A simulation method for calculating the flow rate of a pipeline purging process

Abstract

The application relates to a simulation calculation method for pipeline purging process flow velocity, which respectively utilizes an ideal gas model and a constant model to calculate first density and second density of a fluid medium for purging, utilizes a strong temperature-dependent model and a constant model to calculate first viscosity and second viscosity, carries out weighted summation on the first density and the second density to obtain a corrected density, carries out weighted summation on the first viscosity and the second viscosity to obtain a corrected viscosity, compares a calculation flow velocity obtained based on the corrected parameters with an actual flow velocity, adjusts weights through iteration until an error meets a requirement, and finally carries out flow field solving and particle motion tracking on effective density and effective viscosity obtained when the error meets the requirement to obtain simulation results. The method utilizes a dynamic coupling calculation model and weight iterative adjustment in combination, integrates multiple-dimensional parameters such as temperature, pressure and medium characteristics, and can be suitable for complex working conditions including different medium characteristics and variable environmental conditions.

Description

Technical Field

[0001] This application relates to the field of pipeline construction and cleaning technology, and in particular to a method for simulating and calculating the flow velocity during pipeline purging. Background Technology

[0002] In industries such as petroleum, chemical, and natural gas, purging is a crucial process for removing physical impurities such as welding slag, iron filings, and sand from pipelines after construction, maintenance, or long-term shutdown. The purging process involves injecting a high-speed flowing medium into the pipeline, utilizing the fluid's kinetic energy to carry impurities out of the system, ensuring the cleanliness of the pipeline interior and guaranteeing the safe operation of subsequent equipment and production.

[0003] Traditional purging process simulation methods often rely on engineers' experience or simple formulas based on a single parameter. These methods ignore the significant impact of temperature and pressure fluctuations on fluid density and viscosity, as well as the differences in the properties of different media, leading to large deviations between the calculated flow rate and actual operating conditions. Inaccurate simulations result in poor actual purging effects, either incomplete cleaning leaving hidden dangers or over-purging causing energy waste and equipment damage.

[0004] Therefore, there is an urgent need in this field for a method that can comprehensively consider multiple dynamic parameters such as temperature, pressure, and media characteristics, and can perform high-precision, adaptive simulation of the pipeline purging process. Summary of the Invention

[0005] To address the shortcomings of the prior art, this application provides a method for simulating and calculating the flow velocity during a pipeline purging process. During pipeline purging, a fluid medium is used to blow particles out of the pipeline. The method includes: Parametric modeling steps: Parametrically model the pipeline to generate a pipeline model composed of several structured mesh units; To obtain the density and viscosity of the fluid medium; Obtain the pipe temperature and pressure corresponding to the structured mesh cells; Weight determination steps: Obtain the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight, and use the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight as the current temperature weight, current pressure weight, current density weight, and current viscosity weight, respectively; For each structured mesh cell, Model density determination steps: Input the pipe temperature, pipe pressure, and medium density corresponding to the structured mesh cell into the first density model to obtain the first density; the first density model is an ideal gas model; input the medium density into the second density model to obtain the second density; the second density model is a constant density model; Model viscosity determination steps: Input the pipe temperature and medium viscosity corresponding to the structured mesh unit into the first viscosity model to obtain the first viscosity; the first viscosity model is a temperature-dependent viscosity model; input the medium viscosity into the second viscosity model to obtain the second viscosity; the second viscosity model is a constant viscosity model. Corrected density determination steps: Determine the weight corresponding to the first density and the weight corresponding to the second density based on at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight; Based on the weight corresponding to the first density and the weight corresponding to the second density, perform a weighted summation on the first density and the second density to obtain the corrected density of the fluid medium corresponding to the structured grid cell. Corrected viscosity determination steps: Determine the weight corresponding to the first viscosity and the weight corresponding to the second viscosity based on at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight; Based on the weight corresponding to the first viscosity and the weight corresponding to the second viscosity, perform a weighted summation on the first viscosity and the second viscosity to obtain the corrected viscosity of the fluid medium corresponding to the structured grid cell. The steps for calculating the velocity of the fluid medium are as follows: The transient solution of the fluid field is performed based on the corrected density and corrected viscosity of each structured mesh element to obtain the calculated velocity of the fluid medium at a specified location and time. A flow meter is installed at the specified location to measure the actual velocity of the fluid medium at the specified location and time. The first judgment and update step: Determine whether the error between the actual flow rate and the calculated flow rate meets the requirements; If the requirements are met, the corrected density of the fluid medium corresponding to each structured grid cell is taken as the effective density of the fluid medium corresponding to each structured grid cell, and the corrected viscosity of the fluid medium corresponding to each structured grid cell is taken as the effective viscosity of the fluid medium corresponding to each structured grid cell. If the requirements are not met, update at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight, and re-execute the corrected density determination step for each structured grid cell, the corrected viscosity determination step for each structured grid cell, the velocity calculation step of the fluid medium, and the first judgment update step until the error between the actual flow velocity and the calculated flow velocity meets the requirements. The simulation results are calculated as follows: based on the pipe temperature, pipe pressure, effective density and effective viscosity corresponding to each structured grid cell, the transient solution of the fluid field and particle motion tracking are performed to obtain the simulation results, which include information on particle retention risk.

[0006] Furthermore, the weight determination steps include: Select an initial weight set from multiple initial weight sets that matches the actual working conditions. Each initial weight set contains initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight. Obtain the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight from the selected set of initial weights.

[0007] Furthermore, update at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight, including: Update the weights corresponding to the labels of the selected initial weight set according to the specified step size, and adjust other weights accordingly to keep the sum of the current temperature weight, current pressure weight, current density weight and current viscosity weight unchanged.

[0008] Furthermore, the first density model includes a first density sub-model and a second density sub-model; the first density includes a first sub-density and a second sub-density. Inputting temperature, pressure, and medium density into the first density model yields the first density, which includes: Temperature and medium density are input into the first density sub-model to obtain the first sub-density; the first density sub-model is a temperature-based ideal gas model. Pressure and medium density are input into the second density sub-model to obtain the second sub-density; the second density sub-model is a pressure-based ideal gas model. The steps for determining the corrected density include: using the current temperature weight, the current pressure weight, and the current density weight as the weights for the first sub-density, the second sub-density, and the second density, respectively; and performing a weighted summation of the first sub-density, the second sub-density, and the second density based on their respective weights to obtain the corrected density of the fluid medium.

[0009] Furthermore, the method also includes: a second judgment and update step: judging whether the simulation results meet the requirements; If the requirements are not met, at least one purging parameter is updated based on the simulation results. The purging parameters include at least one of the following: purging temperature, purging pressure, purging duration, purging inlet position, and purging outlet position. If the updated purging parameter includes the purging duration, the simulation result calculation step and the second judgment update step are re-executed until the simulation results meet the requirements. If the updated purging parameter includes either purging pressure or purging temperature, the steps of obtaining the pipe temperature and pressure corresponding to the structured mesh element, determining the weights, determining the model density for each structured mesh element, determining the model viscosity, determining the corrected density, and determining the corrected viscosity are re-executed. The process involves several steps: determining the velocity of the fluid medium, calculating the velocity, making a first judgment and updating the results, calculating the simulation results, and making a second judgment and updating the results, until the simulation results meet the requirements. If the updated purging parameters include the purging inlet or outlet position, the following steps are repeated: parametric modeling, obtaining the pipe temperature and pressure corresponding to the structured mesh element, determining the model density for each structured mesh element, determining the model viscosity, correcting the density, correcting the viscosity, calculating the velocity of the fluid medium, making a first judgment and updating the results, calculating the simulation results, and making a second judgment and updating the results, until the simulation results meet the requirements.

[0010] Furthermore, updating at least one purging parameter based on the simulation results includes: prioritizing the updating of purging pressure and purging duration; if the simulation results still do not meet the requirements after updating the purging pressure and purging duration for a preset number of rounds, then updating the purging inlet position and / or purging outlet position.

[0011] Furthermore, the purging parameters include the purging inlet location, and the optional purging inlet locations include multiple purging inlet locations located upstream and downstream of the pipeline; Updating at least one purging parameter based on simulation results includes selecting a new purging inlet location in order from the purging inlet location located upstream of the pipeline to the purging inlet location located downstream of the pipeline.

[0012] Furthermore, the particle retention risk information includes the amount of particles retained and the location of particle retention. The method also includes selecting a cleaning location that can be manually cleaned based on the amount of particles retained and the location of particle retention.

[0013] Furthermore, the cleaning location is the valve or flange of the pipeline, and the purging inlet location is the valve or flange of the pipeline.

[0014] Furthermore, the method also includes determining energy consumption information based on the purging duration, and judging whether the simulation results meet the requirements, including judging whether the particle retention risk information meets the retention requirements and judging whether the energy consumption information meets the energy consumption requirements.

[0015] This application's embodiments establish a dynamic coupled calculation model by comprehensively integrating multi-dimensional parameters such as temperature, pressure, and media properties. It employs a weighted fusion method combining an ideal gas model with a constant density model and a temperature-dependent viscosity model with a constant viscosity model, along with a measured flow velocity feedback calibration mechanism. This overcomes the limitations of traditional methods that rely on a single parameter. Through parametric modeling and dynamic weight calibration, the technical solution can adapt to different media properties and varying environmental conditions, effectively addressing the technical pain point of poor versatility in traditional simulation calculation methods. It achieves accurate reconstruction of the flow field within complex pipelines, significantly improving the scientific rigor and reliability of pipeline purging simulation calculations. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for simulating and calculating the flow velocity during pipeline purging, as described in an embodiment of this application. Detailed Implementation

[0017] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0018] This application provides a method 100 for simulating and calculating the flow velocity during a pipeline purging process.

[0019] Pipeline purging is a critical procedure that must be performed before start-up, after maintenance, or after long-term shutdown of industrial plants. Its purpose is to remove all physical impurities (welding slag, iron filings, scale, sand, etc.) from the pipeline system using a high-speed flowing medium (air, steam, etc.), ensuring the cleanliness of the pipeline interior to prevent damage to equipment, valves, instruments, etc., thereby guaranteeing the safety, quality, and efficiency of subsequent production operations. During pipeline purging, a fluid medium is used to blow particles out of the pipeline; the fluid medium can be a gas and / or a liquid.

[0020] like Figure 1 As shown, method 100 includes: Step 10, Parametric Modeling Step: Parametrically model the pipeline to generate a pipeline model composed of several structured mesh units.

[0021] This step requires parametric modeling in the software to transform the actual, complex physical system into a standardized, parametric model that can be recognized and computed by the computer simulation software. Exemplary engineering software includes ANSYS Fluent, and when using ANSYS Fluent, ANSYS Fluent Meshing can be used as a mesh generation tool.

[0022] The parametric modeling process includes steps A and B.

[0023] Step A: Obtain the parameters required for modeling.

[0024] For example, the parameters required for modeling include pipe geometry parameters (which directly determine the flow field morphology), specifically: Diameter D: Pipe inner diameter, unit: meters (m). Obtained by querying the corresponding pipe label.

[0025] Roughness ε: Height of pipe wall irregularities, unit: micrometer (μm). Obtained from: material manual.

[0026] Number of elbows n: Number of 90° elbows. Obtained by counting from construction drawings.

[0027] Length L: Total pipe length, unit: meters (m). Acquisition method: Segmented measurement and accumulation.

[0028] Step B: Based on the input pipe geometry parameters, construct a 3D model of the pipe in the software that can be used for calculation. For example, Step B includes: Step B.1 Geometric simplification. The actual pipeline is broken down into standard components such as straight pipe sections, elbows, and valves, and minor accessories (such as supports) that do not affect the flow field calculation are eliminated.

[0029] Step B.2 Parameter Mapping. For example, straight pipe sections are directly input with length L and diameter D; elbows are equivalent to arcs with a radius of curvature R = 1.5D (D is the inner diameter of the pipe); valves are mapped to equivalent pipe sections according to their actual diameter and resistance coefficient (e.g., the resistance coefficient ζ = 0.1 for ball valves), thus realizing the transformation of non-standard structures into forms recognizable by the calculation model.

[0030] Step B.3 Mesh generation, i.e., generating structured mesh cells. For example, the mesh size for straight pipe sections is set to D / 10 (D is the pipe inner diameter), and the mesh for complex flow fields such as elbows and valves is refined to D / 20, while ensuring that the mesh quality meets the standards (twist rate < 0.8, orthogonality > 0.6), providing a high-precision mesh foundation for subsequent multiphysics coupling calculations.

[0031] In this way, subsequent calculations can be performed at the granularity of structured grid cells.

[0032] Step 11: Obtain the density and viscosity of the fluid medium. In this step, the density and viscosity can be the inherent density and viscosity of the fluid medium, which can be obtained if the type of fluid medium is known.

[0033] Step 12: Obtain the pipe temperature and pipe pressure corresponding to the structured mesh cell.

[0034] Ideally, sensors can be installed within each structured grid cell to collect the temperature and pressure within the pipe corresponding to that grid cell. Alternatively, sensors can be installed at key points to collect temperature and pressure, while the temperature and pressure within the remaining structured grid cells can be calculated using purging temperature, purging pressure, and ambient temperature and pressure. Alternatively, the temperature and pressure can be calculated entirely from purging temperature, purging pressure, and ambient temperature and pressure.

[0035] The temperature and pressure within the corresponding pipeline can be obtained in real time through sensors and then post-processed. For example, for the real-time acquired data, post-processing can be performed such as outlier filtering, sliding window mean filtering, removing data exceeding thresholds (e.g., for temperature data, removing temperature data with temperature jumps >10℃ / s), timestamp alignment (using the pressure acquisition time as a reference, and interpolating and aligning other parameters), and averaging the data over a time period, for use in subsequent calculations.

[0036] Step 13, Weight Determination Step: Obtain the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight, and use the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight as the current temperature weight, current pressure weight, current density weight, and current viscosity weight, respectively.

[0037] In subsequent steps, temperature weights, pressure weights, density weights, and viscosity weights will be used to determine the weights used when calculating the weighted sum of the first and second densities, as well as the weights used when calculating the weighted sum of the first and second viscosities. Appropriate initial temperature weights, initial pressure weights, initial density weights, and initial viscosity weights can serve as a good starting point, helping to more quickly obtain the weighted sums of the first and second densities, as well as the weighted sums of the first and second viscosities, that match the actual operating conditions.

[0038] The initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight can be random values, design default values, or values ​​set according to actual operating conditions. Actual operating conditions can be determined by ambient temperature, ambient pressure, and purging temperature and pressure. For example, under normal temperature and pressure conditions, the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight can be set to 0.25, 0.35, 0.2, and 0.2, respectively. When the pipeline is in a high-temperature condition significantly deviating from normal temperature, the high temperature causes gas expansion and increased flow velocity. Therefore, the effect of temperature must be prioritized. Based on the normal temperature and pressure conditions, the initial temperature weight can be increased, while other weights can be decreased (e.g., increasing the initial temperature weight by deta, and decreasing all other weights by 1 / 3 deta) to keep the sum of the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight constant. When the pipeline is under high pressure conditions that deviate significantly from normal pressure, the linear effect of pressure on flow velocity is more significant. Based on normal temperature and pressure conditions, the initial pressure weight can be increased while other weights can be decreased to keep the sum of the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight constant.

[0039] For example, step 13 may include: Step 131: Select an initial weight set from multiple initial weight sets that matches the actual working conditions; Step 132: Obtain the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight from the selected initial weight set.

[0040] For example, each initial weight set corresponds to a label and includes initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight. Examples include temperature deviation labels (initial temperature weight is larger compared to normal temperature and pressure conditions, other weights are smaller), pressure deviation labels (initial pressure weight is larger compared to normal temperature and pressure conditions, other weights are smaller), and temperature and pressure deviation labels (initial temperature weight and initial pressure weight are larger compared to normal temperature and pressure conditions, other weights are smaller). For example, temperature deviation labels can be further divided into high-temperature labels and low-temperature labels, and pressure deviation labels can be further divided into high-pressure labels, low-pressure labels, and pressure fluctuation labels (e.g., when the purging pressure is high, the pressure at the purging inlet is high, the pressure at the purging outlet is low, and the pressure fluctuation throughout the pipeline is large). An initial weight set whose labels match the actual operating conditions can be selected, and the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight within it can be used as the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight.

[0041] For each structured mesh cell, perform steps 14 through 17.

[0042] Step 14, Model density determination step: Input the pipe temperature, pipe pressure and medium density corresponding to the structured grid cell into the first density model to obtain the first density; the first density model is an ideal gas model; input the medium density into the second density model to obtain the second density; the second density model is a constant density model.

[0043] For example, the first density model is an ideal gas model that takes into account temperature and pressure.

[0044] Specifically, the first density model can be expressed as rho_ideal_gas = Rho nominal (pressure / P nominal ) (T nominal / temp). Among them, Rho nominal Where P is the density of the medium, pressure is the pressure, temp is the temperature, and P is the temperature. nominal For standard atmospheres, T nominal This is the standard reference temperature. rho_ideal_gas is the first density.

[0045] For example, the first density model includes a first density sub-model and a second density sub-model, wherein the first density sub-model is an ideal gas model that takes temperature into account, and the second density sub-model is an ideal gas model that takes temperature into account; the first density includes a first sub-density and a second sub-density.

[0046] Specifically, the first density sub-model can be represented as rho_T = Rho nominal (T nominal / temp); where Rho nominal T represents the density of the medium, and temp represents the temperature. nominal For the standard reference temperature, rho_T is the first sub-density. The second density sub-model can be expressed as rho_P = Rho nominal (pressure / P nominal ), Rho nominal P represents the density of the medium, and pressure represents the force applied. nominal The standard reference temperature is rho_P, and the second sub-density is rho_P.

[0047] For example, the second density model can be a constant model. Specifically, the second density model can be expressed as rho_constant = Rho nominal rho_constant represents the second density.

[0048] This allows us to obtain the first and second densities corresponding to the structured mesh element.

[0049] Step 15, Model viscosity determination step: Input the pipe temperature and medium viscosity corresponding to the structured mesh unit into the first viscosity model to obtain the first viscosity; the first viscosity model is a temperature-dependent viscosity model; input the medium viscosity into the second viscosity model to obtain the second viscosity; the second viscosity model is a constant viscosity model.

[0050] Specifically, the first viscosity model can be expressed as mu_temperature_dependent = Mu nominal exp(b (1.0 / temp - 1.0 / T nominal Among them, Mu nominal T represents the viscosity of the medium, and temp represents the temperature. nominal Where is the standard reference temperature, b is the medium characteristic constant, and mu_temperature_dependent is the first viscosity.

[0051] Specifically, the second viscosity model can be expressed as mu_constant = Mu nominal mu_constant represents the second viscosity.

[0052] Thus, the first and second viscosities corresponding to the structured grid cell can be obtained.

[0053] Step 16, Correction density determination step: Determine the weight corresponding to the first density and the weight corresponding to the second density based on at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight; Based on the weight corresponding to the first density and the weight corresponding to the second density, perform a weighted summation on the first density and the second density to obtain the corrected density of the fluid medium corresponding to the structured grid cell.

[0054] Understandably, in subsequent steps, the values ​​of the current temperature weight, current pressure weight, current density weight, and current viscosity weight can be updated, but the mapping relationship between the current temperature weight, current pressure weight, current density weight, and current viscosity weight and the weight corresponding to the first density remains unchanged; the mapping relationship between the current temperature weight, current pressure weight, current density weight, and current viscosity weight and the weight corresponding to the second density also remains unchanged. Furthermore, the sum of the weights corresponding to the first density and the weights corresponding to the second density is 1. The same applies to the step of determining the corrected viscosity, and will not be elaborated further.

[0055] For example, the corrected density of a fluid medium can be expressed as rho = (Weight_T + Weight_P) rho_ideal_gas + (Weight_Rho + Weight_Mu) `rho_constant`. Here, `Weight_T`, `Weight_P`, `Weight_Rho`, and `Weight_Mu` represent the current temperature weight, current pressure weight, current density weight, and current viscosity weight, respectively. `rho_ideal_gas` and `rho_constant` represent the first and second densities, respectively.

[0056] For example, when the first density model includes a first density sub-model and a second density sub-model, and the first density includes both a first sub-density and a second sub-density, the corrected density of the fluid medium can be expressed as rho = Weight_T rho_T +Weight_P rho_P + Weight_Rho rho_constant. Here, Weight_T, Weight_P, and Weight_Rho represent the current temperature weight, current pressure weight, current density weight, and current viscosity weight, respectively. rho_T, rho_P, and rho_constant represent the first sub-density, the second sub-density, and the second density, respectively.

[0057] Thus, for the density of the fluid medium, an ideal gas model coupled with temperature and pressure fluctuations is used to achieve dynamic correction, while a constant model ensures computational efficiency when the operating conditions are stable. The fusion of the two can better simulate the density of the fluid medium under real operating conditions.

[0058] In the pipeline purging process flow velocity simulation calculation method of this application embodiment, the high-precision model (ideal gas model) and the stable model (constant density model) designed for fluid density calculation each have a clear positioning and work synergistically: the core of the high-precision model (ideal gas model) is dynamic calculation that conforms to physical laws. By introducing real-time temperature temp and real-time pressure pressure, it strictly follows the ideal gas law of state (density is directly proportional to pressure and inversely proportional to temperature), and can accurately reflect the influence of operating conditions on density. For example, in high-pressure pipelines, density increases with pressure, and gas expansion leads to a decrease in density in high-temperature environments. Therefore, this model is suitable for complex operating conditions with significant temperature / pressure fluctuations (such as high-pressure pipelines in petrochemical industries, outdoor pipelines with low temperatures in winter or high temperatures in summer), and can prioritize ensuring the "accuracy" of density calculation; while the core of the stable model (constant density model) is a fixed value that simplifies calculation, directly using the calibration density Rho under standard operating conditions. nominalThe calculation process is simpler and the results are more stable, unaffected by real-time temperature / pressure changes. It avoids calculation deviations caused by parameter fluctuations and is suitable for simple working conditions with relatively stable temperature / pressure (such as short-distance air purging at normal temperature and pressure, and pipelines in constant-temperature workshops). It can effectively reduce computational resource consumption and improve simulation efficiency while ensuring sufficient accuracy. Crucially, the two models are not mutually exclusive but are dynamically allocated according to the actual working conditions through a weighted coupling mechanism designed in this application embodiment. This results in a more accurate density value that better reflects the actual working conditions, providing reliable data support for subsequent transient solutions of the fluid field and particle motion tracking.

[0059] Step 17, Corrected viscosity determination step: Determine the weight corresponding to the first viscosity and the weight corresponding to the second viscosity based on at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight; Based on the weight corresponding to the first viscosity and the weight corresponding to the second viscosity, perform a weighted summation on the first viscosity and the second viscosity to obtain the corrected viscosity of the fluid medium corresponding to the structured grid unit.

[0060] For example, the corrected viscosity of a fluid medium can be expressed as mu = Weight_T mu_temperature_dependent + (1.0 - Weight_T) mu_constant. Where Weight_T is the current temperature weight, and mu_temperature_dependent and mu_constant are the first viscosity and the second viscosity, respectively.

[0061] Understandably, the viscosity of a liquid medium is greatly affected by temperature. If Weight_T is larger, the result will be closer to the first viscosity; conversely, it will be closer to the second viscosity. Therefore, Weight_T can be increased when there are large temperature fluctuations, especially when the fluid medium is liquid.

[0062] For the viscosity of fluid media, a viscosity model with strong temperature dependence is coupled with temperature fluctuations to achieve dynamic correction, while a constant model is used to ensure computational efficiency when the operating conditions are stable. The combination of the two can better simulate the viscosity of fluid media under real operating conditions.

[0063] In the flow velocity simulation calculation method of the pipeline purging process in this application embodiment, a high-precision model (temperature-dependent model) and a stable model (constant viscosity model) designed for fluid viscosity calculation are accurately adapted based on the medium characteristics and the temperature change law of the operating conditions: the core of the high-precision model (temperature-dependent model) is to quantify the dynamic influence of temperature on viscosity and fit the physical relationship between viscosity and temperature through an exponential function. For liquid media, intermolecular forces weaken and viscosity decreases significantly with increasing temperature. For gaseous media, molecular motion intensifies and viscosity increases slightly with increasing temperature. Different media types can be adapted through calibration of the media characteristic constant *b*. Real-time temperature (*temp*) is introduced to achieve dynamic viscosity correction, making it suitable for temperature-sensitive conditions such as high-temperature steam purging, low-temperature hydraulic oil purging, and high-viscosity media purging. This ensures the physical accuracy of viscosity calculations and avoids deviations due to temperature changes. The stable model (constant viscosity model) simplifies calculations by using fixed values ​​directly, resulting in stable and fluctuation-free calculations. It is suitable for conditions with relatively constant temperatures, such as water purging in constant-temperature workshops and low-viscosity gas purging at room temperature. In these scenarios, the temperature effect on viscosity is negligible, prioritizing simulation stability and efficiency. Consistent with the coupling logic of the density model, the two viscosity models achieve synergy through temperature weighting. The contribution ratio of the two models is dynamically adjusted according to the temperature fluctuation range, ultimately obtaining actual viscosity values ​​that conform to the actual operating conditions. This provides accurate viscosity parameters for subsequent transient solutions of the fluid field and particle motion tracking.

[0064] Step 18, fluid medium velocity calculation steps: Perform transient solution of the fluid field based on the corrected density and corrected viscosity corresponding to each structured grid cell to obtain the calculated flow velocity of the fluid medium at a specified location and time; A flow meter is installed at the specified location to measure the actual flow velocity of the fluid medium at the specified location and time.

[0065] It is understandable that flow rate is the amount of fluid flowing through a specific cross-section per unit time, while flow velocity is the speed at which the fluid flows. Given the cross-sectional area of ​​the pipe, the flow velocity can be indirectly calculated by measuring the flow rate with a flow meter.

[0066] For example, the corrected density and corrected viscosity can be input into the transient solution model of the fluid field (combined with the mass conservation and momentum conservation equations to obtain the fluid medium velocity, and then k... The ε model quantifies turbulence effects, and the SIMPLE algorithm decouples pressure and velocity to correct the velocity of the fluid medium, ultimately yielding the calculated fluid medium velocity at a specified location and time. The specific process will be described later.

[0067] For example, the specified location can be the end of the pipe. For example, the specified time can be when the set purging duration is reached.

[0068] Understandably, there can be one or more specified locations.

[0069] Step 19, First judgment update step: Determine whether the error between the actual flow rate and the calculated flow rate meets the requirements; If the requirements are met, the corrected density of the fluid medium corresponding to each structured grid cell is taken as the effective density of the fluid medium corresponding to each structured grid cell, and the corrected viscosity of the fluid medium corresponding to each structured grid cell is taken as the effective viscosity of the fluid medium corresponding to each structured grid cell. If the requirements are not met, update at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight, and re-execute the corrected density determination step for each structured grid cell, the corrected viscosity determination step for each structured grid cell, the velocity calculation step for the fluid medium, and the first judgment update step until the error between the actual flow velocity and the calculated flow velocity meets the requirements.

[0070] For example, when the error is less than the set error threshold, the error can be considered to meet the requirements. This error threshold can be designed according to the purging cleanliness requirements. For pipelines with high purging cleanliness requirements, such as pipelines at the inlet of equipment like compressors, expanders, and cold boxes, the error threshold can be appropriately lowered; for pipelines with low cleanliness requirements, such as circulating cooling water, HVAC, and drainage pipelines, the error threshold can be appropriately raised.

[0071] Understandably, steps 18 and 19 verify the closeness between the simulation results and real-world conditions by checking the error between the simulated and actual velocities of the fluid medium. If the closeness is sufficient, the flow rate during the pipeline purging process is simulated; if it is insufficient, the current temperature weight, pressure weight, density weight, and viscosity weight are adjusted until the simulation results meet the requirements. This adjustment mechanism, combined with the multi-model fusion mechanism used in correcting density and viscosity calculations, ensures that simulation results close to real-world conditions are obtained.

[0072] For example, updating at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight can be an adaptive update.

[0073] For example, this step may include: randomly updating one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight according to a specified step size, and adjusting other unupdated weights accordingly to keep the sum of the current temperature weight, current pressure weight, current density weight, and current viscosity weight unchanged. As another example, this step may include: updating one or more of the current temperature weight, current pressure weight, current density weight, and current viscosity weight that are greater than the weights under normal temperature and pressure conditions according to a specified step size, and adjusting other unupdated weights accordingly to keep the sum of the current temperature weight, current pressure weight, current density weight, and current viscosity weight unchanged. As yet another example, this step may include: updating the weights corresponding to the labels of the selected initial weight set according to a specified step size, and adjusting other weights accordingly to keep the sum of the current temperature weight, current pressure weight, current density weight, and current viscosity weight unchanged. A specific example is that in step 131, the initial weight set is selected with the label of temperature deviation label and the weight corresponding to the label is the current temperature weight. The current temperature weight is 0.5. Then, the current temperature weight is increased by one step (0.05), the current temperature weight is 0.55, and the other 3 weights are decreased by 1 / 3 step accordingly.

[0074] For example, the step size can be set according to actual needs. For pipelines with high purging cleanliness requirements, the step size can be appropriately reduced, while for pipelines with low purging cleanliness requirements, the step size can be appropriately increased.

[0075] Step 20, Calculate simulation results: Based on the pipe temperature, pipe pressure, effective density and effective viscosity corresponding to each structured grid cell, perform transient solution of the fluid field and particle motion tracking to obtain simulation results, which include particle retention risk information.

[0076] For example, simulation results may include information on particle retention risk, as well as particle velocity, fluid medium flow rate, etc.

[0077] Normally, purging results can only be obtained by detecting the number of particles on the target plate set up at the purging outlet. Simulation results can reflect and predict the actual purging results to a certain extent, allowing operators to obtain more detailed (particle retention, particle velocity, and fluid medium flow rate for each structured grid cell) and more multi-dimensional purging results, and adjust purging parameters in a timely manner.

[0078] For example, in step 20, the pipe temperature, pipe pressure, effective density, effective viscosity, and purging time corresponding to each structured grid cell can be input into computational fluid dynamics software to obtain the fluid medium velocity and particle velocity of each structured grid cell. Alternatively, the temperature and pressure detected in step 12, along with ambient temperature, ambient pressure, purging temperature, purging pressure, purging time, and the effective density and effective viscosity corresponding to each structured grid cell, can be input into computational fluid dynamics software to obtain the fluid medium velocity and particle velocity of each structured grid cell.

[0079] Understandably, the parameters that need to be input into the software also include particle diameter, particle density, density of pipe wall material, and elastic modulus of pipe wall material.

[0080] Particle retention risk information includes the number of retained particles and their distribution location. If the particle velocity exceeds the critical retention velocity, there is a risk of particle retention.

[0081] Step 20 can be performed in computational fluid dynamics software, and a specific example is described below.

[0082] Step 20 includes steps 20A and 20B.

[0083] Step 20A: Perform a transient solution to the fluid field to calculate the fluid velocity. Step 20A includes: Step 20A.1: Determine the governing equations, which include the mass conservation equation and the momentum conservation equation.

[0084] The mass conservation equation is: The mass conservation equation states that the inflow / outflow mass is equal per unit time. Here, ρ is the fluid density, i.e., the effective density corresponding to the current structured mesh cell, t is time, and u is the velocity vector of the fluid medium. For Hamiltonian operators.

[0085] The momentum conservation equation is The momentum conservation equation states that fluid acceleration = pressure difference + viscous force + gravity, where P is the pressure inside the pipe corresponding to the current structured mesh cell, μ is the fluid viscosity (i.e., the effective viscosity corresponding to the current structured mesh cell), and g is the acceleration due to gravity. ² represents the Laplace operator.

[0086] Step 20A.2: Select a turbulence model and solution algorithm to correct the velocity of the fluid medium obtained in step 20A.1.

[0087] For turbulent flow inside a pipe (Reynolds number Re > 4000), k is used. The ε two-equation model quantifies the energy loss caused by eddies; the SIMPLE algorithm (semi-implicit pressure correlation equation solution method) is used to decouple the pressure and velocity coupling relationship, and the iterative convergence criterion is set as residual < 10. -5 .

[0088] Understandably, step 20A determines the velocity of the fluid medium in each structured grid cell throughout the entire purging time. Step 18 also uses the same calculation method. After determining the velocity of the fluid medium in each structured grid cell, step 18 requires further filtering of the fluid calculation velocity at a specified location and time. Furthermore, in step 18, the corrected density and corrected viscosity are substituted into the governing equations, not the effective density and effective viscosity. Understandably, the transient solution steps for the fluid field in steps 18 and 20 are similar. If the exact same parameters have already been used for the transient solution of the fluid field in step 18, the results of step 18 can be used in step 20 without repeating the solution.

[0089] Step 20B: Track particle movement to assess particle retention risk. Step 20B includes: Step 20B.1: Build a force model of the particles to calculate the forces acting on the particles in the fluid.

[0090] The aerodynamic drag experienced by the particle can be expressed as: 。 This is the drag coefficient; For fluid density; U is the frontal area of ​​the particle, i.e., the projected area of ​​the particle's surface facing the direction of fluid motion; u is the fluid velocity vector. p This is the particle velocity vector; The relative velocity between the fluid and the particles.

[0091] The gravitational force acting on the particle can be expressed as: .in Let be the mass of the particle, and g be the acceleration due to gravity. For spherical particles, It can be calculated based on the particle diameter and particle density.

[0092] When a particle collides with the pipe wall, the force exerted on the particle by the pipe wall can be expressed as: Where t1 is the collision time scale. For particle rebound speed, (where is the particle impact velocity).

[0093] The collision timescale in, Where is the particle radius, The longitudinal wave velocity in the pipe wall material can be obtained through... calculate; These are the particle density and the density of the pipe wall material, respectively. This is the elastic modulus of the pipe wall material.

[0094] Step 20B.2: Calculate the particle trajectory. Establish the particle motion equation based on Newton's second law. ∑F represents the net force acting on the particle, and the particle's velocity and position are iteratively updated using a time step Δt (typically 0.001-0.01 s). Specifically, the velocity update formula is as follows: ;u p (t) represents the particle velocity at time t, and the position update formula is: ;x p (t) represents the particle position at time t.

[0095] Understandably, once the particle velocity u at each position and time is known, the velocity vector v (x,y,z,t) of the particle as a function of position and time can be obtained.

[0096] Step 20B.3: Determine particle retention risk information.

[0097] Calculate the critical settlement velocity , where d p Given the particle diameter, compare the particle velocity u of the current structured mesh element with... , if u< If the number of particles with retention risk in a structured grid cell exceeds a certain value, then the grid cell is marked as a particle retention risk zone.

[0098] For example, simulation results can also be transformed into an intuitive visualization interface with tiered warnings to guide on-site operations. The visualization interface can take the form of: (1) Velocity distribution cloud map The surface of the 3D model of the pipeline is covered with different colors to correspond to different fluid medium flow velocities (e.g., red to blue corresponds to flow velocities from fast to slow), so as to quickly identify low-speed areas (blue areas) and high-speed areas (red areas); it supports cross-sectional views and contour maps of fluid medium flow velocities at any cross section.

[0099] (2) Particle retention thermogram When the particle velocity ν < the critical retention velocity v criticalAt that time, relevant areas are highlighted to quickly identify areas where particles are trapped. Based on particle tracking data and critical flow velocity calculations, a dynamic heat map is generated, using a red-yellow-blue gradient color coding: red represents high trapping risk (particle density > density threshold), yellow represents medium risk, and blue corresponds to low risk areas.

[0100] This allows for real-time marking of risk areas using visualized heat maps, combined with a tiered early warning mechanism, to guide on-site personnel in quickly locating and intervening in potential bottlenecks, optimizing purging process parameter settings, transforming passive response into proactive intervention, and enabling advance prediction of major safety hazards such as pipeline blockage and overpressure rupture, thereby reducing the incidence of construction accidents.

[0101] This application's embodiments establish a dynamic coupled calculation model by comprehensively integrating multi-dimensional parameters such as temperature, pressure, and media properties. It employs a weighted fusion method combining an ideal gas model with a constant density model and a temperature-dependent viscosity model with a constant viscosity model, along with a measured flow velocity feedback calibration mechanism. This overcomes the limitations of traditional methods that rely on a single parameter. Through parametric modeling and dynamic weight calibration, the technical solution can adapt to different media properties and varying environmental conditions, effectively addressing the technical pain point of poor versatility in traditional simulation calculation methods. It achieves accurate reconstruction of the flow field within complex pipelines, significantly improving the scientific rigor and reliability of pipeline purging simulation calculations.

[0102] In some examples, method 100 also includes: Step 21, Second judgment and update step: Determine whether the simulation results meet the requirements.

[0103] If the requirements are not met, at least one purging parameter is updated based on the simulation results. The purging parameters include at least one of the following: purging pressure, purging duration, and purging inlet location. If the updated purging parameter includes the purging duration, the simulation result calculation step and the second judgment update step are re-executed until the simulation results meet the requirements. If the updated purging parameter includes purging pressure or purging temperature, the steps of obtaining the pipe temperature and pressure corresponding to the structured mesh element, determining the weights, determining the model density for each structured mesh element, determining the model viscosity, determining the corrected density, determining the corrected viscosity, and determining the fluid... The process involves the following steps: calculating the velocity of the medium, making a first judgment and updating the results, calculating the simulation results, and making a second judgment and updating the results, until the simulation results meet the requirements. If the updated purging parameters include the purging inlet or purging outlet position, then the following steps are repeated: parametric modeling, obtaining the pipe temperature and pressure corresponding to the structured mesh element, determining the model density for each structured mesh element, determining the model viscosity, correcting the density, correcting the viscosity, calculating the velocity of the fluid medium, making a first judgment and updating the results, calculating the simulation results, and making a second judgment and updating the results, until the simulation results meet the requirements.

[0104] Simulation results can include the number and distribution of retained particles. The number of retained particles is primarily used to determine if the simulation results meet the requirements. Both the number and distribution of retained particles can be used to assess how to adjust subsequent purging parameters. The distribution of retained particles can also be used to assess whether manual cleaning is feasible. Simulation results that do not meet the requirements include an excessive number of retained particles. Simulation results that meet the requirements include a retained particle number below a threshold and purging energy consumption meeting the energy consumption requirements.

[0105] Purging parameters may include at least one of the following: purging temperature, purging pressure, purging duration, purging inlet position, and purging outlet position. Purging temperature is, for example, the temperature to which the fluid medium is adjusted before entering the pipeline; purging pressure is, for example, the pressure of the buffer tank containing the fluid medium; purging duration is the duration of the purging process; and purging inlet and outlet positions are, for example, the positions where the fluid medium enters and exits the pipeline.

[0106] Based on the simulation results, at least one purging parameter can be updated. For example, if the number of retained particles is too high, the purging pressure and / or purging duration can be increased. If increasing the purging pressure and purging duration still does not meet the requirements for the number of retained particles, the purging inlet position and / or purging outlet position can be changed.

[0107] It should be noted that if the number of retained particles is excessive, and the number of retained particles still does not meet the standard after adjusting the purging parameters, but the retained particles are located near a cleaning location where manual cleaning can be performed, then the current purging scheme can be considered a suboptimal acceptable scheme that requires an additional manual cleaning step. Generally, purging time is a secondary consideration. If the energy consumption corresponding to the purging time is slightly higher when the number of retained particles meets the requirements, then the current purging scheme can be considered a suboptimal acceptable scheme with slightly higher energy consumption.

[0108] After updating one or more parameters, certain steps need to be re-executed to obtain simulation results under the new purging parameters.

[0109] For example, in case 1: if the updated purging parameters include the purging duration, the steps that need to be repeated include: the step of calculating the simulation results and the second step of judging and updating, until the simulation results meet the requirements.

[0110] If the updated purging parameter is only the purging duration, then there is no need to perform steps such as parametric modeling.

[0111] Scenario 2: If the updated purging parameters include purging pressure or purging temperature, the steps to be re-executed include: obtaining the pipe temperature and pipe pressure corresponding to the structured mesh element, determining the weight, determining the model density for each structured mesh element, determining the model viscosity, determining the corrected density, determining the corrected viscosity, calculating the velocity of the fluid medium, a first judgment update step, calculating the simulation results, and a second judgment update step, until the simulation results meet the requirements.

[0112] The purging pressure or purging temperature will affect the temperature and pressure inside the pipeline. If the purging pressure or purging temperature is updated, it is necessary to re-acquire the pipeline temperature and pressure corresponding to the structured mesh cell.

[0113] Scenario 3: If the updated purging parameters include the purging inlet position or the purging outlet position, the steps to be re-executed include: parametric modeling step, obtaining the pipe temperature and pipe pressure corresponding to the structured mesh cell, determining the model density for each structured mesh cell, determining the model viscosity, determining the corrected density, determining the corrected viscosity, calculating the velocity of the fluid medium, first judgment update step, calculating the simulation results, and second judgment update step, until the simulation results meet the requirements.

[0114] The location of the purge inlet or outlet will affect the pipeline structure. If the purge pressure or purge temperature is updated, parametric modeling needs to be redone.

[0115] It should be noted that if the updated purging parameters include both the purging parameters listed in Case 1 and the purging parameters listed in Case 2, then the steps that need to be re-executed include the union of the steps listed in Case 1 and Case 2.

[0116] Understandably, when updating the purging parameters and repeating the required steps in step 21, it can be either a completely new purging process, in which case the initial state of the fluid medium and particles is a completely new initial state; or it can be a continuation of the purging process based on the results of the previous purging, in which case the initial state of the fluid medium and particles is the state at the end of the previous purging. A flag can be set to select whether to perform a completely new purging or continue purging. For example, if particles accumulate at point A after the first purging, the purging inlet and outlet can be changed in the second purging to continue purging the particles accumulated at point A.

[0117] In this way, purging parameters can be adjusted and purging schemes optimized based on simulation results, and verified through digital twin pre-simulation, forming a closed loop of "monitoring-calculation-optimization-execution", eliminating the blindness of manual experience-based adjustments, and reducing ineffective energy consumption and time costs while ensuring cleanliness.

[0118] In some embodiments, updating at least one purging parameter in step 21 includes: prioritizing the updating of purging pressure and purging duration; if the simulation results still do not meet the requirements after updating the purging pressure and purging duration for a preset number of rounds, then updating the purging inlet position and / or purging outlet position.

[0119] The adjustment of purging parameters has a priority. Some purging parameters are more effective and have low adjustment costs (e.g., simple to adjust, or low cost of recalculation after adjustment), and these can be adjusted first. When adjusting, start with the purging parameters with higher priority. If that doesn't work, then adjust the purging parameters with lower priority. In this way, you can achieve the required simulation results at the lowest cost.

[0120] In practice, adjusting the purge inlet and outlet positions is quite complex. It requires adjusting the state of flanges and valves to block the previous purge inlet or outlet and open the new one. After changing the purge inlet and outlet positions, the parametric modeling process needs to be repeated. Therefore, when updating purge parameters, purge pressure and purge duration should be updated first.

[0121] The purging temperature, purging pressure, and purging duration can have selectable ranges. For example, the purging temperature range can be [15 degrees Celsius to 60 degrees Celsius], and the purging duration range can be [10 min to 50 min]. These ranges can be adjusted gradually according to the set step size. The purging inlet and outlet positions can include several selectable locations.

[0122] In some embodiments, the purging parameters include the purging inlet location, and the optional purging inlet locations include multiple purging inlet locations located upstream and downstream of the pipeline; The update of at least one purging parameter in step 21 includes selecting a new purging inlet location in order from the purging inlet location located upstream of the pipeline to the purging inlet location located downstream of the pipeline.

[0123] Understandably, if the fluid medium enters the pipeline from the purge inlet located upstream, the area of ​​the pipeline that the fluid medium can purge is larger. If the fluid medium enters the pipeline from the purge inlet located downstream, the fluid medium can only purge the section of the pipeline downstream of that purge inlet location. Therefore, when adjusting the purge inlet location, the purge inlet location located upstream of the pipeline should be selected first.

[0124] Understandably, if the purge inlet position is reselected, the purge nozzle position can be adjusted accordingly to create a more efficient and unobstructed purge path.

[0125] In some embodiments, the particle retention risk information includes the amount of particles retained and the location of particle retention. Method 100 further includes: step 22, selecting a cleaning location that can be manually cleaned based on the amount of particles retained and the location of particle retention.

[0126] Understandably, pipelines have designated cleaning locations for manual removal. If adjusting purging parameters still doesn't meet the target number of retained particles, but the retained particles are located near these manually cleanable locations, then the current purging scheme can be considered a suboptimal acceptable solution requiring additional manual cleaning. For example, if after multiple adjustments to purging pressure and duration the number of retained particles still exceeds the threshold, and the only location where particles are retained is in structured grid cell A, which is a manually cleanable location, then the current purging scheme can be considered a suboptimal acceptable solution requiring additional manual cleaning.

[0127] Understandably, the cleaning location, purging inlet location, or purging outlet location can be set at the valve or flange of the pipeline, since the valve or flange is easy to disassemble.

[0128] It should be noted that the step numbers involved in the above embodiments of the present invention are set only for the convenience of description and do not restrict the execution order of each step. Without departing from the core concept and logical principle of the present invention, those skilled in the art can make adaptive adjustments to the execution order of each step according to the actual working conditions. Such adjustments should be considered as included within the protection scope of the present invention.

[0129] Furthermore, unless there are clear technical contradictions or functional conflicts in different embodiments of the present invention, the technical features, parameter settings, operating logic, and implementation methods disclosed in each embodiment can be combined with each other; any new technical solution formed by the above combination, if it can achieve the inventive purpose of the present invention and does not exceed the technical concept scope of the present invention, should be considered as the content protected by the present invention.

[0130] Principles and steps not explicitly described in this invention are all obtainable by those skilled in the art through conventional technical means, and therefore will not be elaborated upon. Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for simulating and calculating the flow velocity during a pipeline purging process, characterized in that, During the pipeline purging process, a fluid medium is used to blow particles out of the pipeline. The method includes: Parametric modeling steps: Parametric modeling of the pipeline to generate a pipeline model composed of several structured mesh units; Obtain the density and viscosity of the fluid medium; Obtain the pipe temperature and pipe pressure corresponding to the structured grid cell; Weight determination steps: Obtain the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight, and use the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight as the current temperature weight, current pressure weight, current density weight, and current viscosity weight, respectively; For each of the structured mesh cells, Model density determination steps: Input the pipe temperature, pipe pressure, and medium density corresponding to the structured mesh cell into the first density model to obtain the first density; the first density model is an ideal gas model; input the medium density into the second density model to obtain the second density; the second density model is a constant density model; Model viscosity determination steps: Input the pipe internal temperature corresponding to the structured mesh unit and the viscosity of the medium into the first viscosity model to obtain the first viscosity; the first viscosity model is a temperature-dependent viscosity model; input the viscosity of the medium into the second viscosity model to obtain the second viscosity; the second viscosity model is a constant viscosity model; Corrected density determination steps: Determine the weight corresponding to the first density and the weight corresponding to the second density based on at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight; Based on the weight corresponding to the first density and the weight corresponding to the second density, perform a weighted summation on the first density and the second density to obtain the corrected density of the fluid medium corresponding to the structured grid cell. Corrected viscosity determination steps: Determine the weight corresponding to the first viscosity and the weight corresponding to the second viscosity based on at least one of the current temperature weight, current pressure weight, current density weight, and current viscosity weight; Based on the weight corresponding to the first viscosity and the weight corresponding to the second viscosity, perform a weighted summation on the first viscosity and the second viscosity to obtain the corrected viscosity of the fluid medium corresponding to the structured grid unit; The velocity calculation steps for the fluid medium are as follows: A transient solution for the fluid field is performed based on the corrected density and corrected viscosity corresponding to each structured grid cell to obtain the calculated flow velocity of the fluid medium at a specified location and time. A flow meter is installed at the specified location to measure the actual flow velocity of the fluid medium at the specified location at the specified time. First judgment and update step: Determine whether the error between the actual flow rate and the calculated flow rate meets the requirements; The steps for calculating simulation results are as follows: Based on the pipe temperature, pipe pressure, effective density, and effective viscosity corresponding to each structured grid cell, the transient solution of the fluid field and particle motion tracking are performed to obtain the simulation results, which include particle retention risk information.

2. The method according to claim 1, wherein, The weight determination step includes: From multiple initial weight sets, select one initial weight set that matches the actual working conditions. Each initial weight set includes an initial temperature weight, an initial pressure weight, an initial density weight, and an initial viscosity weight. Obtain the initial temperature weight, initial pressure weight, initial density weight, and initial viscosity weight from the selected set of initial weights.

3. The method according to claim 2, wherein, Updating at least one of the current temperature weight, the current pressure weight, the current density weight, and the current viscosity weight includes: Update the weights corresponding to the labels of the selected initial weight set according to the specified step size, and adjust other weights accordingly to keep the sum of the current temperature weight, the current pressure weight, the current density weight, and the current viscosity weight unchanged.

4. The method according to claim 1, wherein, The first density model includes a first density sub-model and a second density sub-model; the first density includes a first sub-density and a second sub-density. Inputting the temperature, pressure, and medium density into a first density model yields a first density, including: The temperature and the medium density are input into a first density sub-model to obtain a first sub-density; the first density sub-model is a temperature-based ideal gas model. The pressure and the medium density are input into a second density sub-model to obtain a second sub-density; the second density sub-model is a pressure-based ideal gas model. The corrected density determination step includes: using the current temperature weight, the current pressure weight, and the current density weight as weights for the first sub-density, the second sub-density, and the second density, respectively; and performing a weighted summation of the first sub-density, the second sub-density, and the second density based on their respective weights to obtain the corrected density of the fluid medium.

5. The method according to claim 1, wherein, The method further includes a second judgment and update step: judging whether the simulation results meet the requirements; If the requirements are not met, at least one purging parameter is updated based on the simulation results. The purging parameters include at least one of the following: purging temperature, purging pressure, purging duration, purging inlet position, and purging outlet position. If the updated purging parameter includes the purging duration, the step of calculating the simulation results and the second judgment and update step are re-executed until the simulation results meet the requirements. If the updated purging parameter includes either purging pressure or purging temperature, the steps of obtaining the pipe temperature and pressure corresponding to the structured mesh unit, determining the weights, determining the model density for each structured mesh unit, determining the model viscosity, determining the corrected density, determining the corrected viscosity, and so on are re-executed. The process involves the following steps: calculating the velocity of the fluid medium, the first judgment and update step, calculating the simulation results, and the second judgment and update step, until the simulation results meet the requirements. If the updated purging parameters include the purging inlet position or the purging outlet position, then the following steps are repeated: parametric modeling, obtaining the pipe temperature and pipe pressure corresponding to the structured mesh unit, determining the model density for each structured mesh unit, determining the model viscosity, determining the corrected density, determining the corrected viscosity, calculating the velocity of the fluid medium, the first judgment and update step, calculating the simulation results, and the second judgment and update step, until the simulation results meet the requirements.

6. The method according to claim 5, wherein, The step of updating at least one purging parameter based on the simulation results includes: prioritizing the updating of purging pressure and purging duration; if the simulation results still do not meet the requirements after updating the purging pressure and purging duration for a preset number of rounds, then updating the purging inlet position and / or purging outlet position.

7. The method according to claim 5, wherein, The purging parameters include the purging inlet location, which includes multiple purging inlet locations located upstream and downstream of the pipeline; The step of updating at least one purging parameter based on the simulation results includes: selecting a new purging inlet position in order from the purging inlet position located upstream of the pipeline to the purging inlet position located downstream of the pipeline.

8. The method according to claim 5, wherein, The particle retention risk information includes the amount of particles retained and the location of the particles retained. The method further includes selecting a cleaning location that can be manually cleaned based on the amount of particles retained and the location of the particles retained.

9. The method according to claim 8, wherein, The cleaning location is the valve or flange of the pipeline, and the purging inlet location is the valve or flange of the pipeline.

10. The method according to claim 5, wherein, The method further includes: determining energy consumption information based on the purging duration; determining whether the simulation results meet the requirements includes: determining whether the particle retention risk information meets the retention requirements, and determining whether the energy consumption information meets the energy consumption requirements.

11. The method according to claim 1, wherein, The first determination and update step includes: If the requirements are met, the corrected density of the fluid medium corresponding to each structured grid cell is taken as the effective density of the fluid medium corresponding to each structured grid cell, and the corrected viscosity of the fluid medium corresponding to each structured grid cell is taken as the effective viscosity of the fluid medium corresponding to each structured grid cell. If the requirements are not met, then update at least one of the current temperature weight, the current pressure weight, the current density weight, and the current viscosity weight, and re-execute the corrected density determination step, the corrected viscosity determination step, the fluid medium velocity calculation step, and the first judgment update step for each structured grid cell, until the error between the actual flow velocity and the calculated flow velocity meets the requirements.

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