An aerosol multi-parameter dynamic monitoring system and a mass transfer source term correction method based on experiment-simulation fusion

Abstract

The present application relates to a kind of aerosol multi-parameter dynamic monitoring system and mass transfer source item correction method based on experiment-simulation fusion, wherein the aerosol multi-parameter dynamic monitoring system includes condensation nucleus control device, flue gas simulation device, multiple measuring point packed tower, condensation nucleus control device is used to generate the monodisperse aerosol condensation nucleus of single particle size;Flue gas simulation device is used to generate controllable component and flow simulation flue gas based on the monodisperse aerosol condensation nucleus;Multiple measuring point packed tower is spaced apart with at least three aerosol sampling measuring points along the height direction of tower body;Particle information acquisition system includes isokinetic sampling gun and ELPI measuring instrument.Compared with prior art, the present application can accurately obtain the mass transfer coefficient of secondary aerosol, and realize the dynamic correction of source item in numerical simulation, thereby improve the simulation accuracy and engineering adaptability of carbon capture system in absorbent loss and aerosol escape control.

Description

Technical Field

[0001] This invention relates to the field of carbon capture and storage technology, specifically to an aerosol multi-parameter dynamic monitoring system and a mass transfer source term correction method based on experimental-simulation fusion. Background Technology

[0002] Organic amine methods, due to their high maturity and absorption efficiency, have been widely used in the CO2 capture stage after fossil fuel combustion. However, in actual operation, a large amount of secondary aerosols are often generated within the absorption tower, especially under conditions of high-speed gas-liquid interface disturbance and solvent atomization, producing amine-carrying aerosols with a particle size of less than 3 micrometers. These aerosols not only carry away large amounts of organic amine solvent, leading to increased operating costs, but also may cause environmental pollution and corrosion risks, seriously affecting the economics and stability of the carbon capture system.

[0003] In organic amine carbon capture technology, the formation and mass transfer characteristics of secondary aerosols directly affect system performance. Reference patent CN118616023A proposes a method for preparing a MOF-based porous solid carbon capture adsorbent. While this method effectively captures CO2, it does not delve into the formation of secondary aerosols and their impact on system performance. Another reference patent, CN109918770A, focuses on the aerosol removal effect of rainfall, studying the scale distribution of aerosols and raindrop capture efficiency, but it does not address the dynamic mass transfer source term correction problem of aerosols during carbon capture. These patents fail to adequately address the insufficient research on the mass transfer behavior of secondary aerosols, particularly in organic amine carbon capture technology, where there is a significant technological gap in the dynamic monitoring and source term correction model construction of secondary aerosols.

[0004] Existing research largely focuses on the liquid or gas film control mechanisms in the main mass transfer process, while studies on the mass transfer behavior of secondary aerosols are insufficient. In particular, model construction often suffers from problems such as mass transfer coefficient values ​​deviating from reality and insufficient precision in source term representation. Furthermore, due to the wide particle size distribution, complex interface morphology, and significant dynamic behavior of secondary aerosols, their role in the mass transfer process cannot be accurately characterized by traditional models, thus affecting the accuracy of simulation and prediction results.

[0005] Therefore, there is an urgent need for a method that combines experimental data acquisition with model correction to model and correct parameters for secondary aerosol mass transfer behavior, so as to improve the rationality and predictive ability of source terms in numerical simulation, thereby providing theoretical support and modeling tools for solvent loss control and process optimization in organic amine carbon capture systems. Summary of the Invention

[0006] The purpose of this invention is to overcome the problems of inaccurate secondary aerosol mass transfer modeling, large source term expression deviation, and insufficient prediction ability in existing organic amine carbon capture systems. It provides a multi-parameter dynamic monitoring system for aerosols and a mass transfer source term correction method based on experiment-simulation fusion. This system can accurately obtain the mass transfer coefficient of secondary aerosols and realize the dynamic correction of source terms in numerical simulation, thereby improving the simulation accuracy and engineering adaptability of carbon capture systems in terms of absorbent loss and aerosol escape control.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] The first aspect of this invention provides an aerosol multi-parameter dynamic monitoring system, including a condensation nucleus control device, a flue gas simulation device, and a multi-point packed absorption tower, wherein specifically:

[0009] The condensation nucleus control device is used to generate monodisperse aerosol condensation nuclei with a single particle size;

[0010] The flue gas simulation device is connected to the condensation nucleus control device and is used to generate simulated flue gas with controllable components and flow rate based on the monodisperse aerosol condensation nuclei.

[0011] The inlet of the multi-point packed absorber is connected to the flue gas simulation device, and at least three aerosol sampling points are spaced apart along the height of the tower. The multi-point packed absorber is used to make the aerosol and the organic amine absorbent come into countercurrent contact to carry out mass transfer reaction, and to monitor the dynamic evolution of the concentration and particle size of the aerosol along the height of the tower through each sampling point.

[0012] The particle information acquisition system includes an isokinetic sampling gun and an ELPI measuring instrument. The isokinetic sampling gun is connected to each of the sampling points, and the ELPI measuring instrument is connected to the isokinetic sampling gun. The ELPI measuring instrument is used to acquire aerosol concentration, particle size distribution, and residence time data in real time.

[0013] Furthermore, the condensation nucleus control device includes:

[0014] Monodisperse particle storage container for storing spherical particles with a standard deviation of particle size ≤5%;

[0015] A magnetically stirred container, connected to the monodisperse particle storage container, is used to disperse monodisperse particles in deionized water to form a uniform suspension.

[0016] An ultrasonic atomizer, connected to the output end of the magnetic stirring container, is used to generate droplets with a particle size of 1-10 μm;

[0017] A silica gel drying tube is connected to the output end of the ultrasonic atomizer and is used to dehydrate the atomized droplets and output dry monodisperse condensation nuclei.

[0018] The premixing tank, connected to the output end of the silica gel drying tube, is used to uniformly mix the dried monodisperse condensation nuclei with the simulated flue gas delivered by the flue gas simulation device to form a simulated flue gas environment with stable aerosol distribution.

[0019] Furthermore, the flue gas simulation device includes:

[0020] Gas cylinder group, including CO2, N2, and O2 gas sources;

[0021] The mass flow meter group is installed on the gas delivery pipeline between the gas cylinder group and the premixing tank for the flow control of each gas.

[0022] Heating bands are wrapped around the outer wall of gas delivery pipelines used for aerosol delivery to maintain the gas temperature at 40-60℃.

[0023] Furthermore, the arrangement of sampling points in the multi-point packed absorption tower includes:

[0024] The first sampling point is 0.3-0.5m away from the upper surface of the packing layer at the bottom of the tower, and the distance between adjacent sampling points is 1 / 5-1 / 3 of the total height of the tower. These sampling points are arranged sequentially from bottom to top.

[0025] Each sampling point is equipped with a dual sampling interface. The first interface is connected to the isokinetic sampling gun, and the second interface is equipped with a pressure sensor, which is used to monitor the pressure difference fluctuation range inside the tower in real time.

[0026] Furthermore, the isokinetic sampling gun is equipped with a PID controller, and based on the PID controller, the isokinetic sampling gun dynamically adjusts the pumping rate according to the flow velocity inside the tower.

[0027] The ELPI measuring instrument contains 12 particle size channels with a detection range of 0.03-10μm and a sampling frequency of ≥1Hz. The first to third levels correspond to ultrafine particles of 0.03-0.1μm, the fourth to eighth levels correspond to fine particles of 0.1-1μm, and the ninth to twelfth levels correspond to coarse particles of 1-10μm.

[0028] A second aspect of the present invention provides a method for correcting mass transfer source terms based on experimental-simulation fusion, comprising the following steps:

[0029] S1. Experimental Data Acquisition:

[0030] Monodisperse aerosol condensation nuclei are generated by a condensation nucleus control device, and then mixed with simulated flue gas of controllable components and introduced into a multi-point packed absorption tower.

[0031] Multiple sampling points are set at intervals along the height direction of the multi-point packed absorption tower. The aerosol concentration, particle size distribution and residence time of each sampling point are collected in real time through the particle information acquisition system.

[0032] S2. Calculation of experimental mass transfer coefficient:

[0033] The experimental mass transfer coefficient was calculated based on the concentration change, average particle surface area, and residence time difference between adjacent sampling points.

[0034] S3. Mass transfer source term correction:

[0035] An initial mass transfer source term model is constructed, in which the mass transfer coefficient is expressed by the correlation between the traditional Sherwood number and the Reynolds number and the Schmidt number;

[0036] The experimental Sherwood number is inferred from the experimental mass transfer coefficient. The empirical parameters in the correlation are optimized using nonlinear regression to minimize the sum of squared residuals between the experimental mass transfer coefficient and the predicted value of the optimized correlation, thereby obtaining the corrected mass transfer source term model.

[0037] Furthermore, S2 specifically includes the following steps:

[0038] Monodisperse particles with a standard deviation of ≤5% in particle size are dissolved in deionized water and stirred in a magnetically stirred container at a speed of 800-1200 rpm for 10-15 minutes to form a uniform suspension.

[0039] The suspension was atomized into droplets with a particle size of 1-10 μm using an ultrasonic atomizer, and then dehydrated to a relative humidity of ≤5% using a silica gel drying tube to obtain dry monodisperse condensate nuclei.

[0040] The condensation nuclei are fed into a premixing tank and mixed with simulated flue gas, with an initial concentration of 1×10⁻⁶ nuclei. 4 -5×10 5 particles / cm 3 .

[0041] Furthermore, in S1, the setting of the sampling measurement points satisfies the following conditions:

[0042] The first sampling point is 0.3-0.5m away from the upper surface of the packing layer, and the distance between adjacent sampling points is 1 / 4-1 / 3 of the effective height of the absorption tower;

[0043] Each measuring point is equipped with a bidirectional sampling interface. The first interface is connected to the isokinetic sampling gun, and the second interface is equipped with a pressure sensor. The pressure sensor is used to monitor the pressure difference fluctuation range inside the tower in real time.

[0044] Furthermore, in S1, the specific process for generating monodisperse aerosol condensation nuclei includes:

[0045] Concentration change extraction: Based on the aerosol concentration data of adjacent measuring points recorded by the particle information acquisition system, the concentration change per unit volume between the two sampling measuring points is calculated to reflect the total mass transfer of aerosols.

[0046] Particle surface area calibration: Based on the particle size distribution data of each sampling point, the average surface area of ​​the particle group is calculated using the spherical particle assumption model to characterize the scale of the aerosol mass transfer interface.

[0047] Dynamic time correlation and coefficient synthesis: The residence time difference of aerosol between adjacent measuring points is calculated by combining the local flow velocity in the absorption tower and the distance between measuring points. The ratio of the concentration change to the average surface area is divided by the residence time difference to obtain the experimental mass transfer coefficient.

[0048] Furthermore, S3 specifically includes the following steps:

[0049] An initial model for the mass transfer source term is established based on empirical formulas. The mass transfer coefficient is expressed as a dimensionless correlation between the Reynolds number of the fluid motion state and the Schmidt number of the material diffusion characteristics. An initial combination of empirical parameters is defined as the starting point for optimization.

[0050] The experimental Sherwood number, a dimensionless mass transfer correlation coefficient under actual working conditions, is derived by back-calculating the experimental mass transfer coefficient. A nonlinear regression algorithm is used to dynamically adjust the empirical parameters in the initial correlation to minimize the cumulative deviation between the experimental values ​​and the model predictions, and finally, the corrected mass transfer source term model is output.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. The monodisperse particle generation system in this invention can control the concentration and size of condensation nuclei entering the absorption tower and unify the original particle size, and can more clearly obtain information on particle size growth caused by mass transfer at adjacent measuring points.

[0053] 2. This invention directly obtains the mass transfer coefficient of secondary aerosols through experimental means, corrects the expression of mass transfer coefficient based on the assumption of ideal liquid film or gas film in traditional models, and improves the accuracy of describing the actual mass transfer process of secondary aerosols.

[0054] 3. The source term correction model constructed in this invention considers key factors such as heterogeneous nucleation, aggregation, local supersaturation, and particle mass transfer driving force, which breaks through the limitations of fixed source term expression in traditional CFD models and makes the simulation results closer to the actual operating state. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the overall structure of the aerosol multi-parameter dynamic monitoring system in this invention;

[0056] Figure 2 This is a schematic diagram of the condensation nucleus control device of the present invention;

[0057] Figure 3This is a schematic diagram of the flue gas simulation device of the present invention;

[0058] Figure 4 This is a schematic diagram of the three modules of the multi-measuring-point packed absorption tower of the present invention;

[0059] Figure 5 This is a schematic diagram of the four modules of the particle information acquisition system of the present invention;

[0060] In the picture:

[0061] 1.1 Monodisperse particles; 1.2 Magnetic stirring device; 1.3 Atomizer device; 1.4 Silica gel drying tube device; 1.5 Premixing tank;

[0062] 2.1 Gas cylinder assembly; 2.2 Mass flow meter assembly; 2.3 Heating belt;

[0063] 3.1 Particle sampling points;

[0064] 4.1 Isokinetic sampling gun; 4.2 ELPI measuring instrument. Detailed Implementation

[0065] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Component models, material names, connection structures, circuit structures, control methods, algorithms, and other features not explicitly described in this technical solution are considered common technical features disclosed in the prior art.

[0066] Example 1

[0067] In this embodiment, the aerosol multi-parameter dynamic monitoring system includes a condensation nucleus control device 1, a flue gas simulation device 2, and a multi-point packed absorption tower 3, as detailed below. Figures 1 to 5 .

[0068] The condensation nucleus control device 1 is used to generate monodisperse aerosol condensation nuclei with a single particle size;

[0069] The flue gas simulation device 2 is connected to the condensation nucleus control device 1 and is used to generate simulated flue gas with controllable components and flow rate based on the monodisperse aerosol condensation nuclei.

[0070] The inlet of the multi-point packed absorption tower 3 is connected to the flue gas simulation device 2, and at least three aerosol sampling points 3.1 are spaced apart along the height of the tower. The multi-point packed absorption tower 3 is used to make the aerosol and the organic amine absorption liquid come into countercurrent contact to carry out mass transfer reaction, and to monitor the dynamic evolution of the concentration and particle size of the aerosol along the height of the tower through each sampling point 3.1.

[0071] The particle information acquisition system 4 includes an isokinetic sampling gun 4.1 and an ELPI measuring instrument 4.2. The isokinetic sampling gun 4.1 is connected to each of the sampling points 3.1, and the ELPI measuring instrument 4.2 is connected to the isokinetic sampling gun 4.1. The ELPI measuring instrument 4.2 is used to acquire aerosol concentration, particle size distribution, and residence time data in real time.

[0072] The condensation nucleus control device 1 includes a monodisperse particle storage container 1.1, a magnetic stirring container 1.2, an ultrasonic atomizer 1.3, a silica gel drying tube 1.4, and a premixing tank 1.5. Specifically: the monodisperse particle storage container 1.1 stores spherical particles with a standard deviation of particle size ≤5%; the magnetic stirring container 1.2 is connected to the monodisperse particle storage container 1.1 and is used to disperse the monodisperse particles in deionized water to form a uniform suspension; the ultrasonic atomizer 1.3 is connected to the output end of the magnetic stirring container 1.2 and is used to generate droplets with a particle size of 1-10μm; the silica gel drying tube 1.4 is connected to the output end of the ultrasonic atomizer 1.3 and is used to dehydrate the atomized droplets to output dried monodisperse condensation nuclei; the premixing tank 1.5 is connected to the output end of the silica gel drying tube 1.4 and is used to uniformly mix the dried monodisperse condensation nuclei with the simulated flue gas delivered by the flue gas simulation device 2 to form a simulated flue gas environment with a stable aerosol distribution.

[0073] The flue gas simulation device 2 includes a gas cylinder group 2.1, a mass flow meter group 2.2, and a heating belt 2.3. Specifically: the gas cylinder group 2.1 includes gas sources of CO2, N2, and O2; the mass flow meter group 2.2 is located on the gas delivery pipeline between the gas cylinder group 2.1 and the premixing tank 1.5 for controlling the flow rate of each gas; the heating belt 2.3 is wrapped around the outer wall of the gas delivery pipeline used for aerosol delivery to maintain the gas temperature at 40-60℃.

[0074] The isokinetic sampling gun 4.1 is equipped with a PID controller, and based on the PID controller, the isokinetic sampling gun 4.1 dynamically adjusts the pumping rate according to the flow velocity inside the tower;

[0075] The ELPI measuring instrument 4.2 includes 12 particle size channels with a detection range of 0.03-10μm and a sampling frequency of ≥1Hz. The first to third levels correspond to ultrafine particles of 0.03-0.1μm, the fourth to eighth levels correspond to fine particles of 0.1-1μm, and the ninth to twelfth levels correspond to coarse particles of 1-10μm.

[0076] In practice, the multi-point absorption tower 3 is a packed tower.

[0077] The top of the multi-point absorption tower 3 is provided with an organic amine absorbent liquid inlet and a purified gas outlet; the bottom of the multi-point absorption tower 3 is provided with a simulated flue gas injection port and a rich amine liquid outlet.

[0078] Example 2

[0079] The core principle of this embodiment is as follows: monodisperse particles are generated by the condensation nucleus control device 1 to simulate the real flue gas environment. Combined with the dynamic monitoring data of aerosol size / concentration in the multi-point packed absorption tower, the experimental mass transfer coefficient (Kexp) of secondary aerosols along the tower height is obtained by inversion. Based on this, the Sherwood number correlation in the CFD model is reconstructed, and the empirical parameters of the traditional mass transfer source term are optimized by nonlinear regression. The static Ranz-Marshall formula is upgraded to a dynamic calibration model, so that the numerical simulation can accurately quantify the coupling effect of heterogeneous nucleation and aggregation on aerosol mass transfer growth. Finally, the prediction error of aerosol escape in the amine carbon capture system is reduced to less than 10%, providing a high-precision digital tool for solvent loss control.

[0080] The mass transfer source term correction method based on experiment-simulation fusion in this embodiment includes the following steps:

[0081] S1. Experimental Data Acquisition:

[0082] Monodisperse aerosol condensation nuclei are generated by the condensation nuclei control device 1, and then mixed with simulated flue gas of controllable components and introduced into the multi-measuring-point packed absorption tower 3.

[0083] Multiple sampling points 3.1 are set at intervals along the height direction of the multi-point packed absorption tower 3. The aerosol concentration, particle size distribution and residence time of each sampling point are collected in real time by the particle information acquisition system 4.

[0084] In S1, the setting of the sampling measurement point 3.1 satisfies the following conditions:

[0085] The first sampling point is 0.3-0.5m away from the upper surface of the packing layer, and the distance between adjacent sampling points is 1 / 4-1 / 3 of the effective height of the absorption tower;

[0086] Each measuring point is equipped with a bidirectional sampling interface. The first interface is connected to the isokinetic sampling gun 4.1, and the second interface is equipped with a pressure sensor. The pressure sensor is used to monitor the pressure difference fluctuation range inside the tower in real time.

[0087] In specific implementation, the process of generating monodisperse aerosol condensation nuclei in S1 includes:

[0088] Monodisperse particles with a standard deviation of ≤5% 1.1 are dissolved in deionized water and stirred in a magnetically stirred container 1.2 at a speed of 800-1200 rpm for 10-15 minutes to form a uniform suspension;

[0089] The suspension is atomized into droplets with a particle size of 1-10 μm using an ultrasonic atomizer 1.3, and then dehydrated to a relative humidity of ≤5% using a silica gel drying tube 1.4 to obtain dry monodisperse condensate nuclei.

[0090] The condensate nuclei are fed into premix tank 1.5 and mixed with simulated flue gas, with an initial concentration of 1×10⁻⁶ condensate nuclei. 4 -5×10 5 particles / cm 3 .

[0091] S2. Calculation of experimental mass transfer coefficient:

[0092] The experimental mass transfer coefficient was calculated based on the concentration change, average particle surface area, and residence time difference at adjacent sampling points 3.1.

[0093] In practice, S2 includes the following steps:

[0094] Concentration change extraction: Based on the aerosol concentration data of adjacent measuring points recorded by the particle information acquisition system 4, the concentration change per unit volume between the two sampling measuring points 3.1 is calculated to reflect the total mass transfer of aerosols;

[0095] Particle surface area calibration: Based on the particle size distribution data of each sampling point in 3.1, the average surface area of ​​the particle group is calculated through the spherical particle assumption model to characterize the scale of the aerosol mass transfer interface.

[0096] Dynamic time correlation and coefficient synthesis: The residence time difference of aerosol between adjacent measuring points is calculated by combining the local flow velocity in the absorption tower and the distance between measuring points. The ratio of the concentration change to the average surface area is divided by the residence time difference to obtain the experimental mass transfer coefficient.

[0097] S3. Mass transfer source term correction:

[0098] An initial mass transfer source term model is constructed, in which the mass transfer coefficient is expressed by the correlation between the traditional Sherwood number and the Reynolds number and the Schmidt number;

[0099] The experimental Sherwood number is inferred from the experimental mass transfer coefficient. The empirical parameters in the correlation are optimized using nonlinear regression to minimize the sum of squared residuals between the experimental mass transfer coefficient and the predicted value of the optimized correlation, thereby obtaining the corrected mass transfer source term model.

[0100] In practice, S3 includes the following steps:

[0101] An initial model for the mass transfer source term is established based on empirical formulas. The mass transfer coefficient is expressed as a dimensionless correlation between the Reynolds number of the fluid motion state and the Schmidt number of the material diffusion characteristics. An initial combination of empirical parameters is defined as the starting point for optimization.

[0102] The experimental Sherwood number, a dimensionless mass transfer correlation coefficient under actual working conditions, is derived by back-calculating the experimental mass transfer coefficient. A nonlinear regression algorithm is used to dynamically adjust the empirical parameters in the initial correlation to minimize the cumulative deviation between the experimental values ​​and the model predictions, and finally, the corrected mass transfer source term model is output.

[0103] In practical implementation, the particle information acquisition system 4 and the isokinetic sampling gun 4.1 can be matched with the gas velocity of the ELPI measuring instrument 4.2 to uniformly extract the aerosol from the absorption tower. The particle information acquisition system 4 collects aerosol information from multiple measuring points 3 on the packed absorption tower, obtaining the particle size Di, particle concentration Ci, and average particle surface area A at each measuring point, and calculates the residence time Δti of adjacent measuring points based on the upward distance. Based on the change in particle surface flux, the true mass transfer coefficient Kexp value (e.g., Eq.1) of the amine aerosol in the absorption tower along the upward direction of the flue gas is derived.

[0104]

[0105] Where ΔC i dm represents the amine vapor concentration difference between adjacent measuring points (the i-th measuring point and the (i+1)-th measuring point), and dm represents the mass change of aerosol particles absorbed or released during the time interval dt.

[0106] In numerical simulations, the mass transfer process and particle growth in multiphase systems based on the Euler-Euler model are described by changes in the mass transfer source term. As shown in Eq.2, the mass transfer source term m i,source Describes the mass exchange between phases:

[0107] m i,source =K cfd ·(C & -C eq )·S Eq.2

[0108] S is the interphase contact area per unit volume, C & and C eq These represent the far-field concentration and the surface equilibrium concentration during mass transfer, respectively, and can be obtained through simulation calculations. The mass transfer coefficient Kcfd and the Sherwood number have the following mathematical relationship (see Eq. 3):

[0109] K cfd =(S hcfd ·D gas ) / D p Eq.3

[0110] Gas phase diffusion coefficient D gas With particle size D pGiven that Shcfd is considered to be related to the Reynolds number (Re) and the Schmidt number (Sc), see Eq. 4 for the specific form:

[0111]

[0112] a corr b corr c corr d corr These are empirical parameters and need to be determined experimentally. In the above experiments, after obtaining the true mass transfer coefficient Kexp, the experimental Sherwood number (Sh...) can be derived. exp By using the nonlinear regression method of Eq.5, empirical parameter values ​​that are highly consistent with experimental data (with small residuals) can be obtained and then substituted into Shcfd to complete the numerical simulation of mass transfer source terms and mass transfer coefficients.

[0113]

[0114] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A method for correcting mass transfer source terms based on experimental-simulation fusion, characterized in that, The mass transfer source term correction method is implemented using an aerosol multi-parameter dynamic monitoring system, which includes: A condensation nucleus control device (1) is used to generate monodisperse aerosol condensation nuclei with a single particle size; The flue gas simulation device (2) is connected to the condensation nucleus control device (1) and is used to generate simulated flue gas with controllable components and flow rate based on the monodisperse aerosol condensation nuclei. The multi-point packed absorption tower (3) has its inlet connected to the flue gas simulation device (2), and at least three aerosol sampling points (3.1) are spaced apart along the height of the tower. The multi-point packed absorption tower (3) is used to make the aerosol and the organic amine absorption liquid come into countercurrent contact to undergo mass transfer reaction, and to monitor the dynamic evolution of the concentration and particle size of the aerosol along the height of the tower through each sampling point (3.1). The particle information acquisition system (4) includes an isokinetic sampling gun (4.1) and an ELPI measuring instrument (4.2). The isokinetic sampling gun (4.1) is connected to each of the sampling points (3.1), and the ELPI measuring instrument (4.2) is connected to the isokinetic sampling gun (4.1). The ELPI measuring instrument (4.2) is used to acquire aerosol concentration, particle size distribution, and residence time data in real time. The mass transfer source term correction method includes the following steps: S1. Data Acquisition: Monodisperse aerosol condensation nuclei are generated by the condensation nuclei control device (1), and then mixed with simulated flue gas of controllable components and introduced into a multi-point packed absorption tower (3). Multiple sampling points (3.1) are set at intervals along the height direction of the multi-point packed absorption tower (3), and the aerosol concentration, particle size distribution and residence time of each sampling point are collected in real time through the particle information acquisition system (4). S2. Calculation of experimental mass transfer coefficient: The experimental mass transfer coefficient was calculated based on the concentration change, average particle surface area, and residence time difference at adjacent sampling points (3.1). S3. Mass transfer source term correction: An initial mass transfer source term model is constructed, in which the mass transfer coefficient is expressed by the correlation between the traditional Sherwood number and the Reynolds number and the Schmidt number; The experimental Sherwood number is inferred from the experimental mass transfer coefficient. The empirical parameters in the correlation are optimized by nonlinear regression to minimize the sum of squared residuals between the experimental mass transfer coefficient and the predicted value of the optimized correlation, thereby obtaining the corrected mass transfer source term model. S2 specifically includes the following steps: Concentration change extraction: Based on the aerosol concentration data of adjacent measuring points recorded by the particle information acquisition system (4), the concentration change per unit volume between the two sampling measuring points (3.1) is calculated to reflect the total mass transfer of aerosols; Particle surface area calibration: Based on the particle size distribution data of each sampling point (3.1), the average surface area of ​​the particle group is calculated by the spherical particle assumption model to characterize the scale of the aerosol mass transfer interface. Dynamic time correlation and coefficient synthesis: The residence time difference of aerosol between adjacent measuring points is calculated by combining the local flow velocity in the absorption tower and the distance between measuring points. The ratio of the concentration change to the average surface area is divided by the residence time difference to obtain the experimental mass transfer coefficient.

2. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, The condensation nucleus control device (1) includes: Monodisperse particle storage container (1.1) for storing spherical particles with a standard deviation of particle size ≤5%; A magnetic stirring container (1.2) is connected to the monodisperse particle storage container (1.1) for dispersing monodisperse particles in deionized water to form a uniform suspension; An ultrasonic atomizer (1.3) is connected to the output end of the magnetic stirring container (1.2) to generate droplets with a particle size of 1-10 μm; A silica gel drying tube (1.4) is connected to the output end of the ultrasonic atomizer (1.3) for dehydrating the atomized droplets and outputting dry monodisperse condensation nuclei. The premix tank (1.5) is connected to the output end of the silica gel drying tube (1.4) and is used to uniformly mix the dried monodisperse condensation nuclei with the simulated flue gas delivered by the flue gas simulation device (2) to form a simulated flue gas environment with stable aerosol distribution.

3. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, The flue gas simulation device (2) includes: The gas cylinder group (2.1) includes gas sources of CO2, N2, and O2; The mass flow meter group (2.2) is installed on the gas delivery pipeline between the gas cylinder group (2.1) and the premix tank (1.5) for the flow control of each gas. Heating band (2.3) is wrapped around the outer wall of the gas delivery pipeline used for aerosol delivery to maintain the gas temperature at 40-60℃.

4. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, The arrangement of the sampling points (3.1) of the multi-point packed absorption tower (3) includes: The first sampling point is 0.3-0.5m away from the upper surface of the packing layer at the bottom of the tower, and the distance between adjacent sampling points is 1 / 5-1 / 3 of the total height of the tower. These sampling points are arranged sequentially from bottom to top. Each sampling point (3.1) is equipped with a dual sampling interface. The first interface is connected to the isokinetic sampling gun (4.1), and the second interface is equipped with a pressure sensor. The pressure sensor is used to monitor the pressure difference fluctuation range inside the tower in real time.

5. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, The isokinetic sampling gun (4.1) is equipped with a PID controller, and based on the PID controller, the isokinetic sampling gun (4.1) dynamically adjusts the pumping rate according to the flow velocity inside the tower. The ELPI measuring instrument (4.2) includes 12 particle size channels with a detection range of 0.03-10μm and a sampling frequency of ≥1Hz. The first to third levels correspond to ultrafine particles of 0.03-0.1μm, the fourth to eighth levels correspond to fine particles of 0.1-1μm, and the ninth to twelfth levels correspond to coarse particles of 1-10μm.

6. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, In S1, the specific process of generating monodisperse aerosol condensation nuclei includes: Monodisperse particles with a standard deviation of particle size ≤5% are dissolved in deionized water and stirred in a magnetically stirred container (1.2) at a speed of 800-1200 rpm for 10-15 minutes to form a uniform suspension. The suspension was atomized into droplets with a particle size of 1-10 μm by an ultrasonic atomizer (1.3), and then dehydrated to a relative humidity of ≤5% by a silica gel drying tube (1.4) to obtain dry monodisperse condensate nuclei; The condensate nuclei are fed into a premixing tank (1.5) and mixed with simulated flue gas, with an initial concentration of 1×10⁻⁶ condensate nuclei. 4 -5×10 5 particles / cm 3 .

7. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, In S1, the setting of the sampling measurement point (3.1) satisfies the following conditions: The first sampling point is 0.3-0.5m away from the upper surface of the packing layer, and the distance between adjacent sampling points is 1 / 4-1 / 3 of the effective height of the absorption tower; Each measuring point is equipped with a bidirectional sampling interface. The first interface is connected to the isokinetic sampling gun (4.1), and the second interface is equipped with a pressure sensor. The pressure sensor is used to monitor the pressure difference fluctuation range inside the tower in real time.

8. The method for correcting mass transfer source terms based on experimental-simulation fusion according to claim 1, characterized in that, S3 specifically includes the following steps: An initial model for the mass transfer source term is established based on empirical formulas. The mass transfer coefficient is expressed as a dimensionless correlation between the Reynolds number of the fluid motion state and the Schmidt number of the material diffusion characteristics. An initial combination of empirical parameters is defined as the starting point for optimization. The experimental Sherwood number, a dimensionless mass transfer correlation coefficient under actual working conditions, is derived by back-calculating the experimental mass transfer coefficient. A nonlinear regression algorithm is used to dynamically adjust the empirical parameters in the initial correlation to minimize the cumulative deviation between the experimental values ​​and the model predictions, and finally, the corrected mass transfer source term model is output.

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