A method and system for analyzing and studying blockage behavior based on the influence of particle shape

Abstract

The present invention relates to the technical field of particle clogging research, and in particular to a method and system for analyzing clogging behavior based on the influence of particle shape. The method comprises the following steps: obtaining ellipsoidal particles of different particle shapes and constructing a first clogging behavior coupling simulation model of the ellipsoidal particles; configuring and verifying the first clogging behavior coupling simulation model to obtain a second clogging behavior coupling simulation model; dynamically simulating the ellipsoidal particles according to the second clogging behavior coupling simulation model to obtain a clogging behavior fitting result; and comprehensively analyzing the clogging behavior based on the clogging behavior fitting result to achieve an analytical study of the clogging behavior. The present invention adopts a fully analytical computational fluid dynamics coupled discrete element method to simulate the particle clogging in a simplified pore geometry of ellipsoidal particles with different aspect ratios under fluid flow conditions. The influence of different particle shapes on pore clogging characteristics is evaluated through parameter analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of particle clogging research, and in particular to a method and system for analyzing and researching clogging behavior based on the influence of particle shape. Background Art

[0002] In existing technologies, numerical simulation methods are commonly used to predict and analyze particle clogging behavior in porous media under fluid-driven conditions. By constructing mathematical models of fluid-particle interactions, the movement, contact, and clogging of particles in pores are simulated. However, to simplify calculations and improve efficiency, existing technologies generally use spherical particle approximations to represent actual particles. This simplified approach reduces modeling complexity, making large-scale simulations possible and, to a certain extent, revealing the fundamental laws governing particle clogging.

[0003] However, the spherical particle approximation ignores the important influence of particle shape on clogging behavior. Particles in actual engineering often have irregular shapes, such as ellipsoids, polyhedrons, or lamellar structures. These shape characteristics play a key role in the interaction between particles and fluids, the contact between particles, and the formation of clogging structures. For example, the rotation behavior, orientation distribution, and contact pattern with pore walls of non-spherical particles are significantly different from those of spherical particles. Therefore, the numerical simulation method based on the spherical particle approximation cannot accurately reflect the complex behavior of real particles, resulting in a significant reduction in the accuracy of the simulation results, making it difficult to explain the diverse clogging phenomena observed in actual engineering.

[0004] In view of this, the present invention provides a method and system for analyzing and studying clogging behavior based on the influence of particle shape. It abandons the assumption of spherical particles and directly simulates the clogging behavior of ellipsoidal particles with different aspect ratios under fluid flow conditions. Through a coupled simulation model of clogging behavior, the influence of different particle shapes on clogging behavior is analyzed and studied, revealing the joint influence of particle shape, flow velocity and pore geometry on clogging events. This not only improves the simulation accuracy of clogging behavior, but also provides a theoretical basis for understanding the clogging and unblocking of irregular particles in pores. It has important application value for optimizing industrial filtration equipment, preventing clogging of formation particle migration and improving the stability of geotechnical engineering. Summary of the Invention

[0005] In view of the defects in the prior art, the present invention provides a method and system for analyzing and studying the blocking behavior based on the influence of particle shape.

[0006] In order to achieve the above-mentioned purpose, in the first aspect, the present invention provides a method for analyzing and studying the clogging behavior based on the influence of particle shape, the method comprising the following steps: obtaining ellipsoidal particles of different particle shapes, and constructing a first clogging behavior coupling simulation model of the ellipsoidal particles; configuring and verifying the first clogging behavior coupling simulation model to obtain a second clogging behavior coupling simulation model; dynamically simulating the ellipsoidal particles according to the second clogging behavior coupling simulation model to obtain a clogging behavior fitting result; and comprehensively analyzing the clogging behavior based on the clogging behavior fitting result to achieve an analytical study of the clogging behavior. The present invention significantly improves the scientificity and practicality of the research on particle clogging behavior through a systematic simulation and analysis process; modeling of ellipsoidal particles based on different aspect ratios breaks through the limitations of the traditional spherical particle assumption, can accurately depict the differentiated influence of particle shape, and makes the simulation results closer to engineering practice; coupling model configuration and verification ensure the reliability of the model and effectively reduce numerical errors; dynamic simulation of the clogging process based on the clogging behavior coupling simulation model provides a reference basis for engineering problems such as industrial filtration equipment optimization and formation particle migration prevention and control.

[0007] Optionally, the method of obtaining ellipsoidal particles of different particle shapes and constructing a first clogging behavior coupled simulation model of the ellipsoidal particles includes: determining different aspect ratios, and constructing ellipsoidal particles of different particle shapes based on the aspect ratios; constructing a first control equation for the particle phase, and solving a second control equation for the fluid phase; and combining the first control equation and the second control equation to construct the first clogging behavior coupled simulation model of the particle phase and the fluid phase. The present invention significantly improves the accuracy and mechanism-revealing ability of clogging behavior simulation by introducing parameterized design of particle shape; constructing ellipsoidal particles based on the aspect ratio breaks through the geometric limitations of the traditional spherical assumption, and can systematically analyze the differentiated effects of particles of different sizes on fluid dynamics responses; establishing the particle phase and fluid phase control equations separately, and realizing full-scale analysis of fluid-solid interaction; the constructed coupled simulation model can accurately capture the clogging behavior process of ellipsoidal particles, and provides an analytical basis for revealing complex clogging mechanisms.

[0008] Optionally, the configuration and verification of the first blocking behavior coupling simulation model to obtain the second blocking behavior coupling simulation model includes: obtaining the pore geometry parameters and fluid parameters corresponding to the ellipsoidal particles; configuring the first blocking behavior coupling simulation model based on the pore geometry parameters and the fluid parameters to obtain model parameters; establishing a model verification test, and verifying the first blocking behavior coupling simulation model based on the model verification test in combination with the ellipsoidal particles to obtain the second blocking behavior coupling simulation model. The present invention significantly improves the engineering applicability of the model through parameterized configuration and multi-dimensional verification, calibrates the model based on pore geometry parameters and fluid parameters, and makes the simulation scenario highly consistent with the actual working conditions; ensures the credibility of the simulation results through model verification tests; provides a benchmark framework for subsequent dynamic simulations, and effectively improves the accuracy of dynamic fitting.

[0009] Optionally, the comprehensive analysis of the blocking behavior based on the blocking behavior fitting result is performed to realize an analytical study of the blocking behavior, including: analyzing the particle migration of the ellipsoidal particles and the blocking behavior based on the blocking behavior fitting result to obtain a first analysis result; analyzing the influence of the ellipsoidal particles on the blocking behavior in combination with the blocking behavior fitting result to obtain a second analysis result; obtaining the force condition and position distribution of the ellipsoidal particles as a third analysis result based on the blocking behavior fitting result; analyzing the fluid pressure drop in the blocking behavior based on the blocking behavior fitting result to obtain a fourth analysis result; analyzing the influence of flow rate and hole cone angle on the blocking behavior based on the blocking behavior fitting result to obtain a fifth analysis result; and realizing an analytical study of the blocking behavior by combining the first analysis result, the second analysis result, the third analysis result, the fourth analysis result, and the fifth analysis result. The present invention realizes the analysis of blocking behavior through multi-dimensional comprehensive analysis. Based on the fitting results, the particle migration trajectory and blockage evolution law were analyzed to reveal the blockage mechanism of ellipsoidal particles; through the analysis of the influence of particle shape, a theoretical basis was provided for the prevention and control of irregular particles; combined with the analysis of blockage structure characteristics, the constituent conditions of blockage behavior were clarified; the fluid pressure drop analysis established a dynamic correlation between flow field distribution and blockage events; through the analysis of flow velocity-hole cone angle parameters, the influence on blockage behavior was analyzed; and a comprehensive analytical study of blockage behavior was conducted.

[0010] Optionally, analyzing the particle migration and blocking behavior of the ellipsoidal particles based on the blocking behavior fitting results to obtain a first analysis result includes: obtaining the blocking and unblocking processes of the ellipsoidal particles in a single-pore structure based on the blocking behavior fitting results; and obtaining flow field changes during the blocking and unblocking processes. The present invention, through refined analysis of single-pore structures, reveals the dynamic evolution mechanism of ellipsoidal particle blocking and unblocking, accurately captures the entire process of particle blocking behavior based on the fitting results, and clarifies the impact of ellipsoidal particles on the flow field, providing a micromechanical basis for analyzing blocking behavior.

[0011] Optionally, the second analysis result is obtained by analyzing the influence of the ellipsoidal particles on the clogging behavior in combination with the clogging behavior fitting result, including: obtaining the particle configuration evolution of the ellipsoidal particles in the clogging behavior according to the clogging behavior fitting result; obtaining the change of the particle scouring rate and the change of the average particle velocity of the ellipsoidal particles in the clogging behavior; and performing a single particle flushing test on the ellipsoidal particles in combination with the change of the particle scouring rate and the change of the average particle velocity to obtain the test result. The present invention reveals the dynamic regulation mechanism of ellipsoidal particles on clogging behavior through multi-dimensional quantitative analysis; clarifies the correlation between particles and pores in the clogging process by tracking the evolution of particle configuration; analyzes the changes in scouring rate and average velocity to more comprehensively analyze the clogging behavior; and provides a mechanical basis for optimizing the anti-clogging flushing process through the analysis of single particle flushing test and fluid velocity field evolution.

[0012] Optionally, the force condition and position distribution of the ellipsoidal particles obtained according to the blocking behavior fitting result are obtained as the third analysis result, including: obtaining the force chain distribution result of the ellipsoidal particles according to the blocking behavior fitting result, and analyzing the force chain distribution result to obtain the force condition; obtaining the blocking particle structure of the ellipsoidal particles according to the blocking behavior fitting result, and using the blocking particle structure as the position distribution. The present invention reveals the intrinsic mechanical mechanism of the blocking structure of ellipsoidal particles through force chain analysis of ellipsoidal particles, obtains the force chain distribution result based on the inter-particle contact force distribution extracted based on the blocking behavior fitting result, quantifies the spatial configuration and stability of the blocking structure, and provides micromechanical evidence for understanding the interlocking effect caused by the orientation arrangement of ellipsoidal particles with different particle shapes. It also provides structural weakening points for optimizing anti-blocking strategies, which helps to deeply analyze the influence of ellipsoidal particles with different particle shapes on blocking behavior.

[0013] Optionally, the fourth analysis result is obtained by analyzing the fluid pressure drop in the blocking behavior based on the blocking behavior fitting result, including: obtaining the fluid pressure drop of the ellipsoidal particles based on the blocking behavior fitting result; obtaining the evolution relationship between the average particle velocity of the ellipsoidal particles and the fluid pressure drop, and judging the blockage condition of the pores based on the evolution relationship. The present invention significantly improves the accuracy of blocking behavior analysis through comparative verification of actual fluid pressure drop and prediction; fluid pressure drop is a direct quantitative indicator of the degree of blocking, and its dynamic changes clearly depict the characteristics of the blocking evolution stage; analyzing the relationship between the average particle velocity and fluid pressure drop provides key data support for optimizing the anti-blocking design of porous media.

[0014] Optionally, the fifth analysis result is obtained by analyzing the influence of flow rate and pore cone angle on the clogging behavior based on the clogging behavior fitting result, including: determining different flow rates and different pore cone angles, and obtaining clogging simulation results based on the flow rates and pore cone angles in combination with the control variable method; for the ellipsoidal particles, analyzing the influence of the flow rate on the particle scouring rate under different pore structures to obtain the influence result. The present invention reveals the synergistic regulation mechanism of flow rate and pore cone angle on clogging behavior through multi-parameter coupling analysis; adopts the control variable method to accurately quantify the nonlinear influence of flow rate on particle scouring rate; combines the analysis of pore cone angle changes to provide a quantitative basis for optimizing anti-clogging operations; and lays a scientific foundation for the design and operation parameter regulation of industrial filtration equipment.

[0015] In a second aspect, the present invention provides a system for analyzing and studying blockage behavior based on the influence of particle shape. The system executes the method for analyzing and studying blockage behavior based on the influence of particle shape provided by the present invention. The system includes an input device, an output device, a processor, and a memory. The input device, output device, processor, and memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions. The present invention realizes the full-process study of blockage behavior through hardware collaborative optimization. The high-performance processor and large-capacity memory work together to significantly shorten the coupled simulation calculation cycle. The high-speed input and output devices ensure the real-time interaction between experimental parameters and simulation results. The hardware parallel computing architecture effectively supports efficient response. This integrated design improves the efficiency of the mechanism research of blockage behavior and provides a highly timely decision support platform for industrial anti-blocking design. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of a method for analyzing and studying clogging behavior based on the influence of particle shape according to an embodiment of the present invention;

[0017] Figure 2 Schematic diagram of a coupling method according to an embodiment of the present invention;

[0018] Figure 3 Schematic diagram of a congestion behavior coupling simulation model according to an embodiment of the present invention;

[0019] Figure 4 A comparison diagram of the results of the coupled simulation model of the blocking behavior and the particle settling test according to an embodiment of the present invention;

[0020] Figure 5 A comparison diagram of the results of the congestion behavior coupling simulation model and the Ergon test according to an embodiment of the present invention;

[0021] Figure 6 is a configuration diagram of ellipsoidal particles during the simulation process of an embodiment of the present invention;

[0022] Figure 7 A graph showing the changing trend of the particle scouring rate and the average particle velocity according to an embodiment of the present invention;

[0023] Figure 8 A diagram illustrating the evolution of particle configurations of different particle shapes during a simulation of an embodiment of the present invention;

[0024] Figure 9 The particle scouring rate and average particle velocity change trend diagram of three particle shapes in the embodiment of the present invention;

[0025] Figure 10 This is a schematic diagram of the results of a single particle flushing test according to an embodiment of the present invention;

[0026] Figure 11 Schematic diagram of the force chain of the blocking particles according to an embodiment of the present invention;

[0027] Figure 12 Schematic diagram of the clogging structure of spherical particles according to an embodiment of the present invention;

[0028] Figure 13 Schematic diagram of the blockage structure of ellipsoidal particles at different flow rates according to an embodiment of the present invention;

[0029] Figure 14 is a graph showing the relationship between fluid pressure drop and average particle velocity according to an embodiment of the present invention;

[0030] Figure 15 Schematic diagram of simulation results under different flow rates and hole cone angles according to an embodiment of the present invention;

[0031] Figure 16 This is a graph showing the changing trend of particle scouring rate at different flow rates according to an embodiment of the present invention;

[0032] Figure 17 This is a framework diagram of a system for analyzing and studying blockage behavior based on the influence of particle shape according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] Specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the present invention. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that these specific details are not necessarily required to practice the present invention. In other instances, well-known circuits, software, or methods are not specifically described to avoid obscuring the present invention.

[0034] Throughout this specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present invention. Therefore, appearances of the phrases "in one embodiment," "in an embodiment," "an example," or "an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combinations and / or subcombinations in one or more embodiments or examples. Furthermore, those of ordinary skill in the art will appreciate that the figures provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0035] See Figure 1 One embodiment of the present invention provides a method for analyzing and studying clogging behavior based on the influence of particle shape, the method comprising the following steps:

[0036] S1. Obtain ellipsoidal particles of different particle shapes, and construct a coupled simulation model of the first blocking behavior of the ellipsoidal particles.

[0037] In this embodiment, different aspect ratios are determined, and ellipsoidal particles of different particle shapes are constructed based on the aspect ratios; the first control equation of the particle phase is constructed, and the second control equation of the fluid phase is solved; and the first control equation and the second control equation are combined to construct a first blocking behavior coupling simulation model of the particle phase and the fluid phase.

[0038] Specifically, different aspect ratios are determined, including 1.0, 1.5, and 2.0. It should be noted that when the aspect ratio is 1.0, the ellipsoidal particle is a perfect sphere.

[0039] Specifically, the Discrete Element Method (DEM) based on Newton's second law of motion and contact model is used to simulate the behavior of dispersed particles to construct the first governing equation of the particle phase. The first governing equation includes the translational motion equation and the rotational motion equation of the ellipsoidal particles.

[0040] The above translational motion equation satisfies the following relationship:

[0041]

[0042] in, is the mass of the particle, is the instantaneous speed, is the total number of particle contacts, is the index variable, is the contact force acting on the particle, is the interaction force between the particle and the fluid.

[0043] The above rotational motion equation satisfies the following relationship:

[0044]

[0045] in, is the moment of inertia tensor of the particle, is the angular velocity, is the total number of particle contacts, is the index variable, is the moment of force exerted by the particle on the particle, is the moment between the particle and the fluid.

[0046] In this embodiment, the focus of the study is on single-phase incompressible fluid, and computational fluid dynamics (CFD) is used to solve the second governing equation of the fluid phase, which includes the continuity equation and the Navier-Stokes equation.

[0047] The above continuity equation satisfies the following relationship:

[0048]

[0049] in, is the fluid density, is the divergence operator, is the average velocity of the fluid unit.

[0050] The above Navier-Stokes equations satisfy the following relationship:

[0051]

[0052] in, is the fluid density, is the average velocity of the fluid unit, is the divergence operator, represents the direct product of two vectors, is the gradient operator, is the fluid pressure, is the fluid viscosity, is the acceleration due to gravity.

[0053] Furthermore, the effect of particle motion on the flow field is achieved by forcing the particle velocity to be equal to the average velocity of the fluid cell.

[0054] The above particle velocities satisfy the following relationship:

[0055]

[0056] in, is the particle velocity, is the instantaneous speed, is the angular velocity, is the positive vector relative to the center point of the particle, is the particle domain, Represents the interior of the particle domain.

[0057] The average velocity of the above fluid unit satisfies the following relationship:

[0058]

[0059] in, is the average velocity of the fluid unit, is the fluid velocity before correction, is the void ratio, is the particle velocity, For the simulation domain, Represents being inside the simulation domain.

[0060] See Figure 2 , the figure is a schematic diagram of the coupling method, Figure 2 (a) is a schematic diagram of the unresolved coupling method. Figure 2 (b) is a schematic diagram of the analytical coupling method; in this embodiment, an analytical coupling method (full-resolution coupling (CFD-DEM) method) is used to simulate the interaction between three-dimensional (3D) fluid and particles. This method can accurately analyze the fluid flow around the particle surface and effectively capture the motion trajectory of elliptical particles in the flow field.

[0061] It should be noted that the analytical coupling method uses a fine fluid grid that explicitly resolves the particle shape, and the particle-fluid grid size ratio is greater than 8.

[0062] Specifically, based on the particle-fluid interaction force, combined with the first control equation and the second control equation, a first blocking behavior coupled simulation model (CFD-DEM) of the particle phase and the fluid phase is constructed, including:

[0063] The hydraulic force exerted by the fluid on the particle is calculated by integrating the fluid stress on the particle surface, satisfying the following relationship:

[0064]

[0065]

[0066] in, is the traction force vector of the fluid on the particle surface, is the fluid stress of Newtonian fluid, is the outward normal vector of the particle surface, is the particle surface, On the particle surface, is the fluid pressure, To unify the tensor, is the viscous stress tensor of the fluid, is the fluid viscosity, is the gradient operator, represents the direct product of two vectors, is the average velocity of the fluid unit.

[0067] Furthermore, by using the divergence theorem and transferring all hydraulic forces to the center of the particle, the hydraulic forces acting on the particle satisfy the following relationship:

[0068]

[0069]

[0070] in, is the hydraulic force vector of the fluid on the particle, is the particle surface, is the traction force vector of the fluid on the particle surface, is the surface area of ​​the particle, is the fluid stress of Newtonian fluid, is the outward normal vector of the particle surface, is the particle domain, is the divergence operator, is the volume of the particle domain, is the gradient operator, is the fluid pressure, is the viscous stress tensor of the fluid, is the hydraulic torque vector of the fluid on the particle, Represents the position vector pointing from the center of the particle to a point on the particle surface.

[0071] In addition, the discretization calculation of the hydraulic resultant force vector and the hydraulic resultant moment vector satisfies the following relationship:

[0072]

[0073]

[0074]

[0075]

[0076] in, is the hydraulic force vector of the fluid on the particle, is the gradient operator, is the fluid pressure, is the divergence operator, is the viscous stress tensor of the fluid, is the volume of the fluid unit, is the void ratio, is the particle-fluid interaction force density, is the hydraulic torque vector of the fluid on the particle, represents the position vector pointing from the center of the particle to a point on the particle surface, is the fluid viscosity, is the average velocity of the fluid unit.

[0077] S2. Configure and verify the first congestion behavior coupling simulation model to obtain a second congestion behavior coupling simulation model.

[0078] In this embodiment, the pore geometry parameters and fluid parameters corresponding to the ellipsoidal particles are obtained; the first blockage behavior coupling simulation model is parameterized based on the pore geometry parameters and the fluid parameters to obtain the model parameters; a model verification test is established, and the first blockage behavior coupling simulation model is verified based on the model verification test in combination with the ellipsoidal particles to obtain the second blockage behavior coupling simulation model.

[0079] See Figure 3 , which is a schematic diagram of a coupled simulation model for congestion behavior; in this embodiment, Figure 3 As shown in (a) of Figure 1, to investigate the effect of particle shape on pore clogging and unblocking, ellipsoidal particles with three different aspect ratios were used in the CFD-DEM simulation. It is noteworthy that when the aspect ratio of the ellipsoidal particle reaches 1.0, its geometry becomes a perfect sphere. This serves as a control case, allowing for systematic comparison with the ellipsoidal particle to isolate and quantify the effect of particle shape.

[0080] In addition, the pore shape has an impact on clogging and unclogging, and the truncated cone pores are used to simplify the pore structure in the porous media clogging process. Figure 3 The truncated cone pore shown in (b) can adjust the pore shrinkage diameter (using D c ) and the duct length (denoted by L cdenoted by α) to achieve a predetermined cone angle (denoted by α). Reducing the pore length increases the cone angle, thereby reducing the pore outlet, squeezing out particles, and hindering their removal. Conversely, increasing the pore contraction diameter decreases the cone angle, increasing the number of particles required for clogging and thus reducing the likelihood of clogging.

[0081] like Figure 3 As shown in (c), the pore structure is simplified to a tubular wall, and the outlet shrinks to a cone to induce particle blockage. p denoted by , 125 particles with a diameter of 100 mm were randomly generated within the tubular region of the pore structure. Fluid flow was directed in the positive x-axis, and the position of the pore structure was fixed. To minimize the influence of particle volume, the volumes of the two ellipsoidal particles were set equal to those of the spherical particle. 125 particles were then generated within the specified region.

[0082] Specifically, the probability of pore clogging is proportional to the ratio of the pore shrinkage diameter to the particle diameter, satisfying the following relationship:

[0083]

[0084] in, is the ratio of the pore contraction diameter to the particle diameter, is the pore contraction diameter, is the particle diameter.

[0085] Preliminary simulation results indicate that pore clogging rarely occurs when R0 > 3.0. We did not perform subsequent simulations for R0 values ​​exceeding this critical value. Therefore, the focus of this study was to analyze clogging behavior within the critical parameter range within which clogging occurs, and to define the ratio of pore length to particle diameter to satisfy the following relationship:

[0086]

[0087] in, is the ratio of pore length to particle diameter, is the duct length, is the particle diameter.

[0088] The pore geometry parameters and fluid parameters in the numerical simulation are shown in Table 1:

[0089] Table 1

[0090]

[0091] It should be noted that V f Indicates the fluid velocity, using D p / s is measured, for example 1D p / s means the fluid velocity is one particle diameter per second.

[0092] Furthermore, fluid properties such as density and viscosity are assigned based on the properties of water at room temperature. Particle properties, including density, friction coefficient, and Poisson's ratio, are defined based on the characteristics of quartz particles. In numerical simulations of particle migration in soil, the Young's modulus of particles is usually set in the range of 106Pa to 1010Pa. The value of 106Pa was selected in this study to balance accuracy and computational efficiency. In addition, the DEM time step was adaptively adjusted to ensure numerical stability and convergence. The model parameters of the first blocking behavior coupled simulation model (CFD-DEM) are shown in Table 2:

[0093] Table 2

[0094]

[0095] See Figure 4 ,The figure shows the comparison of the results of the coupled simulation model of the blocking behavior and the particle settling test; Figure 4 The comparison of the particle settling velocity results from the CFD-DEM model and the experiment is shown. Figure 4 (a) is the result comparison chart of spherical particles. Figure 4 (b) shows the comparison of the results for ellipsoidal particles. It can be seen that the CFD-DEM model accurately predicts the velocity changes of particles in water, which is consistent with the experimental results.

[0096] Furthermore, to verify the ability of the CFD-DEM coupled model to capture the particle-fluid interaction of a granular aggregate, we simulated the Ergun's Experiment (Ergun). In this model, water flows upward from a bottom inlet over a granular bed, and the pressure drop and fluid velocity satisfy the following relationship:

[0097]

[0098] in, is the pressure drop, is the dynamic viscosity of the fluid, is the height of the particle bed, is the porosity of the particle bed, is the particle diameter, is the fluid velocity, is the fluid density.

[0099] See Figure 5 , which shows the comparison of the results of the coupled simulation model of the plugging behavior and the Ergon test; in this study, a particle bed with a size of 100.0mm×30.0mm×90.0mm was generated at the bottom of the fluid domain. Figure 5As shown in (a), the porosity of the particle assembly is set to 0.5, and spherical particles with a diameter of 10.0 mm are filled at the bottom. A constant flow rate is applied at the bottom, and the pressure drop between the inlet and outlet is monitored and recorded. The inlet flow rate ranges from 0.02 m / s to 0.06 m / s to verify the accuracy of the model at different flow rates. Figure 5 As shown in (b), the simulated pressure drop and the pressure drop-fluid velocity relationship at different flow rates show excellent consistency, which indicates that the proposed CFD-DEM model can accurately capture the fluid flow behavior within the particle assembly.

[0100] S3. Performing dynamic simulation on the ellipsoidal particles according to the second blocking behavior coupling simulation model to obtain a blocking behavior fitting result.

[0101] In this embodiment, the blocking behavior of ellipsoidal particles of different particle sizes is simulated based on the constructed second blocking behavior coupling simulation model to obtain blocking behavior fitting results.

[0102] S4. Perform a comprehensive analysis on the congestion behavior based on the congestion behavior fitting result to achieve an analytical study on the congestion behavior.

[0103] Among them, S4 specifically includes the following steps:

[0104] S41 . Analyze the particle migration and the blocking behavior of the ellipsoidal particles based on the blocking behavior fitting result to obtain a first analysis result.

[0105] In this embodiment, the aspect ratio is 2.0, R0=2.3, R c =2.0 and V f =2Dp / s, and used this as an example to illustrate the particle blocking and dredging process.

[0106] See Figure 6 , which shows the configuration of the ellipsoidal particles during the simulation process; it shows a series of snapshots capturing the movement of the ellipsoidal particles, clearly showing the blocking and unblocking process of the particles in the single pore structure. Figure 6 As shown in (a) in Figure 1, at t = 0 seconds, which is the initial stage of the simulation process, the particles gather in a closed area near the pore entrance. They are closely packed but remain stationary due to the zero flow rate. Figure 6 As shown in (b) in Figure 1, at t = 3.5 seconds, the fluid begins to flow, accompanied by the migration of particles into the pores. As the particles continue to migrate toward the outlet, they gather and intertwine in the conical region of the pores, resulting in blockage. The formation of a stable directional dome structure composed of multiple elongated ellipsoidal particles hinders the outward movement of particles, and the system enters a quasi-static stage with low particle velocity. Figure 6As shown in (c) in Figure 3, at t = 5.1 seconds, due to the continuous flow of the fluid, the particles are affected by the relevant flow force, and a few particles near the outlet start to move again, which indicates that the force chain between the particles is weakened or rearranged. Figure 6 As shown in (d) in Figure 3, at t = 9.0 seconds, all particles escape from the pores one after another. The recovery of particle motion after blockage indicates that the blockage structure itself is not stable and can easily be rearranged by fluid.

[0107] See Figure 7 The figure shows the trend of particle scouring rate and average particle velocity; it shows the changes in particle scouring rate and the average velocity of all particles. Figure 7 As shown in (a) in the figure, the particle scouring rate remains zero in the first 2 seconds, indicating that the particles migrate with the fluid within the pore structure and have not yet reached the outlet. Afterwards, the particle scouring rate increases in a step-by-step manner in the time interval from 2.0 seconds to 3.5 seconds, indicating that some particles escape from the outlet in sequence and no serious blockage occurs. At around 3.5 seconds, the particle scouring rate stops increasing and enters a relatively long 1.6-second blockage period, during which no particles are flushed out. Subsequently, the particle scouring rate increases rapidly between 5 seconds and 9 seconds, marking the beginning of the main unblocking stage, during which most of the particles escape from the pores. Several intermittent blockage events were also observed during this stage. These temporary blockages are caused by the unstable structures formed instantaneously between the particles near the pore outlet. As shown in Figure 7 As shown in (b), the average particle velocity initially rises and then drops significantly around 3.5 seconds, corresponding to pore blockage. Five seconds later, the velocity rises again as the flow channel reopens. Subsequent velocity fluctuations reflect repeated cycles of blockage and unblocking. In summary, the blockage process and particle structure are highly dynamic and are affected by transient flow obstructions.

[0108] Furthermore, the changes in the flow field during the blockage and dredging processes were analyzed. At the beginning of the simulation, the fluid flowed smoothly through the pore domain, and the streamlines showed a symmetrical and orderly pattern, converging toward the pores. During the blockage stage, the flow field was significantly disrupted. Dense particle clusters blocked the pores, causing the fluid velocity in the blocked area to drop sharply. The streamlines in this area became sparse and chaotic, and at the same time, the upstream flow direction shifted laterally, forming a high-speed jet on the periphery of the blocked area. Although the blockage restricted the flow of the fluid, it generated a pressure drop, providing a pressure gradient force for pore dredging. As the dredging progressed, the streamlines gradually regained their continuity, and the fluid began to re-infiltrate the pores. Once all the particles escaped, the flow field returned to its original pattern.

[0109] S42. Analyze the influence of the ellipsoidal particles on the blocking behavior in combination with the blocking behavior fitting result to obtain a second analysis result.

[0110] In this example, to investigate the effect of particle shape on clogging behavior, three simulations were performed using particles with aspect ratios of 1.0, 1.5, and 2.0. The pore geometry and inlet fluid velocity were kept constant in all cases, with R0 = 2.3, R c =3.0, V f =2D p / s.

[0111] See Figure 8 , the figure shows the evolution of particle configuration for different particle shapes during the simulation process; the evolution of particle configuration in three representative simulation results for different particle shapes is shown. It can be seen that spherical particles tend to form relatively dense and stable blockage structures near the outlet, and most particles remain motionless after the initial blockage. In contrast, ellipsoidal particles, especially those with higher aspect ratios, exhibit more complex dynamic behaviors, with both blockage and unblocking. The elongated shape leads to more rearrangement under the action of fluid forces, which not only delays the formation of stable blockage structures, but also introduces intermittent flow paths within the blocked area. It is worth noting that for ellipsoidal particles with an aspect ratio of 2.0, the particles completely escape in the final stage, while intermittent blockage occurs about 4.5 seconds before that.

[0112] See Figure 9 The figure shows the particle scouring rate and average particle velocity of three particle shapes; the particle scouring rate (using P e and the changes in the average particle velocity. Figure 9 As shown in (a) in the figure, the particle scouring rates of spherical and ellipsoidal particles with an aspect ratio of 1.5 peak at around 0.12 and 0.45, respectively, indicating blockage. In contrast, the particle scouring rate of ellipsoidal particles with an aspect ratio of 2.0 continues to grow and stops growing between 3.5 seconds and 5 seconds, indicating particle blockage. Due to the shape of the particles, unblocking occurs after 5 seconds, and the particle scouring rate continues to rise until it reaches 1.0. It is worth noting that both spherical and ellipsoidal particles with an aspect ratio of 1.5 will become blocked, but the degree of particle loss varies. Figure 9 (b) shows the average velocity of all particles, indicating an initial increase. Spherical particles reach their peak velocity at 2.0 seconds and slow down to a complete stop at 3.0 seconds. Ellipsoidal particles with an aspect ratio of 1.5 exhibit a similar velocity decay pattern, but their velocity does not return to zero until 5 seconds. This is because even if the front of the ellipsoidal particle becomes blocked, the particles at the rear can still rotate. Ellipsoidal particles with an aspect ratio of 2.0 exhibit significant velocity fluctuations after 5 seconds, due to their inability to form a stable structure to resist the force of the fluid. As the aspect ratio of the particle increases, the likelihood of unblocking increases.

[0113] See Figure 10 , the figure shows the results of a single particle flushing test; in this example, as mentioned above, ellipsoidal particles have a lower tendency to clog than spherical particles. To further explain this phenomenon, a series of single particle flushing tests were conducted under the same conditions. Figure 10 As shown in (a) of the figure, an ellipsoidal particle is placed at different initial angles at the model inlet. Under the influence of fluid forces, the particle gradually rotates and adjusts its direction as it moves leftward. Typically, the particle's principal axis is nearly collinear with the flow direction as it exits the pore. This reorientation makes it easier for the ellipsoidal particle to escape from the pore, reducing the probability of clogging.

[0114] Specifically, Figure 10 (a) shows the particle rotation in experiments with different aspect ratios; Figure 10 (b) shows the change of the angle between the particle main axis and the positive X direction when the initial angle is 30°; Figure 10 (c) shows the change in the angle between the particle's main axis and the positive X direction when the initial angle is 60°.

[0115] S43. Obtain the force condition and position distribution of the ellipsoidal particles according to the blocking behavior fitting result as a third analysis result.

[0116] During the simulation, fluid forces continuously push particles toward the outlet, while the pore walls resist their movement, leading to blockage. Notably, the stability of the particle structure may not be maintained. In the case of intermittent blockage, the temporary structures within the pore cannot withstand the fluid forces. Continuous fluid impact disrupts these unstable structures and their associated force chains, releasing the blocking particles and flushing them out of the pore. Once the blockage structure is established, the front-end particles bear the primary fluid load.

[0117] See Figure 11 , the figure is a schematic diagram of the force chain of the blocked particle; it shows the force chain network in the blocked particle structure; Figure 11 (a) is the force chain distribution result of spherical particles. Figure 11 Figure (b) shows the force chain distribution of an ellipsoidal particle with an aspect ratio of 1.5. Both spherical and ellipsoidal particles form a stable force chain during the plugging process, with the front particle bearing the main load.

[0118] In an alternative embodiment, the plugging structures are classified according to the spatial distribution of spherical particles within the pores. The plugging structures include a single arch structure, a branched arch structure, two separated arch structures, and a dome structure.

[0119] See Figure 12, the figure shows a schematic diagram of the clogging structure of spherical particles; based on the classification of the clogging structure, the present invention identifies three types of spherical particle clogging structures in the pore space, including a single arch structure, a branched arch structure, and a dome structure, Figure 12 (a) is a schematic diagram of a single arch structure. Figure 12 (b) is a schematic diagram of the first type of branched arch structure. Figure 12 (c) is a schematic diagram of the dome structure. Figure 12 (d) in the figure is a schematic diagram of the second type of branched arch structure. In the arch structure, the fluid force mainly propagates along the discrete arch geometry. In the dome structure, the fluid force is distributed through the multi-directional force chain formed by the dense particles near the outlet. It should be noted that R c =3.5.

[0120] Furthermore, compared with spherical particles, the clogging structure of ellipsoidal particles is more sensitive to flow rate. The clogging structure of ellipsoidal particles is classified according to different flow rates.

[0121] See Figure 13 , the figure shows the schematic diagram of the blockage structure of ellipsoidal particles at different flow rates; at low flow rates, Figure 13 (a) is a schematic diagram of the directional dome structure of the first form of ellipsoidal particles. Figure 13 (b) is a schematic diagram of the second directional dome structure of ellipsoidal particles. Under low flow conditions, since the ellipsoidal particles have enough time to adjust their direction, they flow out with their long axis perpendicular to the outlet, thus forming two different directional dome structures. However, since the contraction diameter is too small, the particles cannot escape even at the optimal position. At high flow rates, Figure 13 (c) is a schematic diagram of the interlocking bridge structure of the first form of ellipsoidal particles. Figure 13 (d) is a schematic diagram of the interlocking bridge structure of the second form of ellipsoidal particles. Figure 13 (e) is a schematic diagram of a single arch structure of ellipsoidal particles. Under high flow conditions, two structures will be formed at the outlet: one is an interlocking bridging structure, and the other is a single arch structure with particles arranged in parallel; in this case, the ellipsoidal particles do not have enough time to optimize their position.

[0122] S44: Analyze the fluid pressure drop in the blocking behavior based on the blocking behavior fitting result to obtain a fourth analysis result.

[0123] Fluid pressure drop is a sensitive indicator of pore blockage. Therefore, this paper explores the relationship between fluid pressure drop and particle blockage. The spatial distribution of particles greatly changes the flow field and pressure between the inlet and outlet.

[0124] See Figure 14 , the figure shows the relationship between fluid pressure drop and average particle velocity; when R0=2.3, R c =3.0 and V f =2D p Under the simulation condition of 1000 rpm and 1000 rpm, the pressure drop and average particle velocity of the three particle shapes were monitored. Figure 14 (a) is the relationship between the fluid pressure drop and the average velocity of the spherical particles. Figure 14 (b) is the relationship between the fluid pressure drop and the average velocity of the ellipsoidal particles (aspect ratio of 1.5). Figure 14 Figure (c) shows the relationship between fluid pressure drop and average particle velocity for an ellipsoidal particle (aspect ratio of 2.0). A clear negative correlation is observed between these two variables during both particle blocking and unblocking. When particles become trapped in pores, fluid flow obstruction increases, leading to a corresponding increase in fluid pressure drop. This trend is observed for all particle shapes, demonstrating that fluid pressure drop can reliably indicate the onset and status of blocking and unblocking.

[0125] S45. Analyze the influence of flow velocity and hole cone angle on the clogging behavior according to the clogging behavior fitting result to obtain a fifth analysis result.

[0126] Blockage behavior can occur under different flow rates and pore angle conditions; in addition to particle shape, fluid velocity and pore angle can also have a significant impact on the blockage process. Fluid velocity and pore shape can affect the movement of particles and thus the potential for blockage during migration. To systematically evaluate these effects, the flow velocity and pore angle were tested at different flow rates (i.e., V f =2D p / s、4D p / s、6D p Simulations were performed at different flow rates ( / s) and aperture angles (i.e., α = 23.2°, 25.9°, 26.6°, 27.9°, 29.5°, and 31.7°). In simulations analyzing the effect of flow rate, the aperture angle was kept constant. Conversely, in simulations investigating the effect of aperture angle on clogging, the flow rate was kept constant.

[0127] See Figure 15 , the figure shows a schematic diagram of the simulation results under different flow rates and pore cone angles; the hollow points indicate particle blockage, and the solid points indicate unblocking. In the 54 sets of simulations involving three types of particle shapes, a total of 13 blockage events occurred. The effect of flow rate on blockage is reflected in the shortening of particle migration time and the fact that the higher the flow rate, the greater the fluid force. In particular, when the particles at the outlet have not yet formed a stable structure, the strong fluid force will destroy the blockage structure. The pore cone angle also affects the blockage. When particles move into the pores, the pore walls hinder their movement, resulting in particle retention. This effect becomes more obvious as the pore cone angle increases.

[0128] like Figure 15As shown in (a) of Figure 3, 8 blockage events were observed in 18 simulations involving spherical particles. The flow rate and pore cone angle values ​​are mainly concentrated in V f =2D p / s、4D p / s and α=29.5°, 31.6°.

[0129] like Figure 15 As shown in (b), an ellipsoidal particle with an aspect ratio of 1.5 experienced 5 blockage events in 18 simulations. The blockage events were mainly concentrated under low flow rate and high hole cone angle conditions.

[0130] like Figure 15 As shown in (c), the ellipsoidal particles with an aspect ratio of 2.0 did not experience any blockage in 18 simulations. All ellipsoidal particles successfully escaped from the pores due to their shape.

[0131] See Figure 16 The figure shows the trend of particle scouring rate under different flow rates; it shows the effect of flow rate on the scouring rate of particles with different pore structures, where R is set. c =3.0, R0=2.3, 2.6, 3.0.

[0132] Figure 16 (a) Figure 16 (b) and Figure 16 (c) in the figure describes the effect of different flow rates on the blockage and unblocking of spherical particles under different R0 conditions. Figure 16 In (b), the blockage occurs at V f =2D p / s, and all spherical particles are in V f =4D p / s and V f =6D p / s to escape from the porous space.

[0133] Figure 16 (d) Figure 16 (e) and Figure 16 (f) in Figure 3 shows the behavior of ellipsoidal particles with an aspect ratio of 1.5 at different flow rates under different R0 conditions. As the flow rate increases, the escape rate of the particles also increases, especially at Figure 16 (e) and Figure 16 (f) in the middle.

[0134] Figure 16 (g) Figure 16 (h) and Figure 16 (i) in the figure shows the motion of ellipsoidal particles with an aspect ratio of 2.0 at different flow rates under different R0 conditions. Figure 16In (g), the blockage occurs at V f =2D p / s. Due to the instability of the blockage structure, the blockage was cleared after 5 seconds. At a higher flow rate (V f =4D p / s、6D p / s), the particle escape process becomes smoother. This is because at higher flow rates, the particle escape speed is significantly accelerated, which reduces the possibility of particles being retained in the pore space and generates stronger fluid forces, destroying the intermittently formed blockage structure.

[0135] S46. Perform analytical research on the blocking behavior by combining the first analysis result, the second analysis result, the third analysis result, the fourth analysis result, and the fifth analysis result.

[0136] In this example, a fully analytical CFD-DEM approach was used to simulate the particle-fluid interaction to investigate the effect of particle shape on pore clogging. Furthermore, a representative model was created by varying the particle aspect ratio. To fully analyze the clogging behavior, a detailed comparison was performed between spherical and ellipsoidal particles with varying aspect ratios. Furthermore, key parameters were investigated. The analytical study conclusions include:

[0137] (1) The aspect ratio of the particles has a positive effect on pore dredging behavior. Under the same flow conditions, ellipsoidal particles show a higher particle scouring rate. As the aspect ratio increases, the evacuation effect of these particles becomes more pronounced. Notably, ellipsoidal particles with an aspect ratio of 2.0 can maintain pore dredging even under the most extreme simulation conditions.

[0138] (2) The ellipsoidal particles continuously adjust their orientation during fluid flow, ultimately leaving the pore with their long axis perpendicular to the outlet. This dynamic orientation adjustment facilitates smooth passage of the ellipsoidal particles through the pore. However, ellipsoidal particles with an aspect ratio of 1.5 still cause blockage during the simulation. Blockage also occurs when the pore shrinks too narrow to accommodate multiple ellipsoidal particles simultaneously.

[0139] (3) The clogging structure of the ellipsoidal particles is greatly affected by the flow rate. Under low flow conditions, the ellipsoidal particles have enough time to adjust their orientation so that their long axis is perpendicular to the outlet, thus forming a directional dome structure. Under high flow conditions, two structures are formed at the outlet: one is an interlocking bridge structure with staggered interlocking bridges, and the other is a single arch structure with ellipsoidal particles arranged in parallel. Under these conditions, the ellipsoidal particles do not have enough time to optimize their arrangement.

[0140] (4) A clear negative correlation between fluid flow rate and fluid pressure drop during particle blockage and unblocking processes is observed. When particles become lodged in pores, fluid flow obstruction increases, leading to a corresponding increase in fluid pressure drop. This trend is observed for all particle shapes, indicating that fluid pressure drop can reliably indicate the onset and status of blockage and unblocking.

[0141] This study explores the influence of particle shape on pore clogging. The results provide a theoretical basis for understanding the clogging and unclogging of pores by irregularly shaped particles. The study reveals the pore-clogging behavior of irregularly shaped particles and simulates the transport of particles in porous media under the influence of fluids. This has practical implications for preventing the loss of mechanical stability of soils due to pore emptying caused by irregularly shaped particles, controlling their migration within formations, and understanding the impact of particle clogging on reservoir permeability.

[0142] See Figure 17 In an optional embodiment, the present invention provides a system for analyzing and studying particle shape-based blockage behavior. The system includes an input device, an output device, a processor, and a memory, wherein the hardware components are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to invoke the program instructions and execute the specific steps of the embodiments of the particle shape-based blockage behavior analysis method provided by the present invention. The particle shape-based blockage behavior analysis system provided by the present invention is structurally complete, objective, and stable, enhancing the overall applicability and practical application capabilities of the present invention.

[0143] In summary, the method of the present invention provides a method and system for analyzing the clogging behavior based on the influence of particle shape. The method adopts the fully analytical computational fluid dynamics-discrete element method (CFD-DEM) to simulate the particle clogging of ellipsoidal particles with different aspect ratios in a simplified pore geometry under fluid flow conditions, and evaluates the influence of particle shape on the pore clogging characteristics through parameter analysis. The method of the present invention is easy to understand, simple to calculate, has a small workload, and is convenient for engineering application. It provides a theoretical basis and technical support for the further development of the field of particle clogging research technology.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A method for analyzing and studying clogging behavior based on the influence of particle shape, characterized in that: The steps include: Obtaining ellipsoidal particles of different particle shapes, and constructing a coupled simulation model of the first blocking behavior of the ellipsoidal particles; configuring and verifying the first congestion behavior coupled simulation model to obtain a second congestion behavior coupled simulation model; Performing dynamic simulation on the ellipsoidal particles according to the second blocking behavior coupling simulation model to obtain a blocking behavior fitting result; Performing a comprehensive analysis of the congestion behavior based on the congestion behavior fitting result to achieve an analytical study of the congestion behavior; The step of obtaining ellipsoidal particles of different particle shapes and constructing a coupled simulation model of the first blocking behavior of the ellipsoidal particles includes: determining different aspect ratios, and constructing ellipsoidal particles of different particle shapes based on the aspect ratios; Construct the first governing equation for the particle phase and solve the second governing equation for the fluid phase; Combining the first control equation and the second control equation, constructing the first blocking behavior coupled simulation model of the particle phase and the fluid phase; The first control equation includes the translational motion equation and the rotational motion equation of the ellipsoidal particle; The translational motion equation satisfies the following relationship: in, is the mass of the particle, is the instantaneous speed, is the total number of particle contacts, is the index variable, is the contact force acting on the particle, is the interaction force between the particle and the fluid; The rotational motion equation satisfies the following relationship: in, is the moment of inertia tensor of the particle, is the angular velocity, is the total number of particle contacts, is the index variable, is the moment of force exerted by the particle on the particle, is the moment between the particle and the fluid; The second control equation includes the continuity equation and the Navier-Stokes equation; The continuity equation satisfies the following relationship: in, is the fluid density, is the divergence operator, is the average velocity of the fluid unit; The Navier-Stokes equations satisfy the following relationship: in, is the fluid density, is the average velocity of the fluid unit, is the divergence operator, represents the direct product of two vectors, is the gradient operator, is the fluid pressure, is the fluid viscosity, is the acceleration due to gravity; The effect of particle motion on the flow field is achieved by forcing the particle velocity and the average velocity of the fluid cell to be equal; The particle velocity satisfies the following relationship: in, is the particle velocity, is the instantaneous speed, is the angular velocity, is the positive vector relative to the center point of the particle, is the particle domain, represents the interior of the particle domain; The average velocity of the fluid unit satisfies the following relationship: in, is the average velocity of the fluid unit, is the fluid velocity before correction, is the void ratio, is the particle velocity, For the simulation domain, Represents inside the simulation domain; The configuring and verifying the first congestion behavior coupling simulation model to obtain a second congestion behavior coupling simulation model includes: Obtaining pore geometry parameters and fluid parameters corresponding to the ellipsoidal particles; Configuring the first blocking behavior coupling simulation model based on the pore geometry parameters and the fluid parameters to obtain model parameters; Establishing a model verification test, and verifying the first blocking behavior coupling simulation model based on the model verification test in combination with the ellipsoidal particles to obtain the second blocking behavior coupling simulation model; The probability of pore clogging is proportional to the ratio of the pore shrinkage diameter to the particle diameter, satisfying the following relationship: in, is the ratio of the pore contraction diameter to the particle diameter, is the pore contraction diameter, is the particle diameter; The ratio of pore length to particle diameter is defined to satisfy the following relationship: in, is the ratio of pore length to particle diameter, is the duct length, is the particle diameter; The model validation tests include a particle settling test and an Ergon test.

2. The method for analyzing and studying the clogging behavior based on the influence of particle shape according to claim 1 is characterized in that: The comprehensive analysis of the congestion behavior based on the congestion behavior fitting result to achieve analytical research on the congestion behavior includes: analyzing the particle migration and the blocking behavior of the ellipsoidal particles based on the blocking behavior fitting result to obtain a first analysis result; analyzing the influence of the ellipsoidal particles on the blocking behavior in combination with the blocking behavior fitting result to obtain a second analysis result; Obtaining the force condition and position distribution of the ellipsoidal particles according to the blocking behavior fitting result as a third analysis result; analyzing the fluid pressure drop in the blocking behavior based on the blocking behavior fitting result to obtain a fourth analysis result; Analyzing the influence of flow velocity and hole cone angle on the clogging behavior according to the clogging behavior fitting result to obtain a fifth analysis result; The first analysis result, the second analysis result, the third analysis result, the fourth analysis result and the fifth analysis result are combined to realize an analytical study on the blocking behavior.

3. The method for analyzing and studying the clogging behavior based on the influence of particle shape according to claim 2, characterized in that: The analyzing the particle migration and the blocking behavior of the ellipsoidal particles based on the blocking behavior fitting result to obtain a first analysis result includes: In a single-pore structure, the blocking process and unblocking process of the ellipsoidal particles are obtained based on the blocking behavior fitting results; Obtain flow field changes during the blocking process and the unblocking process.

4. The method for analyzing and studying the clogging behavior based on the influence of particle shape according to claim 2, characterized in that: The analyzing the influence of the ellipsoidal particles on the blocking behavior in combination with the blocking behavior fitting result to obtain a second analysis result includes: Obtaining, according to the blocking behavior fitting result, a particle configuration evolution of the ellipsoidal particles in the blocking behavior; In the blocking behavior, a change in the particle scouring rate and the change in the average particle velocity of the ellipsoidal particles are obtained; In combination with the change in the particle scouring rate and the change in the average velocity of the particles, a single particle scouring test is performed on the ellipsoidal particles to obtain test results.

5. The method for analyzing and studying the clogging behavior based on the influence of particle shape according to claim 2, characterized in that: The force condition and position distribution of the ellipsoidal particles obtained according to the blocking behavior fitting result as a third analysis result includes: Obtaining a force chain distribution result of the ellipsoidal particle according to the blocking behavior fitting result, and analyzing the force chain distribution result to obtain the stress condition; The blocking particle structure of the ellipsoidal particles is obtained according to the blocking behavior fitting result, and the blocking particle structure is used as the position distribution.

6. The method for analyzing and studying the clogging behavior based on the influence of particle shape according to claim 2, characterized in that: The analyzing the fluid pressure drop in the blocking behavior based on the blocking behavior fitting result to obtain a fourth analysis result includes: Obtaining the fluid pressure drop of the ellipsoidal particle based on the blocking behavior fitting result; An evolution relationship between the average particle velocity of the ellipsoidal particles and the fluid pressure drop is obtained, and the pore blockage condition is determined based on the evolution relationship.

7. The method for analyzing and studying the clogging behavior based on the influence of particle shape according to claim 2, characterized in that: The fifth analysis result obtained by analyzing the influence of flow velocity and hole cone angle on the clogging behavior according to the clogging behavior fitting result includes: Determining different flow rates and different hole cone angles, and obtaining a blockage simulation result based on the flow rates and the hole cone angles in combination with a control variable method; For the ellipsoidal particles, the effect of the flow rate on the particle flushing rate was analyzed under different pore structures to obtain the effect results.

8. A system for analyzing and studying clogging behavior based on the influence of particle shape, characterized in that: The system includes an input device, an output device, a processor and a memory, wherein the input device, the output device, the processor and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the blockage behavior analysis research method based on the influence of particle shape as described in any one of claims 1 to 7.

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