Simulation calculation method, device, equipment and medium for sintering anhydrous iron phosphate in rotary kiln

Abstract

The embodiment of the invention provides a simulation calculation method, device, equipment and medium for sintering anhydrous iron phosphate in a rotary kiln, and relates to the technical field of rotary kiln multi-physical phenomenon simulation. According to the method, a rotary kiln three-dimensional geometric model is constructed according to structural parameters of the electric heating type rotary kiln and gridding is carried out, a rotary kiln computational domain model is generated, and a gas-solid two-phase flow model, an electric heating conversion model, a heat transfer model and a chemical reaction kinetic model which are established in advance are integrated in the computational domain model; obtaining a multi-physical field coupling simulation model of the rotary kiln; based on the rotary kiln multi-physics field coupling simulation model, the sintering process of anhydrous iron phosphate in the rotary kiln is subjected to simulation calculation, and a multi-physics field dynamic evolution data set in the rotary kiln is obtained, so that the limitation that the internal process is difficult to observe in real time in a traditional experimental means is overcome, the scientificity of technological parameter optimization and the control ability of product consistency are improved, and the method is suitable for industrial production. And digital support is provided for accurate regulation and control and green and efficient production in the anhydrous iron phosphate sintering process.

Description

Technical Field

[0001] This invention relates to the field of multi-physical phenomenon simulation technology of rotary kilns, and more specifically, to a simulation calculation method, apparatus, equipment and medium for sintering anhydrous ferric phosphate in a rotary kiln. Background Technology

[0002] Iron phosphate, as an important precursor for lithium-ion battery cathode materials, directly affects the electrochemical performance of the final battery product due to the integrity of its crystal structure, purity, and uniformity of its physical properties. In industrial production, anhydrous iron phosphate is typically prepared by high-temperature sintering and dehydration of dihydrate iron phosphate in a rotary kiln. This process involves complex physical and chemical transformations, including water evaporation, sulfate decomposition, and crystal phase reconstruction, and must be completed under precisely controlled temperature and residence time conditions to ensure product consistency and high quality.

[0003] Currently, sintering of ferric phosphate is mostly achieved through continuous heat treatment using rotary kilns. Traditional rotary kilns rely heavily on gas combustion for heating, with heat transferred to the material layer primarily through flame radiation and high-temperature flue gas convection. However, this heating method suffers from problems such as localized high-temperature zones leading to overburning, large temperature fluctuations affecting crystallinity, and complex exhaust emissions. In recent years, with the increasing demand for green manufacturing and precise temperature control, electrically heated rotary kilns have gradually become the next-generation equipment for high-performance ferric phosphate preparation due to their advantages such as uniform heating, absence of combustion byproducts, and ease of automated control.

[0004] Although electrically heated rotary kilns offer good heat source controllability, they still face numerous challenges in actual process optimization. Firstly, the kiln interior is a typical multiphase, multi-field coupled system: solid particles tumble and fall continuously as the kiln rotates, exchanging momentum, heat, and mass with the gaseous medium; simultaneously, electrical energy is converted into Joule heat through resistance wires, conducted through the cylinder wall to the material bed, accompanied by radiation and convection heat transfer; furthermore, iron phosphate undergoes exothermic / endothermic chemical reactions such as dehydration and sulfur impurity decomposition during heating, further exacerbating the system's nonlinearity. These highly coupled processes make it difficult to fully capture their internal spatiotemporal evolution through experimental methods.

[0005] In existing technologies, the analysis of rotary kiln sintering processes mainly relies on empirical trial and error or simplified single-field model simulations. For example, thermocouples are used to measure the surface temperature of the kiln body, but the sampling frequency is low (about 1 Hz) and the true temperature distribution in the high-temperature zone inside the kiln cannot be obtained, making it particularly difficult to monitor the thermal response characteristics inside the material layer. Alternatively, data-driven models (such as LSTM and 3DCNN) are used to predict temperature change trends, but due to the simplistic nature of the models, their generalization ability is poor when operating conditions change or raw material batches differ, and the physical rationality of the thermal gradient region cannot be guaranteed. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a simulation calculation method, apparatus, equipment and medium for anhydrous ferric phosphate sintering in a rotary kiln.

[0007] To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows: In a first aspect, the present invention provides a simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln, the method comprising: Obtain the structural parameters of the electrically heated rotary kiln, and construct a three-dimensional geometric model of the rotary kiln based on the structural parameters; The three-dimensional geometric model of the rotary kiln is meshed to generate a discretized rotary kiln computational domain model that can be used for numerical simulation. By integrating pre-established gas-solid two-phase flow model, electrothermal conversion model, heat transfer model and chemical reaction kinetics model into the rotary kiln computational domain model, a multi-physics field coupled simulation model of the rotary kiln is obtained. Based on the multi-physics coupled simulation model of the rotary kiln, the sintering process of anhydrous ferric phosphate in the rotary kiln is simulated and calculated to obtain a multi-physics dynamic evolution dataset in the rotary kiln.

[0008] Optionally, the step of meshing the three-dimensional geometric model of the rotary kiln to generate a discretized computational domain model of the rotary kiln that can be used for numerical simulation includes: The cylindrical wall region, the guide plate region, and the gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln are respectively meshed to obtain the meshed three-dimensional geometric model of the rotary kiln. The mesh independence of the three-dimensional geometric model of the rotary kiln was verified. If the meshed three-dimensional geometric model of the rotary kiln passes the mesh independence verification, the meshed three-dimensional geometric model of the rotary kiln is used as the computational domain model of the rotary kiln.

[0009] Optionally, the step of meshing the cylinder wall region, the guide vane region, and the gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln includes: A boundary layer mesh is set for the cylinder wall region in the three-dimensional geometric model of the rotary kiln, and a preset wall function is used to handle the near-wall flow. The guide vane region in the three-dimensional geometric model of the rotary kiln is locally refined using a tetrahedral unstructured mesh; The gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln is set as a mixed hexahedral and tetrahedral mesh.

[0010] Optionally, the step of verifying the mesh independence of the meshed rotary kiln three-dimensional geometric model includes: As the number of grids in the three-dimensional geometric model of the rotary kiln increases from the first number to the second number, simulation calculations are performed based on the three-dimensional geometric model of the rotary kiln after meshing, and the standard deviation of the temperature field of the rotary kiln is obtained based on the simulation results. If the variation range of the standard deviation of the temperature field is less than the first preset range, then the three-dimensional geometric model of the gridded rotary kiln is determined to have passed the grid independence verification.

[0011] Optionally, the step of simulating the sintering process of anhydrous ferric phosphate in the rotary kiln based on the multiphysics coupled simulation model of the rotary kiln to obtain a multiphysics dynamic evolution dataset in the rotary kiln includes: The boundary conditions and initial conditions of the rotary kiln multiphysics coupling simulation model are set according to the actual working conditions to obtain the complete simulation system; The complete simulation system is numerically iteratively solved to obtain the multi-physics dynamic evolution dataset inside the rotary kiln, which includes simulation data on the temperature field, gas-solid flow field, component concentration field, and particle motion state over time.

[0012] Optionally, the step of numerically iteratively solving the complete simulation system to obtain the multiphysics dynamic evolution dataset within the rotary kiln, which includes simulation data on the evolution of temperature field, gas-solid flow field, component concentration field, and particle motion state over time, includes: The complete simulation system is numerically iteratively solved, and the temperature change of the kiln head region of the rotary kiln is monitored in real time during the solution process. Based on the temperature change of the kiln head region, it is determined whether the complete simulation system converges in the simulation calculation of the actual working condition. If the complete simulation system converges in the simulation calculation under the actual working condition, the numerical iterative solution is stopped, and the simulation data of the temperature field, gas-solid flow field, component concentration field and particle motion state evolution over time are obtained.

[0013] Optionally, the step of determining whether the complete simulation system converges in the simulation calculation under the actual working condition based on the temperature change in the kiln head region includes: If the temperature change between adjacent time steps is less than the second preset amplitude, then the complete simulation system is determined to have converged in the simulation calculation of the actual working condition.

[0014] Secondly, the present invention provides a simulation calculation device for anhydrous ferric phosphate sintering in a rotary kiln, the device comprising: The geometric modeling module is used to obtain the structural parameters of the electrically heated rotary kiln and construct a three-dimensional geometric model of the rotary kiln based on the structural parameters. The mesh generation module is used to mesh the three-dimensional geometric model of the rotary kiln and generate a discretized rotary kiln computational domain model that can be used for numerical simulation. The multiphysics coupling module is used to integrate pre-established gas-solid two-phase flow model, electrothermal conversion model, heat transfer model and chemical reaction kinetic model into the rotary kiln computational domain model to obtain a multiphysics coupling simulation model of the rotary kiln. The simulation solution module is used to simulate and calculate the sintering process of anhydrous ferric phosphate in the rotary kiln based on the multi-physics coupled simulation model of the rotary kiln, and obtain the dynamic evolution dataset of the multi-physics field in the rotary kiln.

[0015] Thirdly, the present invention provides an electronic device, including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor can execute the machine-executable instructions to implement the rotary kiln sintering anhydrous ferric phosphate simulation calculation method described in the first aspect above.

[0016] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in the first aspect above.

[0017] The present invention provides a simulation calculation method, apparatus, equipment, and medium for sintering anhydrous ferric phosphate in a rotary kiln. This method acquires the structural parameters of an electrically heated rotary kiln and constructs a three-dimensional geometric model of the kiln based on these parameters. The three-dimensional geometric model is then meshed to generate a discretized computational domain model of the rotary kiln suitable for numerical simulation. Pre-established gas-solid two-phase flow models, electrothermal conversion models, heat transfer models, and chemical reaction kinetic models are integrated into the computational domain model to obtain a multi-physics coupled simulation model of the rotary kiln. Based on this multi-physics coupled simulation model, the sintering process of anhydrous ferric phosphate in the rotary kiln is simulated, resulting in a multi-physics dynamic evolution dataset within the rotary kiln. By constructing a high-precision three-dimensional geometric model of an electrically heated rotary kiln and combining it with a meshed model and an integrated multi-physics coupling model of gas-solid two-phase flow, electrothermal conversion, heat transfer, and chemical reaction kinetics, the embodiments of this invention achieve full-scale dynamic simulation of the complex sintering process inside the rotary kiln. Ultimately, a multi-physics spatiotemporal evolution dataset is obtained, which not only overcomes the limitations of traditional experimental methods in real-time observation of internal processes, but also improves the scientific nature of process parameter optimization and the control capability of product consistency, providing strong digital support for the precise control and green and efficient production of anhydrous ferric phosphate sintering process.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This figure shows a schematic block diagram of an electronic device provided by an embodiment of the present invention; Figure 2 A schematic flowchart of a simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln, provided by an embodiment of the present invention, is shown. Figure 3 A simplified schematic diagram of a rotary kiln structure provided by an embodiment of the present invention is shown; Figure 4 This diagram illustrates a gas and particle heat transfer process within a rotary kiln, as provided in an embodiment of the present invention. Figure 5 The diagram shows a functional block diagram of a rotary kiln sintering anhydrous ferric phosphate simulation calculation device provided in an embodiment of the present invention.

[0021] Icons: 100 - Electronic device; 110 - Memory; 120 - Processor; 130 - Communication module; 200 - Rotary kiln sintering anhydrous iron phosphate simulation computing device; 201 - Geometric modeling module; 202 - Mesh generation module; 203 - Multiphysics coupling module; 204 - Simulation solution module. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0023] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0024] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0025] Please refer to Figure 1 This is a block diagram of an electronic device 100. The electronic device 100 includes a memory 110, a processor 120, and a communication module 130. The memory 110, processor 120, and communication module 130 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0026] The memory 110 is used to store programs or data. The memory 110 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0027] The processor 120 is used to read / write data or programs stored in the memory 110 and to perform corresponding functions.

[0028] The communication module 130 is used to establish a communication connection between the electronic device 100 and other communication terminals through the network, and to send and receive data through the network.

[0029] It should be understood that, Figure 1 The structure shown is only a schematic diagram of the electronic device 100. The electronic device 100 may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1The different configurations shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof.

[0030] To overcome the shortcomings of the existing technology, this invention provides a simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln, which will be described in detail below.

[0031] Please refer to Figure 2 The simulation calculation method for sintering anhydrous ferric phosphate in a rotary kiln includes steps S101 to S104.

[0032] S101, obtain the structural parameters of the electrically heated rotary kiln, and construct a three-dimensional geometric model of the rotary kiln based on the structural parameters.

[0033] In this embodiment of the invention, in order to achieve high-precision numerical simulation of the sintering process in an electrically heated rotary kiln, it is first necessary to obtain the structural parameters of an actual industrial rotary kiln and construct an accurate three-dimensional geometric model based on these parameters to ensure the authenticity and engineering applicability of the subsequent computational fluid dynamics simulation.

[0034] like Figure 3 As shown, a rotary kiln typically includes a feeding zone and a heating zone. The structural parameters of a rotary kiln include, but are not limited to: furnace diameter, total kiln length, heating section length, cooling section length, kiln inclination angle, number, size, and arrangement of lifters and guide plates, and material type.

[0035] For example, as shown in Table 1 below, the rotary kiln has a furnace diameter of 2000mm, a total length of 20000mm, and a heating section length of 16000mm; the inclination angle of the kiln is 0° to 2.5°, and can be set to 2° to ensure that the material is smoothly conveyed along the axial direction in the kiln; the lifting plates are 200mm×50mm×4mm in size, evenly distributed along the circumference, and arranged at a 30° angle to the axial direction to enhance the efficiency of material tumbling and heat exchange; the guide plates are 230mm×200mm×4mm in size, arranged in sets every 1.5m along the axial direction, for a total of 10 sets, to guide the flow of material and prevent accumulation.

[0036] Table 1

[0037] Based on the acquired structural parameters, a full-size 3D geometric model of the rotary kiln was constructed using 3D modeling software (such as SolidWorks and AutoCAD). During the modeling process, non-critical structural features (such as bolt holes and local reinforcing ribs) were reasonably simplified to reduce meshing complexity and improve computational efficiency, while key structures affecting the flow field and heat transfer (such as skimmers, guide vanes, and heating zone boundaries) were retained to ensure accurate reconstruction of the physical processes.

[0038] It is important to note that different materials are used for the high-temperature heating section and the low-temperature feeding / discharging section (310S stainless steel for the high-temperature section and 2205 duplex stainless steel for the low-temperature section). This is reflected in the model by defining the material properties in different zones, which provides a basis for subsequent heat conduction and thermal stress analysis.

[0039] S102, mesh the three-dimensional geometric model of the rotary kiln to generate a discretized computational domain model of the rotary kiln that can be used for numerical simulation.

[0040] In a possible implementation, step S102 includes sub-steps S102-1 to S102-3.

[0041] S102-1, the cylinder wall region, guide plate region and gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln are respectively meshed to obtain the meshed three-dimensional geometric model of the rotary kiln.

[0042] In this embodiment of the invention, by implementing differentiated and refined meshing strategies for different physical regions in the model, especially for the cylinder wall region, the guide plate region, and the gas-solid coexistence region, meshing processing is carried out to adapt to their flow and heat transfer characteristics, and finally a high-fidelity meshed three-dimensional model is obtained.

[0043] Specifically, a boundary layer mesh is set for the cylinder wall region in the three-dimensional geometric model of the rotary kiln, and a preset wall function is used to handle the near-wall flow; a tetrahedral unstructured mesh is used to locally refine the guide plate region in the three-dimensional geometric model of the rotary kiln; and the gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln is set as a hybrid mesh of hexahedrons and tetrahedrons.

[0044] Since the cylinder wall is the main interface for the transfer of heat from electric heating to the material particles, the velocity and temperature gradients in the near-wall region are significant, directly affecting the gas-solid heat transfer efficiency and particle motion behavior. Therefore, a multi-layer boundary layer mesh is generated in the normal direction of the inner surface of the cylinder, using an O-type mesh topology. This ensures that the height of the first mesh layer meets the design requirement of y⁺≈30 to adapt to the standard wall function, thereby accurately capturing the velocity and temperature distribution characteristics within the near-wall turbulent boundary layer without significantly increasing the computational load. The preferred number of boundary layers is 5–8, with a growth rate of 1.2–1.4, ensuring smooth gradient changes and good numerical stability.

[0045] As a key structure guiding the axial transport of materials, preventing accumulation, and improving the uniformity of the material layer, the guide vane is surrounded by complex flow separation, vortex formation, and particle redistribution phenomena. To accurately analyze the local flow field structure in this region, an unstructured tetrahedral mesh was used for local refinement, with the mesh size controlled within 0.1m. Simultaneously, the mesh was further refined at the edges and sharp corners of the guide vane, areas prone to flow distortion, to enhance the simulation capability of fluid separation and reattachment processes. This approach balances geometric adaptability and local resolution, effectively improving the simulation fidelity of complex structural regions.

[0046] The gas-solid two-phase coexistence region encompasses the main material filling area and gas flow space within the kiln, involving complex physical processes such as particle group motion, gas turbulence, gas-solid momentum exchange, and multiphase heat transfer. To balance computational efficiency and simulation accuracy, a hybrid mesh strategy is adopted: the mainstream region primarily uses a structured hexahedral mesh to ensure high numerical accuracy and fast convergence speed; in areas with drastically changing flow fields, such as near the particle inlet and in the scraper disturbance zone, an unstructured tetrahedral mesh is used to enhance adaptability to complex geometries and dynamic interfaces. This hybrid mesh arrangement retains the computational efficiency of the main region while ensuring spatial resolution in key interaction areas, significantly improving the accuracy of gas-solid two-phase coupling simulations.

[0047] Meshing can be performed using a preprocessing platform (such as ICEM CFD or ANSYS Meshing), and the mesh can be screened and optimized using mesh quality check indicators (such as Skewness < 0.8, Orthogonal Quality > 0.2) to ensure no negative volume and low twisted elements, thus guaranteeing the stability and convergence of the subsequent solution process.

[0048] This invention implements a differentiated meshing strategy for the cylinder wall, guide vanes, and gas-solid coexistence region. Specifically, it combines the boundary layer mesh with wall functions, locally densifies the tetrahedral mesh in the guide vane region, and uses a hybrid hexahedral-tetrahedral mesh in the main body region. This achieves high-resolution spatial discretization of the complex multiphysics environment inside the rotary kiln. The resulting meshed three-dimensional geometric model not only realistically reflects the structural characteristics of the equipment but also provides a high-precision and high-stability computational foundation for subsequent electro-thermal-mass coupling simulations. It is a key technical support for achieving accurate prediction and process optimization of the sintering process.

[0049] S102-2, Verify the mesh independence of the three-dimensional geometric model of the rotary kiln after meshing.

[0050] In this embodiment of the invention, in order to ensure that the computational fluid dynamics simulation results are not affected by the grid density and to ensure the spatial convergence and engineering reliability of the numerical solution, after completing the partitioned gridding process of the three-dimensional geometric model of the rotary kiln, further grid independence verification is carried out. The aim is to confirm that the number of grids used is sufficient to accurately capture the distribution characteristics of key physical fields (especially temperature fields) in the kiln, and to avoid increased errors due to excessively coarse grids or wasted computational resources due to excessively dense grids.

[0051] The verification process for "mesh independence verification" can be as follows: as the number of grids in the meshed rotary kiln 3D geometric model increases from a first number to a second number, simulation calculations are performed based on the meshed rotary kiln 3D geometric model, and the standard deviation of the temperature field of the rotary kiln is obtained based on the simulation results. If the change range of the temperature field standard deviation is less than a first preset range, then the meshed rotary kiln 3D geometric model is determined to have passed the mesh independence verification.

[0052] That is, as the total number of meshes in the three-dimensional geometric model of the rotary kiln is gradually increased from a first number to a second number, steady-state or transient simulation calculations are performed under the same boundary conditions. For example, the first number can be 500,000 elements, the second number can be 2 million elements, and comparative models with 1 million and 1.5 million elements are built in between to form a multi-level mesh system.

[0053] Each simulation was based on the same physical model settings, including the gas-solid two-phase Eulerian-Lagrange coupling method, the standard k-ε turbulence model, the gray body radiation model, the user-defined function (UDF) for electrothermal conversion, and the coupled heat transfer and chemical reaction model. Consistent initial and boundary conditions (such as wall temperature of 700°C, feed mass flow rate of 8 kg / s, and gas inlet velocity of 15 m / s) were applied to eliminate the influence of non-spatial discretization factors on the results.

[0054] After each simulation is completed, the full-field temperature data of the central region of the heating section inside the kiln (such as the region from x=5m to x=18m along the axial direction) is extracted, and its temperature field standard deviation is calculated as a key indicator to measure the uniformity of temperature distribution and numerical stability. The relative variation of the temperature field standard deviation under adjacent grid densities is further calculated.

[0055] If, during the process of increasing the number of grids from the first quantity to the second quantity, the change in the standard deviation of the temperature field is less than the first preset range (e.g., 3%), then it is determined that the current grid system has reached the convergence state, that is, the temperature field is no longer sensitive to the grid density, and thus it is determined that the three-dimensional geometric model of the gridded rotary kiln has passed the grid independence verification.

[0056] For example, when the number of grids increases from 1.5 million to 2 million, the standard deviation of the temperature field decreases from ±12.6K to ±12.3K, with a relative change of only 2.4%, which meets the preset threshold requirement. Therefore, it is determined that a grid number of around 1.5 million can achieve the best balance between accuracy and efficiency.

[0057] Through the above-described grid independence verification process, the embodiments of the present invention effectively eliminate the interference of spatial discretization errors on simulation results, ensuring that subsequent technical conclusions regarding temperature field evolution, component distribution, reaction rate prediction, and energy consumption analysis have high credibility and engineering guidance significance.

[0058] S102-3, after the three-dimensional geometric model of the gridded rotary kiln passes the grid independence verification, the three-dimensional geometric model of the gridded rotary kiln is used as the computational domain model of the rotary kiln.

[0059] Understandably, after verifying the mesh independence of the three-dimensional geometric model of the meshed rotary kiln, if it is confirmed that the simulation results have spatial convergence, the verified mesh model is determined as the computational domain basis for subsequent multiphysics coupled simulations, i.e., the rotary kiln computational domain model.

[0060] The rotary kiln computational domain model not only includes complete geometric morphology information (such as the structure of the cylinder, lifting plates, and guide plates), but also integrates an optimized mesh topology: including the boundary layer mesh at the cylinder wall, the locally refined tetrahedral mesh in the guide plate region, and the hexahedral-tetrahedral hybrid mesh system in the gas-solid two-phase coexistence region, which can accurately support the numerical solution process of transient, unsteady, and multiphase multi-field coupling.

[0061] S103 integrates pre-established gas-solid two-phase flow model, electrothermal conversion model, heat transfer model and chemical reaction kinetic model into the rotary kiln computational domain model to obtain a multi-physics field coupled simulation model of the rotary kiln.

[0062] Based on the established rotary kiln computational domain model verified by grid independence, this embodiment of the invention further integrates multiple interrelated physical field sub-models within it, including a gas-solid two-phase flow model, an electrothermal conversion model, a heat transfer model, and a chemical reaction kinetic model. A highly integrated multi-physics coupled simulation model of the rotary kiln is constructed through numerical coupling to achieve full-scale, high-fidelity simulation of the complex sintering process in an electrically heated rotary kiln.

[0063] Among them, the gas-solid two-phase flow model is used to describe the dynamic interaction between gas flow and iron phosphate particle movement in the rotary kiln.

[0064] The embodiments of the present invention employ the Euler-Euler two-fluid method, which treats both the gas phase (i.e., air and the reaction-generated gas) and the solid phase (i.e., iron phosphate particles) as continuous media, and couples the interaction forces between the two through momentum exchange source terms, including drag force, virtual mass force and lift force.

[0065] The gas-solid two-phase flow model fully considers the reaction effect of particle concentration changes on gas turbulence characteristics, and can accurately capture key flow features such as material layer tumbling, particle accumulation, and airflow disturbance. Combining the standard k-ε turbulence model with the pressure-velocity coupled SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) algorithm ensures the stability and convergence of the gas phase flow field.

[0066] The gas-solid two-phase flow model satisfies the following formula: (1) Continuity equation:

[0067] In the formula, ρ The density of the gas is kg / m³. 3 u is the gas velocity, in m / s; S m This is a gas phase mass source term.

[0068] (2) Momentum equation:

[0069] In the formula, p represents pressure. μ For dynamic viscosity, f i It is the force between the gas phases; (3) Energy equation:

[0070] In the formula, T is the gas phase temperature; λ is the gas phase thermal conductivity. c p Specific heat capacity of the gas; q m The heat source includes radiative heat and convective heat transfer between particles.

[0071] The flow inside the rotary kiln is turbulent; the embodiments of this invention employ standard turbulent flow. k-ε The model is used for numerical simulation.

[0072] k-equation:

[0073] ε equation:

[0074] In the formula, k It is turbulent kinetic energy; ε The rate of turbulent kinetic energy dissipation; μMolecular viscosity; μ t It is turbulent viscosity. G k It is the turbulent kinetic energy generated by the average velocity gradient. G b It is turbulent kinetic energy generated by buoyancy.

[0075] The electrothermal conversion model is used to characterize the Joule heat distribution generated on the kiln wall after the resistance wire is energized and its transfer to the interior. In this embodiment of the invention, a volumetric heat source term q is defined in the cylinder wall region using a user-defined function, and its expression is:

[0076] In the formula, q Volumetric heat source intensity (W / m) 3 ), which is temperature-dependent; J(T) Current density, A / m 2 , σ(T) ν is the electrical conductivity of the conductor (S / m).

[0077] like Figure 4 As shown, the heat transfer model covers three main heat transfer mechanisms: heat conduction, heat convection, and heat radiation, realizing the modeling of the complete heat transfer chain from the wall to the particle bed.

[0078] The convective heat transfer is performed using the Li-Mason model, and the convective heat transfer coefficient is calculated as follows:

[0079]

[0080]

[0081] In the formula, u The air velocity is taken as 3.4 m / s. l The length of the heating section is taken as 16m. v This is the kinematic viscosity of air, with a value of 15.06 × 10⁻⁶. -6 m 2 / s; Pr is the Prandtl number, with a value of 0.7. λ The thermal conductivity is taken as 2.59 × 10⁻⁶. -2 W / (m·K).

[0082] For radiative heat transfer, the emissivity of the particle surface needs to be set. Since the particle position is constantly changing, Tempreature-Update needs to be added to ensure the particle temperature is updated. The expression for the temperature change of a single particle over time is:

[0083] In the formula,m p It's about quality; c p It is specific heat capacity; T It is the particle temperature; Q heat It is the sum of heat flux from heat exchange and heat conduction.

[0084] The thermal radiation model is as follows:

[0085] In the formula, σ It is the blackbody radiation constant. ε p It is the emissivity of the particle; T local It is the average temperature of a closed grid cell.

[0086] In actual operating conditions, the heat transfer mainly comes from heat conduction between the particles and the wall, and its expression is:

[0087] In the formula, k p It is the thermal conductivity of particles. F N It is the normal component of the contact force; r It is the effective radius of the contact area. E It is the effective elastic modulus of the particle.

[0088] A chemical reaction kinetic model was used to simulate the process of dehydration of ferric phosphate dihydrate to anhydrous ferric phosphate at high temperature, as well as the decomposition reaction of residual sulfuric acid impurities.

[0089] A chemical reaction model is added to the fluid dynamics simulation settings, employing a finite rate / eddy dissipation model. The reaction rate is jointly controlled by diffusion and chemical reaction. The dehydration process conforms to the Arrhenius equation, and the reaction rate can be expressed as:

[0090] In the formula k s is the reaction rate constant. -1 A is the pre-exponential factor, with a value of 1.2 × 10⁻⁶. 8 s -1 E a The activation energy is 100 kJ / mol; R is the gas constant; and T is the absolute temperature (K).

[0091] As shown in the chemical equation below, during the sintering of anhydrous ferric phosphate in a rotary kiln, the main phases are gas and solid. Ferric phosphate dihydrate is a wet material, which undergoes a dehydration reaction and decomposition of sulfuric acid into a low-humidity mixture of sulfur dioxide, water vapor, and oxygen after high-temperature sintering. The sulfuric acid decomposes in two steps at high temperature, which is a gas-phase reaction controlled by both molecular diffusion and chemical reaction. The first step is a rapid reaction, and the second step is a slow reaction.

[0092]

[0093]

[0094]

[0095] The activation energy E of the first step fast reaction a =90 KJ / mol, A is 2×10 12 s -1 The activation energy E of the second slow reaction step a =160 KJ / mol, A can take the value 3.2×10 10 s -1 The reaction order is 2 for all of them.

[0096] By integrating the gas-solid two-phase flow model, electrothermal conversion model, heat transfer model, and chemical reaction kinetics model into the validated rotary kiln computational domain model, the multi-physics coupled simulation model of the rotary kiln described in this invention is formed. This model breaks through the limitations of traditional single-physics simulation and can simultaneously predict the spatiotemporal evolution of the temperature field inside the kiln, the component concentration distribution, particle motion trajectory, and reaction conversion rate, providing comprehensive digital tool support for process optimization, energy consumption analysis, and product quality control.

[0097] S104, based on the multi-physics coupled simulation model of rotary kiln, simulates the sintering process of anhydrous ferric phosphate in rotary kiln and obtains a multi-physics dynamic evolution dataset in rotary kiln.

[0098] In a possible implementation, step S104 includes sub-steps S104-1 to S104-2.

[0099] S104-1 sets the boundary conditions and initial conditions of the rotary kiln multi-physics coupling simulation model according to the actual working conditions to obtain the complete simulation system.

[0100] Based on the establishment of a multi-physics coupling simulation model of a rotary kiln, in order to ensure that the simulation results can truly reflect the operating status of the industrial site, this embodiment of the invention further sets the boundary conditions and initial conditions of the simulation model according to the actual production conditions, thereby forming a complete simulation system with engineering prediction capabilities.

[0101] The boundary conditions are set for multiple key areas, including the gas inlet, solid particle inlet, outlet, and wall surface, and are configured strictly according to the operating parameters measured on-site.

[0102] For example, the gas inlet boundary conditions, particle inlet boundary conditions, pressure outlet boundary conditions, and wall boundary conditions are set based on the operating parameters shown in Table 2 below.

[0103] Table 2

[0104] Gas inlet boundary conditions: set at the feed end of the rotary kiln, using a velocity inlet type. Air enters the kiln body at a flow rate of 15 m / s, with an excess air coefficient of 1.15, used to provide the oxygen required for the reaction and participate in convective heat transfer; turbulence intensity is set to 5%, and the hydraulic diameter is calculated based on the equivalent inlet section to ensure that the turbulence model (k-ε) input is reasonable.

[0105] Particle inlet boundary conditions: Located at the feed port at the front of the kiln body, using a mass flow rate inlet method. Wet ferric phosphate is continuously fed at a mass flow rate of 8 kg / s (i.e., 2020 kg / h), with a particle size distribution following the Rosin-Rammler function distribution, d... 10 =10μm, used to characterize the wide distribution characteristics of actual materials; the initial temperature of the particles was set to room temperature (25°C), and the moisture content was set to approximately 20% based on the measured value.

[0106] Pressure outlet boundary conditions: set at the discharge end of the kiln body, using the pressure outlet type, with a gauge pressure of 0 Pa (atmospheric pressure), allowing gas and a small amount of dust to escape, while the reverse flow temperature is set to 700°C, and the composition is set to typical exhaust gas components (mixture of H2O, SO2, O2, and N2) to simulate the actual exhaust process.

[0107] Wall boundary conditions: The cylinder wall serves as the electric heating heat source, with temperature zones set. The high-temperature roasting section (16m in length) is kept at a constant temperature of 800°C, while the low-temperature feeding and discharging section is kept at a constant temperature of 300°C, simulating the actual heating strategy of segmented temperature control by resistance wire. The wall emissivity is set to 0.85 (typical value for 310S stainless steel), and the thermal radiation behavior is handled using a gray body radiation model. The cylinder tilt angle is set to 2°, and rotational motion (0.22r / min) is reflected in the dynamic mesh or coordinate transformation.

[0108] Initial conditions are used to define the physical field distribution state in the entire computational domain at the time of simulation startup, so as to avoid numerical oscillation or divergence caused by sudden loading.

[0109] For example, the initial conditions can be set as follows: at the initial moment, the gas inside the kiln is air, the temperature is uniformly set to ambient temperature (25°C), and the pressure is standard atmospheric pressure (101325 Pa); the solid particles are statically distributed at the bottom of the feed zone, with a filling rate of approximately 15% and a bulk density of 0.6 kg / m³. 3 The wall temperature is initialized by gradually increasing the temperature in zones to avoid the illusion of thermal shock; the chemical reaction is initially shut off and automatically activated after the temperature rises to the dehydration initiation temperature (approximately 200°C).

[0110] All boundaries and initial conditions are accurately loaded through the graphical interface of the solver platform (such as ANSYS Fluent or Open FOAM) or TUI / UDF scripts, and a dynamic update mechanism is supported. For example, the inlet flow rate or wall heat flow can be adjusted according to real-time feedback to achieve closed-loop simulation control.

[0111] By setting the boundaries and initial conditions based on real operating parameters as described above, this embodiment of the invention transforms the multiphysics coupling simulation model from a theoretical framework into a complete simulation system with practical engineering value. This complete simulation system can not only reproduce the temperature field, flow field, and reaction conversion rate distribution under steady-state operating conditions, but also simulate the dynamic response behavior under start-up and shutdown processes and disturbed conditions (such as feed fluctuations and power changes), providing a highly reliable data foundation for process optimization, fault diagnosis, and intelligent control.

[0112] S104-2, numerical iterative solution of the complete simulation system, to obtain a multi-physics dynamic evolution dataset of the rotary kiln containing simulation data of temperature field, gas-solid flow field, component concentration field and particle motion state over time.

[0113] In this embodiment of the invention, the implementation process of step S104-2 may be as follows: numerical iterative solution is performed on the complete simulation system, and the temperature change of the kiln head region of the rotary kiln is monitored in real time during the solution process. Based on the temperature change of the kiln head region, it is determined whether the complete simulation system converges in the simulation calculation under actual working conditions. If the complete simulation system converges in the simulation calculation under actual working conditions, the numerical iterative solution is stopped, and the simulation data of the temperature field, gas-solid flow field, component concentration field and particle motion state evolution over time are obtained.

[0114] The implementation process of "determining whether the complete simulation system converges in the simulation calculation under actual working conditions based on the temperature change in the kiln head area" can be as follows: if the amplitude of the temperature change between adjacent time steps is less than the second preset amplitude, then it is determined that the complete simulation system converges in the simulation calculation under the actual working conditions.

[0115] After constructing a complete simulation system that includes a multiphysics coupling model and actual boundaries and initial conditions, this embodiment of the invention uses a transient solution strategy to perform numerical iterative solutions on the system in order to obtain dynamic simulation data of the temperature field, gas-solid flow field, component concentration field and particle motion state evolving over time during the actual operation of the electrically heated rotary kiln.

[0116] The complete simulation system was imported into a solver (such as ANSYS Fluent or Open FOAM). The SIMPLE algorithm based on pressure-velocity coupling was used for pressure correction. The momentum, energy, and component transport equations were all discretized using a second-order upwind scheme, such as the QUICK scheme, to improve the accuracy of capturing strong convection terms. An implicit transient scheme was used for time progression, with a time step of 1×10⁻⁶. -3 s, to ensure that computational stability is maintained while taking into account temporal resolution.

[0117] During the solution process, a real-time monitoring mechanism for key physical quantities was established to evaluate the convergence and physical rationality of the calculation process. Among these, the temperature change trend in the rotary kiln head region (i.e., the axial range of 0–2 m near the feed end) was monitored as a key area. As the initial heating zone of the material and the zone where a large amount of moisture evaporates, the thermal response characteristics of the kiln head region have a significant impact on the overall energy balance. Furthermore, it is prone to temperature fluctuations due to heat absorption by wet material and airflow disturbances, making it a crucial observation window for determining whether the system is approaching a steady state.

[0118] To automatically determine the convergence of the calculation, this embodiment of the invention extracts the average temperature value of the kiln head region during continuous time step iterations and calculates the temperature change amplitude between adjacent time steps. If the temperature change amplitude is less than a second preset amplitude (e.g., 0.5°C), it is determined that the temperature in the kiln head region tends to stabilize, indicating that the physical process of the complete simulation system under the current actual working conditions has reached a quasi-steady state or a periodic steady state, that is, the complete simulation system has converged in the simulation calculation under the actual working conditions.

[0119] Furthermore, other auxiliary convergence indicators can be combined for comprehensive judgment, including: the temperature distribution at the furnace centerline no longer drifts significantly, the concentration fluctuation of the outlet gas components is less than ±2%, and the change rate of wall heat flux is less than 1% / step, etc., to enhance the robustness of the convergence criteria.

[0120] Once the complete simulation system is confirmed to have converged, the numerical iteration solution is immediately stopped, and the full-field simulation data at the current moment and in the historical time series is saved. The obtained data includes, but is not limited to: the spatiotemporal evolution distribution of the temperature field in three-dimensional space; the gas phase velocity field and solid phase particle trajectory and concentration distribution (gas-solid flow field); the component concentration field of reaction products such as water vapor, SO2, and O2; the motion state of iron phosphate particles (velocity, residence time, tumbling frequency, contact heat transfer path, etc.); and the spatial distribution of local reaction rate and dehydration conversion rate.

[0121] These high-dimensional, high-resolution simulation data constitute a comprehensive digital representation of the sintering process in an electrically heated rotary kiln, which can be used for subsequent process analysis, hotspot identification, energy consumption assessment, and operating parameter optimization.

[0122] This invention, through real-time monitoring of temperature changes in the kiln head region during the solution process and using whether the temperature change amplitude in adjacent time steps is less than a preset threshold as the core criterion, achieves dynamic and objective determination of the convergence of simulation calculations. This avoids subjective errors caused by human experience judgment, improves the automation level and reliability of the simulation process, and is a necessary step in building an efficient and reliable digital twin system.

[0123] To perform the corresponding steps in the above embodiments and various possible methods, an implementation method of a rotary kiln sintering anhydrous ferric phosphate simulation calculation device 200 is given below. Further, please refer to... Figure 5 , Figure 5 This is a functional block diagram of a rotary kiln sintering anhydrous ferric phosphate simulation calculation device 200 provided in an embodiment of the present invention. It should be noted that the basic principle and technical effects of the rotary kiln sintering anhydrous ferric phosphate simulation calculation device 200 provided in this embodiment are the same as those in the above embodiments. For the sake of brevity, any parts not mentioned in this embodiment can be referred to the corresponding content in the above embodiments. The rotary kiln sintering anhydrous ferric phosphate simulation calculation device 200 includes: The geometric modeling module 201 is used to obtain the structural parameters of the electrically heated rotary kiln and construct a three-dimensional geometric model of the rotary kiln based on the structural parameters.

[0124] The mesh generation module 202 is used to mesh the three-dimensional geometric model of the rotary kiln to generate a discretized rotary kiln computational domain model that can be used for numerical simulation.

[0125] The multiphysics coupling module 203 is used to integrate a pre-established gas-solid two-phase flow model, electrothermal conversion model, heat transfer model and chemical reaction kinetic model into the rotary kiln computational domain model to obtain a multiphysics coupling simulation model of the rotary kiln.

[0126] The simulation solution module 204 is used to simulate and calculate the sintering process of anhydrous ferric phosphate in the rotary kiln based on the multi-physics coupled simulation model of the rotary kiln, and obtain the dynamic evolution dataset of the multi-physics field in the rotary kiln.

[0127] Optionally, the above modules can be stored in the form of software or firmware. Figure 1 The memory 110 shown is either stored in or embedded in the operating system (OS) of the electronic device 100, and can be used by... Figure 1 The processor 120 executes the program. Meanwhile, the data and program code required to execute the above modules can be stored in the memory 110.

[0128] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. 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 marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive 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 a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0129] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0130] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, electronic device 100, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0131] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln, characterized in that, The method includes: Obtain the structural parameters of the electrically heated rotary kiln, and construct a three-dimensional geometric model of the rotary kiln based on the structural parameters; The three-dimensional geometric model of the rotary kiln is meshed to generate a discretized rotary kiln computational domain model that can be used for numerical simulation. By integrating pre-established gas-solid two-phase flow model, electrothermal conversion model, heat transfer model and chemical reaction kinetics model into the rotary kiln computational domain model, a multi-physics field coupled simulation model of the rotary kiln is obtained. Based on the multi-physics coupled simulation model of the rotary kiln, the sintering process of anhydrous ferric phosphate in the rotary kiln is simulated and calculated to obtain a multi-physics dynamic evolution dataset in the rotary kiln.

2. The simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in claim 1, characterized in that, The step of meshing the three-dimensional geometric model of the rotary kiln to generate a discretized computational domain model of the rotary kiln that can be used for numerical simulation includes: The cylindrical wall region, the guide plate region, and the gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln are respectively meshed to obtain the meshed three-dimensional geometric model of the rotary kiln. The mesh independence of the three-dimensional geometric model of the rotary kiln was verified. If the meshed three-dimensional geometric model of the rotary kiln passes the mesh independence verification, the meshed three-dimensional geometric model of the rotary kiln is used as the computational domain model of the rotary kiln.

3. The simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in claim 2, characterized in that, The step of meshing the cylinder wall region, the guide vane region, and the gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln includes: A boundary layer mesh is set for the cylinder wall region in the three-dimensional geometric model of the rotary kiln, and a preset wall function is used to handle the near-wall flow. The guide vane region in the three-dimensional geometric model of the rotary kiln is locally refined using a tetrahedral unstructured mesh; The gas-solid coexistence region in the three-dimensional geometric model of the rotary kiln is set as a mixed hexahedral and tetrahedral mesh.

4. The simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in claim 2, characterized in that, The steps for verifying the mesh independence of the meshed three-dimensional geometric model of the rotary kiln include: As the number of grids in the three-dimensional geometric model of the rotary kiln increases from the first number to the second number, simulation calculations are performed based on the three-dimensional geometric model of the rotary kiln after meshing, and the standard deviation of the temperature field of the rotary kiln is obtained based on the simulation results. If the variation range of the standard deviation of the temperature field is less than the first preset range, then the three-dimensional geometric model of the gridded rotary kiln is determined to have passed the grid independence verification.

5. The simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in claim 1, characterized in that, The steps for simulating the sintering process of anhydrous ferric phosphate in a rotary kiln based on the multi-physics coupled simulation model of the rotary kiln, and obtaining the multi-physics dynamic evolution dataset in the rotary kiln, include: The boundary conditions and initial conditions of the rotary kiln multiphysics coupling simulation model are set according to the actual working conditions to obtain the complete simulation system; The complete simulation system is numerically iteratively solved to obtain the multi-physics dynamic evolution dataset inside the rotary kiln, which includes simulation data on the temperature field, gas-solid flow field, component concentration field, and particle motion state over time.

6. The simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in claim 5, characterized in that, The step of performing numerical iterative solutions on the complete simulation system to obtain the multi-physics dynamic evolution dataset within the rotary kiln, which includes simulation data on the temperature field, gas-solid flow field, component concentration field, and particle motion state over time, includes: The complete simulation system is numerically iteratively solved, and the temperature change of the kiln head region of the rotary kiln is monitored in real time during the solution process. Based on the temperature change of the kiln head region, it is determined whether the complete simulation system converges in the simulation calculation of the actual working condition. If the complete simulation system converges in the simulation calculation under the actual working condition, the numerical iterative solution is stopped, and the simulation data of the temperature field, gas-solid flow field, component concentration field and particle motion state evolution over time are obtained.

7. The simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in claim 6, characterized in that, The step of determining whether the complete simulation system converges in the simulation calculation of the actual working condition based on the temperature change in the kiln head area includes: If the temperature change between adjacent time steps is less than the second preset amplitude, then the complete simulation system is determined to have converged in the simulation calculation of the actual working condition.

8. A simulation calculation device for anhydrous ferric phosphate sintering in a rotary kiln, characterized in that, The device includes: The geometric modeling module is used to obtain the structural parameters of the electrically heated rotary kiln and construct a three-dimensional geometric model of the rotary kiln based on the structural parameters. The mesh generation module is used to mesh the three-dimensional geometric model of the rotary kiln and generate a discretized rotary kiln computational domain model that can be used for numerical simulation. The multiphysics coupling module is used to integrate pre-established gas-solid two-phase flow model, electrothermal conversion model, heat transfer model and chemical reaction kinetic model into the rotary kiln computational domain model to obtain a multiphysics coupling simulation model of the rotary kiln. The simulation solution module is used to simulate and calculate the sintering process of anhydrous ferric phosphate in the rotary kiln based on the multi-physics coupled simulation model of the rotary kiln, and obtain the dynamic evolution dataset of the multi-physics field in the rotary kiln.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor executing the machine-executable instructions to implement the rotary kiln sintering anhydrous ferric phosphate simulation calculation method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the simulation calculation method for anhydrous ferric phosphate sintering in a rotary kiln as described in any one of claims 1-7.

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