Coupling method, device, equipment and storage medium for industrial scale quasi-steady granular fluid multiphase system

Abstract

The application discloses a coupling method and device for an industrial-scale quasi-steady granular fluid multiphase system, equipment and a storage medium, relates to the technical field of computational fluid dynamics and particle discrete element coupling numerical simulation, and comprises the following steps: acquiring real particle information and cold-state simulation parameter information; inputting the real particle information into a predefined coarse-grained model to predict equivalent parameters of large particles after coarse-graining, and determining coarse-grained particle equivalent information; performing transient coupling simulation of a flow field state corresponding to particle motion and fluid change under the condition of ignoring heat transfer and chemical reaction based on the coarse-grained particle equivalent information and the cold-state simulation parameter information, and determining steady-state flow field simulation information; coupling and solving corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determining coupling result information; and controlling system operation regulation and control based on temperature field distribution information, component concentration distribution information and reaction conversion rate distribution information in the coupling result information.

Description

Technical Field

[0001] This application relates to the field of computational fluid dynamics and particle discrete element coupled numerical simulation technology, and in particular to coupling methods, devices, equipment and storage media for industrial-scale quasi-steady-state particle fluid multiphase systems. Background Technology

[0002] In the fields of metallurgy, chemical industry, and energy, industrial particle reactors (such as hydrogen-based vertical shaft furnaces and rotary kilns) involve complex multi-physical field coupling processes, including gas-solid two-phase flow, heat transfer, and chemical reactions. Accurately simulating particle movement, fluid distribution, and reaction processes within such devices has significant engineering application value for guiding reactor design, optimizing process parameters, and achieving energy conservation and emission reduction.

[0003] Currently, existing approaches treat both the gas phase and the particulate phase as a continuous, interpenetrating medium, or use CFD to simulate the continuous gas phase and DEM to accurately track the motion and forces of each discrete particle. However, these approaches have significant shortcomings when applied to industrial-scale reactors. Because simplifying the discrete particulate phase into a continuous medium relies heavily on empirical models, they cannot characterize the real particle-particle-particle-particle collision behavior and wall collision behavior. This results in severely insufficient prediction accuracy for processes such as particle motion, mixing, and local porosity distribution. While coupling CFD and DEM offers high accuracy, the computational resources required are enormous when dealing with a large number of particles and the need to simultaneously solve lengthy heat transfer and chemical reaction processes, making it completely impractical for engineering applications. Therefore, how to more efficiently and accurately simulate long-term reaction processes in industrial-scale particulate reactors based on coarse-graining and stepwise coupling has become an urgent problem to be solved.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this application is to provide a coupling method, apparatus, equipment, and storage medium for industrial-scale quasi-steady-state particulate fluid multiphase systems, aiming to solve the technical problem of how to more efficiently and accurately simulate long-term reaction processes in industrial-scale particulate reactors based on coarse-graining and stepwise coupling.

[0006] To achieve the above objectives, this application proposes a coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems, the method comprising:

[0007] Obtain real particle information and cold-state simulation parameter information;

[0008] Based on the real particle information, the predefined coarsening model is input to predict the equivalent parameters of the coarsened large particles and determine the equivalent information of the coarsened particles.

[0009] Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameter information, the flow field state corresponding to particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction, so as to determine the steady-state flow field simulation information.

[0010] Based on the steady-state flow field simulation information, the corresponding heat transfer and chemical reaction equations are coupled and solved to determine the coupling result information;

[0011] The system operation and regulation are based on the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information.

[0012] In one embodiment, the step of predicting the equivalent parameters of the coarse-grained large particles based on the real particle information input into a predefined coarsening model, and determining the equivalent information of the coarse-grained particles, includes:

[0013] Based on the real particle information, the predefined coarsening model is input to predict the coarsening amplification ratio that satisfies the real particle flow characteristics, and the coarsening amplification ratio information is determined.

[0014] Based on the coarsening amplification ratio information, the equivalent parameters of the corresponding coarsened large particles are calculated to obtain the coarsened particle equivalent information. The coarsened particle equivalent information includes agglomerated particle size information, mass information, volume information, time step information, contact stiffness information, contact force information, and gravity information.

[0015] In one embodiment, the cold simulation parameter information includes geometric model information, mesh generation information, and boundary condition information;

[0016] Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameters, the steps for determining the steady-state flow field simulation information by performing transient coupled simulation of the flow field state corresponding to particle motion and fluid changes under the condition of neglecting heat transfer and chemical reaction include:

[0017] Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameter information, particle motion parameters and fluid variation parameters are determined. The particle motion parameters include particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid force on particles, gravity, tangential contact torque, and rotational torque. The fluid variation parameters include fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor, and momentum source term.

[0018] Based on the particle motion parameters and the fluid change parameters, the flow field state corresponding to particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction to determine transient flow field information.

[0019] Based on the transient flow field information, the average flow field parameter fluctuation amplitude within a predefined time is monitored to obtain steady-state flow field simulation information, which includes gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rate, and bed height.

[0020] In one embodiment, the step of performing transient coupling simulation of the flow field state corresponding to particle motion and fluid change based on the particle motion parameters and the fluid change parameters, under the condition of neglecting heat transfer and chemical reaction, to determine the transient flow field information includes:

[0021] Based on the fluid velocity, velocity gradient, pressure gradient, porosity, fluid force tensor, and momentum source term in the fluid change parameters, the fluid phase flow field at the current moment is calculated, and the flow field update information is determined.

[0022] Based on the fluid phase flow field information and the particle motion parameters such as particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, gravity, tangential contact torque, and rotational torque, the motion state of the particles is updated to determine the updated particle information;

[0023] The momentum source term of the particle's reaction with the fluid, the solid phase velocity, and the porosity in the particle update information are fed back to the fluid phase flow field for alternating iterative coupling calculations until the predefined convergence conditions are met, thus obtaining transient flow field information.

[0024] In one embodiment, the step of coupling and solving the corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determining the coupling result information, includes:

[0025] Based on the steady-state flow field simulation information, the average data of transient fluid flow field within a predefined time period will be extracted to determine the steady-state flow field parameter information, which includes fluid velocity field, velocity gradient field, pressure field, pressure gradient field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area, and turbulence parameter field.

[0026] Based on the steady-state flow field parameter information, generate corresponding fixed flow field file information;

[0027] Based on the fixed flow field file information, the heat transfer and chemical reaction equations under the corresponding steady-state background flow field are coupled and solved to determine the coupling result information of heat transfer source terms and component source terms.

[0028] In one embodiment, the step of coupling the heat transfer and chemical reaction equations under the corresponding steady-state background flow field based on the fixed flow field file information to determine the coupling result information of the heat transfer source term and the component source term includes:

[0029] Based on the fixed flow field file information, the particle specific heat capacity, gas phase specific heat capacity, particle thermal conductivity, gas phase thermal conductivity, and particle-gas phase heat transfer coefficient in the heat transfer coupling equation under the corresponding steady-state background flow field are solved to determine the heat transfer coupling parameter information.

[0030] Based on the heat transfer coupling parameter information, the heterogeneous surface reaction parameters and homogeneous gas phase reaction parameters in the chemical reaction coupling equation under the corresponding steady-state background flow field are solved to determine the chemical reaction coupling parameter information and heat source term;

[0031] The heat source term is fed back to the heat transfer coupling equation and the chemical reaction coupling equation to iteratively update the heat transfer coupling parameter information and the chemical reaction coupling parameter information until the predefined convergence condition is met, thereby obtaining the coupling result information of the heat transfer source term and the component source term.

[0032] In one embodiment, the step of solving the heterogeneous surface reaction parameters and homogeneous gas phase reaction parameters in the chemical reaction coupling equation under the corresponding steady-state background flow field based on the heat transfer coupling parameter information, and determining the chemical reaction coupling parameter information, includes:

[0033] Using the component transport algorithm of homogeneous gas phase reaction and the heat transfer coupling parameter information, the heterogeneous surface reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved to obtain the heterogeneous surface reaction parameter information in the chemical reaction coupling parameter information. The heterogeneous surface reaction parameter information includes mass fraction, effective diffusion coefficient of component, component generation rate and component consumption rate.

[0034] The homogeneous gas phase reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved using the reaction kinetics algorithm and the heat transfer coupling parameter information. The homogeneous gas phase reaction parameter information includes interfacial chemical reaction resistance, diffusion resistance, gas mass transfer resistance, concentration, equilibrium concentration, pressure, solid phase temperature, and gas phase constant.

[0035] Furthermore, to achieve the above objectives, this application also proposes a coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system, the coupling device for the industrial-scale quasi-steady-state particulate fluid multiphase system comprising:

[0036] The acquisition module is used to acquire real particle information and cold simulation parameter information;

[0037] The processing module is used to predict the equivalent parameters of the coarse-grained large particles based on the input of the real particle information into a predefined coarsening model, and to determine the equivalent information of the coarse-grained particles.

[0038] The execution module is also used to perform transient coupling simulation of the flow field state corresponding to particle motion and fluid change based on the equivalent information of the coarse particles and the cold simulation parameter information, under the condition of ignoring heat transfer and chemical reaction, to determine the steady-state flow field simulation information.

[0039] The execution module is used to couple and solve the corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determine the coupling result information;

[0040] The execution module is also used to control the operation of the system based on the temperature field distribution information, component concentration distribution information and reaction conversion rate distribution information in the coupling result information.

[0041] Furthermore, to achieve the above objectives, this application also proposes a coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system. The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the coupling method for an industrial-scale quasi-steady-state particulate fluid multiphase system as described above.

[0042] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems as described above.

[0043] One or more technical solutions proposed in this application have at least the following technical effects:

[0044] This embodiment proposes a coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale. The method acquires real particle information and cold-state simulation parameters. Based on the real particle information, a predefined coarsening model is input to predict the equivalent parameters of the coarsened large particles, determining the equivalent information of the coarsened particles. Based on the coarsened particle equivalent information and the cold-state simulation parameters, a transient coupling simulation of the flow field state corresponding to particle motion and fluid changes is performed, neglecting heat transfer and chemical reactions, to determine the steady-state flow field simulation information. Based on the steady-state flow field simulation information, the corresponding heat transfer and chemical reaction equations are coupled and solved to determine the coupling result information. Based on the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information, the system operation and regulation are controlled. This application integrates a coarse-grained model with a step-by-step coupling strategy. By constructing a coarse-grained model based on real particle information, the number of particles to be calculated is greatly reduced. The coarse-grained particle system is then subjected to transient simulation using cold-state simulation parameters to obtain flow field information under statistical steady state. This steady-state flow field is then solidified as a background field. Within this framework, the coupling parameters of heat transfer and chemical reaction are solved to obtain the distribution information of temperature field, component concentration, and reaction conversion rate, which can be used to optimize the operation and control of industrial reactors. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a simplified flowchart illustrating the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, as described in this application.

[0048] Figure 2 This is a schematic flowchart of Embodiment 1 of the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, as provided in this application.

[0049] Figure 3 This is a geometrical diagram and a computational domain mesh diagram of a hydrogen-based vertical shaft furnace reactor, which is the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems proposed in this application.

[0050] Figure 4 This is a schematic diagram comparing the dynamic packing angle of particles before and after coarsening in the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, as described in this application.

[0051] Figure 5 This is a schematic flowchart of Embodiment 2 of the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, provided in this application.

[0052] Figure 6 This is a schematic diagram of the dynamic stable flow field of the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, as described in this application.

[0053] Figure 7 This is a schematic diagram of the steady-state calculation results of heat transfer and chemical reaction of the coupled method for industrial-scale quasi-steady-state particulate fluid multiphase systems in this application;

[0054] Figure 8 This is a schematic diagram of the module structure of the coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system according to an embodiment of this application;

[0055] Figure 9 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the coupling method for an industrial-scale quasi-steady-state particulate fluid multiphase system in the embodiments of this application.

[0056] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0057] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0058] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0059] The main solution of this application embodiment is as follows: Obtain real particle information and cold-state simulation parameter information; based on the real particle information, input a predefined coarsening model to predict the equivalent parameters of the coarsened large particles, and determine the equivalent information of the coarsened particles; based on the equivalent information of the coarsened particles and the cold-state simulation parameter information, perform transient coupling simulation of the flow field state corresponding to particle motion and fluid change under the condition of ignoring heat transfer and chemical reaction, and determine the steady-state flow field simulation information; based on the steady-state flow field simulation information, couple and solve the corresponding heat transfer and chemical reaction equations to determine the coupling result information; based on the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information, control system operation and regulation.

[0060] In this embodiment, for ease of description, the following description focuses on identifying the coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system.

[0061] Existing technologies have significant shortcomings when applied to industrial-scale reactors. By simplifying discrete particulate phases into continuous media, they rely heavily on empirical models and cannot characterize the real particle-particle-particle-particle collision behavior and wall collision behavior. This results in severely insufficient prediction accuracy for processes such as particle motion, mixing, and local porosity distribution. While coupling CFD and DEM offers high accuracy, the computational resources required are enormous when dealing with a large number of particles and the need to simultaneously solve lengthy heat transfer and chemical reaction processes, making it completely impractical for engineering applications.

[0062] This application provides a solution, such as Figure 1 As shown, Figure 1 This is a simplified flowchart of the coupling method for quasi-steady-state particulate fluid multiphase systems at the industrial scale, as described in this application. By constructing a coarse-grained model, real particles are equivalent to aggregated particles to reduce the computational scale. Transient cold-state simulations with bidirectional CFD-DEM coupling are carried out based on the coarse-grained particles to obtain flow field information when particle motion and fluid flow reach statistical steady state. By extracting and statistically analyzing the key parameters of this steady-state background flow field, these data are solidified into the CFD calculation framework. Using the solidified steady-state flow field as the background field, the coupling calculations of steady-state heat transfer and chemical reaction are performed independently, thereby outputting results such as temperature field, component concentration, and reaction conversion rate, achieving efficient and accurate multiphysics simulation of industrial-scale reactors.

[0063] As can be seen from the above embodiments, this application integrates a coarse-grained model with a step-by-step coupling strategy. It constructs a coarse-grained model based on real particle information to significantly reduce the number of particles to be calculated. It combines cold-state simulation parameters to perform transient simulation on the coarse-grained particle system to obtain flow field information under statistical steady state. This steady-state flow field is then solidified as a background field. Within this framework, the coupling parameters of heat transfer and chemical reaction are solved to obtain the distribution information of temperature field, component concentration and reaction conversion rate, which is used to optimize the operation and control of industrial reactors.

[0064] Based on this, embodiments of this application provide a coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, referring to... Figure 2 , Figure 2 This is a schematic flowchart of the first embodiment of the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems in this application.

[0065] In this embodiment, the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems includes steps S10-S50:

[0066] Step S10: Obtain real particle information and cold simulation parameter information;

[0067] It should be noted that the real particle information refers to the physical property parameters of the actual solid materials involved in the industrial particle reactor to be simulated, such as the physical property parameters of iron ore powder or catalyst particles in a hydrogen-based shaft furnace or rotary kiln. The cold simulation parameter information refers to the control parameters corresponding to the geometric model, boundary conditions, and mesh division that need to be set when performing cold flow field simulation without considering heat transfer and chemical reaction.

[0068] It is understood that the real particle information may include particle geometry, particle physical and mechanical properties, and particle packing and flow characteristics. The particle geometry may include the actual particle size distribution and particle shape (sphericity) of the original particles. The particle physical and mechanical properties may include the actual particle density, Young's modulus, Poisson's ratio, collision recovery coefficient between particles and between particles and the wall, static friction coefficient, and rolling friction coefficient. The particle packing and flow characteristics may be the particle packing angle measured experimentally. The cold simulation parameter information may include geometric and mesh information, boundary condition information, initial condition information, and mesh generation and solution control parameter information. The geometric and mesh information may be the dimensions and structural features (such as inlet and outlet locations and dimensions) of the three-dimensional geometric model of the industrial reactor, as well as the calculation parameters based on this geometric model. The mesh is calculated, and the boundary condition information can be the velocity or flow rate of the gas phase inlet, the gas phase composition at the inlet (such as the mixing ratio of H2, CO, and N2), the pressure conditions at the outlet, the inlet generation rate of the particulate phase, the initial position and velocity distribution, and the particle removal conditions at the outlet. The initial condition information can be the initial velocity and pressure field of the fluid in the computational domain at the start of the simulation, as well as the initial filling state of the particles (such as bed height, initial position, and velocity). The mesh generation and solution control parameter information can be the selected gas-solid phase momentum exchange model (such as the Wen-Yu drag model), particle contact model (such as the Hertz-Mindlin (no-slip) model), turbulence model (such as the standard k-ε model), etc. In addition, it also includes solution control parameters such as the time step of CFD and DEM, the total simulation duration, and the data sampling and monitoring frequency.

[0069] In a specific embodiment, the real particle information can be obtained through laboratory measurements, while the cold-state simulation parameters can be set according to the actual operating conditions of the industrial reactor to be simulated, for example, such as... Figure 3 As shown, Figure 3This document presents a geometrical schematic diagram and computational domain meshing diagram of a hydrogen-based vertical shaft furnace reactor, representing the coupling method for quasi-steady-state particulate fluid multiphase systems at the industrial scale, as described in this application. The simulation object is a simplified hydrogen-based vertical shaft furnace with a diameter of 4.2 m and a height of 9.1 m. The reduced particles inside the furnace are iron ore powder particles. In this case, the actual particle size is approximately 0.008 m, the coarsened particle size is 0.064 m, and the particle density is 7850 kg / m³. 3 The original stiffness is 1×10 8 Pa et al., the cold-state simulation parameters can be generated using a structured mesh. The boundary conditions for the cold-state simulation are set as follows: the gas phase is a mixture of H2, CO, and N2 (hydrogen volume fraction 50%, carbon monoxide volume fraction 30%, nitrogen volume fraction 20%), the gas flow rate is 898 Nm³ / min, the steady-state operation duration of the furnace in industrial production is 24 h, and the particles are continuously added from the top inlet and discharged from the bottom outlet. Simultaneously, the properties of the pellets are set in the DEM, including density, Poisson's ratio, and coefficient of restitution. The interphase momentum exchange uses the Wen-Yu model to calculate the drag force, and the Hertz-Mindlin model to handle particle contact. The CFD time step is set to 0.001 s, and the DEM time step is set to 1.94 × 10⁻⁶. -5 The time step (s) is determined by the subsequent coarse-grained model and is only an example here. The total simulation time is 120 seconds. TF-QFLUX and TF-DEM are used for cold-state bidirectional coupling to monitor the process of the flow field reaching statistical steady state. During the simulation, the average flow field is calculated every 1 second to monitor the fluctuation amplitude of key parameters, such as furnace pressure distribution, gas outlet flow rate, particle bed pressure drop, and particle inlet and outlet rates. When the fluctuation amplitude of each parameter is stable below 5% after 100 seconds of simulation, it is determined that the flow field has reached statistical steady state, the transient coupling is stopped, and the result data is retained.

[0070] In a specific embodiment, the real particle information ensures that the coarse-grained model can accurately reflect the mechanical and flow characteristics of the original material, while the cold simulation parameter information is used to provide the correct computational framework and boundary constraints to accurately simulate particle-fluid interactions, thereby avoiding distortion of simulation results due to errors in the basic input data.

[0071] Step S20: Based on the real particle information, input a predefined coarsening model to predict the equivalent parameters of the coarsened large particles and determine the equivalent information of the coarsened particles.

[0072] Understandably, the coarse-grained model is a particle-scale scaling method used to reduce the computational scale of Discrete Element Model (DEM). While ensuring that the macroscopic flow characteristics of the particle system (such as packing characteristics, flow regime characteristics, and porosity distribution) remain similar to the original real particle system, several physically existing and contacting original particles are aggregated into a virtual aggregate particle, i.e., a coarse-grained particle, through mathematical equivalence. By introducing a coarse-grained scaling factor, the geometric size, mechanical parameters, and computation time step of the original particles are systematically scaled. Thus, while ensuring the simulation accuracy, the total number of particles involved in the calculation is reduced by 1 to 3 orders of magnitude, making the long-term process simulation of hundreds of millions of particles in industrial-scale reactors feasible in engineering.

[0073] In a specific embodiment, based on the real particle information input into a predefined coarsening model, the coarsening amplification ratio that satisfies the flow characteristics of real particles is predicted to determine the coarsening amplification ratio information. This is calculated by inputting the particle size distribution, density, packing characteristics, and flow characteristics of real particles in an industrial-scale particle reactor into the coarsening particle model. The coarsening amplification ratio is used to agglomerate several actual particles into a single coarsening particle, while simultaneously amplifying the interparticle contact forces and gravity to ensure that the mechanical properties of the coarsening system match those of the real system. For example, if the real particle size is approximately 0.008 μm, and the coarsening ratio L is 4, the particle size... ,quality ,volume Equivalent scaling up proportionally is represented as:

[0074]

[0075]

[0076]

[0077] in, For coarse-grained particle size, The original particle size, For coarse-grained ratio, For coarse particle quality, Original particle mass For coarse-grained particle volume, This represents the original particle volume.

[0078] To ensure equivalent contact forces between particles, the time step of coarse-grained particles... Contact stiffness Contact force Scaling according to the coarse-grained ratio is represented as:

[0079]

[0080]

[0081]

[0082] in, , , These represent the time step, contact stiffness, and contact force of the coarse-grained particles, respectively. , , These represent the time step, contact stiffness, and contact force of the actual particles, respectively. This is the magnification ratio.

[0083] Gravity of coarse particles The equivalent formula is expressed as:

[0084]

[0085] in, The gravity of the coarse-grained particles; This represents the actual gravity of the particles.

[0086] Based on the coarsening scale-up information, the equivalent parameters of the corresponding coarsened large particles are calculated to obtain the equivalent information of the coarsened particles. This equivalent information includes agglomerated particle size, mass, volume, time step, contact stiffness, contact force, and gravity information. Specifically, it is based on the calculated particle size... ,quality ,volume Time step Contact stiffness Contact force and gravity The equivalent information of the coarsened particles is obtained. At this point, the actual particle size is approximately 0.008 μm. With a coarsening ratio L of 4, the particle size after coarsening is 0.032 μm. The gravity of the coarsened particles is 64 times that of the original particle size. The original stiffness of the particles is 1 × 10⁻⁶. 8 Pa, the magnified particle stiffness is 4 × 10⁻⁶. 8 The original time step in the Pa, DEM calculation is 4.85 × 10⁻⁶. -6 The magnified time step is 1.94 × 10 s. -5 In the solution process, the forces between particles are amplified by a factor of 16. Dynamic angle of repose experiments are used to verify the flow similarity between the coarse-grained system and the real system (ensuring constraints such as angle of repose deviation ≤5% and volume fraction distribution deviation ≤8%). This ensures that the coarse-grained model accurately reproduces the macroscopic flow characteristics of the real particle system while significantly reducing the computational scale (reducing the number of particles by 1-3 orders of magnitude). Figure 4 As shown, Figure 4 This is a schematic diagram comparing the dynamic packing angle of particles before and after coarsening in the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, as described in this application. The dynamic packing angle is calculated under the original particle size and parameters, and the particles and dynamic packing angle after coarsening are also calculated. It can be found that the packing results are similar and satisfy the constraint conditions.

[0087] In one feasible implementation, step S20 may include steps A11-A12:

[0088] Step A11: Based on the real particle information, input the predefined coarsening model to predict the coarsening amplification ratio that satisfies the real particle flow characteristics, and determine the coarsening amplification ratio information.

[0089] It should be noted that the coarse-grained scaling ratio information is a dimensionless multiplier used to systematically scale the geometric dimensions, mechanical parameters, and computation time steps of the original particles to significantly reduce the computational scale while ensuring that the macroscopic flow characteristics of the particle system are similar to those of the real particle system. By calculating and predicting the particle size, density, packing characteristics, and flow characteristics of the real particles, several real particles are equivalently aggregated into a single aggregated particle. The mass, volume, and gravity of the particles are amplified by L³, the particle size, time step, and contact stiffness are amplified by L, and the contact force between particles is amplified by L². This ensures that the coarse-grained particle system can accurately reproduce the flow and collision behavior of the real particle system while significantly reducing the number of computational particles.

[0090] Step A12: Based on the coarsening amplification ratio information, calculate the corresponding equivalent parameters of the coarsened large particles to obtain the coarsened particle equivalent information. The coarsened particle equivalent information includes agglomerated particle size information, mass information, volume information, time step information, contact stiffness information, contact force information, and gravity information.

[0091] It should be noted that the equivalent information of the coarse-grained particles is a parameter obtained by converting the real particle information, which is used to uniquely describe the physical state and behavior of each aggregated particle, and characterizes the geometric, mechanical and dynamic properties of each particle in the coarse-grained particle system.

[0092] It is understood that the aggregated particle size information is the equivalent diameter after the coarsening and refining of the particles; the mass information is the mass of the aggregated particles, scaled by the cubic ratio of the particle size to ensure that the density remains unchanged and correctly reflects the effects of inertia and gravity; the volume information is the volume of the aggregated particles, also scaled by the cubic ratio, used to calculate the volume fraction of the particles in the fluid mesh; the time step information is the time step of the discrete element method for this aggregated particle system, and a larger time step directly improves the computational efficiency; the contact stiffness information is the contact stiffness between the aggregated particles, used to calculate the elastic deformation and contact force during collision; the contact force information is the normal and tangential contact force generated by the aggregated particles during the collision, which is a key force term in the particle motion equation; and the gravity information is the gravity acting on the aggregated particles as a volume force acting on each particle.

[0093] Step S30: Based on the equivalent information of the coarse-grained particles and the cold simulation parameter information, the flow field state corresponding to the particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction, so as to determine the steady-state flow field simulation information.

[0094] It should be noted that the steady-state flow field simulation information is a set of parameters obtained by averaging transient flow field data over a characteristic time period after the particle-fluid coupling reaches a statistical steady state.

[0095] It is understandable that the flow field state corresponding to particle motion and fluid change is an instantaneous dynamic physical field inside an industrial particle reactor (such as a hydrogen-based vertical shaft furnace or rotary kiln), which is composed of a moving discrete particle phase and a continuous fluid phase (gas or liquid). The two phases interact strongly through momentum exchange. This flow field state describes the complex coupling process at each moment in which the fluid (such as reducing gas) flows and carries and propels the particles, and the particles (such as ore) move, collide, and accumulate, and in turn hinder and guide the fluid flow.

[0096] In a specific embodiment, particle motion parameters and fluid variation parameters are determined based on the equivalent information of the coarse-grained particles and the cold-state simulation parameter information. The particle motion parameters include particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid-particle force, gravity, tangential contact torque, and rotational torque. The fluid variation parameters include fluid velocity, velocity gradient, pressure gradient, porosity, fluid-related force tensor, and momentum source term. Based on the fluid velocity, velocity gradient, pressure gradient, porosity, fluid-related force tensor, and momentum source term in the fluid variation parameters, the fluid phase flow field at the current moment is calculated to determine the flow field update information; that is, the momentum conservation equation and continuity equation of the fluid are solved, wherein the fluid phase control equation is expressed as:

[0097]

[0098]

[0099] in, For fluid velocity, For fluid velocity, For the pressure gradient, This represents the volume fraction of fluid within a fluid unit. It is the stress tensor of the fluid phase.

[0100] and The momentum source term is caused by particulate phase interaction, and its calculation method is expressed as:

[0101]

[0102] in, Where N is the volume of the fluid unit, and N is the number of particles in the fluid unit. It is the force exerted by the fluid on particle i.

[0103] Based on the particle motion parameters, including particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid-particle force, gravity, tangential contact torque, and rotational torque, a transient simulation of the corresponding flow field state is performed to obtain the particle phase flow field solution parameter information. This involves solving the particle motion equations and contact mechanics equations, neglecting heat transfer and chemical reactions, and focusing on obtaining flow field data reflecting the statistical laws of real particle motion. The particle phase motion equation is expressed as:

[0104]

[0105]

[0106] in, For particle mass, For rotational inertia, Indicates particle velocity. Angular velocity. The forces acting on the particles include the normal force generated by collisions. and tangential force The force exerted by the fluid on the particles Its own gravity . The torque generated by the tangential contact force. This refers to the rotational torque caused by the asymmetrical contact pressure distribution.

[0107] The forces exerted by a fluid on particles mainly include drag and lift. Drag is calculated as follows:

[0108]

[0109] in, The particle diameter is It's particle velocity. It is the phase momentum exchange coefficient.

[0110] Based on the transient flow field information, the fluctuation of average flow field parameters within a predefined time period is monitored to obtain steady-state flow field simulation information. This steady-state simulation information includes gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rates, and bed height. Specifically, during the simulation, the average flow field over a specified time interval is calculated, and changes in flow field parameters are monitored until the fluctuation of flow field parameters falls below a preset threshold (≤5%). At this point, the macroscopic motion state of the particles and the fluid flow field are considered to have reached a statistically steady state. The flow field parameters include gas phase outlet flow rate, pressure at key locations, particle mass flow rates at the inlet and outlet, and particle bed height. Simultaneously, turbulent parameter fields can be extracted to provide a basis for subsequent heat transfer and reaction simulations.

[0111] In one feasible implementation, step S30 may include steps B11 to B13:

[0112] Step B11: Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameter information, determine the particle motion parameters and fluid variation parameters. The particle motion parameters include particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid force on particles, gravity, tangential contact torque, and rotational torque. The fluid variation parameters include fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor, and momentum source term.

[0113] It should be noted that the particle motion parameters can be variables required to characterize the instantaneous mechanical state of each coarse-grained particle within the Discrete Element Method (DEM) framework. These include, for example, the translational motion of the particle (such as particle mass and velocity vector) and rotational motion (such as moment of inertia and angular velocity), as well as the mechanical causes of these motion changes, including the normal and tangential contact forces generated by particle collisions, the interphase forces such as the drag force of the fluid on the particles, gravity, and the tangential torque and rotational torque caused by the contact forces. These are used to calculate the spatial distribution and flow behavior of the particle system within the computational domain. The fluid variation parameters, on the other hand, are variables required to describe the instantaneous state of the fluid phase in the Eulerian grid within the Computational Fluid Dynamics (CFD) framework. These are macroscopic flow fields solved based on the continuity equation and the momentum conservation equation. Examples include, for example, the fluid velocity vector, pressure gradient, porosity (characterizing the proportion of space occupied by the fluid within the grid), the fluid corresponding force tensor, and the momentum source term characterizing the reaction of the particles with respect to the fluid. This momentum source term is calculated by dividing the sum of the fluid forces acting on all particles within the grid by the grid volume.

[0114] Step B12: Based on the particle motion parameters and the fluid change parameters, perform transient coupling simulation of the flow field state corresponding to particle motion and fluid change under the condition of ignoring heat transfer and chemical reaction to determine the transient flow field information;

[0115] Understandably, transient coupling simulation is a step-by-step solution of a gas-solid two-phase system in the time domain with discrete time steps, either explicitly or implicitly. The purpose is to realistically capture the dynamic interaction behavior and flow field evolution of the particulate phase and fluid phase at each moment, and to reproduce the complete process of the flow field evolving from the initial state to dynamic equilibrium.

[0116] In one feasible implementation, step B12 may include steps C11-C13:

[0117] Step C11: Based on the fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor, and momentum source term in the fluid change parameters, calculate the fluid phase flow field at the current moment and determine the flow field update information;

[0118] It should be noted that the flow field update information is a set of data obtained by solving the governing equations of the fluid phase using the fluid change parameters at the current moment during the transient coupled simulation process based on coarse-grained particle equivalent information and cold-state simulation parameter information. This data is used to describe the latest state of the fluid phase at each spatial location in the computational domain at that moment.

[0119] It is understood that the fluid velocity is the instantaneous velocity vector of a fluid element in space, describing the speed and direction of fluid flow in three dimensions, and is a fundamental physical quantity determining the fluid's convective transport capacity. The velocity gradient is the rate of change of fluid velocity in various spatial directions, characterizing the uniformity of velocity distribution and shear deformation intensity in the flow field, directly determining the deformation rate and viscous stress of the fluid element, and regulating interphase momentum exchange by influencing the flow state around the particles. The pressure gradient is the rate of change of pressure per unit spatial distance, serving as the volume force driving fluid motion, characterizing the effect of pressure non-uniformity on fluid acceleration or deceleration. The porosity is defined in any computational network. The volume ratio of fluid within a grid cell characterizes the local phase distribution of the gas-solid two-phase system, directly affecting the resistance experienced by the fluid and the momentum exchange intensity between the two phases. The fluid-related force tensor describes the stress state generated on the surface of the fluid micro-element due to viscous deformation, characterizing the viscous effect of the fluid, which may include normal stress and tangential stress. In flow, it manifests as a viscous force that hinders fluid deformation. The momentum source term is the reaction force source of particles relative to the fluid phase, obtained by summing the fluid forces acting on all particles within the grid cell and dividing by the cell volume. As an additional force term in the fluid momentum equation, it accurately characterizes the consumption or contribution of particle presence to the flow field momentum and is the core coupling variable connecting the particle phase and the fluid phase.

[0120] Step C12: Based on the fluid phase flow field information and the particle motion parameters including particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, gravity, tangential contact torque, and rotational torque, update the particle motion state and determine the particle update information.

[0121] It should be noted that the particle update information is a set of parameters used to describe the latest motion and mechanical state of all particles at the current moment, obtained by solving the translational and rotational motion equations for each coarsened particle during the transient coupling simulation based on the fluid phase flow field information and the particle motion parameters.

[0122] It is understood that the particle mass is the physical mass of each coarsened particle, determining the magnitude of the particle's inertia; the moment of inertia is a measure of the particle's inertia when rotating around its center of mass, depending on the particle's mass distribution; the particle velocity describes the instantaneous speed and direction of the particle's center of mass in space; the angular velocity describes the instantaneous speed and direction of the particle's rotation around its own center of mass; the collision normal force is the elastic or elastoplastic interaction force generated along the normal direction at the contact point when two particles or a particle comes into contact with a wall, used to resist mutual embedding and determine the rebound behavior after the collision; the collision tangential force is the frictional force generated along the tangential direction at the contact point, used to resist the relative... Sliding affects the momentum exchange and energy dissipation of tangential motion. The fluid-particle force is the total force exerted by the fluid phase on a single particle, which may include drag (resistance) and possible lift, pressure gradient force, etc., thereby realizing momentum exchange between the gas and solid phases. Gravity, as a volume force generated by the Earth's gravity, always acts vertically downward on the particle, and its magnitude is equal to the product of the particle's mass and gravitational acceleration. The tangential contact torque is the torque around the particle's center of mass caused by the tangential force of the collision, which directly drives the particle to produce a change in rotational angular velocity. The rotational torque is the torque resisting the particle's rotation generated by the asymmetric stress distribution or rolling friction effect at the contact point, affecting the attenuation and stability of the particle's rotational motion.

[0123] Step C13: The momentum source term of the particle's reaction with the fluid, the solid phase velocity, and the porosity in the particle update information are fed back to the fluid phase flow field for alternating iterative coupling calculation until the predefined convergence condition is met, and transient flow field information is obtained.

[0124] Understandably, within each computation time step, the particle update information obtained from the previous step (including the force exerted by the particle on the fluid (i.e., the momentum source term), the particle's own velocity, and the remaining porosity after the particle occupies the space) is used as input conditions and substituted into the governing equations of the fluid phase for solving, thereby updating the flow field state. The updated flow field information is then used to calculate the force on the particle, updating the particle's motion state again. This alternating solution and data exchange between the fluid and particle is repeated until the difference between the calculation results of two iterations is less than the preset allowable error (i.e., the convergence condition is met). The result obtained at this point is the final flow field data that can accurately reflect the interaction result between the gas and solid phases at that moment, which is the transient flow field information.

[0125] Step B13: Based on the transient flow field information, monitor parameter changes where the average flow field parameter fluctuation amplitude is lower than a preset threshold within a predefined time period to obtain steady-state flow field simulation information. The steady-state flow field simulation information includes gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rate, and bed height.

[0126] It is understood that the gas phase outlet flow rate is the total volumetric flow rate or mass flow rate of gas flowing out from the reactor outlet boundary. It is a macroscopic indicator characterizing the overall aeration capacity and pressure balance of the reactor. Its fluctuation range directly reflects whether the flow field has reached dynamic stability. The key position pressure is the static pressure value at a representative specific location in the reactor. The pressure changes at these locations can sensitively characterize the bed resistance characteristics and the intrinsic evolution of the gas-solid interaction. The particle inlet and outlet mass flow rate is the total mass of the particle phase entering through the reactor inlet or exiting through the outlet per unit time. It is used to measure whether the particle phase has achieved continuous feed-out balance and whether the macroscopic movement has reached dynamic stability. The bed height is the height of the upper interface position of the particle bed in the reactor relative to the reference plane. It directly reflects the particle packing state, porosity distribution, and the macroscopic movement equilibrium position of the particle phase under the combined action of gravity and fluid drag.

[0127] Step S40: Based on the steady-state flow field simulation information, the corresponding heat transfer and chemical reaction equations are coupled and solved to determine the coupling result information;

[0128] It should be noted that the coupling result information is a dataset obtained by jointly solving the heat transfer process and the chemical reaction process in the steady-state background flow field after solidification.

[0129] In a specific embodiment, based on the steady-state flow field simulation information, the average data of the transient fluid flow field within a predefined time period are extracted to determine the steady-state flow field parameter information. This steady-state flow field parameter information includes the fluid velocity field, velocity gradient field, pressure field, pressure gradient field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area, and turbulence parameter field. Based on the steady-state flow field parameter information, corresponding fixed flow field file information is generated. Based on the fixed flow field file information, the heat transfer and chemical reaction equations under the corresponding steady-state background flow field are coupled and solved to determine the coupling result information of the heat transfer source term and the component source term. In other words, steady-state flow field simulation information obtained from transient cold-state simulation can be used. Based on the determination that the fluctuation amplitude of monitored parameters (such as gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rates, and bed height) is consistently lower than a preset threshold (e.g., 5%), a specified time interval after reaching statistical steady state (e.g., the last 20 seconds of the simulation duration) is selected. The flow field data saved at each transient time step within this time interval is then time-averaged to eliminate transient effects and extract steady-state flow field parameters that can stably characterize the average flow state of the reactor. These parameters include, for example, the fluid velocity field of the macroscopic gas transport path and airflow resistance loss. The system utilizes the pressure field, particle volume fraction distribution of particle packing density and porosity, particle velocity distribution of the overall particle group motion mode, particle surface area per unit volume calculated by the number of coarse-grained particles and equivalent particle size within a statistical grid, and turbulence parameter fields (such as turbulent kinetic energy and its dissipation rate) to measure gas-phase turbulence intensity. These time-averaged steady-state flow field parameters are stored in a structured data format (such as a solver-readable field file) to generate corresponding fixed flow field file information, including solidified gas-phase velocity, pressure, particle volume fraction, particle velocity, and particle size distribution at each spatial location. All flow information, including surface area and turbulence parameters, is loaded into the CFD calculation framework as a constant steady-state background flow field. Based on this, the energy equation and chemical reaction component transport model are activated, and corresponding heat transfer parameters and chemical reaction kinetic parameters are set. Coupled calculations of heat transfer and chemical reaction under the steady-state background flow field are carried out. Through iterative solutions, the coupling result information is finally determined, namely the temperature field distribution, gas phase and solid phase component concentration distribution, and reaction conversion rate distribution at various spatial locations within the reactor. This fully realizes the step-by-step coupled calculation from flow simulation to heat transfer and reaction simulation.

[0130] Step S50: Control the operation and regulation of the system based on the temperature field distribution information, component concentration distribution information and reaction conversion rate distribution information in the coupling result information.

[0131] It is understood that the temperature field distribution information is obtained by coupling steady-state heat transfer and chemical reaction to calculate the temperature values ​​and spatial variation patterns at various spatial locations inside the reactor. It intuitively represents the final thermal state distribution under the combined effects of heat transfer and accumulation between the gas phase and the particulate phase, as well as the thermal effect of chemical reaction. The component concentration distribution information is the concentration or mass fraction distribution of each gas phase component (such as hydrogen, carbon monoxide, water vapor, etc.) or solid phase component along different spatial locations inside the reactor. It represents the consumption pattern of reactants during the flow process and the generation and transport path of products. The reaction conversion rate distribution information is the spatial distribution of the degree of reaction of solid materials (such as iron ore powder particles) or gas phase reactants at different locations in the reactor. It shows a trend of gradually increasing from the inlet to the outlet, representing the speed of the reaction process and the degree of reaction completion.

[0132] In specific embodiments, local overheating or underreaction can be avoided by adjusting the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information. The spatial uniformity of the reaction conversion rate can be improved by adjusting the particle feed rate or residence time, thereby achieving energy saving, consumption reduction, quality improvement, efficiency enhancement, and safe and stable operation of the industrial reactor. For example, the temperature field distribution can be optimized to avoid local thermal anomalies, the component concentration distribution can be improved to increase gas utilization, and the uniformity and final value of the reaction conversion rate distribution can be improved. If the temperature field distribution information shows that there are local overheated areas in the reactor (such as exceeding the material softening temperature), the inlet gas preheating temperature can be reduced by controlling the system, the gas flow rate can be increased to enhance convective cooling, or the gas inlet distributor opening can be adjusted to change the local gas velocity, thereby eliminating hot spots. Conversely, if the temperature in a certain area is too low, resulting in insufficient reaction rate, the inlet gas temperature can be appropriately increased or oxygen-enriched combustion can be added. If the component concentration distribution information shows that the reducing gas (such as H2) is largely consumed in the upper part of the furnace, resulting in low concentration and insufficient conversion rate in the lower part, the concentration of H2 in the inlet gas can be appropriately reduced (or inert components can be added) through the control system to slow down the reaction rate and make the reduction reaction proceed more evenly along the furnace body; or the total gas flow rate can be increased to provide more reducing agent. If the CO concentration on one side is found to be abnormally high while H2 has been exhausted, there may be gas flow deviation, and the inlet distributor needs to be adjusted or the uniformity of the material layer needs to be checked. If the reaction conversion rate distribution information shows that the outlet material conversion rate is lower than the target value, it indicates that the reaction is incomplete. At this point, the reaction can be promoted by reducing the particle feed rate (extending the residence time of the material in the furnace) or increasing the temperature of the reaction zone (within the allowable range). If the conversion rate suddenly stagnates in a certain area (a "plateau" appears), a dense product layer may be formed, hindering diffusion. It is necessary to combine temperature field analysis to determine if the temperature is too low, or to consider changing the composition of the reducing gas (such as increasing the proportion of H2 to enhance the reducing potential). Therefore, in the control process, multi-parameter coordinated regulation can be carried out, with the target conversion rate as the primary control objective and the highest temperature point as the constraint condition. Through the model predictive control (MPC) algorithm, the optimal inlet gas temperature, flow rate, component ratio, and particle feed rate setpoints are automatically calculated and sent to the DCS system for execution, realizing the closed-loop optimized operation of the reactor.

[0133] This embodiment proposes a coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale. The method acquires real particle information and cold-state simulation parameters. Based on the real particle information, a predefined coarsening model is input to predict the equivalent parameters of the coarsened large particles, determining the equivalent information of the coarsened particles. Based on the coarsened particle equivalent information and the cold-state simulation parameters, a transient coupling simulation of the flow field state corresponding to particle motion and fluid changes is performed, neglecting heat transfer and chemical reactions, to determine the steady-state flow field simulation information. Based on the steady-state flow field simulation information, the corresponding heat transfer and chemical reaction equations are coupled and solved to determine the coupling result information. Based on the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information, the system operation and regulation are controlled. This invention addresses the technical challenge of more efficiently and accurately simulating long-term reaction processes in industrial-scale particle reactors based on coarse-graining and stepwise coupling. Compared to existing technologies, this application integrates a coarse-graining model with a stepwise coupling strategy. By constructing a coarse-graining model based on real particle information, the number of particles to be calculated is significantly reduced. Transient simulation of the coarse-grained particle system is performed using cold-state simulation parameters to obtain flow field information under statistical steady-state conditions. This steady-state flow field is then solidified as a background field. Within this framework, the coupling parameters of heat transfer and chemical reaction are calculated to obtain the distribution information of temperature field, component concentration, and reaction conversion rate, which can be used to optimize the operation and control of industrial reactors.

[0134] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the first embodiment can be referred to the above description, and will not be repeated hereafter.

[0135] In this embodiment, refer to Figure 5 , Figure 5 This is a schematic flowchart of Embodiment 2 of the coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, wherein step S40 specifically includes steps S41 to S43:

[0136] Step S41: Based on the steady-state flow field simulation information, the average data of the transient fluid flow field within a predefined time period will be extracted to determine the steady-state flow field parameter information. The steady-state flow field parameter information includes the fluid velocity field, velocity gradient field, pressure field, pressure gradient field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area, and turbulence parameter field.

[0137] It should be noted that the steady-state flow field parameter information is a set of data that can stably characterize the average flow state and phase distribution characteristics inside the reactor by performing time averaging or statistical averaging on transient flow field data within a specified time interval after the gas-solid two-phase flow reaches statistical steady state.

[0138] It is understood that the fluid velocity field is the average velocity vector distribution of the gas phase fluid at various spatial locations within the reactor, obtained after time averaging. It characterizes the macroscopic transport path and flow intensity of the gas in the particle bed. The velocity gradient field is a tensor field obtained by averaging the rate of change of fluid velocity in all spatial directions over time. It characterizes the degree of shear deformation and strain rate distribution of the average velocity distribution in the flow field, directly affecting the deformation rate of fluid particles and the interphase forces such as drag force on the particles. The pressure field is the average static pressure distribution at various locations within the reactor, characterizing the resistance loss and pressure gradient characteristics when the airflow passes through the particle bed. The pressure gradient field is a vector field obtained by averaging the rate of change of pressure per unit spatial distance over time. It characterizes the non-uniformity of the average pressure distribution and its macroscopic effect of driving or hindering fluid movement. The particle phase volume fraction distribution is the spatial distribution of the volume ratio of the particle phase in each grid cell after statistical averaging, which characterizes the particle packing density, porosity distribution, and possible fluidization or segregation regions in the reactor. The particle phase velocity distribution is the average velocity vector field of the coarse-grained particle group under statistical averaging, which characterizes the overall motion mode, flow direction, and residence time distribution characteristics of the particle phase. The particle surface area is the sum of the surface areas of all coarse-grained particles per unit volume or a single grid cell, which is a key geometric parameter calculated by statistically analyzing the number of particles, equivalent particle size, and spatial distribution in the grid, and characterizes the effective interface area for heat transfer and surface chemical reactions between the gas and solid phases. The turbulence parameter field is the spatial distribution of statistically averaged quantities (such as turbulent kinetic energy and its dissipation rate, turbulent viscosity, etc.) describing the turbulent state of the gas phase.

[0139] In a specific embodiment, steady-state flow field data can be extracted, including average flow field data between 80-100 s, such as the distribution of gas phase velocity field, particle phase velocity field, and gas phase pressure field. Figure 6 As shown, Figure 6 This is a schematic diagram of the dynamic steady flow field of the coupling method for quasi-steady-state particulate fluid multiphase systems at the industrial scale, as described in this application. Once the flow field reaches statistical steady state, the simulation information of the steady-state flow field at this point is obtained. This allows for the extraction of steady-state flow field parameters after statistical averaging over a specified time interval. These steady-state flow field parameters can include the fluid velocity field, pressure field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area, and turbulent parameter field. The particle surface area can be statistically calculated using the number of coarse-grained particles, equivalent particle size, and spatial distribution, and is expressed as follows:

[0140]

[0141] in, is the total surface area of ​​particles within a unit CFD grid (m²); j is the number of the coarsened particles within the grid. The volume percentage of the j-th coarse-grained particle within the grid.

[0142] Step S42: Generate corresponding fixed flow field file information based on the steady-state flow field parameter information;

[0143] It should be noted that the fixed flow field file information is a collection of computer files obtained by storing the steady-state flow field data after time averaging in a specific data format. In essence, it is a frozen snapshot of the flow field, which transforms the dynamic flow field that originally fluctuates with time but is statistically stable into background field data that is spatially distributed but no longer changes in time. This data is used to provide fixed and unchanging flow boundary conditions and initial physical field values ​​for independent steady-state calculations of heat transfer and chemical reactions.

[0144] In a specific embodiment, steady-state flow field solidification can be performed. Spatial distribution data of gas phase velocity, particle phase volume fraction, particle phase velocity, particle surface area and turbulence parameters in the steady-state background flow field corresponding to the steady-state flow field parameter information can be extracted and solidified into the CFD calculation framework as preset source terms and boundary conditions to generate a fixed flow field file. This solidified flow field serves as the motion background field for subsequent heat transfer and chemical reaction calculations, keeping the parameters unchanged, and is used for accurate calculation of heat source terms and reaction source terms.

[0145] Step S43: Based on the fixed flow field file information, the heat transfer and chemical reaction equations under the corresponding steady-state background flow field are coupled and solved to determine the coupling result information of heat transfer source terms and component source terms.

[0146] Understandably, the heat transfer and chemical reaction coupling equations are a set of governing equations used to describe the interaction between heat transfer and chemical change in a gas-solid two-phase system under a steady-state background flow field. These equations include energy conservation equations that consider convective heat transfer, heat conduction, and the thermal effects of chemical reactions, as well as component transport equations that consider component convection, diffusion, and reaction generation / consumption rates. The equations are tightly coupled through source terms, where the heat released or absorbed by the chemical reaction serves as the source term of the energy equations. In turn, the temperature distribution influences the generation and consumption rates of components through reaction kinetic parameters. Thus, the coupling results are obtained by iteratively solving the equations within a fixed flow field framework.

[0147] Additionally, it should be noted that the heat transfer source term and the component source term are coupling variables when solving the heat transfer and chemical reaction coupling equations under a steady-state background flow field. The heat transfer source term is an additional term in the energy conservation equation, consisting of heat generated by gas-solid interphase convective heat transfer and heat released or absorbed by chemical reactions. It is used to characterize the increase or decrease in heat generated per unit volume per unit time due to interphase heat transfer and chemical changes, directly affecting the distribution and evolution of the temperature field. The component source term is the generation or consumption rate term of each component in the component transport equation, caused by homogeneous gas-phase reactions and heterogeneous surface reactions. It is used to characterize the net change in mass of the j-th component per unit volume per unit time due to chemical reactions. It is the core parameter connecting chemical reaction kinetics and component concentration distribution. Component source terms are generated simultaneously with the chemical reaction to change the concentration of each component and release or absorb heat as heat transfer source terms, affecting the temperature field. The change in the temperature field, in turn, regulates the chemical reaction rate through kinetic parameters such as the reaction rate constant and equilibrium constant. Thus, the solution is iteratively solved within a fixed flow field framework until convergence, obtaining the coupling result information.

[0148] In a specific embodiment, based on the fixed flow field file information, the particle specific heat capacity, gas phase specific heat capacity, particle thermal conductivity, gas phase thermal conductivity, and particle-gas phase relative heat transfer coefficient in the heat transfer coupling equation under the corresponding steady-state background flow field are solved to determine the heat transfer coupling parameter information, that is, to perform steady-state heat transfer and chemical reaction coupling calculation. In the CFD calculation environment, through the acquired solidified steady-state flow field data, the energy equation and / or chemical reaction component transport model are activated, the heat transfer parameters and / or chemical reaction kinetic model of the industrial particle reactor are set, the temperature boundary conditions and initial reaction conditions are set, and steady-state heat transfer and chemical reaction coupling calculation is carried out.

[0149] The heat transfer coupling parameters may include particle specific heat capacity, gas phase specific heat capacity, particle thermal conductivity, gas phase thermal conductivity, and convective heat transfer coefficient between particles and the gas phase, which are calculated as follows:

[0150]

[0151] in, , The specific heat capacity at constant pressure (J / (kg·K)) is given for the gas phase and particles, respectively. , These represent the temperatures (K) of the gas phase and particles, respectively. The equivalent thermal conductivity (W / (m·K)) includes contributions from gas-phase thermal conductivity, particle thermal conductivity, and interphase heat transfer. The heat generation rate of the chemical reaction (W / m³) The convective heat transfer rate between the particles and the gas phase is denoted as W / m³.

[0152] Using the component transport algorithm for homogeneous gas-phase reactions and the heat transfer coupling parameter information, the heterogeneous surface reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved to obtain the heterogeneous surface reaction parameter information in the chemical reaction coupling parameter information. The heterogeneous surface reaction parameter information includes mass fraction, effective diffusion coefficient of components, component generation rate, and component consumption rate. Using the reaction kinetics algorithm and the heat transfer coupling parameter information, the homogeneous gas-phase reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved to obtain the homogeneous gas-phase reaction parameter information in the chemical reaction coupling parameter information. The homogeneous gas-phase reaction parameter information includes interfacial chemical reaction resistance, diffusion resistance, gas mass transfer resistance, concentration, equilibrium concentration, pressure, solid phase temperature, and gas phase constant. That is, the chemical reaction types considered in the chemical reaction component transport equation include heterogeneous surface reactions and / or homogeneous gas-phase reactions. The heterogeneous surface reaction parameters and homogeneous gas-phase reaction parameters in the chemical reaction coupling parameters are solved, wherein the homogeneous gas-phase reaction parameters are calculated as follows:

[0153]

[0154] in, The mass fraction of the j-th component; is the effective diffusion coefficient (m² / s) of the j-th component. Let be the generation / consumption rate of the j-th component (kg / (m³·s)).

[0155] The heterogeneous surface reaction parameters are calculated using a pre-defined reaction kinetic model based on particle surface area, local gas phase component concentration, and temperature. The formulas vary. For example, taking the reaction rate of Fe3O2 being reduced to Fe3O4 as an example, the heterogeneous surface reaction parameter, i.e., the heterogeneous surface reaction rate, can be expressed as:

[0156]

[0157] in, For interfacial chemical reaction resistance, Where F is the diffusion resistance and F is the gas mass transfer resistance. This refers to the Fe3O4 concentration. The concentrations of Fe3O4 and Fe2O3 at thermodynamic equilibrium. The particle diameter is Where is pressure, and T is solid-state temperature. The gas phase constant is taken as 8.314 J / mol / K.

[0158] The heat source term is fed back to the heat transfer coupling equation and the chemical reaction coupling equation to iteratively update the heat transfer coupling parameter information and the chemical reaction coupling parameter information until the predefined convergence condition is met, thereby obtaining the coupling result information of the heat transfer source term and the component source term.

[0159] In a specific embodiment, for the coupled calculation of steady-state heat transfer and chemical reaction, a new CFD calculation task is created, importing the same vertical shaft furnace geometry and mesh. The TF-QFLUX energy equation and component transport equation are activated, considering the convective heat transfer between the gas phase and solid particles. Heat transfer parameters are set: iron ore powder particle specific heat capacity 800 J / (kg·K), thermal conductivity 2.5 W / (m·K); mixed gas specific heat capacity 14300 J / (kg·K), thermal conductivity 0.18 W / (m·K); convective heat transfer coefficient between particles and the gas phase 50 W / (m²·K). Based on the unreacted core model, the reaction rate of the multi-stage reaction is set, a convergence criterion is set, and steady-state simulation is performed. After 2000 iterations, convergence is calculated, thus... Figure 7 As shown, Figure 7 This is a schematic diagram of the steady-state calculation results of heat transfer and chemical reaction of the coupled method for industrial-scale quasi-steady-state particulate fluid multiphase system in this application. In the figure, the left side shows the H2 concentration distribution and the right side shows the H2O concentration distribution. At this time, the complete steady-state temperature distribution, the concentration distribution of each gas component, and the distribution of solid products in the vertical furnace can be obtained.

[0160] In one feasible implementation, step S43 may include steps D11~D13:

[0161] Step D11: Based on the fixed flow field file information, solve the particle specific heat capacity, gas phase specific heat capacity, particle thermal conductivity, gas phase thermal conductivity, and particle-gas phase heat transfer coefficient in the heat transfer coupling equation under the corresponding steady-state background flow field to determine the heat transfer coupling parameter information.

[0162] It should be noted that the heat transfer coupling parameter information is a parameter that characterizes the heat exchange and transfer behavior between the gas and solid phases under the framework of the solidified steady-state background flow field.

[0163] It is understood that the specific heat capacity of particles is the amount of heat absorbed (or released) when the temperature of a unit mass of particulate matter increases (or decreases) by a unit temperature, characterizing the ability of the particulate material to store heat, i.e., the rate of temperature change of particles under the same heat input. The specific heat capacity of gas is the amount of heat change when the temperature of a unit mass of gas medium changes by a unit temperature, characterizing the ability of the gas to carry heat and the degree of response of the gas flow temperature to heat input. The thermal conductivity of particles is the rate at which heat is conducted from high-temperature regions to low-temperature regions within the particulate material, characterizing the thermal conductivity of the particles themselves, affecting the uniformity of temperature distribution within the particles and the depth of heat transfer into the particles. The thermal conductivity of gas is the heat conduction capacity of the gas medium itself, characterizing the efficiency of heat transfer in the gas phase through molecular collisions and diffusion. The convective heat transfer coefficient between particles and gas is a key parameter for the intensity of heat exchange between the gas and solid phases through convection, characterizing the combined influence of fluid flow state, particle surface characteristics, and gas-solid temperature difference on the interphase heat transfer rate, i.e., the efficiency of heat transfer from the gas phase to the particle surface or from the particle surface to the gas phase.

[0164] Step D12: Based on the heat transfer coupling parameter information, solve the heterogeneous surface reaction parameters and homogeneous gas phase reaction parameters in the corresponding steady-state background flow field chemical reaction coupling equation to determine the chemical reaction coupling parameter information and heat source term;

[0165] It should be noted that the chemical reaction coupling parameter information refers to all parameters characterizing the chemical reaction behavior between the gas and solid phases and within the gas phase in the reactor. The heat source term refers to the heat released or absorbed due to the occurrence of chemical reactions under steady-state background flow field. This heat is an additional source term in the energy conservation equation, used to describe the heat change caused by chemical reactions per unit volume per unit time, thereby affecting the temperature field distribution. At the same time, this heat source term is coupled with the heat transfer coupling parameters and the chemical reaction coupling parameters. Through iterative updates, the heat transfer equation and the chemical reaction equation can accurately reflect the interaction between the temperature field and the reaction process when the convergence conditions are met.

[0166] It is understood that the heterogeneous surface reaction parameters are parameters used to characterize the chemical reaction between gas components and the surface of solid particles, and may include mass fraction, effective diffusion coefficient of components, component generation rate and component consumption rate. The homogeneous gas phase reaction parameters are parameters required to describe the chemical reaction between gas components in the gas phase space, and may include interfacial chemical reaction resistance, diffusion resistance, gas mass transfer resistance, concentration, equilibrium concentration, particle diameter, pressure, solid phase temperature and gas phase constant.

[0167] In one feasible implementation, step D12 may include steps E11~E12:

[0168] Step E11: Using the component transport algorithm of homogeneous gas phase reaction and the heat transfer coupling parameter information, the heterogeneous surface reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved to obtain the heterogeneous surface reaction parameter information in the chemical reaction coupling parameter information. The heterogeneous surface reaction parameter information includes mass fraction, effective diffusion coefficient of component, component generation rate and component consumption rate.

[0169] It should be noted that the heterogeneous surface reaction parameter information is a set of all local state variables and rate parameters required to describe the chemical reaction between gas components and solid particle surfaces within a steady-state background flow field framework. It is used to quantify the mass exchange intensity and composition variation of the gas-solid reaction at each spatial location within the reactor.

[0170] Understandably, the mass fraction is the mass proportion of each chemical component (such as hydrogen, carbon monoxide, water vapor, etc.) in the gas mixture. As a basic variable in the component transport equation, it characterizes the spatial distribution of reactants and products in the flow field and their dynamic changes with the reaction process. The effective diffusion coefficient of the component is a comprehensive parameter of the diffusion and transport capacity of gas components between particle surface boundary layers, particle pores, or fluid micro-clusters. It considers the contributions of molecular diffusion and turbulent diffusion and characterizes the speed at which components are transported from the bulk gas phase to the reaction interface. The component generation rate is the mass increase of a component produced per unit volume (or unit particle surface area) through a chemical reaction per unit time. It is a positive value for reaction products and characterizes the production intensity of the reaction. The component consumption rate is the mass decrease of a component consumed per unit volume (or unit particle surface area) due to a chemical reaction per unit time. It is a positive value for reactants and characterizes the consumption intensity of the reaction.

[0171] Step E12: Using the reaction kinetics algorithm and the heat transfer coupling parameter information, the homogeneous gas phase reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved to obtain the homogeneous gas phase reaction parameter information in the chemical reaction coupling parameter information. The homogeneous gas phase reaction parameter information includes interfacial chemical reaction resistance, diffusion resistance, gas mass transfer resistance, concentration, equilibrium concentration, pressure, solid phase temperature and gas phase constant.

[0172] It should be noted that the homogeneous gas phase reaction parameter information is a set of all kinetic parameters and state variables required for chemical reactions to occur between gas components in the gas phase space within the framework of a steady-state background flow field. It is used to quantify the internal chemical reaction rate of the gas phase and its influence on the component concentration distribution.

[0173] It is understood that the interfacial chemical reaction resistance is the resistance inherent in the chemical reaction itself when gas molecules react with the surface of solid particles. It characterizes the energy barrier that reactant molecules need to overcome to transform into products at the reaction interface and is inversely proportional to the reaction rate constant. The diffusion resistance is the resistance encountered by gaseous reactants when diffusing through the formed solid product layer to the unreacted core, and depends on the thickness, porosity, and diffusion coefficient of the product layer. The gas mass transfer resistance is the resistance encountered by gas components during transport from the bulk gas phase through the particle surface boundary layer to the reaction interface, and is closely related to the fluid flow state, particle size, and gas diffusion characteristics. The concentration is the reaction... The instantaneous concentration of a substance or product in the gas phase, expressed as molar concentration or partial pressure, characterizes the thermodynamic driving force of the reaction. The equilibrium concentration is the concentration of reactants or products that should be reached when a chemical reaction reaches thermodynamic equilibrium under given temperature and pressure conditions. The difference between the equilibrium concentration and the actual concentration determines the direction and net rate of the reaction. The pressure is the total pressure of the gas phase at a local location, which affects the partial pressure of gas components and the reaction rate constant. The solid phase temperature is the temperature of the particles themselves, characterizing the speed of the chemical reaction. The gas phase constant is the universal gas constant in the ideal gas law, used in kinetic calculations to relate pressure, concentration, and temperature, and is a fundamental physical constant in the reaction rate formula.

[0174] Step D13: Feed the heat source term back to the heat transfer coupling equation and the chemical reaction coupling equation to iteratively update the heat transfer coupling parameter information and the chemical reaction coupling parameter information until the predefined convergence condition is met, and obtain the coupling result information of the heat transfer source term and the component source term.

[0175] It is understood that the coupling result information may include temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information at various spatial locations within the reactor. Specifically, the temperature field distribution information at various spatial locations within the reactor can characterize the spatial distribution characteristics of heat transfer and accumulation, the component concentration distribution information can characterize the concentration changes and reaction consumption / generation patterns of each gaseous or solid component in space, and the reaction conversion rate distribution information can characterize the reaction progress and completion degree of solid materials or gaseous components along the axial or radial direction of the reactor.

[0176] This embodiment proposes a coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale. Based on the steady-state flow field simulation information, the method extracts the average data of the transient fluid flow field within a predefined time period to determine the steady-state flow field parameters, including the fluid velocity field, velocity gradient field, pressure field, pressure gradient field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area, and turbulence parameter field. Based on the steady-state flow field parameters, a corresponding fixed flow field file is generated. Based on the fixed flow field file, the heat transfer and chemical reaction equations under the corresponding steady-state background flow field are coupled and solved to determine the coupling results of the heat transfer source term and the component source term. This invention addresses the technical challenge of more efficiently and accurately simulating long-term reaction processes in industrial-scale granular reactors based on coarse-graining and stepwise coupling. Compared to existing technologies, this application, after achieving statistical steady-state in transient cold simulation, performs time-averaging on flow field data within a predefined time interval to extract comprehensive parameter information that stably characterizes the average flow state of the reactor. The time-averaged steady-state flow field parameter information is then stored to generate a corresponding fixed flow field file. This fixed flow field file is loaded into the computational framework and used as a constant steady-state background flow field. Based on this, separate excitation is performed... The active energy equation and chemical reaction component transport model are used to perform coupled calculations of heat transfer and chemical reaction, thereby determining the coupling result information and realizing step-by-step decoupled calculations of the flow field and temperature / reaction field. By solving only the motion equations of fluid and particles in the cold simulation stage and solidifying the flow field after reaching steady state, the costly CFD-DEM bidirectional coupling calculations are avoided repeatedly in the long heat transfer and reaction process, which significantly reduces the consumption of computing resources. This makes the long-term reaction process of industrial-scale reactors, which was originally impossible to calculate due to the large number of particles and the long physical time, engineering feasible, ensuring both computational efficiency and simulation accuracy.

[0177] This application also provides a coupling device for industrial-scale quasi-steady-state particulate fluid multiphase systems. Please refer to [reference needed]. Figure 8 The coupling device for industrial-scale quasi-steady-state particulate fluid multiphase systems includes:

[0178] Module 10 is used to acquire real particle information and cold simulation parameter information;

[0179] Processing module 20 is used to predict the equivalent parameters of large particles after coarsening based on the input of the real particle information into a predefined coarsening model, and to determine the equivalent information of coarsened particles.

[0180] The execution module 30 is also used to perform transient coupling simulation of the flow field state corresponding to particle motion and fluid change based on the coarse particle equivalent information and the cold simulation parameter information, under the condition of ignoring heat transfer and chemical reaction, to determine the steady-state flow field simulation information.

[0181] Execution module 30 is used to couple and solve the corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determine the coupling result information;

[0182] The execution module 30 is also used to control the operation of the system based on the temperature field distribution information, component concentration distribution information and reaction conversion rate distribution information in the coupling result information.

[0183] The processing module 20 is also used to predict the coarsening amplification ratio that satisfies the flow characteristics of real particles based on the input of the predefined coarsening model of the real particle information, and to determine the coarsening amplification ratio information.

[0184] Based on the coarsening amplification ratio information, the equivalent parameters of the corresponding coarsened large particles are calculated to obtain the coarsened particle equivalent information. The coarsened particle equivalent information includes agglomerated particle size information, mass information, volume information, time step information, contact stiffness information, contact force information, and gravity information.

[0185] The execution module 30 is further configured to determine particle motion parameters and fluid change parameters based on the coarse-grained particle equivalent information and the cold-state simulation parameter information. The particle motion parameters include particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid force on particle, gravity, tangential contact torque, and rotational torque. The fluid change parameters include fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor, and momentum source term.

[0186] Based on the particle motion parameters and the fluid change parameters, the flow field state corresponding to particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction to determine transient flow field information.

[0187] Based on the transient flow field information, the average flow field parameter fluctuation amplitude within a predefined time is monitored to obtain steady-state flow field simulation information, which includes gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rate, and bed height.

[0188] The execution module 30 is also used to calculate the fluid phase flow field at the current moment based on the fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor and momentum source term in the fluid change parameters, and determine the flow field update information;

[0189] Based on the fluid phase flow field information and the particle motion parameters such as particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, gravity, tangential contact torque, and rotational torque, the motion state of the particles is updated to determine the updated particle information;

[0190] The momentum source term of the particle's reaction with the fluid, the solid phase velocity, and the porosity in the particle update information are fed back to the fluid phase flow field for alternating iterative coupling calculations until the predefined convergence conditions are met, thus obtaining transient flow field information.

[0191] The execution module 30 is also used to extract the average data of transient fluid flow field within a predefined time based on the steady-state flow field simulation information, and determine the steady-state flow field parameter information, which includes fluid velocity field, velocity gradient field, pressure field, pressure gradient field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area and turbulence parameter field.

[0192] Based on the steady-state flow field parameter information, generate corresponding fixed flow field file information;

[0193] Based on the fixed flow field file information, the heat transfer and chemical reaction equations under the corresponding steady-state background flow field are coupled and solved to determine the coupling result information of heat transfer source terms and component source terms.

[0194] The execution module 30 is also used to solve the particle specific heat capacity, gas phase specific heat capacity, particle thermal conductivity, gas phase thermal conductivity, and particle-gas phase heat transfer coefficient in the heat transfer coupling equation under the corresponding steady-state background flow field based on the fixed flow field file information, and to determine the heat transfer coupling parameter information.

[0195] Based on the heat transfer coupling parameter information, the heterogeneous surface reaction parameters and homogeneous gas phase reaction parameters in the chemical reaction coupling equation under the corresponding steady-state background flow field are solved to determine the chemical reaction coupling parameter information and heat source term;

[0196] The heat source term is fed back to the heat transfer coupling equation and the chemical reaction coupling equation to iteratively update the heat transfer coupling parameter information and the chemical reaction coupling parameter information until the predefined convergence condition is met, thereby obtaining the coupling result information of the heat transfer source term and the component source term.

[0197] The execution module 30 is further configured to use the component transport algorithm of homogeneous gas phase reaction and the heat transfer coupling parameter information to solve the heterogeneous surface reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field, so as to obtain the heterogeneous surface reaction parameter information in the chemical reaction coupling parameter information. The heterogeneous surface reaction parameter information includes mass fraction, effective diffusion coefficient of component, component generation rate and component consumption rate.

[0198] The homogeneous gas phase reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved using the reaction kinetics algorithm and the heat transfer coupling parameter information. The homogeneous gas phase reaction parameter information includes interfacial chemical reaction resistance, diffusion resistance, gas mass transfer resistance, concentration, equilibrium concentration, pressure, solid phase temperature, and gas phase constant.

[0199] The coupling device for industrial-scale quasi-steady-state particulate fluid multiphase systems provided in this application employs the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems described in the above embodiments. This addresses the technical problem of how to more efficiently and accurately simulate long-term reaction processes within industrial-scale particulate reactors based on coarse-graining and stepwise coupling. Compared to existing technologies, the beneficial effects of the coupling device for industrial-scale quasi-steady-state particulate fluid multiphase systems provided in this application are the same as those of the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems provided in the above embodiments. Furthermore, other technical features of the coupling device for industrial-scale quasi-steady-state particulate fluid multiphase systems are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0200] This application provides a coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system. The coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the coupling method for an industrial-scale quasi-steady-state particulate fluid multiphase system in the above embodiment 1.

[0201] The following is for reference. Figure 9 This document illustrates a schematic diagram of a coupling device suitable for implementing embodiments of this application for an industrial-scale quasi-steady-state particulate-fluid multiphase system. The coupling device for an industrial-scale quasi-steady-state particulate-fluid multiphase system in this application embodiment may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 9 The coupling device shown for an industrial-scale quasi-steady-state particulate fluid multiphase system is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0202] like Figure 9 As shown, the coupling device for an industrial-scale quasi-steady-state particulate-fluid multiphase system may include a processing unit 1001 (e.g., a central processing unit, graphics processor, etc.) that can perform various appropriate actions and processes based on programs stored in ROM (Read Only Memory) 1002 or programs loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the coupling device for the industrial-scale quasi-steady-state particulate-fluid multiphase system. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the coupling device for an industrial-scale quasi-steady-state particulate-fluid multiphase system to exchange data with other devices wirelessly or via wired communication. Although the figure shows coupling devices for an industrial-scale quasi-steady-state particulate-fluid multiphase system with various systems, it should be understood that it is not required to implement or possess all of the systems shown. More or fewer systems may be implemented alternatively.

[0203] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0204] The coupling device for industrial-scale quasi-steady-state particulate-fluid multiphase systems provided in this application employs the coupling method for industrial-scale quasi-steady-state particulate-fluid multiphase systems described in the above embodiments. This addresses the technical problem of how to more efficiently and accurately simulate long-term reaction processes within industrial-scale particulate reactors based on coarse-graining and stepwise coupling. Compared to existing technologies, the beneficial effects of the coupling device for industrial-scale quasi-steady-state particulate-fluid multiphase systems provided in this application are the same as those of the coupling method for industrial-scale quasi-steady-state particulate-fluid multiphase systems provided in the above embodiments. Furthermore, other technical features of this coupling device for industrial-scale quasi-steady-state particulate-fluid multiphase systems are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0205] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0206] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0207] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the coupling method for an industrial-scale quasi-steady-state particulate fluid multiphase system described in the above embodiments.

[0208] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0209] The aforementioned computer-readable storage medium may be included in a coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system; or it may exist independently and not assembled into a coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system.

[0210] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by a coupling device for an industrial-scale quasi-steady-state particulate-fluid multiphase system, the coupling device for the industrial-scale quasi-steady-state particulate-fluid multiphase system: acquires real particle information and cold-state simulation parameter information; predicts the equivalent parameters of the coarsened large particles based on the real particle information input into a predefined coarsening model, and determines the equivalent information of the coarsened particles; performs transient coupling simulation of the flow field state corresponding to particle motion and fluid change under the condition of ignoring heat transfer and chemical reaction based on the equivalent information of the coarsened particles and the cold-state simulation parameter information, and determines the steady-state flow field simulation information; couples and solves the corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determines the coupling result information; and controls the operation and regulation of the system based on the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information.

[0211] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0212] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0213] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0214] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems. This method can solve the technical problem of how to more efficiently and accurately simulate long-term reaction processes in industrial-scale particulate reactors based on coarse-graining and stepwise coupling. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the coupling method for industrial-scale quasi-steady-state particulate fluid multiphase systems provided in the above embodiments, and will not be elaborated upon here.

[0215] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A coupling method for quasi-steady-state particulate fluid multiphase systems on an industrial scale, characterized in that, The method includes: Obtain real particle information and cold-state simulation parameter information; Based on the real particle information, the predefined coarsening model is input to predict the equivalent parameters of the coarsened large particles and determine the equivalent information of the coarsened particles. Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameter information, the flow field state corresponding to particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction, so as to determine the steady-state flow field simulation information. Based on the steady-state flow field simulation information, the corresponding heat transfer and chemical reaction equations are coupled and solved to determine the coupling result information; The system operation and regulation are based on the temperature field distribution information, component concentration distribution information, and reaction conversion rate distribution information in the coupling result information. The cold simulation parameter information includes geometric model information, mesh generation information, and boundary condition information; Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameters, the steps for determining the steady-state flow field simulation information by performing transient coupled simulation of the flow field state corresponding to particle motion and fluid changes under the condition of neglecting heat transfer and chemical reaction include: Based on the equivalent information of the coarse-grained particles and the cold-state simulation parameter information, particle motion parameters and fluid variation parameters are determined. The particle motion parameters include particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid force on particles, gravity, tangential contact torque, and rotational torque. The fluid variation parameters include fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor, and momentum source term. Based on the particle motion parameters and the fluid change parameters, the flow field state corresponding to particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction to determine transient flow field information. Based on the transient flow field information, the average flow field parameter fluctuation amplitude within a predefined time is monitored to obtain steady-state flow field simulation information, which includes gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rate, and bed height.

2. The method as described in claim 1, characterized in that, The step of predicting the equivalent parameters of the coarse-grained large particles and determining the equivalent information of the coarse-grained particles by inputting the predefined coarsening model based on the real particle information includes: Based on the real particle information, the predefined coarsening model is input to predict the coarsening amplification ratio that satisfies the real particle flow characteristics, and the coarsening amplification ratio information is determined. Based on the coarsening amplification ratio information, the equivalent parameters of the corresponding coarsened large particles are calculated to obtain the coarsened particle equivalent information. The coarsened particle equivalent information includes agglomerated particle size information, mass information, volume information, time step information, contact stiffness information, contact force information, and gravity information.

3. The method as described in claim 1, characterized in that, The step of performing transient coupling simulation of the flow field state corresponding to particle motion and fluid change based on the particle motion parameters and the fluid change parameters, under the condition of neglecting heat transfer and chemical reaction, and determining the transient flow field information includes: Based on the fluid velocity, velocity gradient, pressure gradient, porosity, fluid force tensor, and momentum source term in the fluid change parameters, the fluid phase flow field at the current moment is calculated, and the flow field update information is determined. Based on the information of the fluid phase flow field and the particle motion parameters such as particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, gravity, tangential contact torque, and rotational torque, the motion state of the particles is updated to determine the updated particle information; The momentum source term of the particle's reaction with the fluid, the solid phase velocity, and the porosity in the particle update information are fed back to the fluid phase flow field for alternating iterative coupling calculations until the predefined convergence conditions are met, thus obtaining transient flow field information.

4. The method as described in claim 1, characterized in that, The step of coupling and solving the corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determining the coupling result information, includes: Based on the steady-state flow field simulation information, the average data of transient fluid flow field within a predefined time period will be extracted to determine the steady-state flow field parameter information, which includes fluid velocity field, velocity gradient field, pressure field, pressure gradient field, particle phase volume fraction distribution, particle phase velocity distribution, particle surface area, and turbulence parameter field. Based on the steady-state flow field parameter information, generate corresponding fixed flow field file information; Based on the fixed flow field file information, the heat transfer and chemical reaction equations under the corresponding steady-state background flow field are coupled and solved to determine the coupling result information of heat transfer source terms and component source terms.

5. The method as described in claim 4, characterized in that, The step of coupling and solving the heat transfer and chemical reaction equations under the corresponding steady-state background flow field based on the fixed flow field file information, and determining the coupling result information of heat transfer source terms and component source terms, includes: Based on the fixed flow field file information, the particle specific heat capacity, gas phase specific heat capacity, particle thermal conductivity, gas phase thermal conductivity, and particle-gas phase heat transfer coefficient in the heat transfer coupling equation under the corresponding steady-state background flow field are solved to determine the heat transfer coupling parameter information. Based on the heat transfer coupling parameter information, the heterogeneous surface reaction parameters and homogeneous gas phase reaction parameters in the chemical reaction coupling equation under the corresponding steady-state background flow field are solved to determine the chemical reaction coupling parameter information and heat source term; The heat source term is fed back to the heat transfer coupling equation and the chemical reaction coupling equation to iteratively update the heat transfer coupling parameter information and the chemical reaction coupling parameter information until the predefined convergence condition is met, thereby obtaining the coupling result information of the heat transfer source term and the component source term.

6. The method as described in claim 5, characterized in that, The step of solving the heterogeneous surface reaction parameters and homogeneous gas phase reaction parameters in the chemical reaction coupling equation under the corresponding steady-state background flow field based on the heat transfer coupling parameter information, and determining the chemical reaction coupling parameter information includes: Using the component transport algorithm of homogeneous gas phase reaction and the heat transfer coupling parameter information, the heterogeneous surface reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved to obtain the heterogeneous surface reaction parameter information in the chemical reaction coupling parameter information. The heterogeneous surface reaction parameter information includes mass fraction, effective diffusion coefficient of component, component generation rate and component consumption rate. The homogeneous gas phase reaction parameters in the chemical reaction coupling parameters under the corresponding steady-state background flow field are solved using the reaction kinetics algorithm and the heat transfer coupling parameter information. The homogeneous gas phase reaction parameter information includes interfacial chemical reaction resistance, diffusion resistance, gas mass transfer resistance, concentration, equilibrium concentration, pressure, solid phase temperature, and gas phase constant.

7. A coupling device for an industrial-scale quasi-steady-state particulate fluid multiphase system, characterized in that, The device includes: The acquisition module is used to acquire real particle information and cold simulation parameter information; The processing module is used to predict the equivalent parameters of the coarse-grained large particles based on the input of the real particle information into a predefined coarsening model, and to determine the equivalent information of the coarse-grained particles. The execution module is used to perform transient coupling simulation of the flow field state corresponding to particle motion and fluid change under the condition of ignoring heat transfer and chemical reaction, based on the equivalent information of the coarse particles and the cold simulation parameter information, and to determine the steady-state flow field simulation information. The execution module is used to couple and solve the corresponding heat transfer and chemical reaction equations based on the steady-state flow field simulation information, and determine the coupling result information; The execution module is also used to control the operation of the system based on the temperature field distribution information, component concentration distribution information and reaction conversion rate distribution information in the coupling result information; The execution module is further configured to determine particle motion parameters and fluid variation parameters based on the coarse-grained particle equivalent information and the cold-state simulation parameter information. The particle motion parameters include particle mass, moment of inertia, particle velocity, angular velocity, collision normal force, collision tangential force, fluid force on particle, gravity, tangential contact torque, and rotational torque. The fluid variation parameters include fluid velocity, velocity gradient, pressure gradient, porosity, fluid corresponding force tensor, and momentum source term. Based on the particle motion parameters and the fluid change parameters, the flow field state corresponding to particle motion and fluid change is subjected to transient coupling simulation under the condition of ignoring heat transfer and chemical reaction to determine transient flow field information. Based on the transient flow field information, the average flow field parameter fluctuation amplitude within a predefined time is monitored to obtain steady-state flow field simulation information, which includes gas phase outlet flow rate, pressure at key locations, particle inlet and outlet mass flow rate, and bed height.

8. A coupling device for industrial-scale quasi-steady-state particulate fluid multiphase systems, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the coupling method for an industrial-scale quasi-steady-state particulate fluid multiphase system as claimed in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the coupling method for an industrial-scale quasi-steady-state particulate fluid multiphase system as described in any one of claims 1 to 6.

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