Method for determining installation position of binary mixed gas medium ultrasonic flowmeter

Abstract

This invention discloses a method for determining the installation location of an ultrasonic flow meter for binary mixed gas media, belonging to the field of multi-component fluid metering and detection technology. The method sequentially implements the following steps: parameter acquisition and setting, modeling and mesh generation, operating condition setting, data simulation and processing, parameter fitting and calculation, and result verification and optimization. A three-dimensional geometric model of the multi-component gas confluence pipeline is constructed, and mesh generation and independence verification are completed. The ideal mixing law is used to calculate the physical properties of the mixed gas. Steady-state and transient simulations are completed using a k-ε turbulence model combined with component transport equations. The evolution law of the sound velocity variation coefficient is obtained by extracting cross-sectional parameters. Characteristic parameters are determined by fitting with an exponential decay model, and the theoretical critical installation distance is calculated. After adding a safety margin for dynamic operating conditions, flow field verification is completed, and the optimal installation distance is output. This invention is adaptable to various binary mixed gases and dynamic operating conditions, effectively improving metering accuracy and the scientific and versatile nature of the installation method.

Description

Technical Field

[0001] This invention relates to the field of multi-component fluid metering and testing, specifically to a method for determining the installation location of an ultrasonic flow meter for binary mixed gas media. Background Technology

[0002] In petroleum refining, natural gas processing, and industrial flare gas emission systems, ultrasonic flow meters are widely used for measuring the flow of binary gas mixtures such as hydrogen-hydrocarbons and hydrogen-acid gases due to their advantages of no pressure loss, fast response, and wide measurement range. The metering accuracy of ultrasonic flow meters is highly dependent on the uniformity of the upstream flow field, and its installation location and straight pipe section length are the core parameters for ensuring metering reliability.

[0003] Currently, the industry widely adopts GB / T18604-2023 "Measurement of Natural Gas Flow Rate Using Ultrasonic Gas Flow Meters" as the installation guideline for ultrasonic flow meters. This standard, based on steady-state operating conditions and the flow field characteristics of a single natural gas component, provides minimum straight pipe length requirements for different flow obstructions in a fixed tabular format, forming a standardized installation specification system. Simultaneously, flow field simulation technology based on computational fluid dynamics (CFD) is gradually being applied to installation location optimization. By constructing pipe geometric models and using turbulence models and component transport equations to simulate the gas mixing process, the flow field velocity distribution characteristics are analyzed, providing numerical references for determining installation distances.

[0004] However, the aforementioned existing technologies have significant limitations in industrial multi-component gas mixture metering scenarios: the national standard, based on steady-state conditions and single-component assumptions, stipulates fixed straight pipe lengths that cannot adapt to dynamic conditions such as sudden flow increases and pressure fluctuations. When the system experiences significant flow disturbances, the stability of the flow field is difficult to guarantee, directly leading to a significant deviation of metering accuracy from the design value; existing CFD simulation optimization methods are mostly limited to steady-state flow field analysis, lacking research on the dynamic response and mixing recovery characteristics of transient disturbance processes, and cannot accurately predict the flow field evolution of mixed gases after sudden flow changes; existing installation and positioning methods do not establish a quantitative correlation between flow field uniformity and metering accuracy, relying solely on empirical values ​​to determine the installation distance, which cannot achieve precise positioning for typical binary mixtures such as hydrogen-propane and hydrogen-sulfide; existing technologies do not consider the impact of differences in mixed gas components on sound velocity distribution and mixing uniformity rate, resulting in poor versatility and difficulty in meeting the high-precision metering requirements under complex and variable industrial conditions.

[0005] Therefore, in order to solve the problems existing in the prior art, the present invention proposes a method for determining the installation position of an ultrasonic flow meter for binary mixed gas media. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a method for determining the installation location of an ultrasonic flow meter for binary mixed gas media.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium includes: The parameter acquisition and setting steps involve acquiring the geometric parameters of the multi-component gas manifold, the components and proportion range of the mixed gas, and the geometric parameters of the multi-component gas manifold, including the pipe diameter, pipe length and pipe structure. The monitoring section position is determined based on the pipe diameter, and the operating condition parameters are set. The modeling and meshing steps involve constructing a three-dimensional geometric model of the multi-component gas confluence pipe based on its geometric parameters, dividing the three-dimensional geometric model of the multi-component gas confluence pipe into a hexahedral mesh, refining the mesh in the gas confluence region, and determining the number of meshes through mesh independence verification. The operating condition setting steps include unifying the operating pressure and temperature, calculating the physical property parameters of the mixed gas based on the components and proportion range of the mixed gas, including density, viscosity, sound velocity, molar mass, specific heat capacity and thermal conductivity, and configuring steady-state and transient operating conditions based on the physical property parameters. The data simulation and processing steps include performing steady-state and transient simulations, obtaining pipeline cross-sectional parameters based on the simulation results, including hydrogen mole fraction distribution, sound velocity spatial distribution, and time series data for each cross-section of the pipeline, and calculating the evolution law of the sound velocity variation coefficient along the pipeline axis based on the pipeline cross-sectional parameters. The parameter fitting and calculation steps are as follows: determine the initial position sound velocity variation coefficient and the background variation coefficient at infinity; obtain the attenuation constant through fitting; and calculate the theoretical critical installation distance according to the sound velocity variation coefficient calculation accuracy criterion. The result verification and optimization steps involve adding a safety margin to the dynamic operating conditions to obtain the optimal installation distance, and verifying whether the optimal installation distance meets the conditions. If the conditions are met, the optimal installation distance is output.

[0008] As a further improvement of the present invention, the three-dimensional geometric model of the multi-component gas manifold includes two mutually perpendicular first inlet pipes and second inlet pipes, and an outlet pipe horizontally connected to the first inlet pipes, wherein the length of the outlet pipe is set to 150 times the pipe diameter.

[0009] As a further improvement of the present invention, the physical property parameters are calculated by the ideal mixing law. The density, viscosity, sound velocity, molar mass, specific heat capacity and thermal conductivity of the mixed gas are obtained by weighted calculation based on the known physical property parameters of each pure component in the mixed gas and the proportion of each component in the mixed system.

[0010] As a further improvement of the present invention, the operating condition setting step includes setting at least two binary mixed gas systems including hydrogen, configuring steady-state operating conditions with constant rated flow rates respectively, and preset transient operating conditions with sudden changes in flow rate amplitude based on the steady-state conditions, wherein the other component in the mixed gas system is a hydrocarbon or an acidic corrosive gas.

[0011] As a further improvement of the present invention, the data simulation and processing steps include: performing steady-state simulation and transient simulation; selecting all grid nodes covered by each monitoring section by locating preset axial monitoring sections; extracting hydrogen concentration data of all grid nodes in each monitoring section; obtaining the hydrogen mole fraction distribution of each section through statistical processing; extracting the sound velocity values ​​of all grid nodes in each monitoring section; obtaining the sound velocity spatial distribution of each section through statistical analysis; when performing transient simulation, extracting the sound velocity and hydrogen mole fraction related time series data of each monitoring section at different time nodes to generate the sound velocity spatial distribution; obtaining the sound velocity variation coefficient of each section by statistically analyzing the sound velocity standard deviation and sound velocity mean value of each section based on the sound velocity spatial distribution of each section; and obtaining the evolution dataset of the sound velocity variation coefficient along the pipeline axis based on the sound velocity variation coefficient of each section.

[0012] As a further improvement of the present invention, the evolution dataset of the sound velocity variation coefficient is fitted nonlinearly using an exponential decay model to determine the sound velocity variation coefficient at the initial position, the background sound velocity variation coefficient at infinity in the pipeline, and the attenuation constant of the axial attenuation characteristic of the sound velocity variation coefficient. Based on the criterion that the sound velocity variation coefficient does not exceed a preset measurement accuracy threshold, the theoretical critical installation distance is derived and calculated using the exponential decay model.

[0013] As a further improvement of the present invention, the data simulation and processing steps include simulating the turbulent flow state of the mixed gas in the pipeline using a realizable k-ε turbulence model, tracking the concentration transfer and distribution law of each gas component in combination with the component transport equation, completing steady-state simulation and transient simulation, and obtaining the flow field and component distribution data of the entire pipeline.

[0014] The beneficial effects of this invention are as follows: This invention establishes the correlation between flow field uniformity and metering accuracy through the coefficient of variation of sound velocity, and determines the installation position of the ultrasonic flowmeter according to a preset accuracy criterion, thus ensuring the accuracy and operational stability of binary mixed gas flow measurement. It adds a safety margin for dynamic operating conditions, adapting to industrial scenarios with fluctuating flow rates, overcoming the limitation of traditional installation methods that are only applicable to steady-state conditions. It quantitatively determines the installation distance using numerical simulation combined with model fitting, replacing traditional empirical methods with scientific calculations, and improving the scientific rigor and reliability of the installation position determination method with grid optimization and turbulence model simulation. Furthermore, this application is adaptable to various binary mixed gas systems such as hydrogen and hydrocarbons, and hydrogen and acidic corrosive gases, matching the metering needs of multiple scenarios such as petroleum refining and multi-component gas processing, thus broadening the applicability of the method. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to the present invention.

[0016] Figure 2 This is a schematic diagram simulating the coefficient of variation of sound velocity under stable operating conditions of the hydrogen-propane mixed gas according to the present invention.

[0017] Figure 3 This is a schematic diagram simulating the coefficient of variation of sound velocity under dynamic operating conditions of a hydrogen-propane mixed gas according to the present invention.

[0018] Figure 4 This is a schematic diagram simulating the coefficient of variation of sound velocity under stable operating conditions of the hydrogen-hydrogen sulfide mixed gas according to the present invention.

[0019] Figure 5 This is a schematic diagram simulating the coefficient of variation of sound velocity under dynamic operating conditions of a hydrogen-hydrogen sulfide mixed gas according to the present invention. Detailed Implementation

[0020] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Identical components are denoted by the same reference numerals. It should be noted that the terms "front," "rear," "left," "right," "upper," and "lower" used in the following description refer to directions in the accompanying drawings, and the terms "bottom surface," "top surface," "inner," and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.

[0021] The first embodiment of the present invention takes flare gas and a T-type manifold as an example, such as... Figures 1 to 5 As shown, a method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium is proposed, including: The parameter acquisition and setting steps are used to obtain all the basic data required for the simulation calculation. The geometric parameters of the multi-component gas manifold are parameters characterizing the physical shape and structural dimensions of the manifold, including pipe diameter, pipe length, and pipe structure. The pipe diameter serves as a dimensionless reference for determining the monitoring section location, the pipe length defines the pipeline range covered by the simulation calculation, and the pipe structure clarifies the connection form and spatial layout of the manifold. The mixed gas components and proportion range refer to the individual gas types constituting the binary mixed gas and the content range of each individual gas in the mixed system. This data provides the basis for subsequent physical property parameter calculations and operating condition configuration. The monitoring section location is the cross-sectional location of the pipeline along the pipeline axis used to extract flow field-related data; this location is determined based on the pipe diameter. Operating condition parameters include parameters such as flow rate, pressure, and temperature in industrial operation. Setting these parameters can unify the boundary conditions of the simulation calculation, making the simulation results closely match the actual operating state of the multi-component gas system.

[0022] The modeling and meshing steps are used to construct the digital carrier and discretized computing units for simulation calculations. A three-dimensional geometric model of the multi-component gas confluence pipe, built based on its geometric parameters, can completely reproduce the actual flow space of the multi-component gas confluence. Hexahedral meshes are used to decompose the three-dimensional geometric model of the multi-component gas confluence pipe into multiple regular computing units. This type of mesh can balance the accuracy and computational efficiency of flow field calculations. The gas confluence region is the area where two gases come into contact and mix. The flow field parameters in this region vary significantly. Mesh refinement in this region improves the accuracy of flow field parameter calculations. Mesh independence verification involves conducting multiple sets of comparative calculations by adjusting the number of meshes to select a mesh size that maintains stable calculation results. This determines the final number of meshes to be used, avoiding interference from differences in mesh size in the simulation results.

[0023] The specific criterion for verifying grid independence is as follows: steady-state simulations are performed using three sets of grids with approximately 600,000, 1.16 million, and 2 million grids respectively. The coefficient of variation (CV) of the sound velocity at the downstream 80D section of the outlet pipe is calculated. When the relative change in CV values ​​between two adjacent sets of grids is less than 1%, the number of grids is considered to meet the computational accuracy requirements. In this embodiment, the CV value is 0.032 when the number of grids is approximately 600,000, and 0.018 when the number of grids is 1.16 million, with a relative change of 43.8% (not converged). The CV values ​​corresponding to the number of grids of 1.16 million and 2 million are 0.018 and 0.0177 respectively, with a relative change of 1.67%, close to but slightly higher than 1%. Considering both computational resources and accuracy, a grid of 1.16 million is ultimately selected. Simultaneously, the grid is locally refined within the gas confluence region. The grid size in the refined region is 1 / 20 of the pipe diameter, and the height of the first layer of the boundary layer is set to satisfy y+≈30~100 to adapt to the application requirements of the standard wall function.

[0024] Specifically, such as Figures 1 to 5 As shown, the three-dimensional geometric model of the multi-component gas manifold is constructed based on the actual structure of the multi-component gas manifold to fully reproduce the spatial morphology of the pipeline where two media converge and mix. The first and second inlet pipes serve as the flow channels for the media entering the pipeline. The two pipes are arranged perpendicularly to each other, which can reproduce the structural characteristics of the perpendicular convergence of the two media in the multi-component gas manifold. The outlet pipe is responsible for transporting the mixed media. This pipe is horizontally connected to the first inlet pipe, which allows the mixed media to flow stably along the pipeline axis. The length of the outlet pipe is set to 150 times the pipe diameter. This length setting provides sufficient flow and mixing space for the mixed gas, ensuring that the media completes sufficient flow development within the pipeline and meeting the spatial conditions for flow field simulation and cross-sectional data extraction.

[0025] The operating condition setup steps are used to standardize the operational boundary conditions for simulation calculations, eliminating the impact of environmental parameter variations on fluid simulation results. Operating pressure and temperature are fundamental environmental parameters for simulation calculations; standardizing these parameters ensures consistency and comparability of simulation results under different media compositions and operating conditions. Mixed gas physical properties are used to characterize the fundamental physical and thermal properties of the fluid. Density reflects the mass distribution characteristics of the mixed gas; viscosity characterizes the internal frictional characteristics during gas flow; sound velocity is a core correlation parameter linking mixing homogeneity and ultrasonic metering; molar mass distinguishes the fundamental material properties of different gas components; and specific heat capacity and thermal conductivity reflect the heat transfer and energy exchange characteristics of the mixed gas. Based on these physical properties, steady-state and transient operating conditions can be configured separately, providing complete conditional support for subsequent flow field simulations.

[0026] Four typical operating conditions were set up to simulate the actual flare gas system: Operating condition 1: H2-C3H6 (75%:25%), steady state, 2500 Nm 3 / h; Operating Condition 2: H2-C3H6, flow rate suddenly increases from 2500 Nm³ to 3000 Nm³. 3 / h; Operating condition 3: H2-H2S (50%:50%), steady state, 1000 Nm 3 / h; Operating Condition 4: H2-H2S, flow rate suddenly increases from 1000 to 1300 Nm 3 / h; Specifically, such as Figures 1 to 5As shown, the ideal mixing rule is a fundamental rule applicable to the calculation of the physical properties of binary gas mixtures. This calculation method uses the inherent physical property parameters of a single pure gas component as the basis for calculation. The physical property parameters of a pure gas component are the inherent property data of a single medium under a given environment. By combining the weighted calculation with the proportion of each component in the mixture system, the physical property characteristics of each single medium can be proportionally integrated, ultimately obtaining the overall density, viscosity, sound velocity, molar mass, specific heat capacity, and thermal conductivity of the mixed gas. This allows the calculated parameters to truly reflect the comprehensive fluid characteristics of the binary gas mixture, providing accurate parameter support for operating condition configuration and flow field simulation.

[0027] Specifically, such as Figures 1 to 5 As shown, a binary mixed gas system is formed by combining two single gas components in a fixed proportion. This method uses hydrogen as the base component and combines it with other media to form at least two mixed systems, adapting to common media compositions in multi-component gas systems. Hydrocarbon media and acidic corrosive gases are common media components in industrial multi-component gas systems, covering mainstream media types in petroleum refining and multi-component gas processing scenarios. The steady-state operating condition uses a constant rated flow rate, under which the medium maintains a stable flow state. The transient operating condition uses the rated flow rate of the steady-state condition as a benchmark, setting a sudden change in flow rate to simulate flow fluctuations during industrial operation, comprehensively verifying the adaptability of the installation location under different operating conditions.

[0028] For dynamic operating conditions (such as operating conditions 2 and 4), the loading method for sudden flow changes is set to a ramp step, meaning that the flow rate increases linearly from the initial value to the target value within a time interval of Δt = 0.5s, rather than an instantaneous step, to avoid numerical oscillations. Time discretization uses a first-order implicit scheme with a fixed time step of Δt = 0.001s, an upper limit of 20 iterations per time step, and a residual convergence threshold of 10. -5 The total simulation time was as follows: 2 seconds for the initial steady-state phase to allow the flow field to fully develop, followed by a 0.5-second flow ramp change, and then 3 seconds of continuous operation until the flow field stabilized again. When extracting data, the cross-sectional parameters were recorded at the instant the ramp change ended (t=2.5s) and during the subsequent steady-state phases (t=3.5s, 4.5s, 5.5s) to analyze the recovery characteristics of the flow field after disturbance.

[0029] The data simulation and processing steps rely on numerical calculations to analyze the flow field characteristics. By simultaneously conducting steady-state and transient simulations, the flow characteristics of the mixed gas within the pipeline under both constant flow and flow rate variation conditions can be fully reproduced. Pipeline cross-sectional parameters are used to quantitatively characterize the medium distribution and flow properties across the pipeline cross-section. The hydrogen mole fraction distribution reflects the uniformity of hydrogen composition within the pipeline cross-section, the spatial distribution of sound velocity reflects the spatial differences in sound velocity parameters within the cross-section, and time-series data records the process characteristics of parameter changes over time. Based on these cross-sectional parameters, the coefficient of variation of sound velocity can be calculated. This coefficient measures the uniformity of sound velocity distribution across the pipeline cross-section. By integrating the coefficients of variation of sound velocity at different axial positions, the evolution law of this parameter along the pipeline axis can be obtained.

[0030] Specifically, such as Figures 1 to 5 As shown, the data simulation and processing steps rely on the numerical simulation output to complete the directional extraction and systematic analysis of flow field data. By simultaneously executing steady-state and transient simulations, comprehensive information on the internal flow field of the mixed gas under constant flow and flow variation conditions can be obtained. The axial monitoring section is a pre-defined detection section along the pipeline axis, used for point-to-point acquisition of flow field characteristic parameters, and is the core carrier for realizing section data extraction. Each axial monitoring section corresponds to several grid nodes formed by meshing the three-dimensional geometric model. The grid nodes are the basic points that carry the flow field calculation results during the numerical simulation process. By locating the pre-defined axial monitoring section and screening all the grid nodes it covers, the integrity and accuracy of the section data extraction can be ensured. For each axial monitoring section, the raw hydrogen concentration data of all grid nodes within the section range are completely extracted. By normalizing and spatially statistically integrating the raw data, a hydrogen mole fraction distribution that reflects the spatial arrangement of hydrogen components within the pipeline section is formed. This distribution can intuitively reflect the uniformity of component mixing within the section. The sound velocity values ​​of all grid nodes within each axial monitoring section are extracted synchronously. Spatial domain statistical and regularization processing is performed on these sound velocity values ​​to form a spatial distribution of sound velocity that characterizes the distribution characteristics of sound velocity parameters within the pipe section, providing fundamental data support for subsequent calculation of the sound velocity variation coefficient. During transient simulation, sound velocity values ​​and hydrogen mole fraction data of each axial monitoring section are collected at different time points to form time-series data reflecting parameter changes over time. Based on the time-series data, statistical processing is performed at corresponding times to generate the spatial distribution of sound velocity at different time points, fully reconstructing the dynamic change process of sound velocity distribution under transient conditions. Statistical calculations are performed on the spatial distribution of sound velocity at each axial monitoring section to obtain the standard deviation and mean of the sound velocity values ​​within the section. The standard deviation characterizes the dispersion of sound velocity within the section, and the mean characterizes the overall level of sound velocity within the section. The correlation calculation between the two yields the sound velocity variation coefficient for the corresponding section. The sound velocity variation coefficient includes: ; in, and Let $\begin{pmatrix} \ ...

[0031] Specifically, such as Figures 1 to 5 As shown, the data simulation and processing steps rely on a multiphysics-coupled numerical calculation framework to achieve a complete simulation of the fluid characteristics within the pipeline. A realizable k-ε turbulence model is used to construct the core of the gas mixture flow calculation. This model is adaptable to the complex turbulent flow patterns within multi-component gas confluence pipelines, accurately characterizing the vortex structure, velocity fluctuations, and momentum transfer features during gas confluence, thus reproducing the true turbulent flow state of the gas mixture within the pipeline and providing a matching physical model support for the numerical calculation of flow field parameters. During the simulation calculation, the component transport equation is solved simultaneously. This equation quantitatively describes the mass transfer laws of each component in the binary gas mixture under convection and diffusion, tracking the migration paths, mixing processes, and spatial distribution changes of different gas components throughout the pipeline, and clarifying the concentration distribution characteristics of hydrogen and the supporting medium throughout the confluence, mixing, and transport process. Through the collaborative calculation of the realizable k-ε turbulence model and the component transport equation, stable numerical solutions for steady-state and transient simulations can be completed.

[0032] The inlet turbulence intensity I of the realizable k-ε turbulence model is defined as I = 0.16·Re. {-1 / 8} The turbulent viscosity ratio was estimated to be 5, and the model constants were set to their default values ​​(Cμ=0.09, C1=1.44, C2=1.9, σk=1.0, σε=1.2). The near-wall surface was treated using the standard wall function. The component diffusion coefficients in the component transport equations were estimated using the Fuller-Schettler-Giddings semi-empirical formula. The transient simulation employed first-order implicit time discretization with a time step of 0.001 s, and the total simulation time covered until the flow field reached a new steady state after the sudden change in flow rate.

[0033] Steady-state simulations can obtain the flow field morphology and component distribution results that tend to be stable within the pipeline under constant boundary conditions, while transient simulations can capture the dynamic evolution of the flow field and component distribution over time under varying flow rates. The above simulation calculations can output comprehensive data covering the entire length of the pipeline, including the inlet section, confluence zone, and outlet. This data includes flow field motion parameters and gas component distribution parameters, providing complete and continuous raw data for subsequent parameter extraction of axial monitoring sections and statistical calculation of the sound velocity variation coefficient, ensuring data integrity for subsequent flow field uniformity analysis and installation location determination.

[0034] The parameter fitting and calculation steps are used to mathematically model and extract characteristic parameters from the evolution dataset of the sound velocity variation coefficient. By constructing quantitative correlations between parameters, the theoretical critical installation distance of the ultrasonic flowmeter is quantitatively solved. The initial position sound velocity variation coefficient is used to characterize the dispersion of the sound velocity distribution of the mixed gas at the initial confluence section, reflecting the initial non-uniformity of the flow field when the two gases just meet. The background variation coefficient at infinity in the pipeline is used to characterize the stable sound velocity variation after the mixed gas flow has fully developed, which is only affected by the turbulence characteristics of the fluid, serving as a benchmark reference index for the uniformity of the flow field. The attenuation constant is used to describe the attenuation rate of the sound velocity variation coefficient as it extends axially along the pipeline, reflecting the gradual uniformity of the mixed gas flow field. Combined with the preset metering accuracy control criteria, the theoretical critical installation distance can be calculated using the above characteristic parameters.

[0035] Specifically, such as Figures 1 to 5 As shown, the exponential decay model is a mathematical model that adapts to the axial evolution trend of the sound velocity variation coefficient. It can accurately describe the change law of the sound velocity variation coefficient gradually stabilizing as the axial distance of the pipeline increases.

[0036] In a preferred embodiment, the attenuation process of the sound velocity variation coefficient along the pipe axis is fitted using the following exponential attenuation model: Where x is the axial distance from the confluence point, CV(0) is the coefficient of variation of the sound velocity at the initial position (x=0), representing the maximum degree of inhomogeneity at the start of mixing, and is also CV0, λ is the attenuation constant, the larger its value, the longer the distance required for uniform mixing. The coefficient of variation at infinity in the pipeline represents the residual fluctuation level determined by turbulent characteristics after full mixing, and is also the CV. ∞ .

[0037] Among them, the background coefficient of variation This can be obtained by averaging the CV values ​​of multiple sections in the fully developed downstream segment (e.g., after x > 120D): ; The attenuation constant λ is obtained by fitting using the nonlinear least squares method, and its objective function is to minimize the sum of squared errors between the simulated values ​​and the model predictions: ; Among them, CV sim (x i Let be the sound velocity variation coefficient calculated from simulated data on the i-th cross section. In the above fitting process, the nonlinear least squares method is solved using the Levenberg-Marquardt algorithm, and the iterative convergence condition is set to the relative change of the objective function value between two adjacent iterations being less than 10. -6 The turbulence intensity I is defined as I = u' / ū, where u' is the root mean square of the fluctuating velocity and ū is the average velocity. The proportionality coefficient k ranges from 0.2 to 0.5 and is fitted using the least squares method. The attenuation curve is obtained. In practical engineering applications, if it is impossible to collect enough data points through the fully developed section (x>120D), theoretical estimation formulas can be used based on turbulence theory. As an alternative, ≈k·I has been verified to have an error of less than ±15% under multiple operating conditions.

[0038] Simulation data shows that in the fully developed stage It remains stable within the range of 0.01-0.02.

[0039] Eleven monitoring sections were selected along the pipeline: x=[0,25D,50D,...,150D], and the corresponding CV value was calculated for each section.

[0040] The physical properties were calculated according to the ideal mixing principle, with an operating pressure of 0.1 MPa and a temperature of 30℃.

[0041] After performing the above fitting on working condition 1, we obtain λ=18.2D and the coefficient of determination R. 2 =0.98, indicating that the model fits the data very well.

[0042] Nonlinear least squares fitting is used to match the evolution dataset of the sound velocity variation coefficient with the exponential decay model. By reducing the deviation between the model calculation results and the actual evolution data, the accuracy of determining the model's characteristic parameters is improved. This fitting process can determine the sound velocity variation coefficient at the initial position, the background sound velocity variation coefficient at infinity in the pipeline, and the decay constant, fully characterizing the axial evolution of the sound velocity variation coefficient. A preset measurement accuracy threshold is a control standard to ensure the normal measurement performance of the ultrasonic flowmeter. The sound velocity variation coefficient must be controlled within this threshold range, with a calculation accuracy threshold of CV ≤ 0.03. Combining the quantization relationship of the exponential decay model with the accuracy control criteria, the theoretical critical installation distance that meets the measurement requirements can be derived and calculated. This distance provides a core theoretical reference for determining the installation location of the ultrasonic flowmeter.

[0043] Specifically, based on the exponential decay model and using the criterion that the coefficient of variation of the sound speed does not exceed a preset measurement accuracy threshold (e.g., CV ≤ 0.03), the critical safe distance can be obtained: ; This formula provides a precise quantitative basis for determining the optimal installation location of the ultrasonic flow meter. For the above operating conditions, the critical distance for each condition can be calculated as follows: Operating condition 1: Lcrit = 65D; Operating Condition 2: Lcrit=85D (increase of 30.8%); Operating condition 3: Lcrit = 110D; Operating condition 4: Lcrit=145D (increase of 31.8%).

[0044] The initial coefficient of variation CV0 can be estimated using the operating condition mapping method, with the sound velocity c of the pure component gas at inlet A and inlet B respectively. A and c B The theoretical maximum value of the instantaneous non-uniformity of the confluence section is calculated using the following formula: CV0≈|c A -c B | / c mix ;where c mix This represents the ideal weighted average of the sound velocity of the mixed gas. It should be noted that all numerical simulations involved in this method are based on computational fluid dynamics (CFD), specifically using a realizable k-ε turbulence model combined with component transport equations. When the deviation between the theoretical value and the CFD simulation value exceeds ±20%, the CFD simulation value is taken as the standard. The CFD simulation value refers to the coefficient of variation of the sound velocity, i.e., CV, directly calculated by CFD simulation at the confluence section. sim (0), if CFD simulation conditions are available, this value should be used as the final value of CV0. In this case, the estimation formula is only used to verify the rationality of the simulation results or as the initial iteration value for nonlinear least squares fitting. If CFD simulation conditions are not available, the estimation formula can be used alone to approximate CV0, but its theoretical approximation properties must be noted in the application report.

[0045] The dynamic operating condition safety margin is determined by the logarithmic relationship between the flow rate change magnitude ΔQ / Q0, where ΔQ is the flow rate variable and Q0 is the initial flow rate. Safety margin (%) = 15% + 5% × log2(ΔQ / Q0); For example, when ΔQ / Q0 = 20%, the safety margin is 15% + 5% × 1 = 20%; when ΔQ / Q0 = 40%, the safety margin is 15% + 5% × 2 = 25%. The final optimal installation distance is determined by the following formula: Lfinal =Lcrit×(1+safety margin).

[0046] Specifically, such as Figures 1 to 5 As shown, the result verification and optimization steps are used to perform engineering corrections and compliance checks on the theoretical critical installation distance. Parameter optimization is completed by adapting to the operating characteristics of dynamic conditions, ensuring that the final determined installation location can adapt to the complex operating conditions of the industrial site. The theoretical critical installation distance is calculated based on steady-state flow field characteristics. Sudden changes in flow rate under dynamic conditions can cause flow field disturbances. Therefore, correction parameters need to be introduced based on the theoretical critical installation distance. By adding a safety margin, the anti-disturbance capability of the installation scheme is improved, ultimately forming the optimal installation distance suitable for all operating conditions. After determining the optimal installation distance, verification and judgment need to be carried out based on preset indicators to confirm that the flow field state corresponding to this distance meets the metering requirements. After successful verification, the optimal installation distance is output as the final positioning result.

[0047] Specifically, such as Figures 1 to 5 As shown, the safety margin for dynamic operating conditions is a length correction amount set for flow disturbances. It is increased based on the theoretical critical installation distance according to a set ratio to offset the decrease in flow field uniformity caused by sudden flow changes, ensuring that the flow field meets measurement conditions under dynamic operating conditions. The verification conditions include two parallel judgment indicators: the sound velocity variation coefficient meets the measurement accuracy requirements, indicating that the uniformity of the sound velocity distribution within the pipe cross-section meets the standard for stable operation of the ultrasonic flowmeter; and the sound velocity fluctuation amplitude is within the preset allowable range, indicating that the change in sound velocity parameters during transient changes will not interfere with the measurement results. When the optimal installation distance simultaneously meets both verification conditions, the installation distance is deemed to have practical application feasibility and can be used as the final ultrasonic flowmeter installation positioning result output.

[0048] The sound velocity fluctuation amplitude is the average sound velocity μ calculated over five consecutive time steps at the same monitoring section under transient conditions. c(t) The maximum relative deviation, with a fluctuation range of max|μ c(ti) -μ c(tj) | / μ cavg ×100%, where μ cavg This is the arithmetic mean of the sound velocity over these 5 time steps. The preset allowable range is ≤±2%, meaning the fluctuation amplitude does not exceed 2%. This indicator is used to quantify the dynamic stability of the flow field and avoid false counting or frame loss in the signal processing unit of the ultrasonic flowmeter due to excessive instantaneous pulsation.

[0049] The time step size in the above five consecutive time steps is consistent with the fixed time step size used in transient simulation, which is 0.001s in this example, corresponding to a 5ms time window. In practical applications, the time step size can be adjusted appropriately according to the simulation accuracy requirements, but it must be clearly recorded in the report.

[0050] The foregoing has illustrated and described the basic features, principles, and advantages of the present invention. It should be noted that the present invention is not limited to the above embodiments, but only to some embodiments. Any improvements and additions made without departing from the spirit and scope of the present invention are considered to be within the scope of protection of the present invention.

Claims

1. A method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium, characterized in that, include: The parameter acquisition and setting steps involve acquiring the geometric parameters of the multi-component gas manifold, the components and proportion range of the mixed gas, and the geometric parameters of the multi-component gas manifold, including the pipe diameter, pipe length and pipe structure. The monitoring section position is determined based on the pipe diameter, and the operating condition parameters are set. The modeling and meshing steps involve constructing a three-dimensional geometric model based on the geometric parameters of the multi-component gas confluence pipe, dividing the three-dimensional geometric model into a hexahedral mesh, refining the mesh in the gas confluence region, and determining the number of meshes through mesh independence verification. The operating condition setting steps include unifying the operating pressure and temperature, calculating the physical property parameters of the mixed gas based on the components and proportion range of the mixed gas, including density, viscosity, sound velocity, molar mass, specific heat capacity and thermal conductivity, and configuring steady-state and transient operating conditions based on the physical property parameters. The data simulation and processing steps include performing steady-state and transient simulations, obtaining pipeline cross-sectional parameters based on the simulation results, including hydrogen mole fraction distribution, sound velocity spatial distribution, and time series data for each cross-section of the pipeline, and calculating the evolution law of the sound velocity variation coefficient along the pipeline axis based on the pipeline cross-sectional parameters. The parameter fitting and calculation steps are as follows: determine the initial position sound velocity variation coefficient and the background variation coefficient at infinity; obtain the attenuation constant through fitting; and calculate the theoretical critical installation distance according to the sound velocity variation coefficient calculation accuracy criterion. The result verification and optimization steps involve adding a safety margin to the dynamic operating conditions to obtain the optimal installation distance, and verifying whether the optimal installation distance meets the conditions. If the conditions are met, the optimal installation distance is output.

2. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, The physical properties are calculated using the ideal mixing principle. The density, viscosity, velocity of sound, molar mass, specific heat capacity, and thermal conductivity of the mixed gas are obtained by weighted calculation based on the known physical properties of each pure component in the mixed gas and the proportion of each component in the mixed system.

3. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, The data simulation and processing steps include: performing steady-state and transient simulations; selecting all grid nodes covered by each monitoring section by locating preset axial monitoring sections; extracting hydrogen concentration data of all grid nodes within each monitoring section; statistically organizing the data to obtain the hydrogen mole fraction distribution of each section; extracting the sound velocity values ​​of all grid nodes within each monitoring section; statistically obtaining the sound velocity spatial distribution of each section; when performing transient simulations, extracting the time-series data related to sound velocity and hydrogen mole fraction at different time points of each monitoring section to generate a sound velocity spatial distribution; statistically calculating the sound velocity standard deviation and mean value of each section based on the sound velocity spatial distribution to obtain the sound velocity variation coefficient of each section; and obtaining the evolution dataset of the sound velocity variation coefficient along the pipeline axis based on the sound velocity variation coefficient of each section.

4. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, The evolution dataset of the sound velocity variation coefficient is fitted nonlinearly using an exponential decay model to determine the sound velocity variation coefficient at the initial position, the background sound velocity variation coefficient at infinity in the pipeline, and the attenuation constant of the axial attenuation characteristic of the sound velocity variation coefficient. Based on the criterion that the sound velocity variation coefficient does not exceed the preset measurement accuracy threshold, the theoretical critical installation distance is derived and calculated using the exponential decay model.

5. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, The data simulation and processing steps include simulating the turbulent flow state of the mixed gas in the pipeline using a realizable k-ε turbulence model, tracking the concentration transfer and distribution of each gas component using the component transport equation, completing steady-state simulation and transient simulation, and obtaining flow field and component distribution data for the entire pipeline.

6. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, In the modeling and meshing steps, local mesh refinement is performed in the gas confluence region. The mesh size in the refinement region is 1 / 20 of the pipe diameter. The criterion for mesh independence verification is to perform steady-state simulation using at least three different mesh numbers and calculate the sound velocity variation coefficient at the downstream 80D section. When the relative change in the sound velocity variation coefficient between two adjacent meshes is less than 1%, it is confirmed that the mesh number meets the accuracy requirements, and the final mesh number is determined.

7. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, The three-dimensional geometric model of the multi-component gas manifold includes two mutually perpendicular first inlet pipes and second inlet pipes, and an outlet pipe that is horizontally connected to the first inlet pipe. The length of the outlet pipe is set to 150 times the pipe diameter.

8. The method for determining the installation location of an ultrasonic flow meter for a binary mixed gas medium according to claim 1, characterized in that, The operating condition setting step includes setting up at least two binary mixed gas systems including hydrogen, configuring steady-state operating conditions with constant rated flow rates, and preset transient operating conditions with sudden changes in flow rate amplitude based on the steady-state conditions. The other component in the mixed gas system is a hydrocarbon or an acidic corrosive gas.

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