A method and system for predicting fly ash abrasion of superheater in coal-fired boilers

Abstract

The present invention discloses a method and a system for predicting fly ash erosion of a superheater of a coal-fired boiler. The present invention includes performing continuous phase flow field simulation and discrete phase simulation on a superheater physical model through a DPM model in sequence, and outputting the impact velocity of particles; constructing an impact angle function based on the empirical coefficients of a plurality of preset erosion models and the impact angle numbers; and calculating the wear amount of the heat exchange tube screen of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe, and the velocity exponent. The technical problem that the existing research only focuses on fly ash erosion in the boiler tube bundle and there are potential safety hazards is solved. This method numerically simulates the flow field distribution and obtains the flue gas velocity distribution inside the furnace tube, and then calculates the wall wear rate and the wear rate distribution law of the furnace tube under high-temperature flue gas, laying a theoretical foundation for controlling the erosion wear of the flue gas on the tube wall in the superheater.

Description

Technical Field

[0001] The present invention relates to the technical field of superheaters of coal-fired boilers, and particularly relates to a method and a system for predicting fly ash erosion of superheaters of coal-fired boilers. Background Art

[0002] The furnace tubes of power station boilers are continuously eroded by high-temperature flue gas for a long time. The thinning degree of the furnace tubes has an exponential function relationship with the flue gas ash particle concentration and the flue gas velocity. When the flue gas temperature decreases, the ash particles harden, the flue gas velocity is uneven at the airflow turning points, the arrangement of the tube bundles changes, and non-standard operating conditions such as oxidation slagging of high-volatile pulverized coal will all exacerbate the local erosion of the furnace tubes. The complex and changeable flue gas flow field environment makes it difficult to determine the thinning rate of the furnace tubes due to flue gas erosion. Even when the power station boiler is shut down for maintenance, due to the large number and long length of the tube bundles, it is impossible to conduct a full-coverage and non-blind-spot inspection, and the detection results cannot truly reflect the thinning situation of all furnace tubes.

[0003] Therefore, usually, the fly ash erosion in the boiler tube bundles is studied. However, the above method only focuses on the fly ash erosion in the boiler tube bundles and does not study the three-dimensional erosion of the overall heat exchange tube screens of the boiler, resulting in overly one-sided erosion information of the whole boiler and potential safety hazards. Summary of the Invention

[0004] The present invention provides a method and a system for predicting fly ash erosion of superheaters of coal-fired boilers, which solve the technical problem that the existing method only focuses on the fly ash erosion in the boiler tube bundles and does not study the three-dimensional erosion of the overall heat exchange tube screens of the boiler, resulting in overly one-sided erosion information of the whole boiler and potential safety hazards.

[0005] A method for predicting fly ash erosion of superheaters of coal-fired boilers provided by the first aspect of the present invention includes:

[0006] In response to the received fly ash erosion prediction request, obtaining the superheater data of the coal-fired boiler superheater corresponding to the fly ash erosion prediction request;

[0007] Inputting the superheater data into a preset physical model to generate a superheater physical model, and inputting it into a preset DPM model;

[0008] Performing continuous-phase flow field simulation and discrete-phase simulation on the superheater physical model in sequence through the DPM model, and outputting the impact velocity of the particles;

[0009] Constructing an impact angle function based on the empirical coefficients and impact angle numbers of a preset plurality of erosion models;

[0010] Calculating the wear amount of the heat exchange tube screen of the coal-fired boiler superheater by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe, and the velocity index.

[0011] Optionally, the step of inputting the superheater data into a preset physical model to generate a superheater physical model and inputting the generated model into a preset DPM model includes:

[0012] Input the superheater data into a preset physical model;

[0013] Construct an initial superheater physical model according to the number and size of the pipes corresponding to the superheater data;

[0014] Perform meshing on the initial superheater physical model through the physical model to generate a meshed superheater physical model;

[0015] Input the meshed superheater physical model into a preset DPM model.

[0016] Optionally, the step of performing a continuous-phase flow field simulation and a discrete-phase simulation on the superheater physical model in sequence through the DPM model and outputting the impact velocity of the particles includes:

[0017] Perform a continuous-phase flow field simulation on the meshed superheater physical model through the DPM model and output the gas operation data in the superheater of the coal-fired boiler; wherein, the calculation equation for the continuous-phase flow field simulation is:

[0018]

[0019]

[0020] In the formula, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, P refers to the static pressure, refers to the stress tensor, refers to the body force, refers to the momentum increased due to the discrete phase, and t refers to time;

[0021] Perform a discrete-phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model and output the impact velocity of the particles.

[0022] Optionally, the step of performing a discrete-phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model and outputting the impact velocity of the particles includes:

[0023] Perform a discrete-phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model and output the impact velocity of the particles; wherein, the calculation equation for the impact velocity vector of the particles is:

[0024]

[0025] In the formula, refers to the impact velocity vector of the particle, and t refers to time, refers to the drag force, refers to the pressure gradient force, refers to the virtual mass force, refers to the buoyancy force.

[0026] Optionally, it further includes:

[0027] The drag force is:

[0028]

[0029] In the formula, refers to the drag force, refers to the velocity vector of the particle; d p refers to the particle diameter; ρ p refers to the particle density; Re p refers to the particle Reynolds number; C d refers to the drag coefficient, and μ refers to the viscosity;

[0030] The pressure gradient force is:

[0031]

[0032] In the formula, refers to the pressure gradient force, ρ refers to the gas density, ρ p refers to the particle density, and P refers to the static pressure;

[0033] The virtual mass force is:

[0034]

[0035] In the formula, refers to the virtual mass force, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, refers to the impact velocity vector of the particle, ρ p refers to the particle density;

[0036] The buoyancy force is:

[0037]

[0038] In the formula, refers to the buoyancy force, ρ p refers to the particle density, refers to the body force.

[0039] Optionally, the step of constructing the impact angle function based on the empirical coefficients and impact angle numbers of a preset plurality of erosion models includes:

[0040] Set a plurality of preset erosion models as the elbow wear rate model;

[0041] Input the historical operation data of the superheater of the coal-fired boiler into each of the elbow wear rate models according to a plurality of preset operation scenarios to generate the empirical coefficients of each of the elbow wear rate models;

[0042] Construct an impact angle function according to the empirical coefficients and impact angle degrees of each of the elbow wear rate models; wherein, the impact angle function is:

[0043]

[0044] In the formula, f(θ) refers to the impact angle function, the constant 2×10 -9 refers to the empirical parameter of the steel pipe, θ refers to the degree of the impact angle, B i refers to the empirical coefficient obtained from the parameters of the erosion model.

[0045] Optionally, the step of calculating the wear amount of the heat exchange tube bank of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the preset steel pipe, and the velocity exponent includes:

[0046] Calculate the wear amount of the heat exchange tube bank of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the preset steel pipe, and the velocity exponent; wherein, the calculation formula for the wear amount of the heat exchange tube bank is:

[0047]

[0048] In the formula, ER refers to the wear amount, f(θ) refers to the impact angle function, the constant 2×10 -9 refers to the empirical parameter of the steel pipe, θ refers to the degree of the impact angle, u p is the impact velocity of the particles, and 2.6 refers to the velocity exponent of the steel pipe.

[0049] A fly ash wear prediction system for a superheater of a coal-fired boiler provided by the second aspect of the present invention includes:

[0050] An acquisition module, configured to acquire the superheater data of the coal-fired boiler corresponding to the fly ash wear prediction request in response to the received fly ash wear prediction request;

[0051] A DPM model module, configured to input the superheater data into a preset physical model to generate a superheater physical model and input it into a preset DPM model;

[0052] An impact velocity module for performing continuous phase flow field simulation and discrete phase simulation on the superheater physical model in sequence through the DPM model, and outputting the impact velocity of particles;

[0053] An impact angle function module for constructing an impact angle function based on the empirical coefficients and impact angle degrees of a plurality of preset erosion models;

[0054] A wear amount module for calculating the wear amount of the heat exchange tube screen of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe, and the velocity index.

[0055] An electronic device provided in the third aspect of the present invention includes a memory and a processor. When a computer program stored in the memory is executed by the processor, the processor executes the steps of the method for predicting fly ash wear of the superheater of the coal-fired boiler as described in any one of the above.

[0056] A computer-readable storage medium provided in the fourth aspect of the present invention has a computer program stored thereon. When the computer program is executed, it implements the method for predicting fly ash wear of the superheater of the coal-fired boiler as described in any one of the above.

[0057] It can be seen from the above technical solutions that the present invention has the following advantages:

[0058] This method uses Ansys Fluent software to perform three-dimensional numerical simulation on the high-temperature superheater furnace tube model, modifies various limited wear models by using user-defined functions, obtains the internal flue gas velocity distribution of the furnace tube by numerically simulating the flow field distribution, and further calculates the wall wear rate and the wear rate distribution law of the furnace tube under high-temperature flue gas, laying a theoretical foundation for controlling the erosion wear of the flue gas on the tube wall in the superheater. Description of the Drawings

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0060] Figure 1 It is a flowchart of the steps of a method for predicting fly ash wear of the superheater of the coal-fired boiler provided in Embodiment 1 of the present invention;

[0061] Figure 2 It is a flowchart of the steps of a method for predicting fly ash wear of the superheater of the coal-fired boiler provided in Embodiment 2 of the present invention;

[0062] Figure 3Schematic diagram of the structure of a superheater provided in the second embodiment of the present invention;

[0063] Figure 4 Schematic diagram of the grid structure division of a physical model of a superheater provided in the second embodiment of the present invention;

[0064] Figure 5 Schematic diagram of the wear distribution of the separated screen pipes after UDF processing provided in the second embodiment of the present invention;

[0065] Figure 6 Schematic diagram of the comparison of the maximum wear amounts of the UDF and Oka models provided in the second embodiment of the present invention;

[0066] Figure 7 Schematic diagram of the comparison of the average wear amounts under the UDF and Oka models provided in the second embodiment of the present invention;

[0067] Figure 8 Block diagram of the structure of a fly ash wear prediction system for a superheater of a coal-fired boiler provided in the third embodiment of the present invention. Detailed implementation manners

[0068] The embodiments of the present invention provide a fly ash wear prediction method and system for a superheater of a coal-fired boiler, which are used to solve the technical problem that the existing research only focuses on the fly ash erosion in the boiler tube bundle and does not study the three-dimensional erosion of the overall heat exchange tube screen of the boiler, resulting in too one-sided erosion information of the overall boiler and potential safety hazards.

[0069] To make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0070] Please refer to Figure 1 , Figure 1 Flowchart of the steps of a fly ash wear prediction method for a superheater of a coal-fired boiler provided in the first embodiment of the present invention.

[0071] A fly ash wear prediction method provided by the present invention includes the following steps:

[0072] 101. In response to the received fly ash wear prediction request, obtain the superheater data of the superheater of the coal-fired boiler corresponding to the fly ash wear prediction request.

[0073] It should be noted that the fly ash erosion prediction request refers to a request for predicting the three-dimensional erosion information of the overall heat exchange tube screen of a coal-fired boiler.

[0074] The superheater data refers to the relevant data obtained from the on-site operation data of the boiler and the basic data of the overall boiler, such as the number and size data of the pipes, etc.

[0075] In specific implementation, when receiving the fly ash erosion prediction request, obtain the basic data, on-site operation data of the superheater of the coal-fired boiler for the fly ash erosion prediction request, and the relevant data obtained from the on-site operation data.

[0076] 102. Input the superheater data into a preset physical model to generate a superheater physical model, and input it into a preset DPM model.

[0077] It should be noted that the preferred coal-fired boiler superheater is the SG-1025 / 18.3-M830 type coal-fired subcritical once-through reheat controlled circulation drum boiler manufactured by Shanghai Boiler Works. The last-stage superheater of this boiler consists of 81×4 W-shaped tubes, and the quantity and size both meet the calculation requirements. Therefore, the superheater data is preferably the basic data, on-site operation data of the SG-1025 / 18.3-M830 type coal-fired subcritical once-through reheat controlled circulation drum boiler, and the relevant data obtained from the on-site operation data.

[0078] In specific implementation, input the superheater data into a physical model (i.e., geometric model) to generate a superheater physical model, then perform meshing processing to generate a meshed superheater physical model, and input it into the DPM model.

[0079] Specifically, the DPM (Discrete Phase Model) model adopts the Euler-Lagrange method, that is, the Euler method is used to solve the flow field and the Lagrange method is used to track the particle position.

[0080] 103. Through the DPM model, perform continuous phase flow field simulation and discrete phase simulation on the superheater physical model in sequence, and output the impact velocity of the particles.

[0081] It should be noted that the DPM model performs continuous phase flow field simulation on the gas of the meshed superheater physical model and particle tracking on the particles, so as to obtain the impact velocity of the particles.

[0082] In specific implementation, the gas is regarded as a continuous phase and solved by the Navier-Stokes equation; the particles are regarded as a discrete phase and solved by Newton's second law. In addition, two-way coupling is applied between the continuous phase and the discrete phase.

[0083] 104. Based on the empirical coefficients and impact angle numbers of a preset multiple of erosion models, construct an impact angle function.

[0084] It should be noted that the multiple preset erosion models are the DNV, E / CRC, Neilson and Gilchrist, and Oka erosion models. These four models are used as a reference for improving the elbow wear rate model, and a new wear model based on DNV is proposed. By fitting a large number of numerical simulation results, the empirical coefficients and impact angles are obtained by fitting the parameters of multiple models.

[0085] 105. The wear amount of the heat exchange tube screen of the superheater of a coal-fired boiler is calculated by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe, and the velocity index.

[0086] It should be noted that by applying the new wear model of DNV and fitting a large number of numerical simulation results, the relationship between the impact function and the wear amount is deduced, so as to obtain the wear amount of the heat exchange tube screen of the superheater of a coal-fired boiler.

[0087] Please refer to Figures 2-7 , Figure 2 which is the step flowchart of a method for predicting fly ash wear of a superheater of a coal-fired boiler provided in Embodiment 2 of the present invention.

[0088] A method for predicting fly ash wear of a superheater of a coal-fired boiler provided by the present invention includes the following steps:

[0089] 201. In response to the received fly ash wear prediction request, obtain the superheater data of the superheater of the coal-fired boiler corresponding to the fly ash wear prediction request.

[0090] In the embodiment of the present invention, the specific implementation process of step 201 is similar to that of step 101, and will not be elaborated here.

[0091] 202. Input the superheater data into a preset physical model.

[0092] It should be noted that the superheater data is the relevant data obtained through the instruction manual of the superheater of the coal-fired boiler or through the on-site operation data of the boiler. By inputting the superheater data into the physical model, the superheater physical model, that is, the superheater geometric model, can be obtained.

[0093] 203. Construct an initial superheater physical model according to the number of pipes and the pipe size corresponding to the superheater data.

[0094] It should be noted that the superheater of the coal-fired boiler is preferably the SG-1025 / 18.3-M830 type coal-fired subcritical once-through reheat controlled circulation drum boiler manufactured by Shanghai Boiler Works. The last-stage superheater of this boiler consists of 81×4 W-shaped tubes. The number and size of the pipes corresponding to the superheater data are the same as those of the SG-1025 / 18.3-M830 type coal-fired subcritical once-through reheat controlled circulation drum boiler. Specifically, the structure of the superheater is as Figure 3 shown.

[0095] The physical model can construct an initial superheater physical model, that is, a superheater geometric model, through the number and size of the pipes of the superheater.

[0096] 204. Mesh the initial superheater physical model through the physical model to generate a meshed superheater physical model.

[0097] In specific implementation, the present invention only considers the wear of the main part of the superheater tube screen, and does not consider the steam-water drum part and other parts that are not the heat-receiving working surface or not subject to wear; assume that the superheater tube screen is composed of multiple parallel pipes with a certain spacing; when the flue gas coming out of the boiler passes through various heat exchange surfaces and flue ducts and reaches the superheater tube screen, the distribution of the flue gas velocity and particle concentration is uneven. In this simulation, it is assumed that the flue gas velocity and particle concentration are uniform at the inlet boundary, and complex situations such as swirl are not considered, and the velocity direction is perpendicular to the inlet boundary; assume that the flow field velocity and particle movement only change in the direction perpendicular to the superheater tube screen; assume that the particle shape is circular, has the same flow velocity as the main-phase flue gas, is evenly distributed in the main phase, and the physical properties of each particle such as density and hardness are the same, only the size is different.

[0098] Considering the above reasonable simplifications comprehensively, the geometric model is a full-size fine pipe modeling, and the hybrid grid method is used for division as Figure 4 shown. Structured grids are used for the straight pipes and the surrounding flue gas flow field regions, and unstructured encrypted grids are used for the bent pipes and the central regions. After grid independence verification, the number of model grids obtained is 9.999×10 6 .

[0099] Specifically, the structured grid has high division quality and few grid numbers; the unstructured grid has a decreased quality and more grid numbers.

[0100] 205. Input the meshed superheater physical model into the preset DPM model.

[0101] It should be noted that the superheater physical model after structured meshing is input into the preset DPM model.

[0102] 206. Perform continuous phase flow field simulation and discrete phase simulation on the superheater physical model through the DPM model in sequence, and output the impact velocity of the particles.

[0103] Optionally, step 206 includes the following steps S11 - S12:

[0104] S11. Perform a continuous - phase flow - field simulation on the meshed superheater physical model through the DPM model, and output the gas operation data inside the coal - fired boiler superheater; wherein, the calculation equation for the continuous - phase flow - field simulation is:

[0105]

[0106]

[0107] In the formula, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, P refers to the static pressure, refers to the stress tensor, refers to the body force, refers to the momentum increased due to the discrete phase, and t refers to time;

[0108] S12. Perform a discrete - phase simulation on the particles inside the coal - fired boiler superheater through the DPM model, and output the impact velocity of the particles.

[0109] It should be noted that the fluid phase, as a continuous medium, solves the Navier - Stokes equation, while the particle phase solves by tracking the motion trajectories of a large number of particles, bubbles or droplets. The particle phase can exchange momentum, mass, and energy with the fluid phase. When the volume fraction of the particle phase in the flow - field region is small enough, the interaction between particles can be ignored, and at this time, it becomes quite simple to use the DPM method to track the particle motion trajectories.

[0110] Specifically, the gas is regarded as a continuous phase and solved using the Navier - Stokes equation. The Navier - Stokes equation used for continuous - phase calculation is as follows:

[0111]

[0112]

[0113] In the formula, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, P refers to the static pressure, refers to the stress tensor, refers to the body force, refers to the momentum increased due to the discrete phase, and t refers to time.

[0114] Among them, the calculation formula for the stress tensor is as follows:

[0115]

[0116] In the formula, refers to the stress tensor, refers to the instantaneous velocity vector of the gas, μ refers to the gas viscosity; I refers to the unit tensor.

[0117] Specifically, the particles are regarded as a discrete phase and solved by Newton's second law. In addition, two-way coupling is applied between the continuous phase and the discrete phase.

[0118] Optionally, step S12 includes the following step S21:

[0119] S21. Perform discrete phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model, and output the impact velocity of the particles; among them, the calculation equation of the impact velocity vector of the particles is:

[0120]

[0121] In the formula, refers to the impact velocity vector of the particles, t refers to time, refers to the drag force, refers to the pressure gradient force, refers to the virtual mass force, refers to the buoyancy force.

[0122] It should be noted that the DPM model performs discrete phase simulation on the particles in the superheater of the coal-fired boiler. The discrete phase model integrates the motion equation of the particles in the Lagrangian coordinate system to obtain the motion trajectory of the particles. According to Newton's second law, the proposed particle motion control equation is as follows:

[0123]

[0124] In the formula, refers to the impact velocity vector of the particles, t refers to time, refers to the drag force, refers to the pressure gradient force, refers to the virtual mass force, refers to the buoyancy force.

[0125] Optionally, this method further includes the following steps S31-S34:

[0126] S31. The drag force is:

[0127]

[0128] In the formula, refers to the drag force, refers to the velocity vector of the particles; d p refers to the particle diameter; ρp refers to the particle density; Re p refers to the particle Reynolds number; C d refers to the drag coefficient, and μ refers to the viscosity;

[0129] S32. The pressure gradient force is:

[0130]

[0131] In the formula, refers to the pressure gradient force, ρ refers to the gas density, ρ p refers to the particle density, and P refers to the static pressure;

[0132] S33. The virtual mass force is:

[0133]

[0134] In the formula, refers to the virtual mass force, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, refers to the impact velocity vector of the particle, ρ p refers to the particle density;

[0135] S34. The buoyancy force is:

[0136]

[0137] In the formula, refers to the buoyancy force, ρ p refers to the particle density, refers to the body force.

[0138] It should be noted that the drag force is the main force applied to the particle, and the drag force is:

[0139]

[0140] In the formula, refers to the drag force, refers to the velocity vector of the particle; d p refers to the particle diameter; ρ p refers to the particle density; Re p refers to the particle Reynolds number; C d refers to the drag coefficient, and μ refers to the viscosity.

[0141] The pressure gradient force is caused by the pressure change in the fluid, and the pressure gradient force is:

[0142]

[0143] In the formula, refers to the pressure gradient force, ρ refers to the gas density, ρ p refers to the particle density, and P refers to the static pressure.

[0144] The virtual mass force is:

[0145]

[0146] In the formula, refers to the virtual mass force, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, refers to the impact velocity vector of the particle, ρ p refers to the particle density.

[0147] The buoyancy force is:

[0148]

[0149] In the formula, refers to the buoyancy force, ρ p refers to the particle density, refers to the body force.

[0150] Specifically, since the particles doing work are very small, the pressure change within the range of one particle diameter can be ignored. At the same time, since the density of the fluid is much smaller than the density of the particles, the pressure gradient force can be ignored. Since the virtual mass force is only important when the fluid density is greater than the particle density, the virtual mass force can also be ignored.

[0151] The steady-state DPM model is applicable to the case where particles are injected into a continuous flow field with clear inlet and outlet conditions, and cannot effectively simulate the flow field in which particles are suspended in a continuous medium indefinitely, such as solid particles in a closed system (stirred tank, mixing vessel or fluidized bed). Using a steady-state solution for unsteady flow will lead to deterioration of the calculation results. Therefore, the transient DPM model is used to simulate the fly ash erosion in the superheater area of the present invention.

[0152] 207. Construct an impact angle function based on the empirical coefficients and impact angle numbers of a plurality of preset erosion models.

[0153] Optionally, step 207 includes the following steps S41 - S43:

[0154] S41. Set a plurality of preset erosion models as elbow wear rate models;

[0155] S42. Input the historical operation data of the superheater of the coal-fired boiler into each elbow wear rate model according to a plurality of preset operation scenarios to generate the empirical coefficients of each elbow wear rate model;

[0156] S43. Construct an impact angle function based on the empirical coefficients and impact angle degrees of each elbow wear rate model. The impact angle function is as follows:

[0157] where is the degree of the impact angle, and B i refers to the empirical coefficient obtained from the parameters of the erosion model.

[0158] It should be noted that in the present invention, four erosion models, namely DNV, E / CRC, Neilson and Gilchrist, and Oka, are selected as the improvement references for the elbow wear rate model. A new wear model based on DNV is proposed. The historical operation data of the superheater of the coal-fired boiler are input into each elbow wear rate model according to multiple preset operation scenarios for simulation. Through the fitting of a large number of numerical simulation results, the empirical coefficients obtained by fitting the parameters of multiple models are obtained.

[0159] In specific implementation, construct an impact angle function according to the empirical coefficients and impact angle degrees of each elbow wear rate model. The impact angle function is as follows:

[0160] where is the degree of the impact angle, and B i refers to the empirical coefficient obtained from the parameters of the erosion model.

[0161] Specifically, the empirical coefficient B obtained by fitting the parameters of multiple models i is listed in Table 1 below:

[0162] <![CDATA[B1]]> <![CDATA[B2]]> <![CDATA[B3]]> <![CDATA[B4]]> <![CDATA[B5]]> <![CDATA[B6]]> <![CDATA[B7]]> <![CDATA[B8]]> 11.620 62.571 181.297 300.133 291.035 163.078 48.633 5.931

[0163] Table 1. Selection of fitting empirical parameter Bi.

[0164] 208. Calculate the wear amount of the heat exchange tube screen of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe, and the velocity index.

[0165] Optionally, step 208 includes the following step S51:

[0166] S51. Calculate the wear amount of the heat exchange tube screen of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the preset steel pipe, and the velocity index. The calculation formula for the wear amount of the heat exchange tube screen is as follows:

[0167]

[0168] In the formula, ER refers to the wear amount, f(θ) refers to the impact angle function, the constant 2×10 -9 refers to the empirical parameters of the steel pipe, θ refers to the degree of the impact angle, u p is the impact velocity of the particles, and 2.6 refers to the velocity index of the steel pipe.

[0169] It should be noted that the historical operation data of the superheater of the coal-fired boiler are input into each elbow wear rate model according to multiple preset operation scenarios for simulation. Through the fitting of a large number of numerical simulation results, the relationship between the impact angle function and the wear amount is derived:

[0170]

[0171] In the formula, ER refers to the wear amount, f(θ) refers to the impact angle function, the constant 2×10 -9 refers to the empirical parameter of the steel pipe, θ refers to the degree of the impact angle, u p is the impact velocity of the particles, and 2.6 refers to the velocity exponent of the steel pipe.

[0172] Specifically, based on the above wear model, the present invention constructs a UDF empirical equation by using the DPM_DEFINE_EROSION macro, and compares it with the calculation results of the Oka wear model. The k-epsilon Realizable format is used for the turbulence model to obtain accurate flow and heat transfer characteristics. In order to improve the convergence, the SIMPLE algorithm is used to couple the pressure and velocity. The pressure term adopts the standard discretization format, and the convection term and divergence term adopt the second-order upwind discretization format. The convergence criterion for all calculations is set such that the residual in each control equation is less than 10-6 or the number of iterations reaches 500 times during the steady-state simulation. The number of continuous phase iterations for each iteration coupled with the discrete phase model is set to 10 times. The average diameter of the pulverized coal particles used is 50μm

[30] , the particle movement velocity is 10.4m / s, and a total of 402,800 particles are tracked in this simulation.

[0173] Specifically, as Figure 5 shown, the wear distribution of the separating screen pipeline after correcting the elbow wear model by using UDF can be seen more intuitively from this figure. The wear distribution of the straight pipe part is similar to that presented by the Oka model, both being a strip-shaped distribution concentrated on the side of the front screen near the flue gas inlet; the wear distribution of the elbow part still conforms to the point-shaped distribution of the Oka model, but it is more in line with the conclusion in many studies that the wear of the elbow at the same position is more serious than that of the straight pipe. Combining with the improved relational expression (10), it can be analyzed that this model pays more attention to the influence of the impact angle on the wear amount compared with other models. The geometric flow field of this simulation is more inclined to local flue gas erosion, so the impact angle of wear on the elbow part is relatively small, resulting in an unclear calculation result of the elbow part in the conventional wear model. The improved model can make up for the influence brought by the simplification of the calculation model.

[0174] Refer to Figure 6 shown Figure 6The comparison of the growth rate of the maximum wear amount over time is given. The wear amount of the Oka model shows a linear growth, while the wear amount of the udf model is more inclined to exponential growth. This indicates that considering the impact angle function, the wear of the elbow will become more severe over time. On the contrary, the order of magnitude of the maximum wear amount of the Oka model is higher than that of the udf model, but the change amount within the same time interval is very small. It is more difficult to see the wear change law for non-long-term simulations, especially the wear comparison between the straight pipe and the elbow in the short term. In Figure 7 it can be seen that the average wear amount of the straight pipe is larger than that of the elbow. Obviously, the wear gap between the straight pipe and the elbow of the udf model is smaller. Compared with the 6-fold average wear amount gap of the Oka model, the gap of the udf model is only 3 times, which is also in line with the previous analysis and consistent with the prediction that the wear amount of the elbow increases after adopting the udf model.

[0175] Please refer to Figure 8 , Figure 8 which is the structural block diagram of a fly ash wear prediction system for the superheater of a coal-fired boiler provided in Embodiment 3 of the present invention.

[0176] A fly ash wear prediction system for the superheater of a coal-fired boiler provided by the present invention includes:

[0177] An acquisition module 801, configured to acquire superheater data of the coal-fired boiler superheater corresponding to the fly ash wear prediction request in response to the received fly ash wear prediction request;

[0178] A DPM model module 802, configured to input the superheater data into a preset physical model to generate a superheater physical model and input it into a preset DPM model;

[0179] An impact velocity module 803, configured to perform a continuous phase flow field simulation and a discrete phase simulation on the superheater physical model through the DPM model in sequence, and output the impact velocity of the particles;

[0180] An impact angle function module 804, configured to construct an impact angle function based on the empirical coefficients of a preset plurality of erosion models and the impact angle degrees;

[0181] A wear amount module 805, configured to calculate the wear amount of the heat exchange tube screen of the coal-fired boiler superheater by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe, and the velocity exponent.

[0182] Optionally, the DPM model module 802 includes:

[0183] A physical model sub-module, configured to input the superheater data into a preset physical model;

[0184] A construction sub-module, configured to construct an initial superheater physical model according to the number of pipes and the pipe size corresponding to the superheater data;

[0185] The superheater physical model sub-module is used to mesh the initial superheater physical model through a physical model to generate a meshed superheater physical model;

[0186] The DPM model sub-module is used to input the meshed superheater physical model into a preset DPM model.

[0187] Optionally, the impact velocity module 803 includes:

[0188] The gas operation data sub-module is used to perform a continuous phase flow field simulation on the meshed superheater physical model through the DPM model and output the gas operation data in the superheater of the coal-fired boiler; where the calculation equation for the continuous phase flow field simulation is:

[0189]

[0190]

[0191] In the formula, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, P refers to the static pressure, refers to the stress tensor, refers to the body force, refers to the momentum increased due to the discrete phase, and t refers to time;

[0192] The impact velocity sub-module is used to perform a discrete phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model and output the impact velocity of the particles.

[0193] Optionally, the impact velocity sub-module includes:

[0194] The particle impact velocity sub-module is used to perform a discrete phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model and output the impact velocity of the particles; where the calculation equation for the particle impact velocity vector is:

[0195]

[0196] In the formula, refers to the particle impact velocity vector, t refers to time, refers to the drag force, refers to the pressure gradient force, refers to the virtual mass force, refers to the buoyancy force.

[0197] Optionally, it further includes:

[0198] The drag force sub-module is used for the drag force to be:

[0199]

[0200] In the formula, refers to the drag force, refers to the velocity vector of the particle; d p refers to the particle diameter; ρ p refers to the particle density; Re p refers to the particle Reynolds number; C d refers to the drag coefficient, and μ refers to the viscosity;

[0201] The pressure gradient force sub-module is used for the pressure gradient force to be:

[0202]

[0203] In the formula, refers to the pressure gradient force, ρ refers to the gas density, ρ p refers to the particle density, and P refers to the static pressure;

[0204] The virtual mass force sub-module is used for the virtual mass force to be:

[0205]

[0206] In the formula, refers to the virtual mass force, ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, refers to the impact velocity vector of the particle, ρ p refers to the particle density;

[0207] The buoyancy sub-module is used for the buoyancy to be:

[0208]

[0209] In the formula, refers to the buoyancy, ρ p refers to the particle density, refers to the body force.

[0210] Optionally, the impact angle function module includes:

[0211] The elbow wear rate model sub-module is used to set a plurality of preset erosion models as the elbow wear rate model;

[0212] The empirical coefficient sub-module is used to input the historical operation data of the superheater of the coal-fired boiler into each elbow wear rate model according to a plurality of preset operation scenarios to generate the empirical coefficients of each elbow wear rate model;

[0213] The impact angle function sub-module is used to construct an impact angle function according to the empirical coefficients of each elbow wear rate model and the impact angle degrees; among them, the impact angle function is:

[0214]

[0215] In the formula, f(θ) refers to the impact angle function, and the constant 2×10 -9 refers to the empirical parameter of the steel pipe, θ refers to the degree of the impact angle, and B i refers to the empirical coefficient obtained from the parameters of the erosion model.

[0216] Optionally, the wear amount module 805 includes:

[0217] A wear amount sub-module, configured to calculate the wear amount of the heat exchange tube screen of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the preset steel pipe, and the velocity index; wherein, the calculation formula for the wear amount of the heat exchange tube screen is:

[0218]

[0219] In the formula, ER refers to the wear amount, f(θ) refers to the impact angle function, and the constant 2×10 -9 refers to the empirical parameter of the steel pipe, θ refers to the degree of the impact angle, and u p is the impact velocity of the particles, and 2.6 refers to the velocity index of the steel pipe.

[0220] Embodiment 4 of the invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program; when the computer program is executed by the processor, the processor is enabled to execute the steps of the fly ash wear prediction method for the superheater of the coal-fired boiler as described in any one of the foregoing embodiments.

[0221] Embodiment 5 of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the fly ash wear prediction method for the superheater of the coal-fired boiler as described in any one of the foregoing embodiments is implemented.

[0222] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0223] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be in electrical, mechanical, or other forms.

[0224] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0225] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0226] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or 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. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0227] As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A method for predicting fly ash wear of a coal-fired boiler superheater, characterized in that: include: In response to the received fly ash wear prediction request, obtaining superheater data of a coal-fired boiler superheater corresponding to the fly ash wear prediction request; Inputting the superheater data into a preset physical model, generating a superheater physical model, and inputting the superheater physical model into a preset DPM model; The DPM model is used to sequentially perform continuous phase flow field simulation and discrete phase simulation on the superheater physical model, and output the impact velocity of particles; Based on the empirical coefficients and impact angles of multiple preset erosion models, an impact angle function is constructed; The wear amount of the heat exchange tube panel of the coal-fired boiler superheater is calculated by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe and the velocity index; The step of sequentially performing continuous phase flow field simulation and discrete phase simulation on the superheater physical model through the DPM model and outputting the impact velocity of particles comprises: The DPM model is used to perform continuous phase flow field simulation on the gridded superheater physical model, and the gas operation data in the superheater of the coal-fired boiler is output; wherein the calculation equation of the continuous phase flow field simulation is: Where ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, P refers to the static pressure, is the stress tensor, refers to the volume force, refers to the momentum added due to the discrete phase, and t refers to the time; The DPM model is used to perform discrete phase simulation on the particles in the superheater of the coal-fired boiler, and the impact velocity of the particles is output; wherein the calculation equation of the impact velocity vector of the particles is: In the formula, is the particle's impact velocity vector, refers to the drag force, refers to the pressure gradient force, refers to the virtual mass force, It refers to buoyancy.

2. The method for predicting fly ash wear of a superheater of a coal-fired boiler according to claim 1, characterized in that: The step of inputting the superheater data into a preset physical model, generating a superheater physical model, and inputting a preset DPM model comprises: Inputting the superheater data into a preset physical model; Constructing an initial superheater physical model according to the number of pipes and pipe sizes corresponding to the superheater data; Meshing the initial superheater physical model through the physical model to generate a meshed superheater physical model; The gridded superheater physical model is input into a preset DPM model.

3. The method for predicting fly ash wear of a coal-fired boiler superheater according to claim 1, characterized in that: Also includes: The drag force is: In the formula, refers to the drag force, refers to the velocity vector of the particle; d p refers to the particle diameter; ρ p Refers to the particle density; Re p Refers to the particle Reynolds number; C d refers to the drag coefficient, and μ refers to the viscosity; The pressure gradient force is: In the formula, refers to the pressure gradient force, ρ refers to the gas density, and ρ p refers to the particle density, and P refers to the static pressure; The virtual mass force is: In the formula, refers to the virtual mass force, ρ refers to the gas density, is the instantaneous velocity vector of the gas, refers to the particle impact velocity vector, ρ p refers to the particle density; The buoyancy is: In the formula, is the buoyancy, ρ p refers to the particle density, It refers to volume force.

4. The method for predicting fly ash wear of a superheater of a coal-fired boiler according to claim 1, characterized in that: The step of constructing the impact angle function based on the empirical coefficients and impact angles of the preset multiple erosion models includes: Setting multiple preset erosion models as elbow wear rate models; Inputting historical operation data of the coal-fired boiler superheater into each of the elbow wear rate models according to a plurality of preset operation scenarios to generate empirical coefficients of each of the elbow wear rate models; According to the empirical coefficients and impact angles of each elbow wear rate model, an impact angle function is constructed; wherein the impact angle function is: Where f(θ) refers to the impact angle function, θ refers to the degree of the impact angle, and B i Refers to the empirical coefficients obtained from the parameters of the erosion model.

5. The method for predicting fly ash wear of a coal-fired boiler superheater according to claim 1, characterized in that: The step of calculating the wear amount of the heat exchange tube panel of the coal-fired boiler superheater by using the impact velocity of the particles, the impact angle function, the preset empirical parameters of the steel pipe and the velocity index comprises: The impact velocity of the particles, the impact angle function, the empirical parameters of the preset steel pipe and the velocity index are used to calculate the wear amount of the heat exchange tube panel of the coal-fired boiler superheater; wherein the calculation formula for the wear amount of the heat exchange tube panel is: Where ER refers to the wear amount, f(θ) refers to the impact angle function, and the constant is 2×10 -9 refers to the empirical parameters of the steel pipe, θ refers to the degree of the impact angle, u p is the impact velocity of the particles, and 2.6 refers to the velocity index of the steel pipe.

6. A coal-fired boiler superheater fly ash wear prediction system, characterized in that: include: an acquisition module, configured to, in response to a received fly ash wear prediction request, acquire superheater data of a coal-fired boiler superheater corresponding to the fly ash wear prediction request; A DPM model module, used for inputting the superheater data into a preset physical model, generating a superheater physical model, and inputting the superheater physical model into a preset DPM model; An impact velocity module, used to perform continuous phase flow field simulation and discrete phase simulation on the superheater physical model in sequence through the DPM model, and output the impact velocity of particles; An impact angle function module is used to construct an impact angle function based on the empirical coefficients and impact angles of multiple preset erosion models; A wear amount module, for calculating the wear amount of the heat exchange tube panel of the superheater of the coal-fired boiler by using the impact velocity of the particles, the impact angle function, the empirical parameters of the steel pipe and the velocity index; The impact velocity module comprises: The gas operation data submodule is used to perform continuous phase flow field simulation on the gridded superheater physical model through the DPM model, and output the gas operation data in the superheater of the coal-fired boiler; wherein the calculation equation of the continuous phase flow field simulation is: Where ρ refers to the gas density, refers to the instantaneous velocity vector of the gas, P refers to the static pressure, is the stress tensor, refers to the volume force, refers to the momentum added due to the discrete phase, and t refers to the time; An impact velocity submodule, used to perform discrete phase simulation on particles in the superheater of the coal-fired boiler through the DPM model, and output the impact velocity of the particles; The impact velocity submodule includes: The particle impact velocity submodule is used to perform discrete phase simulation on the particles in the superheater of the coal-fired boiler through the DPM model and output the impact velocity of the particles; wherein the calculation equation of the impact velocity vector of the particles is: In the formula, is the particle's impact velocity vector, refers to the drag force, refers to the pressure gradient force, refers to the virtual mass force, It refers to buoyancy.

7. An electronic device, characterized in that: It comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the method for predicting fly ash wear of a coal-fired boiler superheater as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the method for predicting fly ash wear of a coal-fired boiler superheater according to any one of claims 1 to 5 is implemented.

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