Method for predicting thermal wear of pump for direct coal liquefaction considering high temperature effect

Abstract

The application discloses a pump heat wear prediction method for coal direct liquefaction considering high temperature effect, and belongs to the technical field of fluid machinery and reliability engineering, and comprises the following steps: coupling iteration of a liquid phase control equation and a solid particle dynamics model by considering the high temperature effect to obtain a solid-liquid two-phase flow numerical model; full flow field modeling is performed on a fluid domain composed of a pump overcurrent component for coal direct liquefaction, and the fluid domain is meshed; a heat-flow-solid multi-field coupling calculation system is constructed, a large eddy simulation method based on temperature correction and a discrete element method coupling method are used to solve the solid-liquid two-phase flow numerical model, and flow field and particle field information at each position in the pump are obtained; operating condition parameters are acquired, a heat wear rate is obtained through a heat wear rate calculation formula based on the flow field and particle field information at each position in the pump, and a predicted wear amount of the overcurrent component is obtained; and the prediction precision and applicability of the wear model are improved.

Description

Technical Field

[0001] This application belongs to the field of fluid machinery and reliability engineering technology, and specifically relates to a method for predicting the thermal wear of pumps used in direct coal liquefaction that takes into account the high temperature effect. Background Technology

[0002] The coal direct liquefaction pump is a core piece of equipment in the coal-to-oil hydrocracking suspension bed technology. Its main function is to provide expansion power to the catalyst bed within the reactor, achieving high backmixing of the materials, maintaining high homogeneity in the properties, operating pressure, and temperature of the materials within the reactor, and enhancing the depth of the hydrocracking reaction. Due to process requirements, the coal direct liquefaction pump needs to transport oil slurry containing up to 45% coal particles under high temperature (455℃), high pressure (19.388MPa), and hydrogen-containing conditions, making its operating conditions particularly harsh. Investigations have revealed that in past use, the coal direct liquefaction pump frequently experienced erosion and wear of its flow-through components, such as… Figure 1 (a) in the diagram is the impeller wear diagram, such as... Figure 1 (b) in the diagram shows damage to the pump body sealing surface, which leads to deterioration of the unit's performance and severely restricts the continuous and normal operation of the coal-to-oil process system.

[0003] Unlike the wear conditions in conventional pumps, the wear mechanisms and behaviors in pumps used for direct coal liquefaction are far more complex due to the high temperature, high solids content, and significant phase differences in the transported medium. The thermal wear behavior caused by high temperatures differs from traditional flow-induced wear, which does not consider thermal factors, in terms of wall wear mechanisms and characteristics. Secondly, the high temperature effect causes a significant temperature rise in the flow components, leading to adverse thermal effects such as thermal stress, thermal expansion, and thermal softening, ultimately resulting in a decrease in material strength and exacerbating wear in the small contact area of ​​the flow component walls. Given the current lack of research on thermal-fluid-structure interaction wear in pumps under high-temperature environments, the unclear influence of thermal softening effects caused by temperature rise in the flow component walls and plastic strengthening effects caused by plastic deformation on the material surface flow yield pressure, and the absence of flow erosion thermal wear models considering temperature effects, suitable numerical methods are currently unavailable for predicting and analyzing the thermal wear behavior and wear amount in pumps used for direct coal liquefaction and other high-temperature pumps. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method for predicting the thermal wear of pumps used in direct coal liquefaction that considers the high-temperature effect. This method can accurately simulate the flow state, particle motion characteristics, and particle-fluid interaction mechanisms within the pump. Based on the results of particle-fluid coupling, the traditional wear model is modified to obtain the wear amount and wear distribution of the pump's flow components under high-temperature conditions, thereby enabling the prediction of thermal flow wear within the pump.

[0005] The method includes:

[0006] Considering the high temperature effect, the liquid phase control equation is coupled and iterated with the solid particle dynamics model to obtain a numerical model of solid-liquid two-phase flow.

[0007] A full flow field model was performed on the fluid domain consisting of the pump flow components used in direct coal liquefaction, and the fluid domain was meshed.

[0008] A multi-field coupled calculation system of heat-fluid-solid was constructed. The numerical model of solid-liquid two-phase flow was solved by the coupled method of temperature-corrected large eddy simulation and discrete element method to obtain the flow field and particle field information at various points in the pump.

[0009] By acquiring operating parameters and using the thermal wear rate calculation formula based on the flow field and particle field information at various points within the pump, the predicted wear amount of the flow-through components is obtained.

[0010] Optionally, considering the high-temperature effect, the liquid phase control equation is coupled and iterated with the solid particle dynamics model to obtain a solid-liquid two-phase flow numerical model, including:

[0011] The reaction relationship between particles and fluid is realized by introducing momentum exchange source terms into the liquid phase control equations, which include continuity equations, momentum equations, and energy equations.

[0012] Considering the influence of the medium temperature gradient on the particles, a thermophoretic force is introduced to establish a dynamic model of solid particles;

[0013] A two-way coupling method is used to handle the interaction between the fluid phase and the solid particle phase. At the same time, the Eulerian-Lagrange method is used to process the solid-liquid two-phase flow, resulting in a numerical model of the solid-liquid two-phase flow.

[0014] Optionally, the liquid phase control equations include a continuity equation, a momentum equation, and an energy equation;

[0015] The expression for the continuity equation is:

[0016]

[0017] in, The mathematical symbol for the partial derivative of a multivariable function; t represents time; It represents the liquid phase volume fraction; The density of the liquid; The mathematical notation for representing vector differential operators; The velocity vector of the liquid;

[0018] The expression for the momentum equation is:

[0019]

[0020] Where p is the pressure; It is the acceleration due to gravity; The dynamic viscosity of the liquid phase; This is the momentum exchange source term between the liquid and solid phases;

[0021] The expression for the energy equation is:

[0022]

[0023] in, The internal energy per unit mass of the liquid phase. The liquid phase heat flux vector. This is the energy dissipation term within the liquid phase. This is the energy conversion term between the liquid and solid phases. For liquid phase heat capacity, This refers to the temperature of the liquid medium itself.

[0024] Optionally, the expression for the solid particle dynamics model is:

[0025]

[0026]

[0027] in, For particle mass, For particle velocity, Let gravitational force be the force acting on the particle. The drag force acting on the particle. The Saffman lift force acting on the particle. The force exerted on a particle is the interparticle force. The additional mass force experienced by the particle. The pressure gradient force acting on the particles. The surface tension experienced by the particles, The thermophoretic force experienced by the particles, For the moment of inertia of the particle, Represents particle acceleration. The torque applied to the liquid phase, This refers to the torque generated by the contact between particles.

[0028] Optionally, the expression for the thermal wear rate is:

[0029]

[0030] in, This represents the volumetric rate at which material is worn away per unit time. Reference temperature Benchmark efficiency, It is the temperature sensitivity coefficient. It is the stress state suppression coefficient. It is the yield strength of the material at that temperature. For local stress, , , For coefficients, For the particle collision angle, The basic hardness of the material. Where is the softening coefficient of the material, and T is the temperature determined by the coupled simulation. For the enhancement coefficient, For reference impact frequency, N is the total number of particles impacting this micro-element per unit time. For the first in the flow field The mass of each particle For the first in the flow field The speed of each particle.

[0031] Optionally, the thermal-fluid-solid multi-field coupled calculation system includes:

[0032] Based on the actual operating conditions of the pump, the boundary conditions for solving the flow field are correctly set, the fluid domain is solved, and the obtained flow field information is applied to the particles. The numerical model of solid-liquid two-phase flow is solved using a coupled method of temperature-corrected large eddy simulation and discrete element method to solve the dynamic model of solid particles, calculate the trajectory of the particles, and apply the effect of the particles on the fluid in reverse to the continuous phase fluid to obtain the solid-liquid two-phase flow parameters. The flow field information includes, but is not limited to, velocity, pressure, and temperature.

[0033] A solid domain model of the pump is established, the solid domain mesh is divided, the initial boundary conditions of the solid domain are set, and the calculated solid-liquid two-phase flow information is applied to the solid domain to perform finite element mechanical deformation calculations to obtain the stress and deformation of the pump flow components; the solid-liquid two-phase flow information includes, but is not limited to, flow field pressure, velocity, temperature and particle motion trajectory.

[0034] By utilizing the stress and deformation data of the pump's flow components, the flow domain mesh is updated and iterated repeatedly until the calculation converges, thus obtaining information on the flow field and particle field at various points within the pump.

[0035] Optionally, the method of solving the numerical model of solid-liquid two-phase flow using a coupled method of temperature-corrected large eddy simulation and discrete element method includes:

[0036] A temperature-corrected large eddy simulation method is used to process the turbulence model, and an anisotropic joint constraint dynamic stress model suitable for high-temperature transient thermal flow is constructed.

[0037] The discrete element method is used to process the discrete phase of solid particles. The contact force between particles is calculated by the soft ball collision model. The interaction between particles and fluid is solved iteratively by CFD-DEM bidirectional coupling method to obtain the temperature field, pressure field and velocity field of solid and liquid two phases.

[0038] Optionally, the step of performing full flow field modeling on the fluid domain composed of the pump flow components for direct coal liquefaction and meshing the fluid domain includes:

[0039] A full flow field model was performed on the fluid domain consisting of the pump flow components for direct coal liquefaction, including the suction section, discharge section, impeller, guide vanes, and pump chamber. Tetrahedral unstructured meshes were generated for each flow component.

[0040] Furthermore, this application also provides a computing device, comprising: at least one processor and a memory;

[0041] The memory is used to store one or more programs;

[0042] When the one or more programs are executed by the one or more processors, a method for predicting pump thermal wear in direct coal liquefaction that takes into account high-temperature effects, as described above, is implemented.

[0043] In another aspect, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the above-described method for predicting pump thermal wear in direct coal liquefaction, taking into account the high-temperature effect.

[0044] Compared with the prior art, this application has the following advantages:

[0045] This application provides a method for predicting the thermal wear of a pump used in direct coal liquefaction considering high-temperature effects. The method includes: considering the high-temperature effect, coupling and iterating the liquid phase control equation with a solid particle dynamics model to obtain a numerical model of solid-liquid two-phase flow; modeling the entire flow field of the fluid domain composed of the pump's flow components and meshing the fluid domain; constructing a thermal-fluid-solid multi-field coupled calculation system, and using a temperature-corrected large eddy simulation method and a discrete element method coupled to solve the numerical model of solid-liquid two-phase flow, obtaining flow field and particle field information at various points within the pump; acquiring operating condition parameters, and obtaining the thermal wear rate based on the flow field and particle field information at various points within the pump using a thermal wear rate calculation formula, thus obtaining the predicted wear amount of the flow components; improving the prediction accuracy and applicability of the wear model.

[0046] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 The failure morphology of the pump flow-through components is shown;

[0049] Figure 2 A flowchart illustrating the implementation of a method for predicting pump thermal wear in direct coal liquefaction that considers high-temperature effects, as provided in this application, is shown.

[0050] Figure 3 This application illustrates the full flow field fluid domain model of the pump provided in this application;

[0051] Figure 4 The thermal-fluid-solid multi-field coupling calculation process provided in this application is shown. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] Example 1

[0054] This application aims to construct a numerical calculation method for multiphase flow in pumps under extreme operating conditions of high temperature, high pressure, and high solids content, and to predict the thermal wear of flow components. It also provides a method for predicting the thermal wear of pumps used in direct coal liquefaction that considers the high-temperature effect. Figure 2 ,include:

[0055] Considering the high temperature effect, the liquid phase control equation is coupled and iterated with the solid particle dynamics model to obtain a numerical model of solid-liquid two-phase flow.

[0056] A full flow field model was performed on the fluid domain consisting of the pump flow components used in direct coal liquefaction, and the fluid domain was meshed.

[0057] A multi-field coupled calculation system of heat-fluid-solid was constructed. The numerical model of solid-liquid two-phase flow was solved by the coupled method of temperature-corrected large eddy simulation and discrete element method to obtain the flow field and particle field information at various points in the pump.

[0058] By acquiring operating parameters and using the thermal wear rate calculation formula based on the flow field and particle field information at various points within the pump, the predicted wear amount of the flow-through components is obtained.

[0059] 1.1 Establishing a numerical model for solid-liquid two-phase flow considering temperature effects

[0060] (1) Derivation of the control equation for the continuous phase under high temperature conditions

[0061] In solid-liquid two-phase flow, the interaction and influence between the fluid phase and the solid particle phase necessitate a two-way coupling method to handle the interaction when establishing the flow numerical model. Simultaneously, temperature effects are considered, and heat transfer during the flow process is incorporated into the governing equations of the discrete element. This invention employs the Euler-Lagrange method to handle solid-liquid two-phase flow. The liquid phase governing equations introduce momentum exchange source terms to realize the reaction relationship between particles and the fluid. The liquid phase governing equations include continuity equations, momentum equations, and energy equations, as follows:

[0062] The expression for the continuity equation is:

[0063]

[0064] in, The mathematical symbol for the partial derivative of a multivariable function; t represents time; It represents the liquid phase volume fraction; The density of the liquid; The mathematical notation for representing vector differential operators; The velocity vector of the liquid;

[0065] The expression for the momentum equation is:

[0066]

[0067] Where p is the pressure; It is the acceleration due to gravity; The dynamic viscosity of the liquid phase; This is the momentum exchange source term between the liquid and solid phases;

[0068] The energy equation differs from the energy equation at room temperature. Because it transports a high-temperature medium, the influence of temperature changes on the liquid phase properties and energy transfer needs to be considered. To describe this influence, a term related to the liquid phase temperature is introduced into the energy equation to reflect this energy change. Assume the liquid phase heat capacity is... The temperature of the liquid medium itself is The energy change caused by the temperature change of the liquid phase itself can be expressed as, which reflects the heat absorbed or released per unit volume of liquid phase per unit time due to temperature change. The expression for the energy equation is then:

[0069]

[0070] in, The internal energy per unit mass of the liquid phase. The liquid phase heat flux vector. This is the energy dissipation term within the liquid phase. This is the energy conversion term between the liquid and solid phases. For liquid phase heat capacity, This refers to the temperature of the liquid medium itself.

[0071] (2) Construction of a dynamic model for solid particles considering high temperature effect

[0072] Based on Newton's second law, the drag force, gravity, pressure gradient force, and additional mass force acting on the particles are classified and their magnitudes are analyzed to determine the key forces and establish a particle motion model. Considering the influence of the medium temperature gradient on the particles, thermophoretic force is introduced to correct the model.

[0073] Optionally, the expression for the solid particle dynamics model is:

[0074]

[0075]

[0076] in, For particle mass, For particle velocity, Let gravitational force be the force acting on the particle. The drag force acting on the particle. The Saffman lift force acting on the particle. The force exerted on a particle is the interparticle force. The additional mass force experienced by the particle. The pressure gradient force acting on the particles. The surface tension experienced by the particles, The thermophoretic force experienced by the particles, For the moment of inertia of the particle, Represents particle acceleration. The torque applied to the liquid phase, This refers to the torque generated by the contact between particles.

[0077] According to relevant literature, the formula for calculating thermophoretic force is:

[0078]

[0079] in, Particle size; It is the thermophoretic diffusion coefficient, which can be calculated using empirical formulas; It is the fluid temperature gradient.

[0080] As can be seen from the above formula, to accurately calculate the thermophoretic force, the fluid temperature in the flow field at any given moment must be known. This term is a variable and cannot be directly obtained. This application innovatively couples the particle motion equation and the liquid phase energy equation, and solves them iteratively within each time step to take into account the mutual influence between particle temperature and liquid phase temperature.

[0081] This completes the re-establishment of a high-precision numerical model for solid-liquid two-phase flow that takes into account temperature effects. The processing and solution of the new model will be completed in subsequent steps.

[0082] 1.2 Modeling and Meshing of the Entire Flow Field

[0083] Using 3D software, a full flow field model was performed on the fluid domain composed of the flow components of a pump used for direct coal liquefaction. This model mainly consists of the main flow field region and the interstitial flow field region, including the suction section, discharge section, impeller, guide vanes, and pump chamber. Figure 3 .

[0084] Using relevant software, tetrahedral unstructured meshes were generated for each flow component. Different meshes were used for different flow field regions. In the gap flow field region, the mesh was refined to capture its small-scale flow, while the mesh for the mainstream flow field region was generated using large-size cells. This approach ensured boundary layer distribution and mesh uniformity while reducing computational resource requirements. Furthermore, to meet computational accuracy requirements, the number of mesh layers in each part should be no less than 5.

[0085] 1.3 Solution Methods and Steps for Numerical Models of High-Temperature Solid-Liquid Two-Phase Flow

[0086] Under high-temperature conditions, the presence of a temperature gradient leads to more disordered particle motion and a more complex interaction mechanism between particles and fluid. Using conventional RANS methods to handle turbulence models results in poor flow capture within the boundary layer and excessive turbulence dissipation. Therefore, a temperature-corrected Large Eddy Simulation (LES) method is adopted to handle the turbulence model, constructing an anisotropic jointly constrained dynamic stress model suitable for high-temperature transient thermal flow, as follows:

[0087]

[0088] in, For subgrid stress terms, The stress term is dynamically determined by two filtering steps. For the velocity gradient nonlinear term, This is the effect of helicity on subgrid stress.

[0089] , , It is a dimensionless constant, given empirically. It is the square of the filter width. For strain tensor The model, This is the filtered strain rate tensor. The filtered velocity components (i=1,2,3) For spatial coordinate components (k=1,2,3). For characteristic scales related to helicity, For the subgrid rotation rate tensor,

[0090] right and Approximate isotropic subgrid eddy viscosity coefficient , The Smagorinsky constant can be used to represent the formula. use replace. , , Let x, y, z be the grid dimensions. Simultaneously, an anisotropic correction method based on local velocity field information is proposed to incorporate local flow field information into the filter, i.e.:

[0091]

[0092] in, The equivalent filtering scale or equivalent grid scale is used in advanced turbulence models such as Large Eddy Simulation (LES) to characterize the physical scale used for numerical filtering or averaging of turbulence. , , , The geometric parameters characterizing the anisotropy of the computational mesh represent the mesh size ratios in the X and Z directions, and the Y and Z directions, respectively. Their values ​​directly affect the accuracy of the subgrid-scale turbulence model. The local velocity vector is the independent variable that reflects anisotropy; through reasonable construction... The function form is used to construct a LES correction model based on anisotropic local structure and flow field information.

[0093] The discrete element method (DEM) was used to process the discrete phase of solid particles. The contact force between particles was calculated using a soft sphere collision model. The interaction between particles and fluid was iteratively solved using a CFD-DEM bidirectional coupling method. Finally, to characterize the adverse thermal effects of high temperatures on the material, finite element thermal analysis was performed on the solid domain of the flow-through components. Through data exchange, a multi-field coupled thermal-fluid-solid analysis system was established. The specific steps are as follows:

[0094] Based on the actual operating conditions of the pump, the boundary conditions for solving the flow field are correctly set, the fluid domain is solved, and the obtained flow field information, such as velocity, pressure, and temperature, is applied to the particles. Then, by solving the solid particle dynamics model, the motion trajectory of the particles is calculated, and the effect of the particles on the fluid is applied in reverse to the continuous phase fluid, and the solid-liquid two-phase flow parameters are obtained.

[0095] A solid domain model of the pump is established, the solid domain mesh is divided, the initial boundary conditions of the solid domain are set, and the calculated solid-liquid two-phase flow information, such as flow field pressure, velocity, temperature, and particle motion trajectory, is applied to the solid domain to perform finite element mechanical deformation calculations to obtain the stress and deformation of the pump flow components.

[0096] Using the obtained stress and deformation data of the pump's flow components, the flow domain mesh is updated. This process is repeated iteratively until the calculation converges. The overall calculation flow is as follows: Figure 4 As shown.

[0097] 1.4 Thermal Wear Model Construction and Wear Prediction

[0098] This section mainly describes the derivation process of the thermal wear model. The innovation of this model lies in the construction of dynamic evolution coefficients that are interrelated with temperature, pump operating conditions, and material properties, thus creating a difference from existing wear models.

[0099] Existing wear models, such as Finnie, Bitter, and Archard, are typically based on ambient temperature and a single medium, with coefficients that are empirical constants or simple functions. These models cannot cope with the extremely complex environment of high temperature, high solids content, and multi-field coupling in pumps used for direct coal liquefaction. The fundamental problem is that they treat wear as a static process determined by instantaneous impact parameters, neglecting the effects of changes in material properties and dynamic changes caused by continuous high-temperature environments.

[0100] The present invention views wear as a dynamic evolutionary process related to time and space. The amount of wear is not determined solely by the parameters at the moment of impact, but is the result of the combined effects of the local temperature field, stress field, and particle collisions within the pump. Therefore, the parameters in the thermal wear model are all functions of the aforementioned physical fields, and are solved simultaneously using the thermo-fluid-structure interaction system proposed in this application.

[0101] like Figure 4The thermal-fluid-solid multi-field coupling calculation process is the basis for the derivation of the thermal wear model in this invention, which ensures that the correlation coefficients are derived from numerical simulation and experiment rather than empirical assumptions.

[0102] (1) Derivation of particulate wear power based on energy conservation

[0103] Based on the fundamental principle of energy conservation, this application calculates the total impact kinetic energy acting on the wall element per unit time. for:

[0104]

[0105] In the formula, For the first in the flow field The mass of each particle For the first in the flow field The velocity of each particle, N is the total number of particles impacting the micro-element per unit time. This parameter is obtained from the CFD-DEM coupled simulation results, and its magnitude directly depends on the operating conditions such as pump speed, flow rate, and solid content of the medium.

[0106] (2) Dynamic thermal wear efficiency

[0107] During the collision between particles and flow components, kinetic energy dissipation mainly occurs through elastic deformation, rebound, heat generation, and plastic deformation. Plastic deformation energy is the primary energy consumed by the wall material during yielding, cutting, and plowing deformations, and is the root cause of material wear. Therefore, by determining the plastic deformation energy per unit time, the wear energy dissipation can be obtained. Thus, this invention defines a dynamic thermal wear efficiency... Then the plastic deformation energy per unit time It can be represented as follows:

[0108]

[0109] Dynamic thermal wear efficiency for It is not a constant, but rather depends on the temperature T and stress distribution at the point of particle impact on the wall, as determined by coupled simulation. σ v Collision angle of particles α The relevant comprehensive relation can be expressed as follows:

[0110]

[0111] In the formula, the efficiency factor takes into account the effect of temperature. The thermal softening effect of materials, i.e., the reduction of yield strength at high temperatures, making materials more susceptible to plastic deformation, thus allowing a larger proportion of particle impact kinetic energy to be used for plastic deformation, is determined through high-temperature mechanical property tests and can be expressed as follows:

[0112]

[0113] In the formula, Reference temperature Benchmark efficiency, It is a temperature sensitivity coefficient, obtained by comparing the particle impact test results at different temperatures.

[0114] Efficiency factor considering local stress at the point of particle impact The implicit influence of stress on the yielding behavior of materials is characterized by the superposition of stress fields from fluid pressure, thermal stress, and other particle impacts. Furthermore, high hydrostatic pressure inhibits plastic deformation of the wall material. It can be represented as follows:

[0115]

[0116] In the formula, It is the stress state suppression coefficient. This is the yield strength of the material at that temperature. Local stress. It needs to be obtained through thermal-fluid-structure interaction simulation.

[0117] Efficiency factor considering particle impact angle Characterizing particle impact behavior, To determine the particle collision angle, collision and rebound tests were conducted on high-temperature particles and the pump wall surface. The incident and rebound velocities, as well as the collision and rebound angles, were statistically analyzed to establish a database of particle collision and rebound characteristics under varying operating conditions. An empirical relationship applicable to the combination of coal particle and pump wall materials was then fitted, which can be expressed as follows:

[0118]

[0119] In the formula, the coefficients A, B, and C can be determined by nonlinear regression analysis of the collision test data.

[0120] In summary, the dynamic thermal wear efficiency can be expressed as:

[0121]

[0122] In the formula, the correlation coefficient , , , A , B , C Variables can be determined through experiments. T , , It can be solved through multi-field numerical simulation. It is a physical quantity that varies with time and space, and can reflect the difference in wear efficiency at different locations and under different operating conditions inside the pump in real time.

[0123] Therefore, the effective power used for wear per unit time (i.e., plastic deformation energy per unit time) P p It can be fully represented as follows:

[0124]

[0125] (3) Dynamic hardness of the material

[0126] According to mechanics of materials, the hardness value H of a material is... v The concept of the work required to induce plastic deformation per unit volume is based on static and ideal conditions. However, for pumps used in direct coal liquefaction, the actual wear conditions are extremely complex. Temperature thermal effects and particle impact effects can alter the surface hardness of the material, necessitating the introduction of dynamic equivalent hardness. To characterize this effect, which is a function of temperature T and the number of particle impacts N, it can be expressed as follows:

[0127]

[0128] In the formula, Describes the high-temperature softening effect of materials 。H 0 and β These are the basic hardness and softening coefficient of the material, determined through a high-temperature hardness test. The reference impact frequency N represents the total number of particles impacting the micro-element per unit time.

[0129] The plastic strengthening effect is described. Under continuous and repeated impact from particles, the material surface undergoes plastic deformation strengthening, leading to an increase in its hardness within a certain range. λ It is the enhancement coefficient. N 0 is the reference impact frequency. This improvement introduces the influence of cyclic loading on material properties into the wear model for the first time, changing the traditional wear model's assumption that the material is an ideal elastoplastic body and improving the accuracy of wear prediction under real-world conditions.

[0130] (4) Construction of thermal wear prediction model

[0131] The ultimate goal of this invention is to predict the wear of flow-through components within a pump. Once the wear rate (i.e., the volumetric wear per unit time) is determined, the wear of the flow-through components can be calculated. We now assume that the volumetric rate at which material is removed by wear per unit time is... The effective power of wear per unit time P pIt can also be expressed as:

[0132]

[0133] The thermal wear rate can be obtained by combining the two equations. The expression is as follows:

[0134]

[0135] Optionally, the expression for the thermal wear rate is:

[0136]

[0137] in, This represents the volumetric rate at which material is worn away per unit time. Reference temperature Benchmark efficiency, It is the temperature sensitivity coefficient. It is the stress state suppression coefficient. It is the yield strength of the material at that temperature. For local stress, , , For coefficients, For the particle collision angle, The basic hardness of the material. Where is the softening coefficient of the material, and T is the temperature determined by the coupled simulation. For the enhancement coefficient, The reference impact frequency N represents the total number of particles impacting the micro-element per unit time. For the first in the flow field The mass of each particle For the first in the flow field The speed of each particle.

[0138] The above formula is the thermal wear prediction model that takes temperature effect into account, which is derived by the present invention. It is a manifestation and expression of the principle of energy conservation in the specific physical process of wear, and has an essential difference from the traditional wear model.

[0139] In terms of originality, this application abandons the traditional wear model's reliance on empirical coefficients and static unidirectional calculations, and uniquely constructs a prediction system with dynamically changing coefficients and multi-field coupling. It proposes a wear efficiency... and dynamic equivalent hardness By comprehensively considering the wear process with actual factors such as pump operating conditions, structural parameters, and material properties, the predictive accuracy and applicability of the wear model are improved. This is a capability that previous wear models did not possess, and it has significant engineering practical value.

[0140] The thermal wear model constructed in this application can be directly used for predicting wear conditions, optimizing design, and assessing lifespan of pumps used in direct coal liquefaction. It can effectively reduce abnormal pump shutdowns and performance degradation caused by wear, and provides an effective technical means to solve the wear problem of pumps under high temperature, high pressure, and high solids content conditions.

[0141] Example 2

[0142] Based on the same inventive concept, this application also provides an electronic device. The electronic device of this application includes at least one processor and at least one storage medium electrically connected to the processor. The storage medium is electrically connected to the processor, wherein the storage medium stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method described above.

[0143] Example 3

[0144] Based on the same inventive concept, this application also provides a storage medium storing instructions executable by at least one processor, the instructions being executed by at least one processor to enable at least one processor to perform the method described above.

[0145] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects, characterized in that, include: Considering the high temperature effect, the liquid phase control equation is coupled and iterated with the solid particle dynamics model to obtain a numerical model of solid-liquid two-phase flow. A full flow field model was performed on the fluid domain consisting of the pump flow components used in direct coal liquefaction, and the fluid domain was meshed. A multi-field coupled calculation system of heat-fluid-solid was constructed. The numerical model of solid-liquid two-phase flow was solved by the coupled method of temperature-corrected large eddy simulation and discrete element method to obtain the flow field and particle field information at various points in the pump. By acquiring operating parameters and using the thermal wear rate calculation formula based on the flow field and particle field information at various points inside the pump, the thermal wear rate is obtained, and the predicted wear amount of the flow-through components is obtained. The liquid phase control equations include the continuity equation, the momentum equation, and the energy equation; The expression for the continuity equation is: in, The mathematical symbol for the partial derivative of a multivariable function; t represents time; It represents the liquid volume fraction; The density of the liquid; The mathematical notation for representing vector differential operators; The velocity vector of the liquid; The expression for the momentum equation is: Where p is the pressure; It is the acceleration due to gravity; The dynamic viscosity of the liquid phase; This is the momentum exchange source term between the liquid and solid phases; The expression for the energy equation is: in, The internal energy per unit mass of the liquid phase. This is the liquid phase heat flux vector. This is the energy dissipation term within the liquid phase. This is the energy conversion term between the liquid and solid phases. For liquid phase heat capacity, This refers to the temperature of the liquid medium itself.

2. The method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects according to claim 1, characterized in that, Considering the high-temperature effect, the liquid phase control equation is coupled and iterated with the solid particle dynamics model to obtain a numerical model of solid-liquid two-phase flow, including: The reaction relationship between particles and fluid is realized by introducing momentum exchange source terms into the liquid phase control equations, which include continuity equations, momentum equations, and energy equations. Considering the influence of the medium temperature gradient on the particles, a thermophoretic force is introduced to establish a dynamic model of solid particles; A two-way coupling method is used to handle the interaction between the fluid phase and the solid particle phase. At the same time, the Eulerian-Lagrange method is used to process the solid-liquid two-phase flow, resulting in a numerical model of the solid-liquid two-phase flow.

3. The method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects according to claim 1, characterized in that, The expression for the solid particle dynamics model is as follows: in, For particle mass, For particle velocity, Let gravitational force be the force acting on the particle. The drag force acting on the particle. The Saffman lift force acting on the particle. The force exerted on a particle is the interparticle force. The additional mass force experienced by the particle. The pressure gradient force acting on the particles. The surface tension experienced by the particles, The thermophoretic force experienced by the particles, For the moment of inertia of the particle, Represents particle acceleration. The torque applied to the liquid phase, This refers to the torque generated by the contact between particles.

4. The method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects according to claim 1, characterized in that, The expression for the thermal wear rate is: in, This represents the volumetric rate at which material is worn away per unit time. Reference temperature Benchmark efficiency, It is the temperature sensitivity coefficient. It is the stress state suppression coefficient. It is the yield strength of the material at that temperature. For local stress, , , For coefficients, For the particle collision angle, The basic hardness of the material. Where is the softening coefficient of the material, and T is the temperature determined by the coupled simulation. For the enhancement coefficient, For reference impact frequency, N is the total number of particles impacting the micro-element per unit time. For the first in the flow field The mass of each particle For the first in the flow field The speed of each particle.

5. The method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects according to claim 1, characterized in that, The thermal-fluid-solid multi-field coupled calculation system includes: Based on the actual operating conditions of the pump, the boundary conditions for solving the flow field are correctly set, the fluid domain is solved, and the obtained flow field information is applied to the particles. The numerical model of solid-liquid two-phase flow is solved using a coupled method of temperature-corrected large eddy simulation and discrete element method to solve the dynamic model of solid particles, calculate the trajectory of the particles, and apply the effect of the particles on the fluid in reverse to the continuous phase fluid to obtain the solid-liquid two-phase flow parameters. The flow field information includes, but is not limited to, velocity, pressure, and temperature. A solid domain model of the pump is established, the solid domain mesh is divided, the initial boundary conditions of the solid domain are set, and the calculated solid-liquid two-phase flow information is applied to the solid domain to perform finite element mechanical deformation calculations to obtain the stress and deformation of the pump flow components; the solid-liquid two-phase flow information includes, but is not limited to, flow field pressure, velocity, temperature and particle motion trajectory. By utilizing the stress and deformation data of the pump's flow components, the flow domain mesh is updated and iterated repeatedly until the calculation converges, thus obtaining information on the flow field and particle field at various points within the pump.

6. The method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects according to claim 5, characterized in that, The method employing a coupled approach of temperature-corrected large eddy simulation and discrete element method to solve the numerical model of solid-liquid two-phase flow includes: A temperature-corrected large eddy simulation method is used to process the turbulence model, and an anisotropic joint constraint dynamic stress model suitable for high-temperature transient thermal flow is constructed. The discrete element method is used to process the discrete phase of solid particles. The contact force between particles is calculated by the soft ball collision model. The interaction between particles and fluid is solved iteratively by CFD-DEM bidirectional coupling method to obtain the temperature field, pressure field and velocity field of solid and liquid two phases.

7. The method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects according to claim 1, characterized in that, The process of modeling the entire flow field of the fluid domain composed of the pump flow components used in direct coal liquefaction and meshing the fluid domain includes: A full flow field model was performed on the fluid domain consisting of the pump flow components for direct coal liquefaction, including the suction section, discharge section, impeller, guide vanes, and pump chamber. Tetrahedral unstructured meshes were generated for each flow component.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects as described in any one of claims 1-7.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When executing a program stored in memory, the processor implements the steps of the method for predicting pump thermal wear in direct coal liquefaction considering high-temperature effects as described in any one of claims 1-7.

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