A horizontal pipeline gas-solid two-phase flow pattern recognition method based on dimensionless parameter joint analysis

Abstract

The present application belongs to the technical field of multiphase flow, and particularly relates to a horizontal pipeline gas-solid two-phase flow pattern recognition method based on dimensionless parameter joint analysis, which comprises: collecting gas-solid two-phase flow parameters, wherein the gas-solid two-phase flow parameters include gas phase density, gas phase velocity, gas phase viscosity, pipeline diameter, particle density and particle diameter; calculating dimensionless parameters based on the gas-solid two-phase flow parameters, wherein the dimensionless parameters include Reynolds number, Stokes number and Froude number; calculating sensitivity values by using finite element software, and calculating concentration values of each region of the horizontal pipeline based on the sensitivity values; and performing flow pattern discrimination on the gas-solid two-phase flow of the horizontal pipeline based on the dimensionless parameters and the concentration values to obtain a flow pattern recognition result. The present application improves the robustness of the overall recognition method.

Description

Technical Field

[0001] This invention belongs to the field of multiphase flow technology, specifically relating to a method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters. Background Technology

[0002] Gas-solid two-phase flow is widely used in industrial pipeline transportation processes, such as in metallurgy, power generation, chemical industry, and building materials. In horizontal pipelines, the flow state (i.e., flow pattern) of gas-solid two-phase flow directly affects transportation efficiency, energy consumption, and equipment stability. Accurate identification of the flow pattern is crucial for optimizing transportation processes and improving operational reliability. Because gas-solid two-phase flow involves complex interactions between solid particles and gaseous fluids, its flow pattern is influenced by various factors such as particle characteristics, gas velocity, and pipeline structure. Therefore, it is necessary to establish a reasonable flow pattern identification method to guide practical engineering applications.

[0003] Currently, flow pattern identification methods mainly rely on empirical criteria, single feature parameters, or machine learning techniques based on signals and images. Empirical criteria are usually based on experimental data under specific operating conditions, with limited applicability and difficulty in adapting to changes in particulate properties, pipe diameters, and transport conditions. Methods based on single feature parameters (such as pressure drop fluctuations, concentration distribution, etc.) can only reflect local characteristics of the flow and cannot comprehensively characterize the dynamic evolution of flow patterns. In addition, although machine learning-based identification methods have a certain degree of adaptability, they are highly dependent on sample data and lack generalization ability. Dimensionless parameters can effectively characterize the dominant mechanical mechanisms in the flow process and have good scale independence, but existing studies mostly use single dimensionless parameters (such as Froude number, Stokes number, etc.) for flow pattern classification, considering only the unilateral dynamic characteristics of the gas or solid phase, ignoring the coupling effect of multiple physical mechanisms, resulting in insufficient accuracy in flow pattern identification. Summary of the Invention

[0004] The aforementioned flow pattern identification methods struggle to achieve high accuracy and strong generalization under varying operating conditions, and lack a comprehensive consideration of the coupling effects of multiple physical mechanisms. Therefore, this invention provides a flow pattern identification method for gas-solid two-phase flow in horizontal pipelines based on joint analysis of dimensionless parameters. This invention primarily constructs multiple dimensionless parameters reflecting the dynamic mechanisms and spatial distribution of gas-solid two-phase flow, and jointly discriminates them to accurately identify suspended flow, laminar flow, dune flow, and plunger flow. This method does not rely on a single empirical threshold and has good engineering applicability.

[0005] The technical means employed in this invention are as follows:

[0006] A method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters includes the following steps: Collect gas-solid two-phase flow parameters, including gas phase density, gas phase velocity, gas phase viscosity, pipe diameter, particle density, and particle diameter; Based on the gas-solid two-phase flow parameters, dimensionless parameters are calculated, including Reynolds number, Stokes number, and Froude number. The sensitivity value is calculated using finite element software, and the concentration value of each region of the horizontal pipe is calculated based on the sensitivity value. Based on the combined analysis of the Reynolds number, Stokes number, and Froude number, and combined with the distribution characteristics of the axial concentration sequence and the radial concentration sequence, the flow pattern of the gas-solid two-phase flow in the pipeline is identified according to the flow pattern discrimination rule constructed based on the gas-solid two-phase fluid dynamics mechanism.

[0007] Furthermore, the sensitivity value calculated using finite element software includes: A horizontal pipeline geometric model including a six-plate capacitive sensor is established. The horizontal pipeline model is meshed according to the concentration analysis window. The concentration analysis window is divided into N sub-segments along the axial direction. An axial concentration sequence is constructed based on the sub-segments. The concentration analysis window divides the region into six isoangular regions with the pipeline center axis. A radial concentration sequence is constructed based on the isoangular regions. The sensitivity value is calculated using finite element simulation software, and the formula for calculating the sensitivity value is as follows:

[0008] in, This is the sensitivity value. For excitation voltage, and These respectively represent the excitation voltage. Applied to the electrode and electrodes At that time, within the measurement area, the first The center point of each unit The electric field strength at that location.

[0009] Furthermore, the calculation of concentration values ​​for each region of the horizontal pipe based on the sensitivity value includes a forward simulation process: Run a gas-solid two-phase flow coupled simulation to obtain particle distribution data in each analysis region during the simulation process; The number of particles in each analysis region is counted in the simulation software, and the solid concentration value of each region is calculated by combining the region volume, forming axial concentration distribution characteristics and radial concentration distribution characteristics.

[0010] Furthermore, the calculation of concentration values ​​in each region of the horizontal pipeline based on the sensitivity value also includes an actual operating condition inversion process: A six-plate capacitive sensor is installed in the target horizontal pipeline to determine the measurement area corresponding to the sensitivity value. The segmented concentration analysis area is divided into N axial sub-segments and 6 radial equiangular regions. The volume ratio of each unit is calculated. A sensor calibration experiment was conducted to measure the capacitance value of the empty tube and the capacitance value at a known concentration, and to determine the general formula for concentration calculation. The first parameter Second parameter ,in, solid concentration The capacitance vector. This is the capacitance value in the empty tube state; Under actual working conditions, the capacitance values ​​of each plate pair of the six-plate capacitive sensor are measured to obtain the capacitance vector; Using the general formula or the relationship between capacitance and dielectric constant obtained from calibration The concentration values ​​for each region were calculated by combining the sensitivity values, where, For simulating the capacitance vector, For the first One equivalent dielectric constant.

[0011] Furthermore, the formula for calculating the Reynolds number is as follows:

[0012] in, Let Reynolds number be 1. For gas phase density, For gas phase velocity, For pipe diameter, The viscosity is the gas phase viscosity. When the particle Reynolds number is less than or equal to 1, the formula for calculating the Stokes number is:

[0013] in, For Stokes numbers, For particle relaxation time, For fluid characteristic time, When the particle Reynolds number is greater than 1, the Stokes number will be corrected, and the calculation formula is as follows:

[0014] in, This is the corrected particle relaxation time. The formula for calculating the Froude number is as follows:

[0015] in, For Froude number, This is the acceleration due to gravity.

[0016] Furthermore, the formula for calculating the particle relaxation time is as follows:

[0017] in, For particle relaxation time, The particle diameter is The revised formula for calculating particle relaxation time is as follows:

[0018] in, The drag coefficient, The particle Reynolds number, The formula for calculating the fluid characteristic time is:

[0019] in, For pipe diameter, The formula for calculating the particle Reynolds number is:

[0020] in, The particle Reynolds number, The particle diameter is denoted as .

[0021] Furthermore, the process of determining the flow pattern of the gas-solid two-phase flow in the horizontal pipe based on the dimensionless parameter and the concentration value includes: By jointly analyzing the Stokes number and Froude number, and combining the distribution characteristics of the axial and radial concentration sequences, flow pattern discrimination rules are constructed based on the gas-solid two-phase flow dynamics mechanism to identify flow patterns.

[0022] Furthermore, the flow pattern discrimination includes: When correcting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a suspended flow; When correcting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was determined to be laminar flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a dune flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a plunger flow.

[0023] Furthermore, when the Reynolds number is less than 2300, the flow pattern of the gas-solid two-phase flow in the horizontal pipe is laminar; when the Reynolds number is greater than or equal to 2300 and less than 4000, the flow pattern of the gas-solid two-phase flow in the horizontal pipe is transitional; and when the Reynolds number is greater than or equal to 4000, the flow pattern of the gas-solid two-phase flow in the horizontal pipe is turbulent.

[0024] Furthermore, the formula for the axial concentration variation coefficient is:

[0025] in, The coefficient of variation is the axial concentration. The standard deviation of axial concentration. The axial average concentration, , , For the first Concentration at each axial position, This represents the number of axial sampling points. The formula for the peak-to-valley amplitude ratio is:

[0026] in, The peak-to-valley amplitude ratio, The maximum concentration along the axis. Minimum axial concentration, The axial average concentration, The radial concentration stratification index is:

[0027] in, The concentration in the top region. The concentration in the bottom region, This represents the average concentration across all regions. , For the first Concentration at a radial location, This represents the number of radial partitions.

[0028] Compared with the prior art, the present invention has the following advantages: 1. This invention introduces the gas phase Reynolds number to predict the fluid state and combines the Stokes number and Froude number to quantitatively analyze the particle inertial effect and gas phase carrying capacity. This makes the flow pattern identification based on the clear physical mechanism of gas phase turbulence characteristics, particle following behavior and gravity gas-solid competition relationship, rather than relying on a single empirical threshold. This significantly enhances the applicability and stability of the method under different working conditions.

[0029] 2. This invention achieves non-invasive and accurate inversion of the axial and radial concentration distributions of gas-solid two-phase flow through a six-stage plate capacitive sensor and its sensitivity field calculation. This provides crucial data support for flow pattern identification, moving from "average concentration" to "spatial structure."

[0030] 3. This invention creatively incorporates dimensionless parameters characterizing dynamic mechanisms (Stokes number, Froude number) and concentration distribution characteristics characterizing spatial morphology (axial coefficient of variation, radial stratification index, etc.) into the same analytical framework. This multi-scale fusion analysis of "mechanism + morphology" enables manifold identification to maintain high stability in overlapping boundary regions, greatly improving the robustness and generalization ability of the method.

[0031] 4. This invention uses a six-plate capacitive sensor to acquire multi-channel capacitance signals and uses the capacitance-concentration mapping function for inversion, realizing non-invasive online measurement of the spatial structure of gas-solid two-phase flow in pipelines, providing a feasible technical means for real-time monitoring of flow patterns and process optimization in industrial sites.

[0032] Based on the above reasons, this invention can be widely applied in fields such as multiphase flow. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a schematic flowchart of a method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters, according to the present invention.

[0035] Figure 2 This is the axial concentration distribution map obtained from multiphysics numerical simulation in Embodiment 1 of the present invention.

[0036] Figure 3 This is a radial concentration distribution map obtained from multiphysics numerical simulation in Embodiment 1 of the present invention.

[0037] Figure 4 This is an axial concentration distribution diagram obtained based on actual working conditions in Embodiment 2 of the present invention.

[0038] Figure 5 This is a radial concentration distribution diagram obtained based on actual working conditions in Embodiment 2 of the present invention. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0041] In gas-solid two-phase flow in horizontal pipes, the flow pattern is influenced by gas phase inertia, particle inertia, gravity, and the spatial distribution of particles. Relying solely on a single physical quantity or empirical threshold for flow pattern identification is insufficient to address the evolving flow pattern under varying operating conditions. Dimensionless parameters can combine multiple influencing factors such as gas phase velocity, particle characteristics, and pipe dimensions, exhibiting good scale consistency and generalization ability across operating conditions. Furthermore, axial and radial solid phase concentration distributions directly reflect the spatial non-uniformity and structural morphology of particles within the pipe. Joint analysis of fluid dynamic parameters with axial and radial concentration characteristics allows for simultaneous characterization of the gas-solid two-phase flow state from both dynamic and spatial distribution perspectives, significantly improving the accuracy and stability of flow pattern identification.

[0042] like Figure 1 As shown, this invention provides a method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters, including the following steps: S1. Collect gas-solid two-phase flow parameters, including gas phase density, gas phase velocity, gas phase viscosity, pipe diameter, particle density, and particle diameter.

[0043] S2. Calculate dimensionless parameters based on gas-solid two-phase flow parameters, including Reynolds number, Stokes number, and Froude number.

[0044] The formula for calculating the Reynolds number is:

[0045] in, Let Reynolds number be 1. For gas phase density, For gas phase velocity, For pipe diameter, This refers to the gas phase viscosity. The Reynolds number describes the ratio of inertial force to viscous force in gas-phase flow. When the Reynolds number is less than 2300, the flow pattern of gas-solid two-phase flow in a horizontal pipe is laminar. When the Reynolds number is greater than or equal to 2300 and less than 4000, the flow pattern of gas-solid two-phase flow in a horizontal pipe is transitional. When the Reynolds number is greater than or equal to 4000, the flow pattern of gas-solid two-phase flow in a horizontal pipe is turbulent.

[0046] When the particle Reynolds number is less than or equal to 1, the Stokes number is calculated as follows:

[0047] in, For Stokes numbers, For particle relaxation time, The characteristic time of the fluid. The Stokes number is used to characterize the relative magnitude between particle inertial forces and gas-phase viscous drag. The formula for calculating particle relaxation time is:

[0048] in, For particle relaxation time, The particle diameter is denoted as .

[0049] The formula for calculating the characteristic time of a fluid is:

[0050] in, This refers to the pipe diameter.

[0051] When the particle Reynolds number is greater than 1, the Stokes number will be corrected, and the calculation formula is as follows:

[0052] in, This is the corrected particle relaxation time.

[0053] when When the particle inertia is negligible, the particles closely follow the fluid motion; when At that time, the particle inertia is comparable to the fluid resistance, and the particles partially follow the gas phase flow; when At this time, particle inertia dominates, and particle motion is almost unaffected by the fluid.

[0054] The formula for calculating the particle Reynolds number is:

[0055] in, The particle Reynolds number, The particle diameter is denoted as .

[0056] The revised formula for calculating particle relaxation time is as follows:

[0057] in, The drag coefficient, is the particle Reynolds number.

[0058] The formula for calculating the Froude number is:

[0059] in, For Froude number, This is the acceleration due to gravity. When When gravity dominates, particles tend to settle; when... When gravity and inertial forces are in balance, a transitional flow pattern is easily formed; when... Inertial force dominates, making particles easily suspended.

[0060] S3. Use finite element software to calculate the sensitivity value, and then calculate the concentration value of each region in the horizontal pipe based on the sensitivity value.

[0061] The sensitivity value was calculated using finite element software, and this sensitivity matrix... It is key to realizing the mapping from "capacitance value" to "concentration value," establishing a bridge between the measured signal (capacitance) and the spatial distribution of matter (concentration), including: A horizontal pipe geometric model including a six-plate capacitive sensor is established. The horizontal pipe assembly model is meshed according to the concentration analysis window. The concentration analysis window is divided into N sub-segments along the axial direction. An axial concentration sequence is constructed based on the sub-segments. The concentration analysis window divides the region into six isoangular regions with the central axis of the pipe. A radial concentration sequence is constructed based on the isoangular regions. The sensitivity value is calculated using finite element simulation software. The formula for calculating the sensitivity value is as follows:

[0062] in, This is the sensitivity value. For excitation voltage, and These respectively represent the excitation voltage. Applied to the electrode and electrodes At that time, within the measurement area, the first The center point of each unit The electric field strength at that location.

[0063] The concentration values ​​of each region in the horizontal pipeline are calculated based on the sensitivity values, including the forward simulation process: Run a gas-solid two-phase flow coupled simulation to obtain particle distribution data in each analysis region during the simulation process; The number of particles in each analysis region is counted in the simulation software, and the solid concentration value of each region is calculated by combining the region volume, forming axial concentration distribution characteristics and radial concentration distribution characteristics.

[0064] The concentration values ​​for each region of the horizontal pipeline are calculated based on sensitivity values, and the process also includes an inversion process based on actual operating conditions: A six-plate capacitive sensor is installed in the target horizontal pipeline to determine the measurement area corresponding to the sensitivity value. The segmented concentration analysis area is divided into N axial sub-segments and 6 radial equiangular regions. The volume ratio of each unit is calculated. A sensor calibration experiment was conducted to measure the capacitance value of the empty tube and the capacitance value at a known concentration, and to determine the general formula for concentration calculation. The first parameter Second parameter ,in, solid concentration The capacitance vector. This is the capacitance value in the empty tube state; Under actual working conditions, the capacitance values ​​of each plate pair of the six-plate capacitive sensor are measured to obtain the capacitance vector; Using the general formula or the relationship between capacitance and dielectric constant obtained from calibration The concentration values ​​for each region were calculated by combining the sensitivity values, where, For simulating the capacitance vector, Let be the k-th equivalent dielectric constant.

[0065] S4. Based on dimensionless parameters and concentration values, the flow pattern of the gas-solid two-phase flow in the horizontal pipeline is determined, and the flow pattern identification results are obtained.

[0066] By combining the Stokes number and Froude number with the distribution characteristics of axial and radial concentration sequences, flow pattern discrimination rules are constructed based on the dynamic mechanism of gas-solid two-phase flow to identify different flow patterns.

[0067] Specifically, flow pattern determination includes: When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a suspended flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was determined to be laminar flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a dune flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on the characteristics, it is identified as a plunger flow. The calculation formula for the concentration evaluation index is as follows: Axial concentration variation coefficient: , , in For the first Concentration at each axial position, This represents the number of axial sampling points. The axial average concentration, This represents the standard deviation of axial concentration.

[0068] Axial concentration peak-to-valley amplitude ratio: in The maximum concentration along the axis. Minimum axial concentration, The average concentration is axial.

[0069] Radial concentration stratification index: , ,in The concentration in the top region. The concentration in the bottom region, For the first Concentration at a radial location, This represents the number of radial partitions. This represents the average concentration across all regions.

[0070] Finally, the flow pattern type of the current gas-solid two-phase flow in the horizontal pipe is output. The flow pattern types include suspended flow, laminar flow, dune flow, and plunger flow.

[0071] This method first classifies gas-solid two-phase flows by calculating the gas-phase Reynolds number to determine whether the gas phase is in a laminar or turbulent state, thereby determining the formulas for other dynamic parameters. After determining the flow state, the Stokes number and Froude number are further calculated to analyze the relative relationship between particle inertial effects and gas phase carrying capacity, achieving flow pattern prediction at the dynamic level. Subsequently, capacitance signals are acquired using a capacitive sensor array, and a concentration inversion region is established based on the sensor sensitivity distribution to calculate the axial and radial solid phase concentration distribution. If multiphysics simulation is performed, particle volume can be directly calculated to obtain the solid phase concentration distribution. Finally, by analyzing the axial fluctuation characteristics and radial non-uniformity characteristics of the concentration, a comprehensive judgment of the flow pattern is made, achieving stable identification of suspended flow, laminar flow, dune flow, and plug flow.

[0072] It should be noted that the specific numerical thresholds involved in the above flow pattern discrimination rules, such as... and The thresholds were not chosen arbitrarily. The applicant collected flow pattern data under different particle diameters, densities, and gas phase velocities through extensive CFD-DEM numerical simulations and laboratory-scale horizontal pipeline gas-solid two-phase flow experiments. By conducting sensitivity analysis and statistical induction of the dimensionless parameters and concentration distribution characteristics near the flow pattern transition point, it was found that the aforementioned thresholds can most effectively distinguish between the four typical flow patterns: suspended flow, laminar flow, dune flow, and plunger flow. These thresholds constitute the key technical points of this invention, ensuring the robustness and accuracy of the method under different operating conditions.

[0073] Example 1 This embodiment provides a method for flow pattern identification based on multiphysics numerical simulation. Through multiphysics numerical simulation, specifically a CFD-DEM method, a gas-solid two-phase flow pattern is simulated, with the pipe diameter set as [value missing]. The gas phase velocity is The particle diameter is Particle density is The gas phase density is The gas phase viscosity is The calculated Reynolds number is: It is in a turbulent state, and the Stokes number is Froude number The axial concentration variation coefficient was 0.40, the peak-to-valley amplitude ratio was 0.89, and the radial concentration stratification index was 2.24. Figure 2 and Figure 3 As shown in the axial and radial concentration distribution maps, there are significant peak and valley variations in the axial concentration. In terms of radial concentration, regions 3 (Q3), 4 (Q4), and 5 (Q5) show significantly higher concentrations, which are identified as significant dune flow patterns. The identification results are consistent with experimental observations, verifying the effectiveness of the method of the present invention.

[0074] Example 2 This embodiment provides a flow pattern identification method based on measured data of gas-solid two-phase flow in a horizontal pipeline, combined with actual operating parameters, where the pipeline diameter in the actual case is... The gas phase velocity is The particle diameter is Particle density is The gas phase density is The gas phase viscosity is The calculated Reynolds number is: It is in a turbulent state, and the Stokes number is Froude number The axial concentration variation coefficient was 0.04, the peak-to-valley amplitude ratio was 0.12, and the radial concentration stratification index was 4.13. Figure 4 and Figure 5 As shown in the axial and radial concentration distribution maps, the axial concentration is relatively stable, while the radial concentration shows that region 4 (Q4) has a significantly higher concentration, which is identified as a laminar flow pattern. The identification results are consistent with experimental observations, verifying the effectiveness of the method of the present invention.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention 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 or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters, characterized in that, Includes the following steps: Collect gas-solid two-phase flow parameters, including gas phase density, gas phase velocity, gas phase viscosity, pipe diameter, particle density, and particle diameter; Based on the gas-solid two-phase flow parameters, dimensionless parameters are calculated, including Reynolds number, Stokes number, and Froude number. The sensitivity value is calculated using finite element software, and the concentration value of each region of the horizontal pipe is calculated based on the sensitivity value. Based on the combined analysis of the Reynolds number, Stokes number, and Froude number, and combined with the distribution characteristics of the axial concentration sequence and the radial concentration sequence, the flow pattern of the gas-solid two-phase flow in the pipeline is identified according to the flow pattern discrimination rule constructed based on the gas-solid two-phase fluid dynamics mechanism.

2. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 1, characterized in that, The sensitivity value calculated using finite element software includes: A horizontal pipeline geometric model including a six-plate capacitive sensor is established. The horizontal pipeline model is meshed according to the concentration analysis window. The concentration analysis window is divided into N sub-segments along the axial direction. An axial concentration sequence is constructed based on the sub-segments. The concentration analysis window divides the region into six isoangular regions with the pipeline center axis. A radial concentration sequence is constructed based on the isoangular regions. The sensitivity value is calculated using finite element simulation software, and the formula for calculating the sensitivity value is as follows: in, This is the sensitivity value. For excitation voltage, and These respectively represent the excitation voltage. Applied to the electrode and electrodes At that time, within the measurement area, the first The center point of each unit The electric field strength at that location.

3. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 1, characterized in that, The calculation of concentration values ​​for each region of the horizontal pipeline based on the sensitivity value includes a simulation forward modeling process: Run a gas-solid two-phase flow coupled simulation to obtain particle distribution data in each analysis region during the simulation process; The number of particles in each analysis region is counted in the simulation software, and the solid concentration value of each region is calculated by combining the region volume, forming axial concentration distribution characteristics and radial concentration distribution characteristics.

4. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 1, characterized in that, The calculation of concentration values ​​for each region of the horizontal pipeline based on the sensitivity value also includes an inversion process under actual operating conditions: A six-plate capacitive sensor is installed in the target horizontal pipeline to determine the measurement area corresponding to the sensitivity value. The segmented concentration analysis area is divided into N axial sub-segments and 6 radial equiangular regions. The volume ratio of each unit is calculated. A sensor calibration experiment was conducted to measure the capacitance value of the empty tube and the capacitance value at a known concentration, and to determine the general formula for concentration calculation. The first parameter Second parameter ,in, solid concentration The capacitance vector. This is the capacitance value in the empty tube state; Under actual working conditions, the capacitance values ​​of each plate pair of the six-plate capacitive sensor are measured to obtain the capacitance vector; Using the general formula or the relationship between capacitance and dielectric constant obtained from calibration The concentration values ​​for each region were calculated by combining the sensitivity values, where, For simulating the capacitance vector, For the first One equivalent dielectric constant.

5. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 1, characterized in that, The formula for calculating the Reynolds number is: in, Let Reynolds number be 1. For gas phase density, For gas phase velocity, For pipe diameter, The viscosity is the gas phase viscosity. When the particle Reynolds number is less than or equal to 1, the formula for calculating the Stokes number is: in, For Stokes numbers, For particle relaxation time, For fluid characteristic time, When the particle Reynolds number is greater than 1, the Stokes number will be corrected, and the calculation formula is as follows: in, This is the corrected particle relaxation time. The formula for calculating the Froude number is as follows: in, For Froude number, This is the acceleration due to gravity.

6. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 5, characterized in that, The formula for calculating the particle relaxation time is: in, For particle relaxation time, The particle diameter is The revised formula for calculating particle relaxation time is as follows: in, The drag coefficient, The particle Reynolds number, The formula for calculating the fluid characteristic time is: in, For pipe diameter, The formula for calculating the particle Reynolds number is: in, The particle Reynolds number, The particle diameter is denoted as .

7. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 1, characterized in that, The process of determining the flow pattern of the gas-solid two-phase flow in the horizontal pipeline based on the dimensionless parameter and the concentration value includes: By jointly analyzing the Stokes number and Froude number, and combining the distribution characteristics of the axial and radial concentration sequences, flow pattern discrimination rules are constructed based on the gas-solid two-phase flow dynamics mechanism to identify flow patterns.

8. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 7, characterized in that, The flow pattern discrimination includes: When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a suspended flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was determined to be laminar flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a dune flow; When adjusting the Stokes number And Froude number At the same time, combined with the axial concentration variation coefficient Peak-to-valley amplitude ratio and radial concentration stratification index Based on its characteristics, it was identified as a plunger flow.

9. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 1, characterized in that, When the Reynolds number is less than 2300, the flow pattern of the gas-solid two-phase flow in the horizontal pipe is laminar; when the Reynolds number is greater than or equal to 2300 and less than 4000, the flow pattern of the gas-solid two-phase flow in the horizontal pipe is transitional; and when the Reynolds number is greater than or equal to 4000, the flow pattern of the gas-solid two-phase flow in the horizontal pipe is turbulent.

10. The method for identifying the flow pattern of gas-solid two-phase flow in a horizontal pipeline based on joint analysis of dimensionless parameters according to claim 8, characterized in that, The formula for the axial concentration variation coefficient is: in, The coefficient of variation is the axial concentration. The standard deviation of axial concentration. The axial average concentration, , , For the first Concentration at each axial position, This represents the number of axial sampling points. The formula for the peak-to-valley amplitude ratio is: in, The peak-to-valley amplitude ratio, The maximum concentration along the axis. Minimum axial concentration, The axial average concentration, The radial concentration stratification index is: in, The concentration in the top region. The concentration in the bottom region, This represents the average concentration across all regions. , For the first Concentration at a radial location, This represents the number of radial partitions.

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