Carbon immersion reduction lead-zinc reactor optimization method, system and medium

Abstract

The invention discloses an optimization method and system for a carbon immersion reduction lead-zinc reactor and a medium, and the method comprises the steps: presetting basic size parameters of an initial carbon immersion reduction lead-zinc reactor, and constructing a geometric model of a fluid computational domain of the carbon immersion reduction lead-zinc reactor; determining a reaction control equation of the geometric model; initializing operation parameters of the geometric model, and performing grid division on the geometric model; performing analogue simulation calculation based on the geometric model of grid division to obtain reaction parameters in the carbon immersion reduction lead-zinc reactor, and obtaining gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect based on the reaction parameters; judging whether the optimization basis meets a preset condition or not; if yes, ending simulation; and if not, adjusting the structure parameters and / or operation parameters of the reactor based on the optimization basis until the preset conditions are met. And efficient reduction and recovery of iron in the depleted slag are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of slag treatment, and in particular to an optimization method, system and medium for a carbon immersion reduction lead-zinc reactor. Background Art

[0002] With the intensified mining of high-grade lead and zinc resources, easy-to-smelt lead-zinc sulfide ores are becoming increasingly scarce. Currently, there are a large number of complex lead-zinc mixed ores, which have not been effectively utilized due to their complex composition and complex lead-zinc metal embedding, making it difficult to separate the valuable metals. Therefore, direct smelting of lead-zinc mixed ores without separation is a very effective way to solve the tight supply of lead and zinc industry resources in my country.

[0003] The existing lead-zinc reduction slag is mainly treated by fuming process, and zinc is produced in the form of secondary zinc oxide, which has low added value and still needs further treatment to obtain metallic zinc. At present, it is difficult to recycle iron resources in non-ferrous smelting slag such as depleted slag, and they have not been recycled, resulting in high-iron, low-calcium-silicon tailings that can only be used at low dosage and low value. Summary of the invention

[0004] In view of the deficiencies in the background technology, the present invention provides a method, system and medium for optimizing a carbon immersion reduction reactor for lead and zinc. The method realizes efficient reduction of lead and zinc components and metallic recovery of lead and zinc through electrically assisted carbon immersion reduction and zinc vapor condensation in a closed furnace; realizes efficient reduction and recovery of iron in depleted slag, and realizes the cascade recovery of lead, zinc and iron in smelting slag.

[0005] In a first aspect, the present invention provides a method for optimizing a carbon immersion reduction lead-zinc reactor, comprising:

[0006] S1: Preset the basic size parameters of the initial carbon immersion reduction lead-zinc reactor and construct a geometric model of the fluid calculation domain of the carbon immersion reduction lead-zinc reactor; wherein the geometric model simulates the upper and lower parts of the carbon immersion reduction lead-zinc reactor, the lower part of the model simulates the flow field changes and physical and chemical processes of the slag phase, and the upper part of the model simulates the flow field changes of the gas phase;

[0007] S2: determining a reaction control equation of the geometric model, wherein the reaction control equation is used to simulate a lead-zinc reduction process by carbon immersion in a reactor;

[0008] S3: Initializing the operating parameters of the geometric model and meshing the geometric model; wherein the operating parameters are corresponding boundary conditions and initial parameter values;

[0009] S3: Based on the meshed geometric model, simulation calculation is performed to obtain the reaction parameters inside the carbon immersion reduction lead-zinc reactor, and based on the reaction parameters, the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect are obtained;

[0010] Among them, one or more of the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect are selected as optimization basis;

[0011] S4: Determine whether the selected optimization basis meets the preset conditions: if so, output the basic size parameters of the lead-zinc reduction reactor; if not, adjust the structural parameters and / or operating parameters of the reactor based on the optimization basis and return to S3.

[0012] Furthermore, the reaction control equation of S2 is set as follows:

[0013] In order to describe the diffusion and convection process of substances in the reactor, the substance flux vector equation in the carbon immersion reduction lead-zinc reactor is set:

[0014]

[0015] Where i refers to the substance i in the reactor; N i is the material flux vector; D i is the diffusion coefficient of the substance, which indicates the diffusion ability of the substance in the cutoff, c i is the concentration of the substance, is the concentration of a substance c i The sum of the first-order partial differentials in three directions is used to describe the change in concentration; u is the velocity vector of the material fluid;

[0016] The mass transfer equation is used to describe the transfer of substances between different phases or regions, that is, the transmission and reaction process of the reactants in the reaction, including diffusion and convection processes. The concentrated species transfer model is selected to study chemical mass transfer to obtain the amount of change of the mass fraction of each substance over time. The concentrated species transfer model can calculate the mass fraction of all participating substances. The mass transfer equation is:

[0017]

[0018] Where ρ represents the fluid density (SI unit: kg / m 3 ), u represents the mass average velocity vector of the mixture (SI unit: m / s); ω i represents the quality score; j i Expresses the mass flux relative to the mass average velocity (SI unit: kg / m 2 ·s); R i Indicates the rate at which a substance is generated or consumed (SI unit: kg / m 3 s); is the Laplace operator.

[0019] The chemical reactions contained in the reactor include surface reactions and bulk reactions, and all the reactions involved are irreversible reactions; among them, the surface reactions include the reactions of carbon on the surface of the carbon rod with lead oxide, zinc oxide and zinc ferrite, and the chemical reaction formulas are as follows:

[0020] PbO(l)+C(ads)=Pb(g)+CO(g)

[0021] ZnO(l)+C(ads)=Zn(g)+CO(g)

[0022] ZnFe2O4(l)+2C(ads)=Zn(g)+2FeO(l)+2CO(g)

[0023] The bulk reaction includes the reaction of carbon particles with lead oxide, zinc oxide and zinc ferrite, and the chemical reaction formulas are shown below.

[0024] PbO(l)+C(s)=Pb(g)+CO(g)

[0025] ZnO(l)+C(s)=Zn(g)+CO(g)

[0026] ZnFe2O4(l)+2C(s)=Zn(g)+2FeO(l)+2CO(g)

[0027] The initial mass fractions of the substances in the melt are: PbO 3.23wt%, ZnO 8.07wt%, ZnFe2O411.71wt%, FeO 35wt%, CaO 12.33wt%, SiO224.66wt%, and other 5wt%. A layer of C particles is spread on the surface of the melt, and its mass percentage relative to the melt is 3.5wt%.

[0028] The lower part of the model uses the two-fluid Euler-Euler model as the control equation to simulate the bubbling flow, and then calculates the volume fraction, flow velocity, and streamline of each phase. The control equation is:

[0029]

[0030] Among them, φ l is the liquid volume fraction (SI unit: m 3 / m 3 );ρ l is the liquid density (SI unit: kg / m 3 ); is the Laplace operator (total differential in all directions of space); u l is the liquid phase velocity vector (SI unit: m / s); p is the pressure (SI unit: Pa); μ l is the liquid phase dynamic viscosity (SI unit: Pa·s); μ Tis the turbulent viscosity (SI unit: Pa·s); g is the gravity vector (SI unit: m / s 2 ); F is the body force (SI unit: N / m 3 ); I represents unit tension; superscript T represents matrix transposition, subscript "l" represents liquid phase; subscript "g" represents gas phase;

[0031] The pressure distribution is calculated by the mixed average continuity equation, which is:

[0032]

[0033] Among them, φ g is the gas phase volume fraction (SI unit: m 3 / m 3 );ρ g is the gas phase density (SI unit: kg / m 3 );u g is the gas phase velocity vector (SI unit: m / s);

[0034] The volume fraction of bubbles is tracked by solving the gas phase transport equation for the effective gas density, which is as follows:

[0035]

[0036] Among them, -m gl is the mass transfer rate from gas phase to liquid phase (SI unit: kg / (m 3 ·s));

[0037] The calculation formula for gas velocity is:

[0038] u g =u l +u slip +u drift

[0039] Among them, u g is the gas velocity; u slip is the slip velocity, u drift is the displacement velocity (SI unit: m / s). The displacement velocity is defined as:

[0040]

[0041] Among them, D gc is the gas diffusion coefficient; μ T is the turbulent viscosity; σ Tis the turbulent Schmidt number. The offset velocity helps to analyze the flow characteristics of gas-liquid two-phase flow. Secondly, in the reactor, the gas phase offset velocity has an important influence on the mixing and mass transfer process of the reactants. By controlling the offset velocity, the reaction conditions in the reactor can be improved, and the reaction efficiency and product quality can be improved. Finally, changes in the gas phase offset velocity may lead to fluid instability, and obtaining the offset velocity can observe its changes.

[0042] The upper part of the model uses the Navier-Stokes formula for compressible flow as the governing equation to calculate its flow field distribution:

[0043]

[0044] Where ρ is the fluid density (SI unit is kg / m 3 ); u is the fluid velocity vector (SI unit is m / s).

[0045] The momentum conservation equation is:

[0046]

[0047] Where p is the fluid pressure (SI unit is Pa); μ is the fluid dynamic viscosity (SI unit is Pa·s); I is the unit tensor; F is the volume force (SI unit is N / m 3 ). The purpose of the momentum conservation equation is to describe the change in momentum of a fluid flow, that is, the rate of change of momentum of an object over time is equal to the net external force acting on the object. In fluid mechanics, the momentum conservation equation is used to predict changes in the velocity field of a fluid.

[0048] The governing equations for the gas phase and slag phase include the continuity equation and the momentum equation, which describe the flow behavior of the fluid, that is, the flow characteristics of the gas phase and slag phase (flow velocity, flow direction, and volume fraction). The continuity equation expresses the conservation of mass, while the momentum equation describes the relationship between the force and acceleration on the fluid. By solving these equations, the velocity field and pressure field of the fluid can be obtained, and then the streamlines can be obtained. The flow field distribution characteristics can be obtained by solving the continuity equation, momentum equation, and energy equation simultaneously to obtain the flow field distribution. In specific implementation, you only need to input all the data, and the model can automatically export the calculation results.

[0049] Furthermore, the k-ε model is used in the geometric model to describe the turbulence effect, and the turbulent viscosity μ T It can be expressed as:

[0050]

[0051] Among them, ρ is the fluid density, k is the turbulent kinetic energy, ε is the turbulent energy dissipation rate, and k and ε satisfy:

[0052]

[0053] In the formula, the derivative term P k satisfy:

[0054]

[0055] Among them, C μ , σ k , σ ε , C ε1 , C ε2 , and C ε are model parameters, S k To express the fluid turbulence caused by bubbles, it is expressed by the following formula:

[0056]

[0057] In the formula, C k is the model constant; u slip is the slip speed.

[0058] Furthermore, the heat transfer equation describes the heat transfer process in the reactor and is the heat balance equation of the temperature field. The heat balance equation of the temperature field distribution is:

[0059]

[0060] Where ρ is the density (SI unit: kg / m 3 );C p is the specific heat capacity at constant pressure (SI unit: J / (kg·K)); T is the absolute temperature (SI unit: K); u is the velocity vector (SI unit: m / s); q is the conduction heat flux (SI unit: W / m 2 ); Q is the heat source (SI unit: W / m 3 );Q P is the pressure work (SI unit: W / m 3 );Q vd Heat generated by fluid viscosity dissipation (SI unit: W / m 3 ), Τ is the temperature gradient, and a is the proportionality coefficient, i.e. the thermal conductivity (SI unit: W / (m·k)).

[0061] Furthermore, the relationship between the reaction parameters and the two-phase flow field distribution of the gas phase and the slag phase, the temperature field distribution and the lead-zinc depletion effect is as follows: the gas turbulence in the melt in the reactor gradually intensifies, and the temperature and gas distribution gradually become uniform. The enhancement of gas turbulence is conducive to the transfer of heat and mass, thereby improving the uniformity of the flow field and the temperature field; the gas turbulence between the electrodes is more intense, the slag stratification effect is weakened, the reduction reaction is more intense, and the lead-zinc depletion effect is enhanced, which shows that the flow and reaction conditions inside the reactor can be optimized by adjusting the electrode parameters; the density and viscosity of the melt in the electric furnace are related to the temperature and its components, and the disturbance caused by the density gradient caused by the temperature difference is one of the main driving forces of the fluid flow; wherein, the reaction parameters include the structural parameters of the reactor (such as the gas outlet position, the electrode arrangement) and the operating parameters (such as the temperature and the amount of material).

[0062] Furthermore, when the reactor is adjusted using the gas and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect as optimization basis, the optimization strategy is as follows: if the lead-zinc depletion effect is to be improved, the heat-conducting carbon rods are reduced, the materials are reduced, the gas outlet position in the reactor is moved upward, and the temperature is increased; wherein the reaction parameters include the structural parameters and operating parameters of the reactor.

[0063] Furthermore, the boundary conditions and parameter initial values ​​include: flow field boundary conditions and initial values, reactor concentration field boundary conditions and initial values, and heat transfer field boundary conditions and initial values;

[0064] The initial values ​​corresponding to the flow field include: pressure and gravity conditions of the calculation domain in the carbon immersion reduction lead-zinc reactor;

[0065] The initial values ​​corresponding to the concentration field in the reactor include: the initial overall regional material concentration setting of the carbon immersion reduction lead-zinc reactor, the diffusion coefficient setting of each material, and the custom function setting of the chemical reaction rate of zinc oxide and zinc ferrite;

[0066] The initial values ​​corresponding to the heat transfer field include: the shape and size of the heat-conducting object, the physical properties of the heat-conducting object (including density, specific volume, thermal conductivity, etc.), and the temperature distribution in the heat-conducting object at the initial moment;

[0067] The boundary conditions of the flow field in the model are as follows: the surface of the carbon rod in the mixed melt at the bottom of the model is set as the gas inlet surface, the gas generation rate is coupled with the chemical reaction rate, the boundary has no slip, the two-phase interface is set as the gas outlet surface, and it is also the gas inlet at the top of the model, slipping at the liquid phase boundary, the upper wall has two symmetrical gas outlets, which are set as pressure outlets, and the other wall surfaces are non-slip surfaces and have no gas flux:

[0068] u l n = 0

[0069]

[0070] u l =0

[0071] Among them, u l is the fluid velocity vector; n is the boundary normal vector; K n is the sum of viscosity and elasticity; ρ l is the fluid density; u τ is the friction speed; y + is the ratio of the fluid velocity vector to the friction velocity; is the gas mass flux (SI unit is kg / (m 2 ·s). When u l = 0, indicating that there is no flux of fluid at the interface other than the interface between the gas phase and the slag phase, that is, the fluid is completely still at the boundary; K n It is used to describe the dynamic interaction between gas molecules and the wall, that is, the upper wall has two symmetrical gas outlets, and the other walls are non-slip surfaces and have no gas flux.

[0072] The boundary condition of the concentration field in the reactor is that no gas flux boundary condition is applied to each surface. Only 1 / 3 of the furnace height of the material is added before the reaction starts. The initial mass fraction of each substance in the melt in the reactor is PbO3.23wt%, ZnO8.07wt%, ZnFe2O411.71wt%, FeO35wt%, CaO12.33wt%, SiO224.66wt%, and other 5wt%. A layer of C particles is spread on the surface of the melt, and its mass percentage relative to the melt is 3.5wt%;

[0073] The heat transfer field boundary conditions are set to the melt initial temperature of 1100°C, the carbon rod temperature of 1250°C, and other walls are set to thermal insulation surfaces:

[0074] -n·q=0

[0075] Where n is the direction of the boundary normal (the direction in which heat flows perpendicular to the boundary); q is the heat transfer flux.

[0076] Furthermore, the optimization in S4 is based on the preset conditions that are satisfied:

[0077] Different colors in the simulation diagram of gas and slag two-phase flow field distribution and temperature field distribution represent different values. When the value is within the preset fluctuation range, the color distribution is uniform, indicating that the preset conditions are met;

[0078] The lead-zinc depletion effect is achieved by making the mass fraction of lead-zinc less than or equal to a preset value, indicating that the preset condition is met. In specific implementation, the preset value of the mass fraction of lead-zinc can be adjusted according to specific circumstances, and is set to 3% in this application.

[0079] In a second aspect, the present invention provides an optimization system for an immersion reduction lead-zinc reactor, comprising:

[0080] Geometric model construction model: used to construct a geometric model of the fluid calculation domain of the carbon immersion reduction lead-zinc reactor according to the basic size parameters of the preset initial carbon immersion reduction lead-zinc reactor; wherein the geometric model simulates the upper and lower parts of the carbon immersion reduction lead-zinc reactor, the lower part of the model simulates the flow field changes and physical and chemical processes of the slag phase, and the upper part of the model simulates the flow field changes of the gas phase;

[0081] A reaction control equation determination module: used to determine the reaction control equation of the geometric model, wherein the reaction control equation is used to simulate the process of carbon immersion reduction of lead and zinc in a reactor;

[0082] Parameter setting and simulation module: used to initialize the operating parameters of the geometric model and mesh the geometric model; wherein the operating parameters are the corresponding boundary conditions and parameter initial values; the geometric model based on meshing is used to simulate and calculate the reaction parameters inside the carbon immersion reduction lead-zinc reactor, and the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect are obtained based on the reaction parameters;

[0083] Among them, at least the flow field distribution of gas phase and slag phase, temperature field distribution and lead and zinc depletion effect are used as optimization basis;

[0084] Model optimization module: Determine whether the selected optimization basis meets the preset conditions: If so, output the basic size parameters of the lead-zinc reduction reactor; if not, adjust the structural parameters and / or operating parameters of the reactor based on the optimization basis and return to the parameter setting and simulation module.

[0085] The third invention provides a readable storage medium storing a computer program, wherein the computer program is used to execute the steps of the method described above when called by a processor.

[0086] Beneficial Effects

[0087] The present invention proposes an optimization method, system and medium for carbon immersion reduction of lead and zinc reactor. The method realizes efficient reduction of lead and zinc components and recovery of lead and zinc in metallic state through electric auxiliary heating carbon immersion reduction and zinc vapor condensation in a closed furnace. On the one hand, it effectively overcomes the difficulty of recovering iron resources in non-ferrous smelting slag such as depleted slag in traditional processes, which cannot be recycled and reused, resulting in the problem that high-iron low-calcium silicon tailings can only be used at low dosage and low value. On the other hand, it realizes efficient reduction and recovery of iron in depleted slag, realizes the step-by-step recovery of lead, zinc and iron in smelting slag and strengthens its recovery effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0089] Figure 1 A geometric diagram of a reactor under a preliminary structural design provided by an embodiment of the present invention;

[0090] Figure 2 A grid division diagram of a reactor under a preliminary structural design provided by an embodiment of the present invention;

[0091] Figure 3 The flow field distribution diagrams of the gas phase and the slag phase at different times provided by the embodiment of the present invention: (a) is the section at 1h; (b) is the section at 2h; (c) is the zx section at 1h; (d) is the zx section at 2h;

[0092] Figure 4 The mass percentage of C particles relative to slag and the distribution diagram of the mole fraction of CO in the gas phase at different times provided by the embodiment of the present invention: (a) 1h; (b) 2h;

[0093] Figure 5 The mass percentage of Pb liquid to slag and the mole fraction distribution diagram of Pb vapor in the gas phase at different times provided by the embodiment of the present invention: (a) is 1h; (b) is 2h;

[0094] Figure 6 Distribution diagram of the mass fraction of PbO in the slag phase and the molar fraction of Pb vapor in the gas phase at different times provided by the embodiment of the present invention: (a) is 1h; (b) is 2h;

[0095] Figure 7 Distribution diagram of the mass fraction of ZnO in the slag phase and the molar fraction of Zn vapor in the gas phase at different times provided by the embodiment of the present invention: (a) 1h; (b) 2h;

[0096] Figure 8 Distribution diagram of the mass fraction of ZnFe2O4 in the slag phase and the molar fraction of Zn vapor in the gas phase at different times provided by the embodiment of the present invention: (a) is 1h; (b) is 2h;

[0097] Fig. 9 Distribution diagram of FeO mass fraction in slag phase and CO mole fraction in gas phase at different times provided by the embodiment of the present invention: (a) is 1h; (b) is 2h;

[0098] Fig.10Temperature distribution diagrams of gas phase and slag phase at different times provided in the embodiment of the present invention: (a) is 1 hour; (b) is 2 hours;

[0099] Fig.11 Flow field distribution diagram of two electrodes provided in an embodiment of the present invention: (a) section diagram; (b) zx section diagram;

[0100] Fig.12 The mole fractions of CO and Pb in the gas phase of the two electrodes and the mass percentage distribution diagram of carbon particles and lead liquid relative to slag provided in the embodiment of the present invention are as follows: (a) CO, C; (b) Pb, Pb;

[0101] Fig.13 Distribution diagram of the mole fractions of CO and Pb in the gas phase of two electrodes and the mass fractions of FeO and PbO in the slag phase provided by the embodiment of the present invention: (a) CO, FeO; (b) Pb, PbO;

[0102] Fig.14 The molar fraction of Zn in the gas phase of the two electrodes and the mass fraction distribution diagram of ZnFe2O4 and ZnO in the slag phase provided by the embodiment of the present invention: (a) ZnFe2O4; (b) ZnO

[0103] Fig.15 Temperature distribution diagram of two electrodes provided by the embodiment of the present invention: (a) section diagram; (b) zx section diagram;

[0104] Fig.16 Flow field distribution diagram after the liquid level is lowered provided by an embodiment of the present invention: (a) section diagram; (b) zx section diagram;

[0105] Fig.17 The mole fractions of CO and Pb in the gas phase after the liquid level is lowered and the mass percentage distribution diagram of carbon particles and lead liquid relative to slag provided in the embodiment of the present invention: (a) CO, C; (b) Pb, Pb;

[0106] Fig.18 Distribution diagram of the mole fractions of CO and Pb in the gas phase after the liquid level is lowered and the mass fractions of FeO and PbO in the slag phase provided in the embodiment of the present invention: (a) CO, FeO; (b) Pb, PbO;

[0107] Fig.19 The molar fraction of Zn in the gas phase after the liquid level is lowered and the mass fraction distribution diagram of ZnO and ZnFe2O4 in the slag phase provided in the embodiment of the present invention: (a) ZnO; (b) ZnFe2O4;

[0108] Fig. 20 Temperature distribution diagram after liquid level drop provided by an embodiment of the present invention: (a) section diagram; (b) zx section diagram;

[0109] Fig.21 Flow field distribution diagram after upward adjustment of gas outlet provided by the embodiment of the present invention: (a) section diagram; (b) zx section diagram;

[0110] Fig. 22 The mole fractions of CO and Pb in the gas phase of the upward-regulated gas outlet and the mass percentage distribution diagram of carbon particles and lead liquid relative to slag provided in the embodiment of the present invention are as follows: (a) CO, C; (b) Pb, Pb;

[0111] Fig.23 The mole fraction distribution diagram of CO and Pb in the gas phase and the mass fraction distribution diagram of FeO and PbO in the slag phase after the gas outlet is adjusted upward provided in the embodiment of the present invention: (a) CO, FeO; (b) Pb, PbO;

[0112] Fig.24 The molar fraction of Zn in the gas phase and the mass fraction distribution diagram of ZnFe2O4 and ZnO in the slag phase after the gas outlet is adjusted upward provided in the embodiment of the present invention: (a) ZnFe2O4; b ZnO;

[0113] Fig.25 Temperature distribution diagram after the gas outlet is adjusted upward provided in an embodiment of the present invention: (a) cross-sectional diagram; (b) zx cross-sectional diagram;

[0114] Fig.26 Flow field distribution diagram after heating provided by the embodiment of the present invention: (a) section diagram; (b) zx section diagram;

[0115] Fig. 27 The mole fractions of CO and Pb in the gas phase after heating and the mass percentage distribution diagram of carbon particles and lead liquid relative to slag provided in the embodiment of the present invention are as follows: (a) CO, C; (b) Pb, Pb;

[0116] Fig.28 Distribution diagram of the mole fractions of CO and Pb in the gas phase after heating and the mass fractions of FeO and PbO in the slag phase provided in the embodiment of the present invention: (a) Pb, PbO; (b) CO, FeO;

[0117] Fig.29 The molar fraction of Zn in the gas phase after heating and the mass fraction distribution diagram of ZnO and ZnFe2O4 in the slag phase provided in the embodiment of the present invention: (a) ZnO; (b) ZnFe2O4;

[0118] Fig.30 The temperature distribution diagram after heating provided by this embodiment of the invention: (a) cross-sectional diagram; (b) zx cross-sectional diagram;

[0119] Fig.31 It is a schematic flow chart of a method for optimizing a carbon immersion reduction lead-zinc reactor provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0120] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0121] like Fig.31 As shown, the present invention provides an optimization method for a carbon immersion reduction reactor for lead and zinc, proposes a new idea for electrically enhanced depletion, realizes efficient reduction of lead and zinc components and recovery of lead and zinc in metallic state by electrically assisted carbon immersion reduction and zinc vapor condensation in a closed furnace; utilizes plasma enhanced reduction to create a supercritical reduction environment, realizes efficient reduction and recovery of iron in depleted slag, and realizes stepwise recovery of lead, zinc and iron in smelting slag, which mainly includes the following steps:

[0122] Step 1: According to the basic size parameters of the carbon immersion reduction lead-zinc reactor under the preliminary structural design, a geometric model of the fluid calculation domain of the carbon immersion reduction lead-zinc reactor is established, mainly to determine the main structure of the reactor and the position of the gas outlet, and parameterize the basic size of the carbon immersion reduction lead-zinc reactor and the position of each inlet and outlet to construct a geometric model;

[0123] Step 2: Determine the reaction control equation of the geometric model. In order to simulate the lead-zinc reduction process in the reactor, the model needs to couple physical fields such as the gas phase and slag phase two-phase flow field, chemical reaction mass transfer field, and heat transfer field.

[0124] Step 3: Define the boundary conditions and initial values ​​of the model under certain operating parameters, and correctly set the model parameters; and mesh the geometric model. For the two-dimensional model, triangular meshing is used, and for the three-dimensional model, tetrahedral meshing is used. The meshing can be controlled by the physical field characteristics;

[0125] Step 4: Perform CFD finite element simulation calculations to solve the distribution characteristics of the model and the concentration distribution structure of the reaction substances, and obtain the dissociation effect, gas-liquid two-phase velocity distribution, gas phase distribution and other results inside the carbon immersion reduction lead-zinc reactor under the set operating parameters;

[0126] Step 5: Based on the calculation results, analyze the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect under certain structural operating parameters in the carbon immersion reduction lead-zinc reactor to obtain further optimization basis;

[0127] Step 6. According to step 5, after analyzing the characteristics of the reactor, further adjust the reactor structure and / or operating parameters according to the actual situation and design ideas, that is, by changing the basic size parameters in step 1 and / or the boundary conditions and initial values ​​in step 3, specifically: the basic shape and size of the carbon immersion reduction lead-zinc reactor, and then simulate according to the methods of steps 4 and 5, compare the calculated data obtained under different conditions, until the result of the optimization of the design of the structure and / or operating parameters of the carbon immersion reduction lead-zinc reactor is obtained to achieve the purpose of efficient reduction and recovery of iron in the depleted slag and the stepwise recovery of lead, zinc and iron in the smelting slag.

[0128] Example

[0129] 1) According to the basic size parameters of the carbon immersion reduction lead-zinc reactor under the preliminary structural design, establish Figure 1 The reactor geometry model is shown in the figure. The reactor is axisymmetric and is scaled to reduce the amount of calculation. Figure 1 As shown, the round openings on both sides are gas outlets. The reactor is generally cylindrical, with a reactor height of 4.6m, a reactor radius of 1.95m, a top sphere radius of 3.9m, an electrode height of 3.8333m, an electrode radius of 0.117m, a gas outlet height of 0.65m, a gas outlet radius of 0.22, and a phase interface height of 1.5333m.

[0130] 2) Determine the control equation of the geometric model. In order to simulate the lead-zinc reduction process in the reactor, multiple physical fields need to be coupled in the geometric model, including at least the two-phase flow field of gas phase and slag phase, the chemical reaction mass transfer field, and the heat transfer field. According to the nature of the chemical reaction, the concentrated species transfer model is selected to study the chemical mass transfer to obtain the amount of change of the mass fraction of each substance over time.

[0131] The material flux vector equation in the reactor

[0132]

[0133] Where i refers to the substance i in the reactor; N i is the material flux vector; D i is the diffusion coefficient of the substance, which indicates the diffusion ability of the substance in the cutoff, c i is the concentration of the substance, is the concentration of a substance c iThe sum of the first-order partial differentials in three directions is used to describe the change in concentration; u is the material fluid velocity vector. The concentrated material transfer model can calculate the mass fraction of all participating substances. The material flux vector equation in the reactor is used to describe the material transfer process in the fluid. It mathematically expresses the distribution of the material in space and the change of the mass fraction over time, and describes the material transfer rate and direction in space. By analyzing the material flux vector equation, the reactor design can be optimized and the reaction efficiency can be improved.

[0134] The mass transfer equation is as follows:

[0135]

[0136] Where ρ represents the fluid density (SI unit: kg / m 3 ), u represents the mass average velocity vector of the mixture (SI unit: m / s); ω i represents the quality score; j i Expresses the mass flux relative to the mass average velocity (SI unit: kg / m 2 ·s); R i Indicates the rate at which a substance is generated or consumed (SI unit: kg / m 3 ·s). The mass transfer equation is used to calculate the rate of material generation or consumption. The mass transfer equation can further calculate the rate of material generation or consumption by using the time-varying mass fraction of the material obtained by the material flux vector equation. These equations together constitute a mathematical model that describes the material transport phenomenon in the fluid, which is crucial for material transfer in the reactor.

[0137] In this model, the chemical reactions involved are divided into surface reactions and bulk reactions, and all the reactions involved are irreversible reactions. Among them, the surface reactions include the reactions of carbon on the surface of the carbon rod with lead oxide, zinc oxide and zinc ferrite, and the chemical reaction formulas are as follows:

[0138] PbO(l)+C(ads)=Pb(g)+CO(g)

[0139] ZnO(l)+C(ads)=Zn(g)+CO(g)

[0140] ZnFe2O4(l)+2C(ads)=Zn(g)+2FeO(l)+2CO(g)

[0141] The bulk reaction includes the reaction of carbon particles with lead oxide, zinc oxide and zinc ferrite, and the chemical reaction formulas are as follows:

[0142] PbO(l)+C(s)=Pb(g)+CO(g)

[0143] ZnO(l)+C(s)=Zn(g)+CO(g)

[0144] ZnFe2O4(l)+2C(s)=Zn(g)+2FeO(l)+2CO(g)

[0145] The initial mass fractions of the substances in the melt are PbO3.23wt%, ZnO8.07wt%, ZnFe2O411.71wt%, FeO35wt%, CaO12.33wt%, SiO224.66wt%, and other 5wt%. A layer of C particles is spread on the surface of the melt, and its mass percentage relative to the melt is 3.5wt%.

[0146] According to the distribution of multi-physical fields in the process of carbon immersion reduction of lead and zinc, the electric furnace is divided into two parts, the lower part of the model is used to simulate the flow field changes and physical and chemical processes of the slag phase, and the upper part is used to simulate the flow field changes of the gas phase.

[0147] The lower part of the model uses the two-fluid Euler-Euler model as the control equation to simulate the bubble flow to calculate the volume fraction, flow rate, streamlines and other physical quantities of each phase. The pressure distribution is calculated by the mixed average continuity equation, and the volume fraction of the bubble is tracked by solving the transport equation of the effective gas density. The lower part of the model uses the two-fluid Euler-Euler model as the control equation to simulate the bubble flow, and then calculates the volume fraction, flow rate and streamline of each phase. The control equation is:

[0148]

[0149] Among them, φ l is the liquid volume fraction (SI unit: m 3 / m 3 );ρ l is the liquid density (SI unit: kg / m 3 ); is the Laplace operator (total differential in all directions of space); u l is the liquid phase velocity vector (SI unit: m / s); p is the pressure (SI unit: Pa); μ l is the liquid phase dynamic viscosity (SI unit: Pa·s); μ T is the turbulent viscosity (SI unit: Pa·s); g is the gravity vector (SI unit: m / s 2 ); F is the body force (SI unit: N / m 3 );I represents unit tension;superscript T represents matrix transposition,subscript "l" represents liquid phase;subscript "g" represents gas phase. The governing equation of slag phase is used to describe the flow characteristics of slag phase, and the volume fraction, flow velocity and streamline can be calculated. The change of volume fraction directly affects the density distribution of fluid, and then affects the pressure distribution; the trend of pressure distribution can be inferred from the flow velocity distribution; the shape and distribution of streamlines can reflect the change of pressure field.

[0150] The pressure distribution of the slag phase is calculated by the mixed average continuity equation, which is:

[0151]

[0152] Among them, φ g is the gas phase volume fraction (SI unit: m 3 / m 3 );ρ g is the gas phase density (SI unit: kg / m 3 );u g is the gas phase velocity vector (SI unit: m / s);

[0153] The volume fraction of bubbles is tracked by solving the gas phase transport equation for the effective gas density, which is as follows:

[0154]

[0155] Among them, -m gl is the mass transfer rate from gas phase to liquid phase (SI unit: kg / (m 3 ·s));

[0156] The calculation formula for gas velocity is:

[0157] u g =u l +u slip +u drift

[0158] Among them, u g is the gas velocity; u slip is the slip velocity, u drift is the displacement velocity (SI unit: m / s). The displacement velocity is defined as:

[0159]

[0160] Among them, D gc is the gas diffusion coefficient; μ T is the turbulent viscosity; σ T is the turbulent Schmidt number. Gas velocity is used to describe the velocity characteristics of fluid flow, which is closely related to the gas phase transport equation. Solving these equations together can obtain a comprehensive description of fluid flow, including gas velocity, pressure distribution, etc.

[0161] The upper part of the model uses the Navier-Stokes formula for compressible flow as the governing equation to calculate its flow field distribution:

[0162]

[0163] Where ρ is the fluid density (SI unit is kg / m 3 ); u is the fluid velocity vector (SI unit is m / s).

[0164] The momentum conservation equation is:

[0165]

[0166] Where p is the fluid pressure (SI unit is Pa); μ is the fluid dynamic viscosity (SI unit is Pa·s); I is the unit tensor; F is the volume force (SI unit is N / m 3 ).

[0167] The k-ε model is used in the geometric model to describe the turbulence effect. The turbulent viscosity μ T It can be expressed as:

[0168]

[0169] Among them, ρ is the fluid density, k is the turbulent kinetic energy, ε is the turbulent energy dissipation rate, and k and ε satisfy:

[0170]

[0171] In the formula, the derivative term P k satisfy:

[0172]

[0173] Among them, C μ , σ k , σ ε , C ε1 , C ε2 , and C ε are model parameters, S k To express the fluid turbulence caused by bubbles, it is expressed by the following formula:

[0174]

[0175] In the formula, C k is the model constant; u slip is the slip speed.

[0176] Theoretically, in gases, it occurs through molecular collisions; in fluids, each molecule occurs by oscillating around its nearest molecule. The heat balance equation for the temperature field distribution is established based on the law of conservation of energy:

[0177]

[0178] Where ρ is the density (SI unit: kg / m 3 );Cp is the specific heat capacity at constant pressure (SI unit: J / (kg·K)); T is the absolute temperature (SI unit: K); u is the velocity vector (SI unit: m / s); q is the conduction heat flux (SI unit: W / m 2 ); Q is the heat source (SI unit: W / m 3 );Q P is the pressure work (SI unit: W / m 3 );Q vd Heat generated by fluid viscosity dissipation (SI unit: W / m 3 ) ; q is the heat flux; Τ is the temperature gradient; a is the proportionality coefficient, that is, the thermal conductivity (SI unit: W / (m·k)).

[0179] In a continuous medium, Fourier's law of heat conduction shows that the heat flux q is proportional to the temperature gradient Τ. The proportionality coefficient k is the thermal conductivity (SI unit: W / (m·k)). A positive value of k means that heat flows from the high temperature area to the low temperature area. Fourier's law of heat conduction:

[0180]

[0181] 3) Define the boundary conditions and initial values ​​of the model. In this example, the surface of the carbon rod in the lower mixed melt is set as the gas inlet surface, and its gas generation rate is coupled with the chemical reaction rate. There is no slip at the boundary, and the two-phase interface is set as the gas outlet surface, which is also the upper gas inlet. It slips at the liquid phase boundary. The upper wall has two symmetrical gas outlets, which are set as pressure outlets. The other wall surfaces are non-slip surfaces and have no gas flux. The initial mass fractions of the melt substances in the reactor are PbO3.23wt%, ZnO8.07wt%, ZnFe2O411.71wt%, FeO35wt%, CaO12.33wt%, SiO224.66wt%, and other 5wt%. A layer of C particles is spread on the surface of the melt, and its mass percentage relative to the melt is 3.5wt%.

[0182] 4) Model meshing. In this embodiment, meshing is mainly based on finite element analysis of various physical field equations. The reactor meshing results are as follows: Figure 2 After completing the mesh independence test, the detailed data of the mesh is as follows: number of boundary layers: 8, rectangular boundary elements form a structured layer on the surface boundary, and these finer boundary element layers are integrated with the existing triangular mesh elements in the model, boundary stretch factor: 1.2; number of vertex elements: 19, number of boundary elements: 228, number of elements: 305930; minimum element quality: 0.09275.

[0183] 5) After completing steps 1 to 4, CFD finite element simulation calculation is performed to couple the gas phase and slag phase two-phase flow control equations, chemical reaction mass transfer and heat transfer equations in the carbon immersion lead-zinc reduction reactor to solve the flow field distribution characteristics, reaction substance concentration distribution and temperature distribution results of the model; the gas phase and slag two-phase flow field distribution, temperature field distribution, gas phase volume fraction distribution and lead-zinc depletion effect of the carbon immersion lead-zinc reduction reactor under the set operating parameters are obtained, respectively as follows: Figure 3-Figure 10 shown.

[0184] 6) Data analysis and further optimization of structure and parameters. In this embodiment, the numerical simulation of the carbon immersion reduction lead-zinc reactor based on CFD technology obtains the results described in step (5). When the liquid level of the melt in the electric furnace containing simulated depleted slag containing lead and zinc is 1 / 3 of the furnace height, the initial temperature of the melt is 1100°C, the temperature of the carbon rod is 1250°C, and there are three heat-conducting carbon rods, the reaction characteristics of the reactor can be summarized from the flow velocity distribution, material distribution and temperature distribution of the flow field inside the reactor. Under the conditions of preliminary structural design and operating parameters, the temperature and gas distribution are relatively uniform; the reaction around the electrode is violent, and the slag stratification is obvious; a large amount of lead-zinc vapor is generated, and the lead-zinc depletion effect is good; the gas turbulence between the electrodes is violent, and the heat transfer effect is good; the lead-zinc vapor migrates to the outlet, and part of it stays at the top. In general, the temperature and gas distribution under this structure and operating parameters are relatively uniform, the lead-zinc depletion effect is better, the lead-zinc vapor migrates to the outlet, and part of it stays at the top, indicating that the lead-zinc depletion effect under this structure can be improved, the gas turbulence can be more intense and the distribution can be more uniform, and part of the lead-zinc vapor stays at the top, which requires further optimization of the structure and operating parameters.

[0185] Based on steps 1 to 6, the reactor structure is optimized. The heat-conducting carbon rods are reduced, the materials are reduced, the gas outlet position in the reactor is moved upward, and the temperature is increased. The above steps are performed to obtain new simulation calculation results. The optimized lead-zinc depletion effect, gas phase volume fraction distribution, flow field distribution, and temperature distribution are shown in the following table. Figure 11-Figure 30 As shown. It can be found that in the carbon immersion reduction lead-zinc reactor with optimized structure, changing the electrode arrangement, such as reducing a heat-conducting carbon rod, the melt heat transfer effect is weakened, the gas phase flow rate is reduced, and the distribution is uniform; reducing the material, such as reducing the height of the melt liquid level from 1 / 3 of the furnace height to 1 / 4 of the furnace height, the gas turbulence between the electrodes is more intense, the slag stratification effect is weakened, the reduction reaction is more intense, and the lead-zinc depletion effect is enhanced; raising the gas outlet position in the reactor, the gas distribution in the slag phase is more uniform, the melt temperature around the electrode rises, the migration amount of lead-zinc vapor to the outlet increases, and the retention amount decreases; raising the temperature, that is, raising the temperature of the slag and the conductive carbon rod in the carbon immersion reactor by 100°C, the heat transfer around the electrode is more sufficient, the turbulence effect is enhanced, the lead-zinc depletion effect is strengthened, and the lead-zinc mass fraction is increased.

[0186] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0187] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

[0188] It should be understood that in the embodiments of the present invention, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the type of device.

[0189] The readable storage medium is a computer-readable storage medium, which may be an internal storage unit of the controller described in any of the foregoing embodiments, such as a hard disk or memory of the controller. The readable storage medium may also be an external storage device of the controller, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. equipped on the controller. Furthermore, the readable storage medium may also include both an internal storage unit of the controller and an external storage device. The readable storage medium is used to store the computer program and other programs and data required by the controller. The readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0190] Based on this understanding, the technical solution of the present invention, in essence or in other words, the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned readable storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., various media that can store program codes.

Claims

1. A method for optimizing a carbon-immersion reduction lead-zinc reactor, characterized in that: include: S1: Preset the basic size parameters of the initial carbon immersion reduction lead-zinc reactor and construct a geometric model of the fluid calculation domain of the carbon immersion reduction lead-zinc reactor; wherein the geometric model simulates the upper and lower parts of the carbon immersion reduction lead-zinc reactor, the lower part of the model simulates the flow field changes and physical and chemical processes of the slag phase, and the upper part of the model simulates the flow field changes of the gas phase; S2: determining a reaction control equation of the geometric model, wherein the reaction control equation is used to simulate a lead-zinc reduction process by carbon immersion in a reactor; S3: Initializing the operating parameters of the geometric model and meshing the geometric model; wherein the operating parameters are corresponding boundary conditions and initial parameter values; S3: Based on the meshed geometric model, simulation calculation is performed to obtain the reaction parameters inside the carbon immersion reduction lead-zinc reactor, and based on the reaction parameters, the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect are obtained; Among them, one or more of the gas phase and slag two-phase flow field distribution, temperature field distribution, and lead-zinc depletion effect are selected as optimization basis; S4: Determine whether the selected optimization basis meets the preset conditions: if so, output the basic size parameters of the lead-zinc reduction reactor; if not, adjust the structural parameters and / or operating parameters of the reactor based on the optimization basis and return to S3.

2. The optimization method of the immersion reduction lead-zinc reactor according to claim 1, characterized in that: The reaction control equation of S2 is set as follows: The material flux vector equation in the carbon immersion reduction lead-zinc reactor is: Where i refers to the substance i in the reactor; N i is the material flux vector; D i is the diffusion coefficient of the substance; c i is the concentration of the substance; is the concentration of a substance c i The sum of the first-order partial differentials in three directions; u is the material fluid velocity vector; The mass transfer equation is: Where ρ represents the fluid density; u represents the mass average velocity vector of the mixture; ω i represents the quality score; j i Represents the mass flux relative to the mass average velocity; R i Indicates the rate at which a substance is produced or consumed; is the Laplace operator; The chemical reactions contained in the reactor include surface reactions and bulk reactions, and all the reactions involved are irreversible reactions; among them, the surface reactions include the reactions of carbon on the surface of the carbon rod with lead oxide, zinc oxide and zinc ferrite, and the chemical reaction formulas are as follows: PbO(l)+C(ads)=Pb(g)+CO(g) ZnO(l)+C(ads)=Zn(g)+CO(g) ZnFe2O4(l)+2C(ads)=Zn(g)+2FeO(l)+2CO(g) The bulk reaction includes the reaction of carbon particles with lead oxide, zinc oxide and zinc ferrite, and the chemical reaction formulas are as follows: PbO(l)+C(s)=Pb(g)+CO(g) ZnO(l)+C(s)=Zn(g)+CO(g) ZnFe2O4(l)+2C(s)=Zn(g)+2FeO(l)+2CO(g) The governing equation for the lower part of the model is: Among them, φ l is the liquid volume fraction; ρ l is the liquid density; is the Laplace operator; u l is the liquid phase velocity vector; p is the pressure; μ l is the liquid phase dynamic viscosity; μ T is the turbulent viscosity; g is the gravity vector; F is the volume force; I represents the unit tension; the subscript "l" represents the liquid phase; the subscript "g" represents the gas phase; The mixed continuity equation is: Among them, φ g is the gas phase volume fraction; ρ g is the gas phase density; u g is the gas phase velocity vector; The gas phase transport equation is as follows: Among them, -m gl is the mass transfer rate from gas phase to liquid phase; The calculation formula for gas velocity is: in g =in l +in slip +in drift Among them, u g is the gas velocity; u slip is the slip velocity, u drift is the displacement velocity; The formula for the offset velocity is: Among them, D gc is the gas diffusion coefficient; μ T is the turbulent viscosity; σ T is the turbulent Schmidt number; The governing equation for the upper part of the model is: Where ρ is the fluid density; u is the fluid velocity vector; The momentum conservation equation is: Where p is the fluid pressure; μ is the fluid dynamic viscosity; I is the unit tensor; and F is the volume force.

3. The optimization method of the immersion reduction lead-zinc reactor according to claim 2, characterized in that: The k-ε model is used in the geometric model to describe the turbulence effect. The turbulent viscosity μ T It can be expressed as: Where ρ is the fluid density; k is the turbulent kinetic energy; ε is the turbulent energy dissipation rate; where k and ε satisfy: In the formula, the derivative term P k satisfy: Among them, C μ , σ k , σ ε , C ε1 , C ε2 , and C ε are model parameters, S k To express the fluid turbulence caused by bubbles, it is expressed by the following formula: In the formula, C k is the model constant; u slip is the slip speed.

4. The optimization method of the immersion reduction lead-zinc reactor according to claim 1, characterized in that: The heat balance equation of the temperature field distribution is: Where ρ is the fluid density; C p is the specific heat capacity at constant pressure; T is the absolute temperature; u is the velocity vector; q is the conduction heat flux; Q is the heat source; Q P is the pressure work; Q vd is the heat generated by the viscous dissipation of the fluid; Τ is the temperature gradient; a is the proportional coefficient, which is the thermal conductivity.

5. The optimization method of the immersion reduction lead-zinc reactor according to claim 1, characterized in that: The relationship between the reaction parameters and the two-phase flow field distribution of gas and slag, the temperature field distribution and the lead-zinc depletion effect is as follows: the gas turbulence in the melt in the reactor gradually intensifies, and the temperature and gas distribution gradually become uniform; the gas turbulence between the electrodes is more intense, the slag stratification effect is weakened, the reduction reaction is more intense, and the lead-zinc depletion effect is enhanced; wherein the reaction parameters include the structural parameters and operation parameters of the reactor.

6. The optimization method for immersion reduction of lead and zinc reactor according to claim 1, characterized in that When the reactor is adjusted using the gas and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect as optimization basis, the optimization strategy is as follows: if the lead-zinc depletion effect is to be improved, the heat-conducting carbon rods are reduced, the materials are reduced, the gas outlet position in the reactor is moved up, and the temperature is increased.

7. The optimization method for immersion reduction of lead-zinc reactor according to claim 1, characterized in that: The boundary conditions and parameter initial values ​​include: flow field boundary conditions and initial values, reactor concentration field boundary conditions and initial values, heat transfer field boundary conditions and initial values; The initial values ​​corresponding to the flow field include: pressure and gravity conditions of the calculation domain in the carbon immersion reduction lead-zinc reactor; The initial values ​​corresponding to the concentration field in the reactor include: the initial overall regional material concentration setting of the carbon immersion reduction lead-zinc reactor, the diffusion coefficient setting of each material, and the custom function setting of the chemical reaction rate of zinc oxide and zinc ferrite; The initial values ​​corresponding to the heat transfer field include: the shape and size of the heat-conducting object, the physical properties of the heat-conducting object, and the temperature distribution in the heat-conducting object at the initial moment; The boundary conditions of the flow field in the model are as follows: the surface of the carbon rod in the mixed melt at the bottom of the model is set as the gas inlet surface, the gas generation rate is coupled with the chemical reaction rate, and there is no slip at the boundary; the two-phase interface is set as the gas outlet surface, which is also the gas inlet at the top of the model, slipping at the liquid phase boundary, and there are two symmetrical gas outlets on the upper wall, which are set as pressure outlets, and the other wall surfaces are non-slip surfaces and have no gas flux: u l ·n=0 u l ＝0 Among them, u l is the fluid velocity vector; n is the boundary normal vector; K n is the sum of viscosity and elasticity; ρ l is the fluid density; u τ is the friction speed; u + is the ratio of the fluid velocity vector to the friction velocity; is the gas mass flux; The boundary condition of the concentration field in the reactor is that no gas flux boundary condition is applied on each surface, and the material with a preset furnace height is added before the reaction starts; The heat transfer field boundary conditions are set to the melt initial temperature of 1100°C, the carbon rod temperature of 1250°C, and other walls are set to thermal insulation surfaces: -n·q=0 Where n is the boundary normal vector and q is the conductive heat flux.

8. The optimization method of the immersion reduction lead-zinc reactor according to claim 1, characterized in that: The optimization in S4 is based on the preset conditions that are satisfied: Different colors in the simulation diagram of gas and slag two-phase flow field distribution and temperature field distribution represent different values. When the value is within the preset fluctuation range, the color distribution is uniform, indicating that the preset conditions are met; The lead-zinc depletion effect is achieved by setting the mass fraction of lead and zinc to be less than or equal to the preset value, indicating that the preset conditions are met.

9. A system based on the method according to any one of claims 1 to 8, characterized in that: include: Geometric model construction model: used to construct a geometric model of the fluid calculation domain of the carbon immersion reduction lead-zinc reactor according to the basic size parameters of the preset initial carbon immersion reduction lead-zinc reactor; wherein the geometric model simulates the upper and lower parts of the carbon immersion reduction lead-zinc reactor, the lower part of the model simulates the flow field changes and physical and chemical processes of the slag phase, and the upper part of the model simulates the flow field changes of the gas phase; Reaction control equation determination module: used to determine the reaction control equation of the geometric model, and the reaction control equation is used to simulate the carbon immersion reduction process of lead and zinc in the reactor; Parameter setting and simulation module: used to initialize the operating parameters of the geometric model and mesh the geometric model; wherein the operating parameters are the corresponding boundary conditions and parameter initial values; the geometric model based on meshing is used to simulate and calculate the reaction parameters inside the carbon immersion reduction lead-zinc reactor, and the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect are obtained based on the reaction parameters; Among them, one or more of the gas phase and slag two-phase flow field distribution, temperature field distribution and lead-zinc depletion effect are selected as optimization basis; Model optimization module: Determine whether the selected optimization basis meets the preset conditions: If so, output the basic size parameters of the lead-zinc reduction reactor; if not, adjust the structural parameters and / or operating parameters of the reactor based on the optimization basis and return to the parameter setting and simulation module.

10. A readable storage medium, characterized in that: A computer program is stored, and when the computer program is called by a processor, the computer program is used to execute: the steps of the method according to any one of claims 1 to 8.

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