therefore, the liquid-phase process that disperses nano-catalysts in a high-boiling-point inert medium for chemical reactions has gradually emerged. This process utilizes the high heat capacity of the liquid phase to rapidly dissipate the reaction heat, effectively controlling the temperature fluctuation and improving the product selectivity. That is, the liquid-phase process disperses nano-catalysts in a high-boiling-point inert medium (such as paraffin oil) to form a slurry system, and utilizes the high heat capacity of the liquid phase (>2.5 kJ / (kg·K)) to rapidly dissipate the reaction heat, which can control the temperature fluctuation within ±10°C and increase the methanol selectivity to over 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 the fixed bed.

[0033] However, although the liquid-phase method has advantages, it still has deficiencies in the following aspects: 1. The design method is limited. The structural parameters of the reactor (such as the blade configuration and the aperture of the gas distributor) mostly rely on empirical formulas, lacking a systematic modeling of the multi-phase flow field - mass transfer - reaction coupling mechanism; 2. The observation means are lacking. Under high-temperature and high-pressure (>200°C, >5MPa) conditions, it is difficult to capture the gas-liquid-solid three-phase flow behavior, interphase mass transfer, and in-phase reaction details in real time through experiments; 3. The optimization cycle is long. Using the traditional trial-and-error method requires dozens of pilot-scale verifications, 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.

[0034] Based on this, according to the embodiments of the present application, an embodiment of a simulation method for multi-phase 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 a different order than here.

[0035] In this embodiment, a simulation method for multi-phase flow coupling is provided, which is applied to the liquid-phase CO2 hydrogenation to methanol process. Figure 1ais a flowchart of a simulation method for multiphase flow coupling according to an embodiment of the present application. As Figure 1a shown, the process includes the following steps:

[0036] S110. Construct an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gaseous phase state parameters, liquid phase state parameters, and particle phase state parameters at the initial stage of the reaction.

[0037] It should be understood that before constructing the initial multiphase flow model, it is also necessary to establish a geometric model including the reactor vessel body, agitator, and gas distributor according to the size and structure of the liquid-phase CO2 hydrogenation to methanol stirred reactor, 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. Exemplarily, a three-dimensional modeling software Solidworks can be used to construct the geometric model of the reactor. The inner diameter of the reactor vessel body is 380 mm, and it is equipped with a concentric coaxial agitator. The inner impeller is a six-straight-blade disk turbine impeller, and the outer impeller is a frame impeller. A circular gas distributor with a diameter of 120 mm is located at a height of 125 mm from the bottom of the kettle, and it has 24 evenly distributed circumferential holes with a hole diameter of 2 mm. Further, it is also necessary to perform mesh division on the geometric model, that is, define the fluid domain and perform mesh division on the geometric model based on computational fluid dynamics numerical simulation software to decompose it into multiple small computational units. Exemplarily, Fluent Meshing can be used to perform mesh division on the geometric model. The mesh can select the Poly-hexcore hexahedral mesh, and the number of meshes needs to be verified for mesh independence. At the same time, to accurately simulate the movement of the agitator, the multiple reference frame method can be adopted, and the areas near the inner and outer agitator paddles are set as moving areas, and the remaining areas are set as static areas. Exemplarily, the mesh schematic diagram of the fluid calculation domain of this geometric model can be referred to Figure 1b shown, the figure shows the mesh structure of the reactor geometric model after mesh division, including the division of the moving area (near the agitator paddle) and the static area.

[0038] Further, after completing the construction and mesh division of the reactor geometric model, it is necessary to determine the state parameters of each phase participating in the reaction at the initial stage of the reaction to establish an initial multiphase flow model. Among them, the gaseous 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 possessed by the substances in the corresponding state phases in the reaction system under specific states. Specifically, the gaseous phase state parameters can include gas flow rate, ambient temperature, ambient pressure, and the composition of the gas, etc.; the liquid phase state parameters can cover the viscosity, density, initial concentration, etc. of the liquid participating in the reaction; the particle phase state parameters can involve the particle size distribution, concentration, density, etc. of the particles participating in the reaction.

[0039] Furthermore, after determining these parameters, they 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 of the gas-liquid-solid three-phase, the interfacial forces between phases, and the energy transfer process. Specifically, after determining the relevant parameters, according to the specific situation of the reactor and the simulation requirements, appropriate basic control equations can be selected as the basis for constructing the multiphase flow model. Exemplarily, the equations under the Euler-Euler system can be used as the basic control equations, where each phase is regarded as an interpenetrating continuous medium, and there are exchanges of mass, momentum, and energy between phases. Further, in the selected multiphase flow model, the interfacial forces between phases are defined, 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.

[0040] S120. Combine and correct the liquid-phase state parameters and the particle-phase state parameters to generate the equivalent state parameters of the slurry phase, so as to simplify the initial multiphase flow model into an equivalent multiphase flow model of the gas-slurry phase two-phase system.

[0041] Among them, the equivalent state parameters of the slurry phase can be parameters used to describe the macroscopic properties after mixing the liquid phase and the particle phase. Specifically, a processing method of correcting using empirical physical property formulas can be adopted to combine and correct 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 such as the viscosity, density, and specific heat capacity of the liquid phase and the particle phase, but also reduces the computational complexity and improves the computational efficiency by reducing the number of phases.

[0042] Exemplarily, 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 the C307 copper-based catalyst, and the gas phase is a gas mixture including CO2, H2, H2O, and CH3OH, then the liquid phase and the particle phase can be treated as 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, the equivalent conversion from the gas-liquid-solid three-phase system to the gas-slurry phase two-phase system is realized.

[0043] Specifically, the corrected equivalent viscosity can be shown as the following formula:

[0044]

[0045] In the formula, is the equivalent viscosity; is the viscosity of the liquid phase; is the solid volume fraction.

[0046] The corrected equivalent density can be shown as the following formula:

[0047]

[0048] In the formula, is the equivalent density; is the density of the liquid phase; is the particle phase density; Is the solid content.

[0049] The corrected equivalent specific heat capacity can be expressed as follows:

[0050]

[0051] 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.

[0052] The corrected equivalent diffusion coefficient can be expressed as follows:

[0053]

[0054] In the formula, is the equivalent diffusion coefficient; is the liquid phase diffusion coefficient; Is the solid content.

[0055] S130. Construct a component transport model based on equivalent state parameters of the equivalent multiphase flow model.

[0056] 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 component 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.

[0057] 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.

[0058] Among them, the reaction model is established based on the reaction equations corresponding to the methanol synthesis process by hydrogenation and is used to simulate the reaction rate of CO2 hydrogenation. It should be understood that the intrinsic kinetic model is the expression selected by the reaction model for calculating the reaction rate and is used to describe the relationship between the reaction rate and variables such as the concentration of reactants and temperature, and can accurately characterize the essential characteristics of the reaction.

[0059] Specifically, according to the reaction equations and the intrinsic kinetic model, to establish a chemical reaction model to simulate the reaction process of CO2 hydrogenation, it is first necessary to determine the reaction steps. The chemical reaction equation for methanol synthesis by CO2 hydrogenation is: . During its reaction process, the possible elementary reaction steps it may experience include the adsorption of CO2, the dissociative adsorption of H2, the generation and transformation of intermediate species, and the desorption of CH3OH, etc. After clarifying its reaction mechanism, an appropriate intrinsic kinetic model can be selected, and by applying the law of mass action and the principle of adsorption equilibrium, the quantitative relationship between the reaction rate and the concentration (or fugacity) of each component can be deduced. Finally, a kinetic equation that can quantitatively analyze the influence of reaction conditions on the reaction rate is obtained, that is, the reaction model.

[0060] Exemplarily, in the kinetics of methanol synthesis reaction, the L-H model with good extrapolation can be used as the intrinsic kinetic model to describe this reaction, and the reaction rate of this reaction process can be described by compiling a user-defined function, and its specific expression can be shown as follows:

[0061]

[0062] In the formula, is the reaction rate; is the reaction rate constant; is the reaction equilibrium constant expressed by 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.

[0063] Among them, the reaction rate constant The expression of can be shown as follows:

[0064]

[0065] In the formula, is the reaction rate constant; R is the gas constant; T is the temperature.

[0066] The adsorption constant of CO2 The expression of can be shown as follows:

[0067]

[0068] In the formula, is the adsorption constant of CO2; T is the temperature.

[0069] Adsorption constant of H2O The expression can be shown as follows:

[0070]

[0071] In the formula, is the adsorption constant of H2O; T is the temperature.

[0072] The reaction equilibrium constant expressed by the fugacity The expression can be shown as follows:

[0073]

[0074] In the formula, is the reaction equilibrium constant; T is the temperature.

[0075] 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.

[0076] 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.

[0077] At the same time, after obtaining the coupled simulation model, it can be further solved to obtain the simulation results of multiphase flow coupling.

[0078] 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.

[0079] Furthermore, in each iteration, the reaction rate can be obtained by solving the model based on the current physical quantity values (such as flow rate, pressure, or temperature, etc.). Then, using the obtained reaction rate, the source term in the component transport model is updated. Subsequently, the component transport equation is solved to obtain the concentration distribution of each component. Then, the physical properties of the fluid (such as density or viscosity, etc.) are updated according to the new component concentrations, 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 being less than a preset threshold can be used as the convergence condition. During the iteration process, it is judged whether the changes of each variable after each iteration meet 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 CO2 hydrogenation to methanol by the liquid phase method.

[0080] Furthermore, after obtaining the simulation results, post-processing software can be used to process the solution results to obtain multi-physical field distribution information. Exemplarily, after the calculation converges, the CFD Post software can be used for post-processing to obtain the gas holdup distribution cloud map, as Figure 1c shown. The figure shows the spatial distribution of the gas holdup in the reactor, and the color depth indicates the high or low gas holdup; the bubble diameter distribution cloud map can also be obtained, as Figure 1d shown. The figure shows the grouped distribution of the bubble diameters in different regions; the slurry-phase velocity distribution cloud map can also be obtained, as Figure 1e shown. The color depth in the figure indicates the velocity magnitude, reflecting the mixing effect of the stirrer on the flow field; the reaction rate distribution cloud map can also be obtained, as Figure 1f shown. The figure shows the local reaction rate of CO2 hydrogenation to methanol in the reactor; the methanol concentration distribution cloud map can also be obtained, as Figure 1g shown. The color gradient in the figure indicates the high or low concentration, showing the spatial distribution of the methanol mass fraction in the slurry phase; the temperature distribution cloud map can also be obtained, as Figure 1h shown. The figure shows the temperature field distribution in the reactor to display the temperature gradient between the high-temperature region (such as near the stirrer) and the low-temperature region.

[0081] Optionally, the obtained simulation results can also be compared with the experimental results under the same conditions. Exemplarily, under the same reaction conditions, the gas holdup of the experimental results is 4.35%, and the gas holdup of the simulation results is 4.11%, with a prediction error of 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, with a prediction error of 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 methanol production by the liquid phase method. Based on this, the key factors and optimization methods affecting the stirring reaction process of methanol production by the liquid phase method can be further studied, providing data support and theoretical basis for the efficient and scientific design of the stirring reaction kettle.

[0082] In the above embodiments, by combining the gas-liquid-solid three-phase system into a gas-slurry two-phase system and modifying the macroscopic properties of the slurry phase based on the equivalent state parameters, while simplifying the model, the equivalent apparent physical properties that can reflect the influence of particles on the slurry phase are corrected, significantly reducing the dimension and computational amount of the multiphase flow model, enabling the efficient characterization of complex gas-liquid-solid interactions, thereby shortening the simulation time on the basis of ensuring the accuracy of the multi-physical field coupling simulation. It realizes the efficient and high-precision simulation of the stirring reaction process of CO2 hydrogenation to methanol by the liquid phase method, provides strong theoretical support and practical basis for the optimized design and industrial scale-up of the stirring reaction kettle, and effectively solves the deficiencies in the design, observation and optimization of the CO2 hydrogenation to methanol process by the liquid phase method.

[0083] In some embodiments, please refer to the appended Figure 2 , perform iterative solution on the coupled simulation model to obtain the simulation results of multiphase flow coupling, including:

[0084] S210. Apply boundary conditions to the coupled simulation model.

[0085] Among them, the boundary conditions are determined based on the operating conditions of the reaction process under actual operating conditions. Exemplarily, the boundary conditions of the fluid domain may include boundary type, inlet flow rate, inlet gas composition, and initial bubble diameter distribution, etc. It can be understood that in order to more accurately simulate the real situation, the inlet boundary of the gas distributor can be set as VelocityInlet, the inlet gas velocity is 8 m / s, the molar ratio of the inlet gas composition is set as CO2 / H2 = 1:3, the initial bubble diameter distribution is uniformly set as 4.5 mm, the outlet boundary is Degassing, and the remaining boundaries are set as Wall.

[0086] S220. Combine the boundary conditions and the coupled simulation model, and use the adaptive step size method to perform iterative solution on the coupled simulation model to obtain the simulation results.

[0087] Specifically, the above boundary conditions can be substituted into the corresponding equations of the coupled simulation model to make the boundary conditions an organic part of the coupled simulation model, ensuring that the model can reflect the external constraints of the actual reaction system.

[0088] Furthermore, during the iterative solution process, if the result does not converge, the time step size can be adjusted according to the adaptive step size method. Exemplarily, the initial time step size (such as s) and the maximum time step size (such as s), and determine the truncation error (less than 0.01) for judging step size adjustment. If the calculation result changes drastically, the time step size is automatically reduced to improve the calculation accuracy; if the calculation result is relatively stable, the time step size is automatically increased without exceeding the maximum time step size to improve the calculation efficiency.

[0089] Optionally, in the simulation, a report file for recording and storing key simulation data can also be obtained to monitor and evaluate the simulation process and results. Exemplarily, the report file can include gas holdup, reaction rate, and component concentration in the reactor, and the data is output every 50 time steps during the calculation process. By analyzing the gas holdup, the distribution of the gaseous phase in the system and the degree of participation in the reaction can be judged; the reaction rate directly reflects the speed of the reaction; the component concentration in the reactor 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, it is only necessary to repeatedly perform iterative calculations until the gas holdup and reaction rate tend to be stable, and at the same time the convergence error is less than 10 -5 , then the iteration can be stopped and the result can be output.

[0090] In the above embodiments, the precise setting of the boundary conditions ensures that the model matches the external constraints of the actual reaction system, and accurately simulates the actual reaction process of CO2 hydrogenation to methanol by the liquid phase method. The use of the adaptive step size method not only improves the calculation efficiency but also ensures the accuracy of the results. Finally, an efficient and accurate simulation of the stirring reaction process of CO2 hydrogenation to methanol by the liquid phase method is achieved, providing a strong theoretical basis and practical guidance for the optimized design and industrial scale-up of the reactor.

[0091] In some embodiments, please refer to the appendix Figure 3 , and construct a component transport model based on the equivalent state parameters of the equivalent multiphase flow model, including:

[0092] S310. Use the population balance model to calculate the interphase mass transfer coefficient based on the equivalent state parameters.

[0093] Among them, the interphase mass transfer coefficient is a physical quantity used to describe the mass transfer rate between different phases during the 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.

[0094] It should be understood that in multiphase reactors such as stirred tanks, there are significant differences in the bubble size distribution (such as coalescence and breakup dynamics). The model assuming a single bubble diameter cannot reflect the impact of this heterogeneity on mass transfer and reactions, resulting in inaccurate simulation results. By using the population balance model to describe the particle size distribution and its evolution process of the dispersed phase (such as bubbles, droplets, etc.), the contribution of bubbles of different sizes can be quantified by statistically analyzing the bubble size distribution, thereby improving the accuracy of the simulation results. 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 balance model, the population behavior can be converted into macroscopic parameters, making the calculation result of the interphase mass transfer coefficient more in line with the actual reaction situation. Specifically, the slurry phase can be set as the main phase and the gas phase as the secondary phase to establish a population balance model reflecting the bubble size characteristics. And set the bubble diameter grouping and define the breakup model and coalescence model. Exemplarily, the discrete method can be used to solve the population balance model, dividing the bubble size into multiple size subintervals, and integrating and solving the population balance equation within each size subinterval to obtain the number density function of all subintervals. The population balance equation can be specifically expressed as:

[0095]

[0096] In the formula, is the bubble density; is the volume fraction of the i-th size subinterval; is the velocity of the i-th size subinterval; is the size of the i-th size subinterval; represents the generation of bubble breakup within the i-th size subinterval; represents the disappearance of bubble breakup within the i-th size subinterval; represents the generation of bubble coalescence within the i-th size subinterval; represents the generation of bubble coalescence within the i-th size subinterval.

[0097] Optionally, to conform to the bubble size distribution in actual production, the bubble diameter range during the flow process can be set to 0.5 - 10 mm, divided into 20 groups in total, and the coalescence-breakup model can be described by the Luo-Luo model.

[0098] Furthermore, by solving according to the population balance 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, substituting the interphase contact area and the diffusion coefficient determined based on the equivalent state parameters into it, the interphase mass transfer coefficient can be calculated.

[0099] It should be understood that during the stirring reaction process of liquid-phase hydrogenation of CO2 to methanol, there is mass transfer between phases involving four components: CO2, H2, CH3OH, and H2O, and their diffusion coefficients are 3.2624×10 -8 、4.1075×10 -8 、2.8411×10 -8 、4.4605×10 -8 .

[0100] Furthermore, the expression of this process can be shown as follows:

[0101]

[0102] 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.

[0103] This formula establishes a calculation model of the mass transfer coefficient based on the diffusion coefficient, turbulent dissipation rate, and viscosity of the slurry phase by quantifying the effects of diffusion ability, turbulent intensity, and fluid resistance on mass transfer, and is used to accurately reflect the comprehensive action mechanism of various physical quantities in the mass transfer process between phases.

[0104] S320. Construct a component transport model according to the mass transfer coefficient between phases and the component conservation equation.

[0105] Among them, the component conservation equation is an equation used to describe the mass change, transport, and transfer process between different phases of each component in space and time during the reaction process.

[0106] It can be understood that the component conservation equation follows the principle of mass conservation and is an equation used to describe the mass change of components in time and space. Further, after determining the component conservation equation, the mass transfer coefficient between phases can be used as a link to incorporate mass transfer-related parameters, and finally a complete component transport model can be constructed. That is, in the liquid-phase hydrogenation reaction, first, the bubble characteristics are obtained through the population balance model to calculate the mass transfer coefficient between phases, and then the mass transfer coefficient between phases is substituted into the component conservation equation. Finally, the accurate simulation of the spatio-temporal distribution of each component in the reaction system can be achieved.

[0107] In the above embodiment, by using the population balance model to calculate the mass transfer coefficient between phases, the mass change, transport, and interphase transfer process of each component in the multiphase reaction system can be accurately described. And by constructing a component transport model according to the mass transfer coefficient between phases and the component conservation equation, the effects of processes such as convection, diffusion, chemical reaction, and mass transfer between phases can be comprehensively considered, so as to achieve accurate simulation and connect the microscopic particle behavior, mass transfer process, and macroscopic component transport of the spatio-temporal distribution of each component in the reaction system.

[0108] 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 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.

[0109] Specifically, the component conservation equation is an equation used to describe the mass change of a component in time and space, which may include convection of the component carried by fluid flow, the transport process of the component naturally migrating and diffusing from a high-concentration region to a low-concentration region, as well as terms such as reactions where the component is generated or consumed due to chemical reactions and mass transfer of the component between different phases (such as the gas phase and the slurry phase). 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 embedded as a source term into the component conservation equation. The interphase mass transfer coefficient is used to calculate the mass transfer source term (such as the transfer rate of the component at the phase interface), and it can be combined with parameters affecting 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, first, the interphase mass transfer coefficient is 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, and 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 transfers 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 influence of interphase mass transfer on the component distribution.

[0110] In the above embodiments, the component transport model constructed by the interphase mass transfer coefficient and the component conservation equation can comprehensively and accurately describe the mass change, transport, and interphase transfer process of each component in a multiphase reaction system. By combining the interphase mass transfer coefficient with parameters such as the interphase contact area and the component concentration difference, determining the mass flux of component interphase mass transfer, and embedding it as a source term into the component conservation equation, this model can not only depict the convection, diffusion, and reaction processes of the component in the gas phase and the slurry phase, but also quantify the influence of interphase mass 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.

[0111] In some embodiments, the component conservation equation is constructed in the following way: the component conservation equation is established based on the gas-phase state parameters and the liquid-phase state parameters.

[0112] Specifically, when establishing the component conservation equation, the influence of the flow, diffusion, and chemical reactions within each phase on each component needs to be considered, so that the constructed component conservation equation can be expressed as:

[0113]

[0114] where \(i = l\) represents the liquid phase and \(i = g\) represents the gas phase; represents the mass fraction of component \(j\) in phase \(i\); represents the diffusion coefficient of component \(j\) in phase \(i\); represents the mass generation or consumption caused by mass transfer between phases; represents the mass generation or consumption caused by chemical reactions.

[0115] This component conservation equation describes the mass conservation of component \(j\) in phase \(i\) in a multiphase flow system, considering the mass change rate of component \(j\) in phase \(i\), convective transport, diffusive transport, and mass changes caused by mass transfer between phases and chemical reactions.

[0116] In the above embodiments, the constructed component conservation equation can accurately describe the mass change law of each component in a multiphase flow system, comprehensively considering the influence of internal flow, diffusion, and chemical reactions in each phase on the component, providing a theoretical basis for the accurate modeling and simulation of complex multiphase flow systems, and improving the reliability and accuracy of simulation results.

[0117] In some embodiments, please refer to Appendix Figure 4 , and based on the state parameters of the gas phase, liquid phase, and particle phase at the initial stage of the reaction, construct an initial multiphase flow model for the gas-liquid-solid three-phase system, including:

[0118] S410. Determine the continuity equation, momentum equation, and energy equation based on the state parameters of the gas phase, liquid phase, and particle phase, and introduce the turbulent diffusion force equation and the initial drag force equation.

[0119] Similarly, the equations under the Euler-Euler system can be used to determine the basic control equations such as the continuity equation, momentum equation, and energy equation based on the state parameters of the gas phase, liquid phase, and particle phase. Exemplarily, the continuity equation can be expressed as:

[0120]

[0121] where \(i = l\) represents the liquid phase and \(i = g\) 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 quantity.

[0122] The continuity equation is used to describe the mass conservation of each phase. Its significance lies in that, at any moment during the reaction, the rate of change of the mass of a certain phase per unit volume, plus the sum of the mass fluxes of this phase through the control volume surface, is zero, ensuring that the mass of each phase in the reaction system will not be generated or disappear out of thin air.

[0123] The momentum equation can be expressed as:

[0124]

[0125] In the formula, i = l represents the liquid phase, and i = g represents the gas phase; is the volume fraction of the i-th phase; is the velocity of the i-th phase; is the density of the i-th phase; t is the time quantity; g is the acceleration due to gravity; P is the pressure inside the reactor; is the force between the gas-liquid phases, the stress-strain tensor term.

[0126] This momentum equation is used to describe the momentum conservation of each phase, taking into account factors such as gravity, pressure gradient, and interphase forces. It shows that the rate of change of the momentum of a certain phase per unit volume with respect to 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.

[0127] The energy equation can be expressed as:

[0128]

[0129] In the formula, i = l represents the liquid phase, and i = g represents the gas phase; represents the temperature of the i-th phase; represents the thermal conductivity of the i-th phase; represents the specific heat capacity at constant pressure of the i-th phase.

[0130] 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.

[0131] Exemplarily, the turbulent diffusion force equation can be expressed as:

[0132]

[0133] In the formula, represents the turbulent diffusion force; is the adjustable turbulent diffusion coefficient, with a value of 1.0, used to regulate the intensity of the turbulent diffusion effect and directly affect the overall level of the turbulent diffusion effect in the calculation as a preset parameter; is the intrinsic turbulent diffusion coefficient, used to characterize the diffusion property of the turbulence itself and reflect the essential ability of mass diffusion in the turbulent state; is the gas-liquid coupled turbulent diffusion coefficient, which focuses on correlating 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, and its value is 0.9; is the volume fraction of the gas phase; is the volume fraction of the liquid phase.

[0134] This turbulent diffusion force equation can describe the diffusion effect between the gas phase and the liquid phase in the turbulent state, quantify the enhancement effect of the turbulent effect on the mass, momentum, and energy transfer between phases, and thus accurately describe the interphase mixing and dispersion behavior under complex flow fields.

[0135] The initial drag force equation can be expressed as:

[0136]

[0137] In the formula, is the drag force; is the drag coefficient; is the characteristic diameter of the bubble; is the volume fraction of the gas phase; is the density of the liquid phase; is the velocity of the gas phase; is the velocity of the liquid phase.

[0138] This initial drag force equation is used to capture the resistance effect generated by the relative motion between phases, indicating that the turbulent diffusion force is related to factors such as the velocity difference between the two phases, turbulent characteristics, and the volume fraction of the phases, and reflects the influence of turbulence on the mass diffusion between the gas and liquid phases.

[0139] S420. Construct an interphase force model based on the turbulent diffusion force equation and the initial drag force equation.

[0140] 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 lies in describing the forces generated by each phase during the flow process due to turbulent diffusion or relative motion, etc., in order 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. Through the parameters in the equations, both the influence of the diffusion force caused by turbulence on the gas phase distribution and the constraint of the drag force on the relative motion between the gas and liquid are considered, and finally a unified interphase force model is formed to comprehensively calculate the total force between phases.

[0141] S430. Construct an initial multiphase flow model based on the continuity equation, momentum equation, energy equation, and interphase force model.

[0142] It is understandable that constructing an initial multiphase flow model requires integrating the continuity equation, momentum equation, energy equation, and interphase force model to systematically describe the flow, mass transfer, and energy transfer processes in a multiphase system. Specifically, the interphase interaction mechanism can be incorporated into the established basic conservation equations, that is, the interphase force model is embedded into the basic continuity equation, momentum equation, and energy equation, thereby forming a complete multiphase flow model to achieve systematic simulation of complex processes such as the flow, mass transfer, and heat transfer in a multiphase flow system.

[0143] In the above embodiments, by integrating the continuity equation, momentum equation, energy equation, and interphase force model, the flow, mass transfer, and energy transfer processes in a multiphase system are systematically described, and the complex interactions between phases in a 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.

[0144] In some embodiments, please refer to the appendix Figure 5 , and an interphase force model is constructed based on the turbulent diffusion force equation and the initial drag force equation, including:

[0145] S510. Dynamically correct the drag coefficient of the initial drag force equation according to the flow characteristics to obtain the corrected drag force equation.

[0146] It should be understood that in a real reaction process, due to factors such as local turbulent intensity changes, particle agglomeration or dispersion, bubble deformation, droplet breakup, particle-particle collisions, and enhanced momentum exchange due to turbulent pulsation, there are significant non-uniformities, dynamic evolution of multiphase interfaces, and non-linear interactions in the real flow. These flow characteristics will cause the drag coefficient of the initial drag force equation to deviate from the preset value in the simulation, thereby affecting the calculation accuracy of interphase momentum transfer in the simulation calculation. Therefore, the drag coefficient of the initial drag force equation can be dynamically corrected. Exemplarily, its expression can be as follows:

[0147]

[0148] In the formula, is the corrected drag coefficient; is the final velocity of the bubble in a stationary fluid; is the Froude number, that is, the ratio of gravity to inertial force;

[0149] This expression can be used to reflect the change in the drag coefficient compared to the static situation in a turbulent environment. Through this formula, the drag coefficient of the initial drag force equation can be corrected to more accurately calculate the drag between gas and liquid phases, thereby more precisely describing the flow characteristics of multiphase flow. Further, after obtaining the corrected drag coefficient, it can be substituted into the initial drag force equation to obtain the corrected drag force equation.

[0150] S520. Construct an interphase force model based on the turbulent diffusion force equation and the modified drag force equation.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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:

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] In some embodiments, the multiphase flow model establishment module 610 is further configured to determine the continuity equation, the momentum equation, and the energy equation based on the gaseous phase state parameters, the liquid phase state parameters, and the particulate phase state parameters, and introduce the turbulent diffusion force equation and the initial drag force equation; construct an interphase force model based on the turbulent diffusion force equation and the initial drag force equation; and construct a multiphase flow model based on the continuity equation, the momentum equation, the energy equation, and the interphase force model.

[0164] In some embodiments, the multiphase flow coupled simulation device 600 further includes an interphase force model establishment module, configured to dynamically correct the drag coefficient of the initial drag force equation according to the flow characteristics to obtain a corrected drag force equation; and construct an interphase force model based on the turbulent diffusion force equation and the corrected drag force equation.

[0165] For the specific limitations of a multiphase flow coupled simulation device, reference may be made to the limitations of a multiphase flow coupled simulation method in the foregoing text, which will not be elaborated herein. Each module in the above-mentioned multiphase flow coupled simulation device can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to the above-mentioned modules.

[0166] The multiphase flow coupled simulation device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0167] An embodiment of the present application further provides a computer device. The computer device may be a terminal, and its internal structure diagram may be as Figure 7As shown in the figure. 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 computer programs. The internal memory provides an environment for the operation of the operating system and computer programs 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 implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a simulation method for multiphase flow coupling. 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 covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0168] Those skilled in the art can understand that Figure 7 the structure shown in the figure is only a block diagram of some structures 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 some components, or have different component arrangements.

[0169] The embodiment of the present application also provides a computer-readable storage medium. The method according to the embodiment of the present application can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be processed by such software stored 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 memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, 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 the computer, the processor, or the hardware, the method shown in the above embodiment is implemented.

[0170] The embodiment of the present application provides a computer program product. The computer program product includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the 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.

[0171] A simulation method, device, computer device and storage medium for multiphase flow coupling illustrated in the above embodiments can be specifically 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, when describing the above device, it is divided into various units according to functions and described separately. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0172] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take 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 code.

[0173] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in one or more flows in the flowchart and / or one or more blocks in the block diagram. These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the functions specified in one or more flows in the flowchart and / or one or more blocks in the block diagram. These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more flows in the flowchart and / or one or more blocks in the block diagram.

[0174] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0175] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of this application, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically and clearly defined. It should also be noted that the term "comprises", "comprising", or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, commodity, or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity, or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, method, commodity, or device comprising the said element. Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. 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 refer to the partial description of the method embodiment.

[0176] The above is only the embodiment of this application and is not used to limit this application. For those skilled in the art, various changes and modifications can be made to this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the scope of the claims of this application.

[0177] Although the embodiments of this application are described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A simulation method for multi-phase 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 initial multiphase flow model includes an interphase force model for describing the mutual mechanical interaction between different phases in the multiphase flow system; wherein the interphase force model is formed by integrating the turbulent diffusion force equation describing the turbulent effect on the driving force of gas phase distribution and diffusion, and the modified drag equation for quantifying the resistance generated by the relative motion of gas and liquid; the modified drag equation is obtained by dynamically correcting the drag coefficient of the initial drag equation according to the flow characteristics using the Froude number; wherein the turbulent diffusion force equation is expressed in the following manner: In the formula, represents the turbulent diffusion force; is the adjusted turbulent diffusion coefficient with a value of 1.0; is the intrinsic turbulent diffusion coefficient; is the gas-liquid coupled turbulent diffusion coefficient; is the turbulent Prandtl number with a value of 0.9; is the gaseous phase volume fraction; is the liquid phase volume fraction; 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; wherein the equivalent state parameters include viscosity, density, specific heat capacity and diffusion coefficient; 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, wherein 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, wherein 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; Construct the component transport model according to the interphase mass transfer coefficient and the component conservation equation; wherein, the component conservation equation is an equation used to describe the mass change, transport, and transfer between different phases of each component in space and time during the reaction process.

4. The method according to claim 3, wherein The construction of the component transport model according to the interphase mass transfer coefficient and the component conservation equation includes: Based on the interphase mass transfer coefficient, determine the mass flux of component interphase mass transfer, and embed it 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, Construct the component conservation equation in the following way: Establish the component conservation equation based on the gaseous phase state parameters and the liquid phase state parameters.

6. The method according to claim 1, characterized in that, The construction of the initial multiphase flow model of the gas-liquid-solid three-phase system based on the gaseous phase state parameters, liquid phase state parameters, and particle phase state parameters at the initial stage of the reaction includes: Based on the gaseous phase state parameters, the liquid phase state parameters, and the particle phase state parameters, determine the continuity equation, momentum equation, and energy equation, and introduce the turbulent diffusion force equation and the initial drag force equation; Construct the interphase force model based on the turbulent diffusion force equation and the initial drag force equation; Construct the initial multiphase flow model based on the continuity equation, the momentum equation, the energy equation, and the interphase force model.

7. A simulation device for multiphase flow coupling, characterized in that, Applied to the liquid-phase CO2 hydrogenation to methanol process, the device includes: A multiphase flow model establishment module for constructing an initial multiphase flow model of a gas-liquid-solid three-phase system based on the gaseous phase state parameters, liquid phase state parameters, and particle phase state parameters at 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; the initial multiphase flow model includes an interphase force model for depicting the mutual mechanical interactions between different phases in the multiphase flow system; wherein, the interphase force model is formed by integrating the turbulent diffusion force equation that describes the turbulent effect on the gas-phase distribution diffusion driving force and the modified drag force equation that quantifies the resistance generated by the relative motion of the gas-liquid phases; the modified drag force equation is obtained by dynamically modifying the drag coefficient of the initial drag force equation according to the flow characteristics; wherein, the turbulent diffusion force equation is expressed in the following way: In the formula, represents the turbulent diffusion force; is the adjusted turbulent diffusion coefficient, with a value of 1.0; is the intrinsic turbulent diffusion coefficient; is the gas-liquid coupled turbulent diffusion coefficient; is the turbulent Prandtl number, with a value of 0.9; is the gaseous phase volume fraction; is the liquid phase volume fraction; A multiphase flow model equivalence module for merging and modifying 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; wherein, the equivalent state parameters include viscosity, density, specific heat capacity, and diffusion coefficient; A component transport model establishment module for constructing 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 gaseous 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, which is used to construct a coupled simulation model by using the equivalent multiphase flow model, the component transport model and the reaction model, and perform iterative solution on the coupled 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 methanol synthesis process by hydrogenation of CO2 and is used to simulate the reaction rate of CO2 hydrogenation; the simulation result is used to quantitatively analyze the stirring reaction process of methanol synthesis by hydrogenation of CO2 in the liquid phase.

8. A computer device, characterized in that, It includes: A memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, Computer instructions are stored on the computer-readable storage medium, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 6.

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