Method and apparatus for mass flow metering of carbon dioxide containing impurities

Abstract

The application discloses a mass flow metering method and device for carbon dioxide containing impurities. The method comprises the following steps: acquiring the gas source composition, real-time temperature, and real-time pressure and other conveying working condition information of the carbon dioxide containing impurities in the conveying pipeline; after the gas source composition is determined, the real-time volume flow in the pipeline and the thermophysical property data of the working medium (the density data of the carbon dioxide containing impurities under different temperatures and pressures) are acquired, and the density correction model suitable for the current gas source composition is determined in combination with the gas source composition (including the component type and the component composition ratio); the real-time density is calculated according to the density correction model and the real-time temperature and pressure of the pipeline; and finally, the real-time mass flow of the carbon dioxide containing impurities is obtained through the real-time volume flow and the real-time density. The application considers the metering accuracy and cost, and provides reliable data support for carbon accounting and carbon trading.

Description

Technical Field

[0001] This application relates to the field of carbon dioxide capture, utilization and storage technology, and in particular to a method and apparatus for measuring the mass flow rate of carbon dioxide containing impurities. Background Technology

[0002] With the advancement of the "dual carbon" goals, carbon dioxide capture, utilization, and storage (CVC) technology has become a key means of industrial carbon emission reduction. Among these technologies, pipeline transportation of supercritical / dense-phase carbon dioxide containing impurities is one of the core links in the entire CVC technology chain. Currently, CVC projects involve large carbon dioxide transport flows, with pipeline diameters mostly exceeding 300 mm. Mass flow rate measurement, because it directly meets the accuracy requirements of carbon trading, has become the core measurement need in this field.

[0003] However, existing methods for measuring the mass flow rate of carbon dioxide containing impurities have significant limitations: Coriolis mass flow meters, while highly accurate, are expensive and only suitable for small-diameter pipes of 150-200 mm or less, making them unsuitable for large-diameter transport scenarios; traditional volumetric flow meters (such as differential pressure and velocity flow meters) require combining density data to derive the mass flow rate, but the density of carbon dioxide containing impurities has a non-linear characteristic that changes with temperature and pressure. Existing density acquisition methods either rely on additional high-precision densitometers or lack specific density correction models for carbon dioxide containing impurities, resulting in large density calculation deviations and ultimately insufficient accuracy in mass flow rate measurement, making it difficult to meet the stringent requirements of carbon accounting and carbon trading.

[0004] Therefore, how to provide a low-cost, high-precision mass flow rate measurement method for large-diameter pipeline transportation of impurity-containing carbon dioxide with a fixed impurity composition and stable pipeline temperature and pressure, as well as for scenarios where the impurity composition is uncertain and the pipeline temperature and pressure are unstable, is an urgent problem to be solved in the current application of carbon dioxide capture, utilization and storage technology. Summary of the Invention

[0005] In view of this, the present application provides a method and apparatus for measuring the mass flow rate of carbon dioxide containing impurities, which can provide a low-cost, high-precision method for measuring the mass flow rate of carbon dioxide containing impurities in large-diameter pipelines where the impurity composition is certain and the temperature and pressure of the conveying pipeline are stable, as well as in situations where the impurity composition is uncertain and the temperature and pressure of the conveying pipeline are unstable. The method and apparatus for measuring the mass flow rate of carbon dioxide containing impurities provided in this application are implemented as follows:

[0006] This application provides a method for measuring the mass flow rate of carbon dioxide containing impurities, comprising:

[0007] Given a defined gas source composition, the real-time volumetric flow rate of carbon dioxide containing impurities and the thermophysical property data of the working fluid in the delivery pipeline are obtained. Based on the gas source composition and the thermophysical property data of the working fluid, a density correction model for carbon dioxide containing impurities under the current gas source composition is determined. The thermophysical property data of the working fluid is the density data of carbon dioxide containing impurities at different temperatures and pressures. The gas source composition is the component type and composition ratio of the carbon dioxide containing impurities.

[0008] The real-time density is obtained based on the density correction model, the real-time pressure of the carbon dioxide pipeline containing impurities, and the real-time temperature.

[0009] The real-time mass flow rate of carbon dioxide containing impurities is obtained based on the real-time volumetric flow rate and the real-time density.

[0010] In some embodiments, the method further includes:

[0011] When the gas source composition is uncertain, the fluid parameters of the delivery pipeline are obtained according to the carbon dioxide flow metering system, and the real-time gas source composition of the working medium in the delivery pipeline is obtained according to the gas component detector. The carbon dioxide flow metering system includes a volumetric flow meter, a temperature transmitter, a pressure transmitter, and a flow manager. The fluid parameters include real-time volumetric flow rate, real-time temperature, and real-time pressure.

[0012] The working fluid thermophysical property data are calculated and processed based on the real-time gas source composition and the fluid parameters to obtain the real-time density;

[0013] The real-time volumetric flow rate and real-time density are calculated to obtain the real-time mass flow rate of carbon dioxide containing impurities.

[0014] In some embodiments, when the gas source composition is determined, acquiring the real-time volumetric flow rate of carbon dioxide containing impurities and the thermophysical property data of the working fluid in the delivery pipeline, and determining the density correction model of carbon dioxide containing impurities under the current gas source composition based on the gas source composition and the thermophysical property data of the working fluid, includes:

[0015] Obtain the real-time volumetric flow rate of carbon dioxide containing impurities in the conveying pipeline;

[0016] Acquire the thermophysical property data of the working fluid containing impurities within a preset temperature range and a preset pressure range;

[0017] Multiple pressure points are selected within the preset pressure range. For each pressure point, the density value corresponding to the thermophysical property data of the working fluid is extracted within the preset temperature range and fitted into a density-temperature correlation curve.

[0018] The density-temperature correlation curves corresponding to the multiple pressure points are interpolated to obtain a density correction model.

[0019] In some embodiments, when the gas source composition is uncertain, obtaining the fluid parameters of the delivery pipeline based on the carbon dioxide flow metering system and obtaining the real-time gas source composition of the working fluid in the delivery pipeline based on the gas component detector includes:

[0020] The volumetric flow rate of carbon dioxide containing impurities is collected by the volumetric flow meter, the real-time temperature in the delivery pipeline is collected by the temperature transmitter, and the real-time pressure in the delivery pipeline is collected by the pressure transmitter.

[0021] The flow manager integrates and processes the real-time volumetric flow rate, real-time temperature, and real-time pressure to obtain the fluid parameters of the delivery pipeline.

[0022] The gas source components are obtained using a gas component detector.

[0023] In some embodiments, the step of calculating and processing the thermophysical property data of the working fluid based on the real-time gas source composition and the fluid parameters to obtain the real-time density includes:

[0024] When the composition of the real-time gas source is uncertain, a preset carbon dioxide density correction model containing impurities is obtained;

[0025] Real-time temperature and real-time pressure are acquired, and the real-time temperature and real-time pressure are smoothed and filtered to obtain the processed real-time temperature and real-time pressure.

[0026] The processed real-time temperature and pressure are input into a preset impurity-containing carbon dioxide density correction model to obtain the real-time density.

[0027] In some embodiments, selecting multiple pressure points within the preset pressure range, and for each pressure point, extracting the density value corresponding to the thermophysical property data of the working fluid within the preset temperature range and fitting it into a density-temperature correlation curve, includes:

[0028] Multiple pressure points are selected at set intervals within the preset pressure range to obtain multiple discrete pressure values;

[0029] Multiple temperature points are selected at set intervals within the preset temperature range to obtain multiple discrete temperature values.

[0030] For each discrete pressure value, the density data corresponding to each discrete temperature value under that pressure is extracted from the thermophysical property data of the working fluid to obtain multiple sets of data pairs.

[0031] A curve fitting algorithm was used to fit each data pair to obtain the initial density-temperature correlation curve;

[0032] Calculate the deviation between the initial density-temperature correlation curve and the density data. If the deviation does not exceed a preset threshold, obtain the density-temperature correlation curve.

[0033] In some embodiments, the preset temperature range is 90K~450K, and the preset pressure range is 0MPa~35MPa.

[0034] This application provides a mass flow metering device for carbon dioxide containing impurities, comprising:

[0035] The acquisition module is used to acquire the transportation condition information of carbon dioxide containing impurities in the transportation pipeline. The transportation condition information includes the gas source composition, the real-time temperature of the transportation pipeline, and the real-time pressure.

[0036] The acquisition module is further configured to acquire, when the gas source composition is determined, the real-time volumetric flow rate of carbon dioxide containing impurities and the working fluid thermophysical property data in the delivery pipeline, and determine the density correction model of carbon dioxide containing impurities under the current gas source composition based on the gas source composition and the working fluid thermophysical property data. The working fluid thermophysical property data is the density data of carbon dioxide containing impurities at different temperatures and pressures, and the gas source composition is the component type and composition ratio of carbon dioxide containing impurities.

[0037] The calculation module is used to obtain the real-time density based on the density correction model, the real-time pressure of the impurity carbon dioxide pipeline, and the real-time temperature.

[0038] The calculation module is also used to obtain the real-time mass flow rate of carbon dioxide containing impurities based on the real-time volumetric flow rate and the real-time density.

[0039] The computer device provided in this application includes a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements the method described in this application.

[0040] The computer-readable storage medium provided in this application embodiment stores a computer program thereon, which, when executed by a processor, implements the method provided in this application embodiment.

[0041] This application provides a method and apparatus for measuring the mass flow rate of carbon dioxide containing impurities. The method acquires information on the gas source composition, real-time temperature, and real-time pressure of the carbon dioxide-containing gas within a transport pipeline. It then acquires real-time volumetric flow rate and working fluid thermophysical property data (density data of the carbon dioxide-containing gas at different temperatures and pressures) within the pipeline, and determines a density correction model suitable for the current gas source composition based on the gas source composition (including component types and their proportions). The real-time density is then calculated based on the density correction model and the real-time temperature and pressure of the pipeline. Finally, the real-time mass flow rate of the carbon dioxide-containing gas is obtained from the real-time volumetric flow rate and real-time density. This application balances measurement accuracy and cost, providing reliable data support for carbon accounting and carbon trading. It solves the problems of high measurement cost and insufficient accuracy in existing technologies. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A schematic diagram illustrating the implementation process of a method for measuring the mass flow rate of carbon dioxide containing impurities, provided in an embodiment of this application;

[0044] Figure 2 A schematic diagram illustrating the implementation process of obtaining the mass flow rate of carbon dioxide containing impurities under unstable operating conditions, provided in an embodiment of this application;

[0045] Figure 3 This application provides a mass flow metering device for carbon dioxide containing impurities. Detailed Implementation

[0046] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0047] The following description of some technologies involved in the embodiments of this application is provided to aid understanding and should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, some descriptions of well-known functions and structures are omitted in the following description.

[0048] Figure 1 This is a schematic flowchart illustrating the implementation of a method for measuring the mass flow rate of carbon dioxide containing impurities, as provided in an embodiment of this application, including steps 101 to 104. Wherein, Figure 1 This is merely one execution order shown in the embodiments of this application and does not represent the only execution order for a method of measuring the mass flow rate of carbon dioxide containing impurities. Where the final result can be achieved, Figure 1 The steps shown can be performed in parallel or in reverse order.

[0049] Step 101: Obtain the transport condition information of carbon dioxide containing impurities in the transport pipeline.

[0050] In this embodiment of the application, common gas component analysis methods such as gas chromatography are used to detect the components of carbon dioxide containing impurities in the delivery pipeline, clarify the gas source components contained therein and the composition ratio of each component, and complete the determination of the gas source components.

[0051] Temperature and pressure transmitters are installed in the metering section of the pipeline to continuously monitor the temperature and pressure of the fluid in the pipeline. When the monitored temperature and pressure fluctuations meet the preset requirements of "stable operating conditions" (i.e., the fluctuation range does not affect the density calculation accuracy), the temperature and pressure are determined to be stable.

[0052] Step 102: Given a fixed gas source composition, obtain the real-time volumetric flow rate of carbon dioxide containing impurities and the thermophysical property data of the working fluid in the delivery pipeline, and determine the density correction model of carbon dioxide containing impurities under the current gas source composition based on the gas source composition and the thermophysical property data of the working fluid.

[0053] In this embodiment of the application, a volumetric flow meter (such as a turbine flow meter or vortex flow meter) is installed in the metering section of the delivery pipeline; the flow meter collects and outputs the real-time volumetric flow rate of carbon dioxide containing impurities at a frequency matched with the temperature and pressure transmitter.

[0054] Based on the detection results of the gas source components, the gas source components are defined as "carbon dioxide containing specific gas source components and corresponding composition ratios", such as "carbon dioxide containing nitrogen (volume fraction 2.1%) and methane (volume fraction 0.8%)".

[0055] Based on the determined gas source composition, the data processing system calls a thermodynamic property database (such as the NIST-REFPROP database) to retrieve the density data of the gas source within a preset temperature range (covering the actual delivery temperature fluctuation range) and a preset pressure range (covering the actual delivery pressure fluctuation range), forming a working fluid thermophysical property dataset containing the correspondence between "temperature-pressure-density".

[0056] Based on the working fluid thermophysical property dataset, a model is constructed using a combination of curve fitting and interpolation. Multiple discrete pressure points are selected within a preset pressure range, and a density-temperature correlation curve is fitted for each pressure point. Then, density data between each pressure point is supplemented by interpolation to form a basic model covering the complete temperature and pressure range. The parameters of the basic model are adjusted in combination with the component characteristics of the gas source components to finally obtain a density correction model adapted to the current gas source components.

[0057] Step 103: Obtain the real-time density based on the density correction model, the real-time pressure of the carbon dioxide pipeline containing impurities, and the real-time temperature.

[0058] In this embodiment, the acquired real-time temperature and pressure data are input into the density correction model obtained in step 102. The model uses the built-in "temperature-pressure-density" mapping relationship based on the input temperature and pressure parameters to calculate and output the real-time density of carbon dioxide containing impurities under the current operating conditions. During the calculation process, the model automatically checks whether the real-time temperature and pressure are within the preset range. If they exceed the range, parameter adaptation logic is triggered to ensure the validity of the density calculation.

[0059] Step 104: Obtain the real-time mass flow rate of carbon dioxide containing impurities based on the real-time volumetric flow rate and the real-time density.

[0060] In this embodiment, the real-time volumetric flow rate and real-time density are numerically calculated by calling the core formula "mass flow rate = real-time volumetric flow rate × real-time density"; the consistency of units is automatically checked before the calculation, and the units are converted as needed to match the calculation requirements; after the calculation is completed, the mass flow rate data is output.

[0061] This application embodiment establishes a density correction model based on gas source composition and working fluid thermophysical property data, eliminating the need to rely on expensive high-precision density meters or dedicated large-diameter mass flow meters. It achieves high-quality flow measurement by combining a volumetric flow meter with a density correction model, thereby reducing equipment investment and maintenance costs.

[0062] exist Figure 1 Based on the above, this application also provides a schematic diagram of the implementation process for obtaining the mass flow rate of carbon dioxide containing impurities under unstable operating conditions, as shown below. Figure 2 As shown, steps 201 to 203 are included:

[0063] Step 201: When the gas source composition is uncertain, the fluid parameters of the delivery pipeline are obtained according to the carbon dioxide flow metering system, and the real-time gas source composition of the working medium in the delivery pipeline is obtained according to the gas component detector.

[0064] In this embodiment, a carbon dioxide flow metering system (comprising a volumetric flow meter, a temperature transmitter, a pressure transmitter, and a flow manager) and a gas / liquid component detection device are deployed in the metering section of the delivery pipeline. The volumetric flow meter, temperature transmitter, and pressure transmitter are all installed in a straight section of the pipeline where the flow field is stable. The flow manager is connected to each measuring instrument via signal lines to receive, process, and calculate the data transmitted by each instrument. The gas / liquid component detection device is located at the front end of the delivery pipeline. The measured gas source component data is transmitted to the flow manager, and combined with pressure and temperature data, the current component and the real-time density under this delivery condition are obtained.

[0065] After the flow metering system is started, the volumetric flow meter continuously collects the volumetric flow signal of carbon dioxide containing impurities in the pipeline, while the temperature transmitter and pressure transmitter synchronously collect the temperature and pressure signals in the pipeline in real time.

[0066] The real-time volumetric flow rate, real-time temperature, and real-time pressure signals collected by each instrument are transmitted to the flow manager. The flow manager preprocesses the received signals, including filtering to remove acquisition noise, signal amplification, and format conversion. Then, the processed parameters are integrated into structured fluid parameters, and the real-time gas source composition of the working fluid in the delivery pipeline is obtained according to the gas component detector.

[0067] Step 202: Calculate and process the thermophysical property data of the working fluid based on the real-time gas source composition and fluid parameters to obtain the real-time density.

[0068] In this embodiment of the application, when the composition of the real-time gas source is uncertain, the flow manager has a built-in preset density correction model for carbon dioxide containing impurities and integrates the NIST-REFPROP thermodynamic property database interface; when the fluid parameters are received, the flow manager automatically loads the density correction model and calls the basic thermophysical property data of carbon dioxide containing unknown impurities in the database through the interface.

[0069] The integrated real-time temperature and pressure parameters are input into the density correction model. Based on the called thermophysical data, a dynamic interpolation algorithm is used to match the initial density value under the current temperature and pressure conditions. At the same time, the initial density value is adaptively corrected by combining the fluctuation characteristics of the real-time volumetric flow rate.

[0070] During the calculation process, it is verified whether the carbon dioxide containing impurities is in a single phase under the current operating conditions. If it is determined to be a single phase, the real-time density is directly output. If there is a risk of phase change, the model will initiate parameter adjustment logic to ensure that the density calculation is completed and the result is output under single-phase conditions.

[0071] Step 203: Calculate the real-time volumetric flow rate and real-time density to obtain the real-time mass flow rate of carbon dioxide containing impurities.

[0072] In this embodiment of the application, the flow manager calls the calculation formula "mass flow rate = real-time volumetric flow rate × real-time density" to perform real-time numerical calculations on the integrated real-time volumetric flow rate and the calculated real-time density.

[0073] After the calculation is completed, the flow manager outputs the mass flow rate data of carbon dioxide containing impurities in real time.

[0074] This application embodiment utilizes an integrated system comprised of a volumetric flow meter, a temperature and pressure transmitter, and a flow manager to acquire fluid parameters in real time and calculate real-time density, ensuring the timeliness and accuracy of mass flow measurement when operating conditions change. By integrating parameter acquisition, data processing, density calculation, and mass flow output, the system offers convenient operation and seamless data transmission, reducing human intervention errors and improving the automation level of the measurement process.

[0075] In some embodiments, when the gas source composition is determined, the real-time volumetric flow rate of carbon dioxide containing impurities in the delivery pipeline and the thermophysical property data of the working fluid are obtained, and the density correction model of carbon dioxide containing impurities under the current gas source composition is determined based on the gas source composition and the thermophysical property data of the working fluid, including: obtaining the real-time volumetric flow rate of carbon dioxide containing impurities in the delivery pipeline.

[0076] Specifically, a volumetric flow meter is deployed in the metering section of the pipeline; the volumetric flow meter is started to continuously collect volumetric flow signals, the collected raw flow data is preprocessed to remove abnormal interference data, and then the effective data is integrated through statistical analysis methods (such as the averaging method) to finally obtain the real-time volumetric flow.

[0077] Furthermore, the thermophysical property data of the working fluid containing impurities carbon dioxide within a preset temperature range and a preset pressure range are obtained.

[0078] Specifically, based on the transportation requirements of carbon dioxide containing impurities, a suitable preset temperature range and preset pressure range are set; based on the determined gas source composition, the density characteristic data of the gas source within the preset temperature and pressure range are retrieved by calling the NIST-REFPROP thermodynamic property database through data processing tools, forming a working fluid thermophysical property dataset.

[0079] Furthermore, multiple pressure points are selected within a preset pressure range. For each pressure point, the density value corresponding to the thermophysical property data of the working fluid is extracted within a preset temperature range and fitted into a density-temperature correlation curve.

[0080] Specifically, multiple discrete pressure points are selected at set intervals within a preset pressure range; for each pressure point, density data corresponding to the preset temperature range is extracted from the working fluid thermophysical property dataset to form multiple sets of "temperature-density" correspondences; a curve fitting algorithm is used to fit each set of data to generate density-temperature correlation curves corresponding to each pressure point, and the deviation between the fitted curves and the original data is verified to meet the accuracy requirements.

[0081] Furthermore, the density-temperature correlation curves corresponding to the multiple pressure points are interpolated to obtain a density correction model.

[0082] Specifically, an interpolation algorithm is used to complete the density-temperature correlation curves corresponding to different pressure points, fill in the density-temperature data corresponding to each intermediate pressure within the preset temperature and pressure range, and construct a density correction model that covers the complete preset working conditions and includes the "temperature-pressure-density" mapping relationship.

[0083] This application embodiment employs a comprehensive process, from volumetric flow rate statistical processing to gas source component confirmation, working fluid data retrieval, curve fitting, interpolation completion, and model optimization, ensuring that the density correction model is built based on real-world operating data and optimized through actual density verification, significantly improving the model's calculation accuracy. By combining "fitting and interpolation," it covers a preset temperature and pressure range, avoiding the limitations of data from a single pressure point.

[0084] In some embodiments, when the gas source composition is uncertain, the fluid parameters of the delivery pipeline are obtained according to the carbon dioxide flow metering system, and the real-time gas source composition of the working medium in the delivery pipeline is obtained according to the gas component detector. This includes: collecting the real-time volumetric flow rate of carbon dioxide containing impurities through a volumetric flow meter, collecting the real-time temperature in the delivery pipeline through a temperature transmitter, and collecting the real-time pressure in the delivery pipeline through a pressure transmitter.

[0085] Specifically, the volumetric flow meter (either a turbine flow meter or a vortex flow meter) is installed in the metering section of the delivery pipeline, ensuring that the installation location is in a straight pipe section with a stable flow field, avoiding flow field disturbances caused by pipe bends, valves, and other components that may affect measurement accuracy; after the volumetric flow meter is started, it continuously collects the volumetric flow signal of carbon dioxide containing impurities in the pipeline, and the collection frequency is matched with the receiving frequency of the flow manager to ensure real-time performance.

[0086] Insert the measuring probe of the temperature transmitter into the delivery pipeline so that the probe comes into direct contact with the carbon dioxide containing impurities to obtain an accurate fluid temperature; the temperature transmitter continuously collects the temperature signal in the pipeline at a set frequency to ensure that the signal can reflect the dynamic changes in temperature.

[0087] Connect the pressure transmitter to the pressure tapping point of the pipeline. The pressure tapping point is located close to the volumetric flow meter and temperature transmitter to reduce spatial deviation of parameter acquisition. The pressure transmitter senses the fluid pressure in the pipeline in real time and converts it into an electrical signal to realize continuous acquisition of real-time pressure data.

[0088] Furthermore, the flow manager integrates and processes real-time volumetric flow rate, real-time temperature, and real-time pressure to obtain the fluid parameters of the delivery pipeline.

[0089] Specifically, the flow manager receives real-time volumetric flow rate, real-time temperature, and real-time pressure signals transmitted from volumetric flow meters, temperature transmitters, and pressure transmitters through a preset signal interface. For the received raw signals, the flow manager first performs filtering to remove noise signals caused by electromagnetic interference, instrument vibration, and other factors. At the same time, it amplifies and converts the signals to convert the output signals of different instruments into digital signals that the flow manager can recognize.

[0090] The flow manager timestamps the preprocessed real-time volumetric flow rate, real-time temperature, and real-time pressure signals to ensure that the three parameters correspond one-to-one at the same time. Then, the matched parameters are integrated according to a preset data structure to form a structured dataset containing "acquisition time - real-time volumetric flow rate - real-time temperature - real-time pressure". This dataset is the fluid parameter of the delivery pipeline.

[0091] The gas source components are obtained using a gas component detector.

[0092] This application clearly defines the data acquisition roles of each instrument, ensuring the independent and accurate acquisition of real-time volumetric flow rate, temperature, and pressure data. Through the integrated processing of the flow manager, time synchronization and format unification of multiple parameters are achieved, avoiding calculation errors caused by parameter misalignment or format incompatibility. The flow manager's integrated processing of the raw acquired signals can initially filter out noise interference, providing clean and consistent basic data for subsequent real-time density calculations, reducing losses during data transmission and conversion.

[0093] In some embodiments, the working fluid thermophysical property data are calculated and processed based on the real-time gas source composition and fluid parameters to obtain the real-time density, including: obtaining a preset density correction model for impurity-containing carbon dioxide when the real-time gas source composition is uncertain.

[0094] Specifically, when the composition of the gas source is uncertain in real time, a pre-set density correction model for impurity-containing carbon dioxide is pre-installed in the flow manager of the carbon dioxide flow metering system. This model is a pre-established and validated general-purpose model that integrates the NIST-REFPROP thermodynamic property database interface. It can adapt to impurity-containing supercritical / dense-phase carbon dioxide with unknown impurity types and proportions. It calculates density by correlating temperature and pressure parameters with thermophysical property data, and has built-in phase verification logic to ensure that the fluid is in a single phase during metering.

[0095] Furthermore, real-time temperature and pressure are acquired, and smoothing filtering is performed on the real-time temperature and pressure to obtain the processed real-time temperature and pressure.

[0096] Specifically, from the fluid parameters integrated by the carbon dioxide flow metering system, real-time temperature and pressure data with the same timestamp as the real-time volumetric flow rate are extracted to ensure the time synchronization of temperature and pressure parameters with flow parameters.

[0097] The extracted real-time temperature and pressure data are processed using a smoothing filtering algorithm (such as a moving average algorithm). By setting the filtering window length, the continuously collected temperature and pressure data are subjected to a sliding calculation to remove instantaneous abnormal fluctuations caused by instrument vibration, electromagnetic interference, etc., resulting in processed real-time temperature and pressure with smooth fluctuations and stable data.

[0098] Furthermore, the processed real-time temperature and pressure are input into a preset impurity-containing carbon dioxide density correction model to obtain the real-time density.

[0099] Specifically, the processed real-time temperature and pressure are synchronously input into the preset carbon dioxide density correction model containing impurities in the flow manager. The model calls the basic thermophysical property data of carbon dioxide containing unknown impurities in the NIST-REFPROP database through the built-in database interface, and combines the input temperature and pressure parameters with a dynamic interpolation algorithm to match the density data under the current temperature and pressure conditions.

[0100] Real-time volumetric flow rate data is extracted from fluid parameters, and the ratio of the standard deviation to the average value of the real-time volumetric flow rate per unit time is calculated to obtain the fluctuation coefficient of the real-time volumetric flow rate.

[0101] According to the preset correction rules, the fluctuation coefficient is correlated with the density data for calculation. If the fluctuation coefficient is small (flow is stable), the density data is slightly adjusted; if the fluctuation coefficient is large (flow fluctuates significantly), the correction range is increased proportionally to offset the indirect impact of flow fluctuations on the density calculation.

[0102] The density data after correction for fluctuation coefficient is the real-time density of carbon dioxide containing impurities under the current operating conditions. The model transmits this real-time density value to the flow manager.

[0103] This application's embodiments utilize smoothing filtering to process real-time temperature and pressure data, effectively eliminating instantaneous anomalies caused by instrument vibration, electromagnetic interference, etc., thus avoiding interference from parameter fluctuations in density calculations. By combining the fluctuation coefficient of real-time volumetric flow rate with density data correction, the indirect impact of flow rate fluctuations on density characteristics is specifically offset, resolving the problem of unstable "temperature-pressure-density" correlation under dynamic operating conditions. Through the logic of "model call to parameter preprocessing to dynamic correction," the real-time density calculation is ensured to adapt to scenarios with unknown impurities and fluctuating operating conditions.

[0104] In some embodiments, multiple pressure points are selected within a preset pressure range, and for each pressure point, the density value corresponding to the thermophysical property data of the working fluid is extracted within a preset temperature range and fitted into a density-temperature correlation curve, including: selecting multiple pressure points within a preset pressure range at set intervals to obtain multiple discrete pressure values.

[0105] Specifically, based on the actual operating conditions of pipeline transportation of supercritical / dense phase carbon dioxide containing components, the preset pressure range is the pressure range that adapts to its transportation requirements (covering the typical transportation pressure of supercritical / dense phase carbon dioxide), specifically, the preset pressure range is 0MPa~35MPa.

[0106] The pressure interval is set according to the density calculation accuracy requirements. Multiple discrete pressure points are selected evenly within the preset pressure range at this interval. All selected pressure points form multiple discrete pressure values ​​that cover the entire preset pressure range.

[0107] Furthermore, multiple temperature points are selected within a preset temperature range at set intervals to obtain multiple discrete temperature values.

[0108] Specifically, the preset temperature range is the temperature range suitable for pipeline transportation of supercritical / dense phase carbon dioxide containing components (covering common transportation temperatures of supercritical / dense phase carbon dioxide), specifically, the preset temperature range is 90K~450K.

[0109] Referring to the pressure point selection logic, the temperature interval is set according to the density characteristic change law. Multiple discrete temperature points are uniformly selected within the preset temperature range according to the interval. All selected temperature points form multiple discrete temperature values ​​covering the entire preset temperature range.

[0110] Furthermore, for each discrete pressure value, density data corresponding to each discrete temperature value under that pressure is extracted from the thermophysical property data of the working fluid to obtain multiple sets of data pairs.

[0111] Specifically, the working fluid thermophysical property data are density characteristic data within a preset temperature and pressure range retrieved from the NIST-REFPROP thermodynamic property database, based on the determined components (component type and composition ratio) of the impurity-containing carbon dioxide gas source.

[0112] For each discrete pressure value, the density data corresponding to all discrete temperature values ​​under that pressure are matched and extracted from the thermophysical property data of the working fluid. Each discrete temperature value is matched one-to-one with its corresponding density data to form multiple sets of "temperature-density" data pairs.

[0113] Furthermore, a curve fitting algorithm is used to fit each data pair to obtain the initial density-temperature correlation curve.

[0114] Specifically, for each pair of temperature-density data, numerical fitting is performed using curve fitting algorithms (such as least squares method) through data processing software (such as MATLAB). With temperature as the independent variable and density as the dependent variable, a functional relationship between the two is constructed, generating an initial density-temperature correlation curve corresponding to the discrete pressure value.

[0115] Furthermore, the deviation between the initial density-temperature correlation curve and the density data is calculated. If the deviation does not exceed a preset threshold, the density-temperature correlation curve is obtained.

[0116] Specifically, for the initial density-temperature correlation curve, the deviation between the fitted density value corresponding to each temperature point on the curve and the actual density data of the corresponding temperature point in the thermophysical property data of the working fluid is calculated.

[0117] The calculated deviation values ​​are compared with preset thresholds. If all deviation values ​​do not exceed the preset thresholds, it indicates that the fitting accuracy of the initial density-temperature correlation curve meets the requirements, and this initial curve is the final density-temperature correlation curve.

[0118] This application's embodiments, through the steps of "selecting points at intervals, extracting data pairs, fitting curves, and then verifying deviations," ensure that each curve is constructed based on discrete data covering a preset temperature and pressure range, and that the fitting results meet the deviation verification standards, thus avoiding deviations between the curves and actual density characteristics. Selecting discrete points at set intervals ensures the uniformity of data coverage; controlling the fitting accuracy through a deviation threshold provides a high-quality base curve for subsequent interpolation to construct the initial density correction model, avoiding overall model errors caused by insufficient accuracy of a single curve.

[0119] While this application provides the method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in this embodiment is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the methods shown in this embodiment or the accompanying drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0120] like Figure 3 As shown in the illustration, this application also provides a mass flow metering device 300 for carbon dioxide containing impurities. The device includes:

[0121] The acquisition module 301 is used to acquire the transport condition information of carbon dioxide containing impurities in the transport pipeline. The transport condition information includes the gas source composition, the real-time temperature of the transport pipeline, and the real-time pressure.

[0122] The acquisition module 301 is also used to acquire the real-time volumetric flow rate of carbon dioxide containing impurities and the thermal properties data of the working fluid in the delivery pipeline when the gas source composition is determined. Based on the gas source composition and the thermal properties data of the working fluid, the density correction model of carbon dioxide containing impurities under the current gas source composition is determined. The thermal properties data of the working fluid are the density data of carbon dioxide containing impurities at different temperatures and pressures. The gas source composition is the component type and composition ratio of carbon dioxide containing impurities.

[0123] The calculation module 302 is used to obtain the real-time density based on the density correction model, the real-time pressure of the carbon dioxide pipeline containing impurities, and the real-time temperature.

[0124] The calculation module 302 is also used to obtain the real-time mass flow rate of carbon dioxide containing impurities based on the real-time volumetric flow rate and the real-time density.

[0125] In some embodiments, the acquisition module 301 is further configured to obtain the fluid parameters of the delivery pipeline according to the carbon dioxide flow metering system and obtain the real-time gas source composition of the working medium in the delivery pipeline according to the gas component detector when the gas source composition is uncertain. The carbon dioxide flow metering system includes a volumetric flow meter, a temperature transmitter, a pressure transmitter and a flow manager. The fluid parameters include real-time volumetric flow rate, real-time temperature and real-time pressure.

[0126] The calculation module 302 is also used to calculate and process the thermophysical property data of the working fluid based on the real-time gas source composition and fluid parameters to obtain the real-time density;

[0127] The calculation module 302 is also used to calculate the real-time volumetric flow rate and real-time density to obtain the real-time mass flow rate of carbon dioxide containing impurities.

[0128] In some embodiments, the acquisition module 301 is further configured to acquire the real-time volumetric flow rate of carbon dioxide containing impurities in the delivery pipeline;

[0129] The acquisition module 301 is also used to acquire the real-time volumetric flow rate of carbon dioxide containing impurities in the conveying pipeline;

[0130] The acquisition module 301 is also used to acquire the thermophysical property data of the working fluid containing impurities within a preset temperature range and a preset pressure range;

[0131] The calculation module 302 is also used to select multiple pressure points within a preset pressure range, and for each pressure point, extract the density value corresponding to the thermophysical property data of the working fluid within a preset temperature range and fit it into a density-temperature correlation curve.

[0132] The acquisition module 301 is also used to interpolate the density-temperature correlation curves corresponding to multiple pressure points to obtain a density correction model.

[0133] In some embodiments, the acquisition module 301 is further configured to acquire the real-time volumetric flow rate of carbon dioxide containing impurities through a volumetric flow meter, acquire the real-time temperature in the delivery pipeline through a temperature transmitter, and acquire the real-time pressure in the delivery pipeline through a pressure transmitter.

[0134] The calculation module 302 is also used to integrate and process real-time volumetric flow rate, real-time temperature and real-time pressure through the flow manager to obtain the fluid parameters of the delivery pipeline.

[0135] The calculation module 302 is also used to obtain the gas source components through a gas component detector.

[0136] In some embodiments, the acquisition module 301 is further configured to acquire a preset impurity-containing carbon dioxide density correction model when the real-time gas source composition is uncertain.

[0137] The acquisition module 301 is also used to acquire real-time temperature and real-time pressure, and to perform smoothing filtering on the real-time temperature and real-time pressure to obtain the processed real-time temperature and real-time pressure.

[0138] The calculation module 302 is also used to input the processed real-time temperature and real-time pressure into a preset impurity-containing carbon dioxide density correction model to obtain the real-time density.

[0139] In some embodiments, the acquisition module 301 is further configured to select multiple pressure points within a preset pressure range at set intervals to obtain multiple discrete pressure values;

[0140] The acquisition module 301 is also used to select multiple temperature points within a preset temperature range at set intervals to obtain multiple discrete temperature values.

[0141] The acquisition module 301 is also used to extract the density data corresponding to each discrete temperature value under the pressure from the working fluid thermophysical property data for each discrete pressure value, and obtain multiple sets of data pairs.

[0142] The calculation module 302 is also used to fit each data pair with a curve fitting algorithm to obtain an initial density-temperature correlation curve;

[0143] The calculation module 302 is also used to calculate the deviation between the initial density-temperature correlation curve and the density data, and to obtain the density-temperature correlation curve if the deviation does not exceed a preset threshold.

[0144] Some modules in the apparatus described in this application can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0145] The apparatus or module described in the above embodiments can be implemented by a computer chip or physical entity, or by a product with a certain function. For ease of description, the above apparatus is described by dividing it into various modules according to their functions. When implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware. Of course, a module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0146] The methods, apparatus, or modules described in this application can be implemented in a computer-readable program code manner. The controller can be implemented in any suitable manner, such as a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of a memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code manner, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included within it for implementing various functions can also be considered as structures within the hardware component. Alternatively, the device used to implement various functions can be viewed as either a software module that implements the method or a structure within a hardware component.

[0147] This application also provides an apparatus, the apparatus comprising: a processor; a memory for storing processor-executable instructions; wherein, when the processor executes the executable instructions, it implements the method described in this application.

[0148] This application also provides a non-volatile computer-readable storage medium storing a computer program or instructions thereon, which, when executed, enables the method described in this application embodiment to be implemented.

[0149] Furthermore, in the various embodiments of the present invention, each functional module can be integrated into a processing module, or each module can exist independently, or two or more modules can be integrated into a single module.

[0150] The aforementioned storage media include, but are not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory can be used to store computer program instructions.

[0151] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary hardware. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, or it can be embodied in the process of data migration. The computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0152] The various embodiments described in this specification are presented in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. All or part of this application can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0153] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. A method for measuring the mass flow rate of carbon dioxide containing impurities, characterized in that, include: The system acquires transport condition information for carbon dioxide containing impurities in the transport pipeline, including gas source composition, real-time temperature of the transport pipeline, and real-time pressure. Given a defined gas source composition, the real-time volumetric flow rate of carbon dioxide containing impurities and the thermophysical property data of the working fluid in the delivery pipeline are obtained. Based on the gas source composition and the thermophysical property data of the working fluid, a density correction model for carbon dioxide containing impurities under the current gas source composition is determined. The thermophysical property data of the working fluid is the density data of carbon dioxide containing impurities at different temperatures and pressures. The gas source composition is the component type and composition ratio of the carbon dioxide containing impurities. The real-time density is obtained based on the density correction model, the real-time pressure of the carbon dioxide pipeline containing impurities, and the real-time temperature. The real-time mass flow rate of carbon dioxide containing impurities is obtained based on the real-time volumetric flow rate and the real-time density. When the gas source composition is determined, the real-time volumetric flow rate of carbon dioxide containing impurities and the thermophysical property data of the working fluid in the delivery pipeline are acquired. Based on the gas source composition and the thermophysical property data of the working fluid, a density correction model for carbon dioxide containing impurities under the current gas source composition is determined, including: Obtain the real-time volumetric flow rate of carbon dioxide containing impurities in the conveying pipeline; Acquire the thermophysical property data of the working fluid containing impurities within a preset temperature range and a preset pressure range; Multiple pressure points are selected within the preset pressure range. For each pressure point, the density value corresponding to the thermophysical property data of the working fluid is extracted within the preset temperature range and fitted into a density-temperature correlation curve. The density-temperature correlation curves corresponding to the multiple pressure points are interpolated to obtain a density correction model. The step involves selecting multiple pressure points within the preset pressure range, and for each pressure point, extracting the density value corresponding to the thermophysical property data of the working fluid within the preset temperature range and fitting it into a density-temperature correlation curve, including: Multiple pressure points are selected at set intervals within the preset pressure range to obtain multiple discrete pressure values; Multiple temperature points are selected at set intervals within the preset temperature range to obtain multiple discrete temperature values. For each discrete pressure value, the density data corresponding to each discrete temperature value under that pressure is extracted from the thermophysical property data of the working fluid to obtain multiple sets of data pairs. A curve fitting algorithm was used to fit each data pair to obtain the initial density-temperature correlation curve; The deviation between the fitted density value at each temperature point on the initial density-temperature correlation curve and the actual density data at the corresponding temperature point in the working fluid thermophysical property data is calculated. The deviation value is compared with a preset threshold. If all deviation values ​​do not exceed the preset threshold, the density-temperature correlation curve is obtained.

2. The method according to claim 1, characterized in that, The method further includes: When the gas source composition is uncertain, the fluid parameters of the delivery pipeline are obtained according to the carbon dioxide flow metering system, and the real-time gas source composition of the working medium in the delivery pipeline is obtained according to the gas component detector. The carbon dioxide flow metering system includes a volumetric flow meter, a temperature transmitter, a pressure transmitter, and a flow manager. The fluid parameters include real-time volumetric flow rate, real-time temperature, and real-time pressure. The working fluid thermophysical property data are calculated and processed based on the real-time gas source composition and the fluid parameters to obtain the real-time density; The real-time volumetric flow rate and real-time density are calculated to obtain the real-time mass flow rate of carbon dioxide containing impurities.

3. The method according to claim 2, characterized in that, When the gas source composition is uncertain, the process of obtaining the fluid parameters of the delivery pipeline based on the carbon dioxide flow metering system and obtaining the real-time gas source composition of the working fluid in the delivery pipeline based on the gas component detector includes: The volumetric flow rate of carbon dioxide containing impurities is collected by the volumetric flow meter, the real-time temperature in the delivery pipeline is collected by the temperature transmitter, and the real-time pressure in the delivery pipeline is collected by the pressure transmitter. The flow manager integrates and processes the real-time volumetric flow rate, real-time temperature, and real-time pressure to obtain the fluid parameters of the delivery pipeline. The gas source components are obtained using a gas component detector.

4. The method according to claim 2, characterized in that, The step of calculating and processing the thermophysical property data of the working fluid based on the real-time gas source composition and the fluid parameters to obtain the real-time density includes: When the composition of the real-time gas source is uncertain, a preset carbon dioxide density correction model containing impurities is obtained; Real-time temperature and real-time pressure are acquired, and the real-time temperature and real-time pressure are smoothed and filtered to obtain the processed real-time temperature and real-time pressure. The processed real-time temperature and pressure are input into a preset impurity-containing carbon dioxide density correction model to obtain the real-time density.

5. The method according to claim 1, characterized in that, The preset temperature range is 90K~450K, and the preset pressure range is 0MPa~35MPa.

6. A mass flow metering device for carbon dioxide containing impurities, characterized in that, include: The acquisition module is used to acquire the transportation condition information of carbon dioxide containing impurities in the transportation pipeline. The transportation condition information includes the gas source composition, the real-time temperature of the transportation pipeline, and the real-time pressure. The acquisition module is further configured to acquire, when the gas source composition is determined, the real-time volumetric flow rate of carbon dioxide containing impurities and the working fluid thermophysical property data in the delivery pipeline, and determine the density correction model of carbon dioxide containing impurities under the current gas source composition based on the gas source composition and the working fluid thermophysical property data. The working fluid thermophysical property data is the density data of carbon dioxide containing impurities at different temperatures and pressures, and the gas source composition is the component type and composition ratio of carbon dioxide containing impurities. The calculation module is used to obtain the real-time density based on the density correction model, the real-time pressure of the impurity carbon dioxide pipeline, and the real-time temperature. The calculation module is also used to obtain the real-time mass flow rate of carbon dioxide containing impurities based on the real-time volumetric flow rate and the real-time density. The acquisition module is further configured to, given that the gas source composition is determined, acquire the real-time volumetric flow rate of carbon dioxide containing impurities and the thermophysical property data of the working fluid in the delivery pipeline, and determine a density correction model for carbon dioxide containing impurities under the current gas source composition based on the gas source composition and the thermophysical property data of the working fluid, wherein: Obtain the real-time volumetric flow rate of carbon dioxide containing impurities in the conveying pipeline; Acquire the thermophysical property data of the working fluid containing impurities within a preset temperature range and a preset pressure range; Multiple pressure points are selected within the preset pressure range. For each pressure point, the density value corresponding to the thermophysical property data of the working fluid is extracted within the preset temperature range and fitted into a density-temperature correlation curve. The density-temperature correlation curves corresponding to the multiple pressure points are interpolated to obtain a density correction model. The acquisition module is further configured to select multiple pressure points within the preset pressure range, and for each pressure point, extract the density value corresponding to the thermophysical property data of the working fluid within the preset temperature range and fit it into a density-temperature correlation curve, wherein: Multiple pressure points are selected at set intervals within the preset pressure range to obtain multiple discrete pressure values; Multiple temperature points are selected at set intervals within the preset temperature range to obtain multiple discrete temperature values. For each discrete pressure value, the density data corresponding to each discrete temperature value under that pressure is extracted from the thermophysical property data of the working fluid to obtain multiple sets of data pairs. A curve fitting algorithm was used to fit each data pair to obtain the initial density-temperature correlation curve; The deviation between the fitted density value at each temperature point on the initial density-temperature correlation curve and the actual density data at the corresponding temperature point in the working fluid thermophysical property data is calculated. The deviation value is compared with a preset threshold. If all deviation values ​​do not exceed the preset threshold, the density-temperature correlation curve is obtained.

7. A computer device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

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