A supercritical carbon dioxide working medium trace impurity sampling distortion calibration correction method

Abstract

This invention discloses a method for calibrating and correcting sampling distortion of trace impurities in supercritical carbon dioxide working fluid. It relates to the field of supercritical carbon dioxide trace impurity detection technology, primarily targeting the entire process from the extraction of a supercritical carbon dioxide sample from the system loop to the inlet of the detection instrument. The method establishes the phase path changes, solubility changes, segmental losses, phase distribution, internal standard recovery, reference correction, and mass closure relationships of the target trace impurity along the sampling path. The recovery rates and correction parameters for different target impurities, different carbon dioxide states, and different sampling path conditions are recorded tabularly, thereby correcting the concentration to the in-situ concentration under the original system loop conditions. This invention improves the comparability of data between different sampling points, different operating conditions, and different test batches, providing a more reliable data foundation for working fluid quality evaluation, impurity source identification, purification control, material corrosion risk assessment, and long-term safe operation of supercritical carbon dioxide energy conversion systems.

Description

Technical Field

[0001] This invention relates to the field of supercritical carbon dioxide trace impurity detection technology, specifically to a method for calibration and correction of sampling distortion of supercritical carbon dioxide working fluid trace impurities. Background Technology

[0002] Supercritical carbon dioxide energy conversion systems are characterized by high cycle efficiency, compact equipment, low working fluid flow resistance, and a wide range of applicable heat sources, making them promising candidates for applications in thermal power unit retrofitting, solar thermal power generation, nuclear power generation, industrial waste heat utilization, and advanced power cycles. However, in actual operation, the circulating working fluid is not ideally pure carbon dioxide. Trace impurities can be introduced into the circulating working fluid from the initial system charge, equipment processing residues, lubricating oil, adsorbents on pipeline walls, air introduced during maintenance, material venting during high-temperature operation, chemical reaction gas products, and organic matter decomposition. Although these impurities are present in low concentrations, they can affect the thermal properties of supercritical carbon dioxide, heat transfer and flow characteristics, compressor and turbine operational stability, and material service behavior. In severe cases, they can induce corrosion, carbon buildup, deposits, blockages, lubricating oil deterioration, and uncontrolled working fluid quality.

[0003] Among the impurities in supercritical carbon dioxide working fluid, moisture, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products, oxygen-containing organic matter, and other soluble, condensable, or easily adsorbed trace components are of particular concern. These components may exhibit certain solubility or entrainment stability in high-pressure, high-density carbon dioxide and migrate within the system along with the working fluid. When the pressure, temperature, and density of the working fluid change, its solubility, distribution state, and form in carbon dioxide may alter, leading to precipitation, condensation, adsorption, retention, re-evaporation, or redistribution. In contrast, non-condensable or weakly condensable gases such as nitrogen, oxygen, argon, carbon monoxide, hydrogen, and methane are generally less prone to significant condensation and precipitation, but can still be affected by factors such as dead volume dilution, leakage, wall reactions, flow integral errors, and instrument drift. Therefore, monitoring trace impurities in supercritical carbon dioxide working fluid requires not only obtaining the instrument detection values ​​after sampling but also determining whether these values ​​represent the in-situ composition or true concentration under the in-situ temperature and pressure conditions of the system loop.

[0004] Currently, trace impurities in supercritical carbon dioxide circulating working fluid are typically detected by sampling and then entering a trace water analyzer, gas chromatograph, total hydrocarbon analyzer, or other ambient temperature and pressure analytical instruments. For some non-condensable gases, under conditions of no significant leakage, dilution, or reaction loss during sampling, the ambient temperature and pressure detection results can reflect the gas phase composition of the original working fluid to a certain extent. However, for water, organic matter, lubricating oil cracking products, and heavy hydrocarbons, after the sample is extracted from the high-temperature, high-pressure supercritical state, it usually undergoes processes such as cooling, depressurization, throttling, expansion, and transport. During this process, carbon dioxide may transform from a supercritical single-phase state to a high-pressure gas, a low-pressure gas, or a partially two-phase state, resulting in significant changes in its density and solubility. Trace impurities originally dissolved or entrained in supercritical carbon dioxide may undergo unexpected precipitation, adsorption, retention, or loss in sampling valves, depressurization ports, cooling sections, sampling tube walls, filter elements, or pretreatment units. Consequently, the detected values ​​may deviate from the in-situ concentrations under the in-situ temperature and pressure conditions of the system loop.

[0005] To reduce errors introduced during sampling, existing technologies typically employ controlled sampling, insulated transport, back pressure control, controlled cooling, phase separation detection, condensate collection, and multi-branch analysis to minimize the possibility of uncontrolled phase transitions and component losses before the sample enters the instrument. These approaches can improve the detection accuracy of moisture, oils, and heavy hydrocarbons to some extent, and provide information on the total amount of the sample after sampling through gas phase component detection and condensate component measurement. However, these approaches primarily address the issue of "how to sample and measure more stably." They still lack systematic quantitative calibration and correction methods for changes in solubility, phase redistribution, wall adsorption, valve retention, condensation loss, dead volume dilution, and changes in detection recovery rate that have occurred or may occur throughout the sampling process.

[0006] Current routine calibration of analytical instruments often employs atmospheric pressure standard gas, standard liquid, or instrument self-calibration. The calibration target is typically the detector response, rather than the overall recovery rate of the supercritical carbon dioxide sample from the loop to the instrument inlet. For supercritical carbon dioxide systems, the dissolution, entrainment, adsorption, and precipitation behavior of target impurities in high-pressure, high-density carbon dioxide differs significantly from their state in atmospheric pressure gas or liquid standard samples. Routine response calibration of the analytical instrument alone cannot reflect phase transition losses, adsorption losses, retention losses, and dilution errors along the sampling path. This is particularly problematic for components such as lubricating oil cracking products, heavy hydrocarbons, light hydrocarbons, and oxygen-containing organic compounds, whose recovery rates may vary significantly under different pressures, temperatures, carbon dioxide densities, pipeline wall materials, and depressurization paths. Without distortion calibration targeting the sampling path, measurement results may suffer from systematic underestimation, batch-to-batch incomparability, or difficulty in cross-sectional comparisons between different sampling points.

[0007] Furthermore, in actual engineering systems or test loops, the temperature, pressure, sampling distance, pipeline layout, and pretreatment conditions at different sampling points often vary. Even when using the same analytical instrument, different sampling paths may exhibit different distortion characteristics. For example, high-temperature sampling may be affected by insufficient heating, local cooling at the pressure drop port, and high-temperature wall reactions; cold-end or near-critical zone sampling may be more susceptible to density abrupt changes, localized agglomeration, and dead volume dilution; long-distance sampling pipelines may produce more pronounced adsorption, retention, and memory effects. If instrument readings at each sampling point are directly compared, the detection deviation caused by the sampling path may be misjudged as a difference in the quality of the system's working fluid, thereby affecting the identification of impurity sources, purification system operation strategies, material compatibility evaluation, and operational risk assessment.

[0008] Therefore, the field of supercritical carbon dioxide working fluid trace impurity monitoring still requires a distortion calibration and in-situ concentration correction method specifically for the sampling process itself. This method should differ from simple analytical instrument response calibration, and also from methods that improve detection accuracy solely through controlled sampling and phase separation measurements. It should be able to evaluate the recovery rate and distortion degree of different target impurities under different sampling paths, and correct the instrument-measured concentration based on the sampling path, working fluid state, target impurity properties, and detection results, thereby correcting the post-sampling detection value to the equivalent in-situ concentration under the in-situ temperature and pressure conditions of the system loop. Summary of the Invention

[0009] To address the shortcomings of existing technologies, the present invention aims to provide a method for calibrating and correcting the sampling distortion of trace impurities in supercritical carbon dioxide working fluid. This method can improve the comparability of data between different sampling points, different operating conditions, and different test batches, and provide a more reliable data foundation for evaluating the quality of working fluid, identifying impurity sources, controlling purification, assessing material corrosion risks, and ensuring long-term safe operation of supercritical carbon dioxide energy conversion systems.

[0010] This invention is achieved through the following technical solution:

[0011] A method for calibrating and correcting sampling distortion of trace impurities in supercritical carbon dioxide working fluid includes the following steps:

[0012] S1: Determine the type of the target trace impurity, the sampling path to be calibrated, and the object to be calibrated;

[0013] S2: Divide the sampling path into several functional segments and obtain the sampling path parameters for each functional segment;

[0014] S3: Under calibration conditions, based on the target trace impurity type, obtain a supercritical carbon dioxide standard sample with a known addition amount or known in-situ concentration of that type;

[0015] S4: Use supercritical carbon dioxide that is free of the target trace impurities or whose target trace impurity content is lower than the preset threshold to perform blank calibration on the sampling path to be calibrated, record and obtain the blank deduction amount of the sampling path under blank conditions.

[0016] S5: Introduce the supercritical carbon dioxide standard sample into the sampling path to be calibrated to obtain the segmented detection quantity of each functional segment;

[0017] S6: Based on the segmented detection amount and combined with the blank deduction amount, the transmission throughput and segmented effective recovery rate of the target trace impurities in each functional segment are obtained through the mass closure relationship, so as to obtain the recovery rate of the sampling path in a comprehensive manner.

[0018] S7: By adjusting the state parameters, target trace impurity parameters, and sampling path parameters of the supercritical carbon dioxide standard sample, and repeating steps S3-S6, various detection and calculation results under different conditions are obtained, thereby establishing a tabular sampling distortion calibration matrix.

[0019] S8: During actual sampling, the actual sampling conditions are matched with the tabular sampling distortion calibration matrix to find suitable sampling conditions, and the corresponding detection and calculation results are output for correction.

[0020] Further optimization is made in step S1:

[0021] The identified target trace impurities include: moisture, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products and oxygen-containing organic matter, as well as trace components that are soluble, condensable, easily adsorbed or easily undergo partition changes, and non-condensable or weakly condensable gases.

[0022] The sampling path to be calibrated is the entire path that the sample travels from the sampling point in the supercritical carbon dioxide system loop to the inlet of the detection instrument, including one or more of the following: sampling valve, pressure reducing element, transmission pipeline, heat tracing pipeline, cooling section, filter element, separation unit, collection unit, pretreatment unit for detection and inlet of the detection instrument;

[0023] The calibration targets include one or more of the following during the sampling process: changes in carbon dioxide density, changes in solubility, valve retention, tube wall adsorption, condensation, filtration retention, separation loss, dead volume dilution, changes in pretreatment recovery rate, and detection response drift of the target trace impurities.

[0024] In a further optimization, step S2 also includes the following steps:

[0025] Based on the sampling path parameters of each functional segment, a segmented state trajectory of the target trace impurity in the sampling path is established.

[0026] Establish the degree of change in carbon dioxide density D in the k-th functional segment.k The calculation model is used to simultaneously establish the solubility margin M of the i-th type of target trace impurity in the k-th functional segment. k,i Computational model;

[0027] When D k Exceeding the preset threshold, or M k,i If the value is less than the preset threshold, it is determined that there is a risk that the target trace impurities may precipitate, condense, adsorb, or redistribute between phases due to the decrease in carbon dioxide density, the decrease in solubility, or the change in phase path.

[0028] Further optimization, step S6 specifically includes the following steps:

[0029] Based on the segmented detection quantities, the existence state of the target trace impurities after sampling is divided into gas phase, condensed phase, adsorbed phase, cut-off phase, residual phase, and unrecovered loss; wherein, for the i-th type of target trace impurity, the material balance relationship in its calibration process is: n 0,i = n g,i + n c,i + n a,i + n f,i + n r,i + n lost,i In the formula, n 0,i n represents the known amount or equivalent in-situ amount of the i-th target trace impurity in a supercritical carbon dioxide standard sample; g,i For gas phase detection quantity; n c,i n represents the amount of condensed phase recovered. a,i n represents the amount of material adsorbed and recovered from the pipe wall or component. f,i For the amount of material to be filtered or retained for recovery; n r,i For pretreatment or other residual recovery amounts; n lost,i This refers to the amount of unrecovered losses.

[0030] Based on material balance, the distribution ratio of the target trace impurity in different phases or positions is obtained: F g,i =n g,i / n 0,i ;F c,i = n c,i / n 0,i ;F a,i = n a,i / n 0,i In the formula, F g,i F c,i F a,i These represent the distribution ratios of the i-th target trace impurity in the gas phase, condensed phase, and adsorbed phase, respectively.

[0031] Subsequently, the transport throughput and segmented effective recovery rate of the i-th target trace impurity in the k-th functional segment were calculated: T k,i = n out,k,i / n in,k,i E k,i = (n out,k,i + n rec,k,i ) / n in,k,i In the formula, T k,i E represents the transport throughput of the i-th target trace impurity in the k-th functional segment. k,i n represents the segmented effective recovery rate of the i-th target trace impurity in the k-th functional segment; in,k,i For the i-th type of target trace impurity mass entering the k-th functional segment; n out,k,i For the i-th type of target trace impurity mass leaving the k-th functional segment and entering the next functional segment or detection unit; n rec,k,i The target trace impurity quantity included in the correction amount is the amount of the i-th type of trace impurity that is recovered in the k-th functional segment through agglomerate collection, filtration retention, tube wall flushing, thermal desorption, solvent extraction, or pre-detection treatment.

[0032] Considering the throughput and effective recovery rate of each functional segment, when the target trace impurity passes through each functional segment continuously in gaseous form without measurable agglomeration, adsorption, retention, or residual recovery, the gas-phase transport recovery rate of the entire sampling path is: R g,i = T 1,i · T 2,i · …… · T m,i When the target trace impurity undergoes aggregation, adsorption, retention, residue, or phase separation recovery during the sampling path, the overall effective recovery rate of the entire sampling path is R. p,eff,i =(n g,i + n c,i + n a,i + n f,i + n r,i ) / n 0,i .

[0033] In a further optimization, step S7 also includes a step of correcting the detection quantity based on the target trace impurity type, based on the tabulated sampling distortion calibration matrix:

[0034] When the target trace impurity is moisture, the adsorption capacity, adsorption rate, desorption rate, response hysteresis time and tailing integral of the sampling path for moisture are obtained through blank purging, calibration of water-containing standard samples and recovery of dried samples.

[0035] In actual moisture detection, the output value of the trace moisture analyzer is corrected based on the background of blank water release before sampling, the rise time of the current moisture detection curve, the stable plateau, the integral response, and the desorption tail after sampling, to obtain the corrected effective moisture detection quantity: n w,corr = n w,m - n b,w + n des,w + n ads,w In the formula, n w,corr This is the corrected effective moisture detection amount; n w,m The water content measured by a trace water analyzer; n b,w Water content for blank background; n des,w For sampling path desorption tail back calculation; n ads,w This is an estimate of the amount of sample that was adsorbed by the tube wall or components during the sampling process and did not enter the detector.

[0036] In a further optimization, step S7 also includes a step of correcting the detection quantity based on the target trace impurity type, based on the tabulated sampling distortion calibration matrix:

[0037] When the target trace impurity is an organic target trace impurity, it is divided into at least two component segments according to the carbon number range, boiling point range, polarity, volatility, supercritical carbon dioxide solubility, or wall adsorption tendency of the target trace impurity.

[0038] For different component segments, internal standards with similar boiling point range, carbon number range, polarity, supercritical carbon dioxide solubility, and wall adsorption tendency were selected.

[0039] During actual sampling, multiple internal standards are added to the sampling branch or standard sample in known amounts, so that they and the target trace impurities go through the same sampling path, in order to obtain the real-time recovery rate of the internal standards and the overall effective recovery rate of the component segment.

[0040] Based on the real-time recovery rate and the overall effective recovery rate, the observed recovery amount and in-situ correction amount of each component segment are obtained, and the total correction amount of the final organic target trace impurities is further obtained.

[0041] In a further optimization, step S7 also includes a step of correcting the detection quantity based on the target trace impurity type, based on the tabulated sampling distortion calibration matrix:

[0042] When the target trace impurity is a non-condensable or weakly condensable gas, corrections are made based on the reference component or standard gas to account for dead volume dilution, leakage contamination, flow integral deviation, wall reaction loss, and detection drift, resulting in a reference correction factor: β = C ref,0 / C ref,mIn the formula, β is the reference correction factor; C ref,0 The theoretical or calibrated concentration of the reference component; C ref,m This represents the measured concentration of the reference component.

[0043] The detection concentration of non-condensable or weakly condensable gases is corrected using a reference correction factor: C g,corr = β ·C g,m In the formula, C g,corr For corrected concentrations of non-condensable or weakly condensable gases; C g,m This represents the measured concentration of the gas.

[0044] Further optimization, the specific correction steps in step S8 include:

[0045] S801: During the actual operation of a supercritical carbon dioxide system, the detected values ​​and real-time sampling status parameters are obtained;

[0046] S802: Based on real-time sampling status parameters, the corresponding segmented recovery rate, path recovery rate, phase distribution ratio, solubility margin, and pretreatment recovery rate are obtained by matching or interpolating from the tabular sampling distortion calibration matrix; and combined with the real-time recovery rate of the internal standard, the correction results of the reference component, the blank background subtraction results, the mass closure deviation of the matching calibration row, and the actual sampling validity judgment results, a comprehensive correction model for the target trace impurities is constructed to invert the in-situ concentration of the target trace impurities;

[0047] S803: During the calibration process, the validity is determined by quality closure verification or by matching the degree of matching of parameters in the calibration row;

[0048] S804: Finally, output the in-situ concentration correction results and the sampling fidelity evaluation results.

[0049] Further optimization is achieved by using the following calculation model for the sampling fidelity:

[0050] F Ii = R use,i · (1-ε i / 100);

[0051] In the formula, F Ii R is the sampling fidelity index for the i-th target trace impurity; use,i The effective recovery rate used for evaluating the fidelity of trace impurities in this target; ε i This refers to the quality closure deviation used for fidelity evaluation.

[0052] Further optimization includes the following steps for grading and evaluating sampling fidelity:

[0053] When R is satisfied simultaneously use,i ≥0.90, εi If the sampling results are ≤10%, the blank background ratio is ≤10%, the actual sampling conditions are within the applicable range of the tabular sampling distortion calibration matrix, and the internal standard recovery rate deviation is ≤10% when using internal standard, the sampling results are judged to be of Class A fidelity, which can be used for in-situ concentration quantitative evaluation and can be used for direct comparison between results from different sampling points or different batches.

[0054] When 0.70≤R use,i <0.90, or 10% <ε i If the sampling result is ≤30%, or 10% < blank background ratio ≤30%, or 10% < internal standard recovery deviation ≤30% when using internal standard, and the actual sampling conditions are still within the applicable range of the tabular sampling distortion calibration matrix, the sampling result is determined to be of Class B fidelity, which can be used for in-situ concentration correction and engineering quantitative evaluation, but the uncertainty range or fidelity description should be given at the same time.

[0055] When 0.50≤R is satisfied use,i <0.70, or 30% < ε i If the sampling result is ≤50%, or the blank background ratio is greater than 30%, or the internal standard recovery rate deviation is greater than 30% when using internal standards, or the actual sampling conditions are close to the applicable boundary of the tabular sampling distortion calibration matrix, the sampling result is determined to be of C-level fidelity. It is only suitable for trend judgment, semi-quantitative evaluation or auxiliary analysis of impurity sources, and should not be used as a basis for accurate quantification on its own.

[0056] When R use,i If the value is less than 0.50, or the actual sampling conditions exceed the applicable range of the tabular sampling distortion calibration matrix, or the blank background is unstable and cannot be subtracted, or an internal standard is used but the internal standard is not effectively recovered, the sampling result is deemed unsuitable for in-situ concentration quantitative correction, and the sampling path should be recalibrated, the sampling path adjusted, or the pretreatment conditions optimized.

[0057] When different evaluation indicators correspond to different fidelity levels, the final fidelity level shall be determined according to the lowest fidelity level among them.

[0058] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0059] 1. The present invention provides a method for calibrating and correcting the sampling distortion of trace impurities in supercritical carbon dioxide working fluid. It does not only perform response calibration on the analytical instrument, but also calibrates and corrects the sampling distortion of supercritical carbon dioxide sample from the loop to the inlet of the detection instrument. It can reflect the comprehensive influence of factors such as phase change, density change, solubility change, wall adsorption, valve retention, condensation, dead volume dilution and pretreatment before detection.

[0060] 2. The present invention provides a method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid. Instead of simply using a single recovery rate to linearly correct the detection value, it establishes a comprehensive correction model that combines segmented path recovery rate, phase distribution ratio, solubility margin, real-time correction of multiple internal standards, reference component correction, calibration quality closure, and actual sampling validity determination. This model can more accurately reflect the complex distortion behavior in the supercritical carbon dioxide sampling process.

[0061] 3. The present invention provides a method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid. By constructing a tabular sampling distortion calibration matrix, the method can associate the target impurity type, carbon dioxide state parameters, phase path parameters, sampling path parameters, segment loss parameters, correction parameters, and applicability criteria, so that the calibration results can be queried, reused, interpolated, and extended, thereby improving the operability and engineering applicability of the method.

[0062] 4. The present invention provides a method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid. By constructing a supercritical carbon dioxide standard sample with a known addition amount or a known in-situ concentration, the sampling recovery rate of the target trace impurities can be obtained under conditions close to the actual working fluid state. Compared with calibration using atmospheric pressure standard gas or standard liquid, it can better reflect the dissolution, precipitation, adsorption and distribution characteristics of the target impurities in high-pressure, high-density carbon dioxide.

[0063] 5. The present invention provides a method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid. For water, an adsorption-desorption memory effect correction is established, which can reduce the influence of tube wall adsorption, desorption tailing, blank background release and detection response lag on the trace water detection results. For complex components such as lubricating oil cracking products, heavy hydrocarbons and oxygen-containing organic matter, a multi-internal standard segmented correction, calibration mass closure and actual sampling validity determination method are established. This can avoid simply equating complex organic mixtures with a single total hydrocarbon signal, thereby improving the correction accuracy for components with different boiling ranges, different polarities and different adsorption tendencies.

[0064] 6. The present invention provides a method for calibrating and correcting the sampling distortion of trace impurities in supercritical carbon dioxide working fluid. It can output the in-situ correction concentration, main distortion links, mass closure deviation and sampling fidelity level, so that the detection results not only have numerical output, but also reliability evaluation, which is beneficial for data comparison between different sampling points, different operating conditions and different test batches.

[0065] 7. The present invention provides a method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid, which can be used for working fluid quality evaluation, impurity source identification, purification control strategy formulation, lubricating oil leakage or cracking monitoring, material corrosion risk assessment and long-term safe operation evaluation in supercritical carbon dioxide energy conversion systems. Attached Figure Description

[0066] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0067] Figure 1 The flowchart illustrates the method for calibrating and correcting the sampling distortion of trace impurities in supercritical carbon dioxide working fluid provided by this invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0069] Example 1: This Example 1 provides a method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid, mainly used to solve the following problems in the prior art:

[0070] (1) To solve the problem that in the existing process of detecting trace impurities in supercritical carbon dioxide working fluid, after the sample is taken out from the system loop under the in-situ high temperature and high pressure state, the phase state, density and solubility of carbon dioxide change due to the cooling, depressurization, throttling, expansion, transportation and pre-detection treatment processes. This causes unexpected precipitation, coagulation, adsorption, retention, re-volatilization or redistribution of water, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products, oxygen-containing organic matter and other soluble, condensable or easily adsorbed trace impurities, making it difficult for the instrument detection value to accurately represent the in-situ concentration under the in-situ temperature and pressure conditions of the system loop.

[0071] (2) To address the problem that conventional calibration of existing analytical instruments mainly targets detector response and is insufficient to reflect the sampling loss of supercritical carbon dioxide samples from the loop to the instrument inlet. By calibrating the recovery rate of target trace impurities under different supercritical carbon dioxide states, different sampling paths, and different pretreatment conditions, the sampling distortion parameters of target impurities are obtained, enabling the detection results to be further corrected from "concentration measured after sampling" to "in-situ concentration in the loop".

[0072] (3) Solving the problem of difficulty in comparing detection results across different sampling points, operating conditions, and sampling paths. In supercritical carbon dioxide systems, differences in temperature, pressure, carbon dioxide density, sampling pipeline length, pipeline wall material, heating conditions, depressurization rate, and pretreatment methods at different sampling points can lead to varying degrees of loss and recovery rates of the same target impurity in different sampling paths. This invention establishes a correspondence between the properties of the target impurity, carbon dioxide state parameters, sampling path parameters, pretreatment parameters, and recovery rate, thereby correcting the actual detection results for path-related errors caused by differences in sampling paths.

[0073] (4) Solve the problem of systematic underestimation of moisture, organic matter, lubricating oil cracking products and heavy hydrocarbon components during supercritical carbon dioxide sampling. By obtaining the phase change loss, adsorption loss, retention loss, condensation loss, dead volume dilution loss and detection recovery loss of the target components in the sampling valve, pressure reduction port, transmission pipeline, cooling section, filter element, separation unit and detection pretreatment unit, a comprehensive correction of the instrument detection value, gas phase measurement value or condensed component measurement value can be achieved.

[0074] (5) To address the problem that pre-calibration results are not fully applicable due to sampling state fluctuations, pipeline memory effects, detection drift, and batch differences during actual sampling. By introducing one or more correction methods from pre-calibration recovery rate, internal standard recovery rate, or stable reference component in the sample, the actual recovery rate, dilution degree, transport loss, and detection drift during this sampling process are corrected, so that in-situ concentration correction can both utilize the pre-established sampling distortion calibration results and reflect the state fluctuations and path differences during the actual sampling process.

[0075] (6) This invention addresses the potential impacts of dead volume dilution, leakage, flow integral error, wall reaction, or instrument drift on the quality evaluation of non-condensable or weakly condensable gases using supercritical carbon dioxide as a working fluid. While focusing on in-situ concentration correction for soluble, condensable, or easily adsorbed trace impurities such as moisture, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products, and oxygen-containing organic matter, this invention can also be used for sampling dilution correction, leakage detection, flow recovery correction, and gas phase component concentration correction for non-condensable or weakly condensable gases such as nitrogen, oxygen, argon, carbon monoxide, hydrogen, and methane.

[0076] Therefore, this invention can improve the accuracy, comparability, and traceability of the detection results of trace impurities in supercritical carbon dioxide working fluid, and reduce the detection deviation caused by changes in carbon dioxide phase, density, solubility, component redistribution, and sampling path. It provides a more reliable data foundation for evaluating the quality of working fluid, identifying impurity sources, formulating purification control strategies, assessing material corrosion risks, monitoring lubricating oil leakage or cracking, and ensuring long-term safe operation of supercritical carbon dioxide energy conversion systems.

[0077] This invention is particularly applicable to the calibration of sampling recovery rates, evaluation of sampling fidelity, and in-situ concentration inversion under operating conditions for trace impurities such as water, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products, and oxygen-containing organic matter that are condensable, soluble, or easily adsorbed in supercritical carbon dioxide circulation systems. It is also applicable to the concentration correction of non-condensable or weakly condensable gases such as nitrogen, oxygen, argon, carbon monoxide, hydrogen, and methane in sampling dilution, leak detection, flow recovery, gas phase component correction, and comprehensive evaluation of working fluid chemical quality.

[0078] like Figure 1 As shown, the specific steps of the present invention include:

[0079] Step 1: Determine the target trace impurity, sampling route, and calibration target:

[0080] The target trace impurities to be corrected are identified. These target trace impurities include moisture, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products, oxygen-containing organic matter, and other trace components that are soluble, condensable, easily adsorbed, or prone to partition changes in supercritical carbon dioxide. The target trace impurities may also include non-condensable or weakly condensable gases such as nitrogen, oxygen, argon, carbon monoxide, hydrogen, and methane. For non-condensable or weakly condensable gases, they are mainly used for sampling dilution correction, leak detection, flow recovery correction, reference correction, or gas phase component concentration correction, and are not the core target of sampling distortion caused by changes in the phase state and solubility of supercritical carbon dioxide in this invention.

[0081] Determine the sampling path to be calibrated. The sampling path refers to the entire path that the sample takes from the sampling point in the supercritical carbon dioxide system loop to the inlet of the detection instrument, including one or more of the following: sampling valve, pressure reducing element, transmission pipeline, heat tracing pipeline, cooling section, filter element, separation unit, collection unit, pretreatment unit, and inlet of the detection instrument.

[0082] Identify the calibration target. The calibration target includes one or more of the following during the sampling process of the target trace impurity: changes in carbon dioxide density, changes in solubility, valve retention, tube wall adsorption, condensation, filtration retention, separation loss, dead volume dilution, changes in pretreatment recovery rate, and detection response drift.

[0083] Step 2: Divide the sampling path into several functional segments and establish a segmented sampling path model:

[0084] Based on the sample's state changes and potential loss locations during the sampling process, the sampling path is divided into several functional segments. These functional segments include one or more of the following: sample extraction segment, pressure reduction and throttling segment, isothermal or heat-traced transport segment, cooling phase change segment, filtration or interception segment, gas-liquid or gas-solid separation segment, condensate collection segment, pretreatment segment, and instrument detection segment. For each functional segment, parameters such as inlet and outlet pressure, temperature, carbon dioxide density, flow rate, residence time, pipe length, pipe inner diameter, inner wall material, heating or cooling conditions, pressure reduction rate, and whether it crosses a critical region or phase boundary are recorded. This establishes a segmented state trajectory of the target trace impurity within the sampling path.

[0085] The degree of change in carbon dioxide density in the kth functional segment can be expressed as:

[0086] D k = |ρ in,k -ρ out,k | / ρ in,k ;

[0087] In the formula, D k ρ represents the degree of density change in the k-th functional segment. in,k ρ represents the carbon dioxide density at the entrance of the k-th functional segment. out,k Let be the carbon dioxide density at the exit of the kth functional segment.

[0088] Furthermore, the solubility margin of the i-th target trace impurity in the k-th functional segment can be expressed as:

[0089] M k,i = (S k,i -x k,i ) / S k,i ;

[0090] In the formula, M k,i S represents the solubility margin of the i-th target trace impurity in the k-th functional segment; k,i The calibrated soluble or portable concentration of the i-th target trace impurity under the pressure, temperature, and carbon dioxide density conditions of the k-th functional segment; x k,i S represents the actual or estimated concentration of the i-th target trace impurity at the inlet of this functional segment. k,i It is not a theoretically assumed constant, but rather the calibrated soluble or portable concentration of the i-th target trace impurity under the pressure, temperature, carbon dioxide density, and wall conditions corresponding to the k-th functional segment. k,iThe breakthrough concentration can be obtained through one or more of the following methods: high-pressure equilibrium dissolution calibration under conditions identical or equivalent to the pressure, temperature, and carbon dioxide density of the k-th functional segment; obtaining the breakthrough concentration by gradually increasing the amount of the target trace impurity and detecting the burst point of the target component in the gas phase, condensed phase, or adsorbed phase; back-calculating from the recovery experiment of a supercritical carbon dioxide standard sample with a known addition amount; or estimating through a property database, equation of state, or empirical correlation, and then correcting it with the calibration results of the standard sample. For lubricating oil cracking products, heavy hydrocarbons, or complex organic mixtures lacking reliable property data, S k,i Experimental calibration values ​​or equivalent portable concentrations are preferred over theoretical estimates.

[0091] When D k Exceeding the preset threshold, or M k,i If the value is less than the preset threshold, it is determined that there is a risk that the target trace impurities may precipitate, condense, adsorb, or redistribute between phases due to the decrease in carbon dioxide density, the decrease in solubility, or the change in phase path.

[0092] Step 3: Construct supercritical carbon dioxide standard samples with known addition amounts or known in-situ concentrations:

[0093] Under calibrated conditions, high-purity carbon dioxide is pressurized and heated to a preset supercritical state, forming a pressure of P. s Temperature T s Density is ρ s A supercritical carbon dioxide standard matrix is ​​prepared. Then, one or more target trace impurities are quantitatively added to the supercritical carbon dioxide standard matrix. After mixing, cycling, steady-state maintenance and homogenization, when the relative deviation of the concentration of the target trace impurities obtained from at least three consecutive sampling tests does not exceed a preset threshold, the supercritical carbon dioxide standard sample is determined to have reached a homogenized steady state, and a supercritical carbon dioxide standard sample with a known amount added or a known in-situ concentration is obtained.

[0094] The molar amount of carbon dioxide in a supercritical carbon dioxide standard sample can be determined by the following formula:

[0095] n(CO2,s) = ρ s V s / M(CO2);

[0096] In the formula, n(CO2,s) is the molar amount of carbon dioxide in the standard sample; ρ s V represents the density of carbon dioxide under calibrated conditions. s M(CO) represents the volume of the standard sample or the volume of carbon dioxide used in the calibration. 2) is the molar mass of carbon dioxide.

[0097] When using pressure, temperature, and compressibility factor for calculations, it can also be determined by the following formula:

[0098] n(CO2,s) = P s V s / (Z s RT s );

[0099] In the formula, P s V represents the pressure of the standard sample. s Z is the standard sample volume; s R is the compressibility factor; T is the gas constant; s This is the temperature of the standard sample.

[0100] The known in-situ concentration of the target trace impurity can be determined by the following formula:

[0101] C(0,i,s) = n 0,i / n(CO2,s);

[0102] In the formula, C(0,i,s) represents the known in-situ concentration of the i-th target trace impurity in the supercritical carbon dioxide standard sample; n 0,i denoted as , where is the known molar amount of the i-th target trace impurity; n(CO2,s) is the molar amount of carbon dioxide in the standard sample.

[0103] For trace impurities added by mass, their molar mass can be converted into molar amount; for lubricating oil cracking products, heavy hydrocarbons or complex organic mixtures, the added mass per unit mass of carbon dioxide can also be used as the equivalent in-situ concentration.

[0104] The method of adding the target trace impurities includes one or more of the following: quantitative mixing of standard gas, high-pressure micro-injection of standard liquid, injection of known mass droplets, evaporation mixing of standard organic matter, mixing of aqueous standard samples, and micro-injection of lubricating oil or lubricating oil pyrolysis simulants.

[0105] For heavy organic components that are difficult to dissolve completely, the known in-situ concentration can be defined as the equivalent amount of the target component added per unit mass or per mole of supercritical carbon dioxide, and confirmed by the mass difference before and after calibration, the amount injected, the amount remaining, and the blank subtraction results.

[0106] Step 4: Conduct blank path calibration to obtain the sampling path background and memory effect:

[0107] Before calibrating for the target trace impurities, a blank calibration was performed on the sampling path to be calibrated using supercritical carbon dioxide that contained no target trace impurities or whose content was below a preset threshold. The background of moisture release, residual organic matter, non-condensable gases, detector response background, and pipeline memory effect were recorded under the blank conditions.

[0108] For moisture, the decrease, stabilization and tailing process of the trace water detection response over time were recorded to obtain the moisture adsorption capacity, blank release rate, response hysteresis time and desorption tailing characteristics of the sampling path.

[0109] For trace organic impurities, clean supercritical carbon dioxide or inert rinsing media are used to purge the sampling path, rinse with solvent, or thermally desorb to obtain the background of organic residues in pipelines, valves, filter elements, collection elements, and pretreatment units.

[0110] Blank deduction amount can be expressed as:

[0111] N b,i =∫t b C b,i(t) · q(t) dt;

[0112] In the formula, N b,i C represents the blank background amount of the i-th target trace impurity; b,i(t) q(t) represents the instantaneous detection concentration of the i-th target trace impurity during blank calibration; t represents the sampling flow rate; b Use blank calibration time.

[0113] Step 5: Pass the supercritical carbon dioxide standard sample through the sampling path to be calibrated and obtain the segmented detection quantities:

[0114] The supercritical carbon dioxide standard sample obtained in step three is introduced into the sampling path to be calibrated, so that it undergoes the same or equivalent sampling, transmission, depressurization, cooling, filtration, separation, collection, pretreatment and instrument detection process as the actual sampling process.

[0115] At different functional section outlets or detachable locations along the sampling path, one or more of the following quantities of target trace impurities are obtained: gas-phase detection quantity, condensate quantity, filtration retention quantity, pipe wall adsorption quantity, flushing recovery quantity, thermal desorption recovery quantity, and pretreatment residue quantity. For functional sections in the actual engineering sampling path that are inconvenient to disassemble, alternative functional sections with the same or equivalent inner diameter, length, material, surface area / volume ratio, heating temperature, and pressure reduction path can be set in the offline calibration device, and the segmented recovery rate can be obtained through the alternative functional sections.

[0116] The gas phase detection quantity can be obtained through gas chromatography, total hydrocarbon analysis, trace water analysis, infrared analysis, mass spectrometry, or online sensors. The amount of condensate can be obtained through weighing, solvent extraction, chromatographic analysis, or thermal desorption analysis. The amount of adsorption on the tube wall, the amount retained by filtration, and the amount of residue after pretreatment can be obtained through solvent washing, heated purging, thermal desorption, or offline analysis.

[0117] Step 6: Establish the closed-loop relationship between phase distribution, segmented loss, and mass:

[0118] Based on the segmented detection quantities obtained in step five, the existence state of the target trace impurities after sampling is divided into gas phase quantity, condensed phase quantity, adsorbed phase quantity, cut-off phase quantity, residual phase quantity, and unrecovered loss quantity.

[0119] For the i-th type of target trace impurity, the material balance relationship in its calibration process is as follows:

[0120] n 0,i = n g,i + n c,i + n a,i + n f,i + n r,i + n lost,i ;

[0121] In the formula, n 0,i n represents the known amount or equivalent in-situ amount of the i-th target trace impurity in a supercritical carbon dioxide standard sample; g,i For gas phase detection quantity; n c,i n represents the amount of condensed phase recovered. a,i n represents the amount of material adsorbed and recovered from the pipe wall or component. f,i For the amount of material to be filtered or retained for recovery; n r,i For pretreatment or other residual recovery amounts; n lost,i This represents the amount of unrecovered loss. Where n... lost,i Instead of being used as a direct measurement, the integrity and reliability of the sampling calibration are evaluated through the quality closure deviation.

[0122] The distribution ratio of the target trace impurity in different phases or positions can be expressed as:

[0123] F g,i = n g,i / n 0,i ;

[0124] F c,i = n c,i / n 0,i ;

[0125] F a,i = n a,i / n 0,i ;

[0126] In the formula, F g,i F c,i F a,i These represent the distribution ratios of the i-th target trace impurity in the gas phase, condensed phase, and adsorbed phase, respectively.

[0127] For the k-th functional segment, the transport throughput and segmental effective recovery rate of the i-th type of target trace impurity are respectively expressed as:

[0128] T k,i = n out,k,i / n in,k,i ;

[0129] E k,i = (n out,k,i + n rec,k,i ) / n in,k,i ;

[0130] In the formula, T k,i E represents the transport throughput of the i-th target trace impurity in the k-th functional segment. k,i n represents the segmented effective recovery rate of the i-th target trace impurity in the k-th functional segment; in,k,i For the i-th type of target trace impurity mass entering the k-th functional segment; n out,k,i For the i-th type of target trace impurity mass leaving the k-th functional segment and entering the next functional segment or detection unit; n rec,k,i The target trace impurity quantity is the amount of the i-th type of impurity that is included in the correction amount in the k-th functional segment through collection of aggregates, filtration, tube flushing, thermal desorption, solvent extraction, or pretreatment for detection.

[0131] When the target trace impurities continuously pass through each functional section in gaseous form without undergoing measurable agglomeration, adsorption, retention, or residual recovery, the gas-phase transport recovery rate of the sampling path can be expressed as:

[0132] R g,i = T 1,i · T 2,i · …… · T m,i ;

[0133] When the target trace impurities undergo aggregation, adsorption, retention, residue, or phase separation recovery in the sampling path, the overall effective recovery rate of the entire sampling path is no longer determined solely by the product of the transmission rates of each functional segment. Instead, it is determined by the combined recovery rates of the gas phase after background subtraction, the recovery rate of the aggregated phase, the recovery rate of the adsorbed phase, the recovery rate of the filtered and retained phases, and the recovery rate of the residue.

[0134] R p,eff,i = (n g,i + n c,i + n a,i + n f,i + n r,i ) / n 0,i ;

[0135] In the formula, R p,eff,i Let n be the overall effective recovery rate of the i-th target trace impurity throughout the entire sampling path; g,i n c,i na,i n f,i and n r,i These are, respectively, the amount detected in the gas phase, the amount recovered in the condensed phase, the amount recovered in the adsorbed phase, the amount recovered by filtration or retention, and the amount recovered from pretreatment or other residues; n 0,i The known amount or equivalent in-situ amount of the i-th target trace impurity in the standard sample.

[0136] Therefore, the path recovery rate in this invention includes two types of parameters: gas phase transport recovery rate and overall effective recovery rate. For non-condensable or weakly condensable gases, gas phase transport recovery rate can be used preferentially; for water, heavy hydrocarbons, lubricating oil cracking products, oxygen-containing organic matter, and other condensable, soluble, or easily adsorbed components, overall effective recovery rate is preferred as the in-situ concentration correction parameter.

[0137] Step 7: Establish a tabular sampling distortion calibration matrix:

[0138] Change one or more of the following parameters of the supercritical carbon dioxide standard sample: pressure, temperature, density, target trace impurity concentration, sampling flow rate, sampling pipeline temperature, depressurization rate, cooling temperature, pipeline inner wall material, pipeline length, pretreatment method, and target trace impurity type. Repeat steps three to six to obtain the fractional recovery rate, phase distribution ratio, solubility margin, path recovery rate, and mass closure deviation under different conditions, and establish a tabular sampling distortion calibration matrix.

[0139] The tabular sampling distortion calibration matrix includes at least state parameters, target impurity parameters, sampling path parameters, segmentation loss parameters, phase allocation parameters, correction parameters, validity parameters, and applicability criteria, as shown in Table 1.

[0140]

[0141] In practical applications, when the actual sampling conditions match a calibration row in the tabular sampling distortion calibration matrix, the segmented recovery rate, path recovery rate, phase distribution ratio, internal standard / reference correction parameters, and fidelity level in that calibration row are directly retrieved. When the actual sampling conditions lie between two or more calibration rows, interpolation is performed based on pressure, temperature, carbon dioxide density, solubility margin, sampling path parameters, and target impurity properties to obtain the corresponding correction parameters. When the actual sampling conditions exceed the applicable range of the tabular sampling distortion calibration matrix, the test results are deemed unsuitable for direct quantitative correction and require supplementary calibration or a reduction in the confidence level.

[0142] Step 8: Establishing an adsorption-desorption memory effect correction for moisture:

[0143] When the target trace impurity is moisture, a moisture adsorption-desorption memory effect correction model is further established based on the tabular sampling distortion calibration matrix. This model obtains the adsorption capacity, adsorption rate, desorption rate, response lag time, and tailing integral of moisture along the sampling path through blank purging, calibration of water-containing standard samples, and recovery of dried samples.

[0144] In actual moisture detection, the output value of the trace moisture analyzer is corrected based on the background of blank water release before sampling, the rise time of the current moisture detection curve, the stable plateau, the integral response, and the desorption tail after sampling.

[0145] The effective detection limit for moisture can be expressed as:

[0146] n w,corr = n w,m - n b,w + n des,w + n ads,w ;

[0147] In the formula, n w,corr This is the corrected effective moisture detection amount; n w,m The water content measured by a trace water analyzer; n b,w Water content for blank background; n des,w For sampling path desorption tail back calculation; n ads,w This is an estimate of the amount of sample that was adsorbed by the tube wall or components during the sampling process and did not enter the detector.

[0148] Step 9: Establish multi-internal-standard segmented calibration for trace organic impurities:

[0149] When the target trace impurity is light hydrocarbon, heavy hydrocarbon, lubricating oil cracking products, oxygen-containing organic matter, or other complex organic trace impurities, it is divided into at least two component segments according to the carbon number range, boiling point range, polarity, volatility, supercritical carbon dioxide solubility, or wall adsorption tendency of the target trace impurity.

[0150] The component segment includes at least two of the following: a light volatile segment, a medium volatile segment, and a heavy low volatile segment. The light volatile segment is mainly obtained through gas phase detection; the medium volatile segment may be distributed simultaneously in the gas phase, condensed phase, and adsorbed phase; the heavy low volatile segment may be mainly distributed in the condensed phase, the tube wall adsorbed phase, the filtration-retained phase, and the residual phase.

[0151] For different component segments, internal standards with similar boiling point ranges, carbon number ranges, polarities, supercritical carbon dioxide solubility, and wall adsorption tendencies are selected. Internal standards should meet the following requirements: they should be distinguishable from the target component peak position or response in the detection method; their solubility, volatility, polarity, and wall adsorption tendency in supercritical CO2 should be similar to the corresponding component segment; they should be absent or have stable content in the system background; and they should not significantly react with CO2, moisture, metal walls, or target impurities along the sampling path. During actual sampling, multiple internal standards are added in known amounts to the sampling branch or standard sample, ensuring they share the same sampling path as the target trace impurity.

[0152] The real-time recovery rate of the internal standard corresponding to the j-th component segment can be expressed as:

[0153] R IS,j = n IS,m,j / n IS,0,j ;

[0154] In the formula, R IS,j n represents the real-time recovery rate of the internal standard corresponding to the j-th component segment; IS,0,j n is the amount of the j-th internal standard added; IS,m,j The measured recovery amount of the j-th internal standard after the sampling path and testing process.

[0155] The overall effective recovery rate of the j-th component segment can be expressed as:

[0156] η j = R p,eff,j,0 · γ j · (R IS,j / R IS,j,0 ) · β j ;

[0157] In the formula, η j R represents the overall effective recovery rate of the j-th component fraction used for in-situ correction under actual sampling conditions. p,eff,j,0 γ represents the basic overall effective recovery rate of the j-th fraction under pre-calibration conditions; j R is the similarity correction coefficient between the target component segment and its corresponding internal standard; IS,j R represents the real-time recovery rate of the j-th internal standard during actual sampling. IS,j,0 β represents the baseline recovery rate of the j-th internal standard under pre-calibration conditions. j β is the reference correction factor; when no reference correction is used, β j Take 1.

[0158] Specifically, under pre-calibration conditions, a representative target substance T of the j-th component segment is added to the supercritical carbon dioxide standard sample or the equivalent sampling branch. j and corresponding internal standard ISj Both samples undergo the same sampling, depressurization, cooling, separation, collection, and pretreatment processes to obtain the basic recovery rate R of the target representative. T,j,0 and the basic recovery rate R of the internal standard IS,j,0 When R p,eff,j,0 When using internal standard-based recovery characterization, γ j It can be determined by the following formula:

[0159] γ j = R T,j,0 / R IS,j,0 ;

[0160] When R p,eff,j,0 When the baseline recovery of the target component fraction representative has been used for characterization, γ j Set to 1; when the actual target component differs from the representative compound in terms of carbon number range, boiling point range, polarity, or adsorption tendency, a correction factor for the actual target component relative to the representative compound can be obtained through supplementary pairwise calibration, and this correction factor can be used as γ. j Or merge into γ j γ j The values, sources, corresponding target component segments, and internal standard names should be recorded in the tabular sampling distortion calibration matrix. When paired calibration is not performed, γ j We can temporarily take 1, but the fidelity level of the segmented correction result for this group should be reduced by one level.

[0161] The observed recovery of the j-th component segment can be expressed as:

[0162] N j,obs = N g,j + N c,j + N a,j + N r,j - N b,j ;

[0163] In the formula, N j,obs N represents the observed recovery amount of the j-th component segment; g,j N represents the gas phase detection quantity of the j-th component segment; c,j N represents the amount of condensed phase recovered in the j-th component segment; a,j N represents the adsorption recovery amount of the j-th component segment; r,j N represents the residual recovery amount of the j-th component segment; b,j The blank background amount for the j-th component segment.

[0164] The in-situ correction for the j-th component segment can be expressed as:

[0165] N j,corr = N j,obs / η j ;

[0166] In the formula, N j,corr This is the in-situ correction amount for the j-th component segment.

[0167] The total correction amount for trace organic impurities can be expressed as:

[0168] N org,corr = Σ N j,corr ;

[0169] In the formula, N org,corr Σ N represents the total correction amount for trace organic impurities; j,corr This is the sum of the correction values ​​for each component segment.

[0170] For the cracking products of lubricating oil, it is preferable to set internal standards for light volatile section, medium volatile section and heavy low volatile section, and perform gas phase, condensed phase, adsorbed phase and residual phase correction respectively, so as to avoid simply equating the complex cracking products of lubricating oil with a single total hydrocarbon signal.

[0171] Step 10: Establish auxiliary reference correction for non-condensable or weakly condensable gases:

[0172] For non-condensable or weakly condensable gases such as nitrogen, oxygen, argon, carbon monoxide, hydrogen, and methane, reference components or standard gases are used to correct for dead volume dilution, leakage mixing, flow integral deviation, wall reaction loss, and detection drift.

[0173] The reference correction factor can be expressed as:

[0174] β = C ref,0 / C ref,m ;

[0175] In the formula, β is the reference correction factor; C ref,0 The theoretical or calibrated concentration of the reference component; C ref,m This represents the measured concentration of the reference component.

[0176] For non-condensable or weakly condensable gases to be corrected, the correction concentration can be expressed as:

[0177] C g,corr = β · C g,m ;

[0178] In the formula, C g,corr For corrected concentrations of non-condensable or weakly condensable gases; C g,m β represents the measured concentration of the gas; β is the reference correction factor.

[0179] Nitrogen, argon, or other stable gases can be used as reference components for dead volume dilution and leak detection. Gases such as oxygen, carbon monoxide, and hydrogen, which may react with metal walls or residual active substances, can have their wall reaction loss coefficients obtained experimentally using blank path calibration and standard gases. The correction results for non-condensable or weakly condensable gases are mainly used for working fluid purity evaluation, leak detection, gas phase component concentration correction, and sampling path effectiveness assessment.

[0180] Step 11: Obtain the detection value and real-time sampling status parameters during actual sampling:

[0181] During the actual operation of the supercritical carbon dioxide system, the following parameters were recorded: sampling point pressure, sampling point temperature, carbon dioxide density, sampling flow rate, sampling time, sampling pipeline temperature, pressure reduction path, cooling conditions, filtration conditions, separation conditions, pretreatment conditions, and instrument status.

[0182] Simultaneously, the gas-phase detection quantity, condensate quantity, trapping quantity, flushing recovery quantity, thermal desorption recovery quantity, detection response quantity, or other equivalent detection quantities of the target trace impurities are obtained. For target trace impurities using internal standard correction, the amount of internal standard added and the measured recovery quantity are also recorded. The internal standard is preferably added through a trace injection port in the sampling branch located downstream of the sampling point and upstream of the first pressure-reducing element or the main distortion function section, so that the internal standard and the target trace impurities undergo the subsequent pressure reduction, cooling, separation, trapping, and pre-detection treatment processes together. The internal standard should not be directly added to the main loop, and the sampled fluid after addition should not flow back into the main circulation. For samples using reference correction, the theoretical concentration, measured concentration, and fluctuation range of the reference component are also recorded.

[0183] Step 12: Retrieve the in-situ concentration of the target trace impurities using the comprehensive correction model:

[0184] Based on the actual sampling state parameters, the corresponding segmented recovery rate, path recovery rate, phase distribution ratio, solubility margin, and pretreatment recovery rate are obtained by matching or interpolating from the tabular sampling distortion calibration matrix. Then, combined with the real-time recovery rate of the internal standard, the correction results of the reference component, the blank background subtraction results, the mass closure deviation of the matching calibration row, and the actual sampling validity judgment results, a comprehensive calibration model for the target trace impurities is constructed.

[0185] For trace impurities in general targets, their in-situ concentration can be determined by the following formula:

[0186] C 0,i = N i,corr / n(CO2);

[0187] In the formula, C 0,i N represents the corrected concentration of the i-th target trace impurity in the in-situ state of the system loop; i,corrN is the correction amount for the i-th target trace impurity after segmented loss, phase partitioning, blank background, internal standard or reference correction; n(CO2) is the corresponding molar amount of carbon dioxide during the actual sampling process. i,corr It is not a single instrument reading, but is determined jointly by gas phase detection quantity, condensate quantity, adsorption recovery quantity, retained recovery quantity, residual recovery quantity, blank background deduction quantity, internal standard correction factor, reference correction factor, and path recovery rate. When the target trace impurity is water, N i,corr The effective detection limit and path recovery rate of moisture in S8 can be used to determine the amount; when the target trace impurity is a complex organic component, N i,corr The sum of the multi-component segmented correction values ​​in S9 can be used to determine the amount; when the target trace impurity is a non-condensable or weakly condensable gas, N i,corr The reference correction results in S10 can be used to determine this.

[0188] Step 13: Perform calibration quality closure and determine the validity of actual sampling:

[0189] The quality closure verification in this invention includes quality closure verification during the calibration stage and validity determination during the actual sampling stage. For calibration processes using supercritical carbon dioxide standard samples with known addition amounts or known in-situ concentrations, since the amount n of the i-th target trace impurity is... 0,i It is known that a quality closure check can be performed. The quality closure check includes comparing the known amount of the target trace impurity added with the sum of the gas phase detection amount, the amount of condensate, the amount adsorbed and recovered from the tube wall, the amount retained by filtration, and the amount of residue after pretreatment.

[0190] The quality closure deviation during the calibration phase can be expressed as:

[0191] ε cal,i = |n 0,i - (n g,i + n c,i + n a,i + n f,i + n r,i )| / n 0,i × 100%;

[0192] In the formula, ε cal,i The mass closure deviation of the i-th target trace impurity during the calibration phase; n 0,i n is the known amount or equivalent in-situ amount of the i-th target trace impurity in the standard sample; g,i For gas phase detection quantity; n c,i n represents the amount of condensed phase recovered. a,i n represents the amount of material recovered through adsorption. f,i For the amount of material to be filtered or retained for recovery; n r,i This refers to the amount of residual material recovered.

[0193] When ε cal,i When ε is less than or equal to a preset threshold, the calibration row is deemed valid, and its segmented recovery rate, overall effective recovery rate, phase distribution ratio, quality closure deviation, and applicable operating condition range are written into a tabular sampling distortion calibration matrix; when ε cal,i If the value exceeds the preset threshold, the calibration row is deemed unsuitable for quantitative correction and needs to be recalibrated, the sampling path adjusted, or the fidelity level of the calibration row reduced.

[0194] For unknown samples in a real system, since the actual in-situ addition amount of the target trace impurity is unknown, the above mass closure formula is not directly used to calculate the mass closure deviation of the actual sample. Instead, it is based on ε in the matching calibration row. cal,i The validity of the method is determined by the deviation of the real-time recovery rate of the internal standard, the fluctuation of the reference correction factor, the proportion of blank background, the deviation of repeated sampling, and the degree of matching between the actual sampling conditions and the applicable range of the calibration matrix.

[0195] The internal standard recovery deviation of the j-th component segment can be expressed as:

[0196] δ IS,j = |R IS,j / R IS,j,0 - 1| × 100%;

[0197] The percentage of blank background can be represented as:

[0198] f b,i = N b,i / (N obs,i + N b,i ) × 100%;

[0199] In the formula, δ IS,j R represents the internal standard recovery deviation for the j-th component segment; IS,j R represents the real-time recovery rate of the internal standard during actual sampling. IS,j,0 f represents the basic recovery rate of the internal standard under pre-calibration conditions. b,i The percentage of blank background; N obs,i The observed recovery amount of the i-th target trace impurity in the actual sample.

[0200] When the actual sampling conditions are within the applicable range of the tabular sampling distortion calibration matrix, and the deviation of the internal standard recovery rate, the fluctuation of the reference correction factor, the proportion of blank background, and the deviation of repeated sampling are all within the preset range, the actual sample calibration result is determined to be usable for quantitative evaluation; when any of the above indicators exceed the preset range, the fidelity level of the actual sample calibration result is reduced; when the actual sampling conditions exceed the applicable range of the calibration matrix or the proportion of blank background is too high, the result should not be used as a quantitative result, but only as a trend judgment or semi-quantitative reference.

[0201] Step Fourteen: Output the in-situ concentration correction results and sampling fidelity evaluation results:

[0202] Based on the comprehensive correction model, the mass closure deviation of the matching calibration line, the actual sampling validity judgment result, and the fidelity level criterion, the in-situ correction concentration of the target trace impurity, the main distortion links, the path recovery rate, the segment recovery rate, the internal standard recovery rate, the reference correction factor, the uncertainty range, and the sampling fidelity level are output.

[0203] The sampling fidelity index can be expressed as:

[0204] F Ii = R use,i · (1- ε i / 100);

[0205] In the formula, F Ii R is the sampling fidelity index for the i-th target trace impurity; use,i The effective recovery rate is used for evaluating the fidelity of trace impurities for this target. For non-condensable or weakly condensable gases, R use,i The gas phase transport recovery rate R can be used. g,i For moisture, heavy hydrocarbons, lubricating oil cracking products, oxygen-containing organic matter, and other condensable, soluble, or easily adsorbed components, R use,i The preferred method is to use the overall effective recovery rate R. p,eff,i ε i ε is the mass closure deviation used for fidelity evaluation; for calibration samples, ε i The calibration stage mass closure deviation ε cal,i For actual unknown samples, ε i The calibration quality closure deviation obtained by matching or interpolating with the actual sampling conditions is used, and combined with the internal standard recovery deviation, reference correction factor fluctuation, blank background ratio and repeat sampling deviation for comprehensive judgment.

[0206] For moisture or non-condensable gases for which no internal standard is used, the internal standard recovery rate deviation index may be omitted, and instead, blank background ratio, reference correction factor fluctuation, repeat sampling deviation, or instrument drift index may be used for determination. When different determination indices correspond to different fidelity levels, the final fidelity level shall be determined according to the most unfavorable index.

[0207] When R is satisfied simultaneously use,i ≥0.90, ε i If the sampling results are ≤10%, the blank background ratio is ≤10%, the actual sampling conditions are within the applicable range of the calibration matrix, and the internal standard recovery rate deviation is ≤10% when using internal standards, the sampling results are judged to be of Class A fidelity, which can be used for in-situ concentration quantitative evaluation and can be used for direct comparison between results from different sampling points or different batches.

[0208] When 0.70≤R use,i <0.90, or 10% <ε i If the sampling result is ≤30%, or 10% < blank background ratio ≤30%, or 10% < internal standard recovery deviation ≤30% when using internal standard, and the actual sampling conditions are still within the applicable range of the calibration matrix, the sampling result is determined to be of Class B fidelity, which can be used for in-situ concentration correction and engineering quantitative evaluation, but the uncertainty range or fidelity description should be given at the same time.

[0209] When 0.50≤R is satisfied use,i <0.70, or 30% < ε i If the sampling result is ≤50%, or the blank background ratio is greater than 30%, or the internal standard recovery rate deviation is greater than 30% when using internal standards, or the actual sampling conditions are close to the applicable boundary of the calibration matrix, the sampling result is determined to be of Class C fidelity. It is only suitable for trend judgment, semi-quantitative evaluation or auxiliary analysis of impurity sources, and should not be used as a basis for accurate quantification on its own.

[0210] When R use,i If the value is less than 0.50, or the actual sampling conditions exceed the applicable range of the calibration matrix, or the blank background is unstable and cannot be subtracted, or an internal standard is used but the internal standard is not effectively recovered, the sampling result is deemed unsuitable for in-situ concentration quantitative correction, and the sampling path should be recalibrated, the sampling path adjusted, or the pretreatment conditions optimized.

[0211] In one specific embodiment, the target trace impurity is moisture. This method obtains the blank release background, adsorption capacity, desorption tailing amount, and path recovery rate of moisture by performing blank purging of dried supercritical carbon dioxide, calibration of supercritical carbon dioxide standard samples containing water, adsorption-desorption response testing of the sampling path, and integration of the detection curve of the actual sample. The output value of the trace water analyzer is then corrected to the in-situ water concentration in the system loop.

[0212] In one specific embodiment, the target trace impurity is a lubricating oil pyrolysis product. This method divides the lubricating oil pyrolysis product into light volatile, medium volatile, and heavy low volatile segments, and uses different internal standards to correct the recovery rate of each segment. The distribution of each component segment is obtained through gas phase detection, condensate weighing, pipeline solvent flushing, filter element extraction, and thermal desorption analysis. Finally, the in-situ concentration of the lubricating oil pyrolysis product in the supercritical carbon dioxide working fluid is determined.

[0213] In one specific embodiment, the target trace impurity is a light hydrocarbon, a heavy hydrocarbon, or an oxygen-containing organic compound. This method selects a matching internal standard based on the target component's boiling point, polarity, and supercritical carbon dioxide solubility, and corrects the actual detection results based on the internal standard's real-time recovery rate, segmented path recovery rate, and segmented detection amount.

[0214] In one specific embodiment, the target trace impurity is a non-condensable or weakly condensable gas. This method uses a stable reference gas or standard gas to correct for dead volume dilution, leakage contamination, flow integral error, and detection drift, and uses the results to evaluate the purity of the working fluid and determine the effectiveness of the sampling path.

[0215] In a specific embodiment, the method of the present invention can be used to correct the detection results of existing supercritical carbon dioxide working fluid impurity monitoring devices. That is, without changing the main structure of the existing sampling and detection device, a tabular sampling distortion calibration matrix corresponding to the device is established. Furthermore, during the actual sampling stage, internal standards, reference components, blank background subtraction, segmented recovery, matching calibration quality closure deviation, and actual sampling validity determination are introduced. This allows the detection values ​​of moisture, total hydrocarbons, heavy hydrocarbons, lubricating oil cracking products, oxygen-containing organic matter, and non-condensable gases output by the existing monitoring device to be further corrected to the in-situ concentrations of the system loop.

[0216] Example 2: Based on Example 1, Example 2 provides a specific embodiment for the calibration of moisture sampling distortion and the correction of in-situ water concentration.

[0217] This embodiment illustrates the blank background, tube wall adsorption, desorption tailing, and path recovery rate calibration methods for water in supercritical carbon dioxide working fluid during the sampling process.

[0218] In this embodiment, a 100 mL high-pressure standard sample vessel is used as the supercritical carbon dioxide standard sample generating unit. High-purity carbon dioxide is introduced into the standard sample vessel, and the pressure and temperature are increased to 20 MPa and 200 °C. The carbon dioxide density ρ under this state is obtained according to the carbon dioxide equation of state or a property database. s The molar amount of carbon dioxide in the standard sample vessel is determined by the following formula:

[0219] n(CO2,s) = ρ s V s / M(CO2);

[0220] Where n(CO2,s) is the molar amount of carbon dioxide in the standard sample vessel, ρ s V represents the density of carbon dioxide under conditions of 20 MPa and 200 ℃. s M(CO2) represents the effective volume of the standard sample vessel, and M(CO2) represents the molar mass of carbon dioxide.

[0221] A known amount of water is introduced into the standard sample vessel to achieve an in-situ water concentration of 50 μmol / mol CO2 in the standard sample. The known amount of water added is n. 0,w The known in-situ concentration of moisture in the standard sample is:

[0222] C(0,w,s) = n 0,w / n(CO2,s);

[0223] Where C(0,w,s) is the known in-situ concentration of moisture in the standard sample, and n 0,w The molar amount of water added is known.

[0224] Before formal moisture calibration, a blank purging was performed on the sampling path to be calibrated using dried supercritical carbon dioxide. The sampling path included a sampling valve, a pressure-reducing element, a heated transmission line, a cooling section, and the inlet of the trace water analyzer. The response curve of the trace water analyzer was recorded during the blank purging process to obtain the blank background moisture content n. b,w For example, during a 120-second blank purge, the trace water analyzer integrates to obtain the blank background water content n. b,w It is 0.80 μmol.

[0225] Subsequently, a water-containing supercritical carbon dioxide standard sample was introduced into the same sampling path, undergoing the same sampling, depressurization, transport, and detection processes as the actual sampling. The water content (n) was measured by the trace water analyzer. w,m The concentration was 15.20 μmol. After sampling, dry carbon dioxide was continuously introduced, and the water desorption tailing curve was recorded. The desorption tailing back-calculation amount n was obtained by integration. des,w The value was 0.60 μmol. Based on the adsorption response before and after blank purge and calibration of water-containing standard samples, the amount of water (n) adsorbed by the tube wall or components during sampling but not entering the detector was estimated. ads,w The value is 1.30 μmol.

[0226] The effective moisture detection limit is determined by the following formula:

[0227] n w,corr = n w,m - n b,w + n des,w + n ads,w ;

[0228] Substituting the above data, we get:

[0229] n w,corr = 15.20 - 0.80 + 0.60 + 1.30 = 16.30 μmol;

[0230] If the moisture content in the standard sample is known, the amount added is n. 0,w If the concentration is 18.75 μmol, then the path recovery rate of moisture for this sampling route is:

[0231] R p,eff,w = n w,corr / n 0,w= 16.30 / 18.75 = 0.869;

[0232] That is, the overall effective recovery rate of moisture for this sampling route is approximately 86.9%. This recovery rate, along with the pressure, temperature, carbon dioxide density variation, pipeline material, heating temperature, and residence time of each functional section in the sampling route, is recorded in a tabular sampling distortion calibration matrix.

[0233] For actual system moisture sampling, when the same sampling path is operating under conditions of approximately 20 MPa and 200 ℃, the measured moisture content n w,m The concentration was 12.10 μmol, and the blank background water content was n. b,w The value is 0.80 μmol, and the desorption tailing backcalculation amount n des,w The concentration was 0.50 μmol, and the estimated amount n was not detected by adsorption. ads,w If the value is 0.90 μmol, then the effective detection limit of moisture in the actual sample is:

[0234] n w,corr = 12.10 - 0.80 + 0.50 + 0.90 = 12.70 μmol;

[0235] Based on the pre-calibrated overall effective recovery rate R p,eff,w = 0.869, the actual in-situ moisture correction amount for the sample is:

[0236] n w,0 = n w,corr / R p,eff,w = 12.70 / 0.869 = 14.61 μmol;

[0237] If the actual sample corresponds to a carbon dioxide molar amount n(CO2) of 0.375 mol, then the in-situ water concentration in the system loop is:

[0238] C(0,w) = n w,0 / n(CO2) = 14.61 μmol / 0.375 mol = 38.96 μmol / mol CO2;

[0239] Therefore, after background subtraction, desorption tailing back calculation, adsorption loss correction, and path recovery rate correction, the direct detection value of the trace water analyzer yields an in-situ water concentration of approximately 38.96 μmol / mol CO2 in the system loop. This result can be used to determine the system's moisture level, the degree of distortion in the sampling path, and the reliability of the moisture detection results.

[0240] In this embodiment, the moisture calibration results can be recorded in the form of Table 2.

[0241]

[0242] Example 3: Based on Example 1, Example 3 provides a specific embodiment of multi-internal standard segmented correction of lubricating oil cracking products.

[0243] This embodiment illustrates a method for the segmented recovery, phase distribution, and multiple internal standard correction of wide-boiling-range organic impurities, especially lubricating oil cracking products, during supercritical carbon dioxide sampling.

[0244] In this embodiment, a lubricating oil pyrolysis simulant is used as the target trace impurity. The lubricating oil pyrolysis simulant consists of a light volatile section, a medium volatile section, and a heavy low volatile section. The light volatile section mainly includes C1-C4 light hydrocarbon components; the medium volatile section mainly includes C5-C16 hydrocarbons and oxygen-containing organic compounds; and the heavy low volatile section mainly includes C16 and above heavy hydrocarbons, esters, ethers, or other low-volatile organic compounds.

[0245] 1.00 mg of lubricating oil pyrolysis simulant was added to supercritical carbon dioxide at 20 MPa and 200 °C using a 100 mL high-pressure standard sample vessel. The mass fractions were: light volatile fraction 0.25 mg, medium volatile fraction 0.35 mg, and heavy low volatile fraction 0.40 mg. The mass distribution of each fraction was determined by pre-prepared standard samples or GC-MS analysis results.

[0246] Internal standards were selected for different component segments. For the light volatile segment, internal standards with behavior similar to light hydrocarbons and distinguishable detection responses were chosen; for the medium volatile segment, medium-boiling-range organic internal standards with boiling ranges and polarities similar to C5–C16 organic compounds were chosen; and for the heavy low-volatile segment, heavy organic internal standards with adsorption and aggregation behaviors similar to heavy hydrocarbons or lubricating oil-based components were chosen. Each internal standard was added in known amounts to the standard sample or sampling branch and underwent sampling, depressurization, cooling, separation, collection, and pretreatment processes together with the target component.

[0247] The sampling path is divided into a sampling extraction section, a pressure reduction and throttling section, a heat tracing and transmission section, a cooling and separation section, a collection section, a pre-detection treatment section, and an instrument detection section. After one calibration, the gas phase detection amount, condensed phase recovery amount, adsorption recovery amount, and residual recovery amount of each component section are obtained, as shown in Table 3.

[0248]

[0249] As shown in Table 3, the light volatiles mainly enter the gas phase for detection; the medium volatiles are distributed among the gas, condensed, and adsorbed phases; and the heavy low volatiles are mainly distributed among the condensed, adsorbed, and residual phases. If segmental correction is not performed and only the total hydrocarbon detection results are used, the actual contents of the medium and heavy low volatiles will be significantly underestimated.

[0250] The observed recovery of the j-th component segment is determined by the following formula:

[0251] N j,obs = N g,j + N c,j + N a,j + N r,j - N b,j ;

[0252] In the formula, N j,obs N represents the observed recovery amount of the j-th component segment; g,j For gas phase detection; N c,j For the amount of condensed phase recovered; N a,j This represents the amount of adsorption and recovery; N r,j Residual recovery amount; N b,j The blank background amount is calculated. In this embodiment, the blank background amount has been deducted through blank path calibration, so the observed recovery amount in Table 2 is the sum of the gas phase, condensed phase, adsorbed phase, and residual phase.

[0253] The real-time recovery rate of the internal standard for each component fraction is determined by the following formula:

[0254] R IS,j = n IS,m,j / n IS,0,j ;

[0255] In the formula, R IS,j n represents the real-time recovery rate of the internal standard corresponding to the j-th component segment; IS,0,j n is the amount of internal standard added; IS,m,j This represents the measured recovery amount of the internal standard after passing through the sampling path.

[0256] The overall effective recovery rate of each component segment is determined by the following formula:

[0257] η j = R p,eff,j,0 · γ j · (R IS,j / R IS,j,0 )· β j ;

[0258] In the formula, η j R represents the overall effective recovery rate of the j-th component fraction used for in-situ correction under actual sampling conditions. p,eff,j,0 γ represents the basic overall effective recovery rate of the j-th fraction under pre-calibration conditions; j R is the similarity correction coefficient between the target component segment and the internal standard; IS,j R represents the real-time recovery rate of the j-th internal standard during actual sampling. IS,j,0 β represents the baseline recovery rate of the j-th internal standard under pre-calibration conditions. jβ is the reference correction factor; when no reference correction is used, β j Take 1.

[0259] The above-mentioned overall effective recovery rate is the basic overall effective recovery rate obtained in the independent pre-calibration test for this sampling route. This embodiment is used to illustrate the calculation process of in-situ quantity inversion of the validation sample under the same or equivalent route conditions. In this embodiment, the overall effective recoveries corresponding to the light volatile section, the medium volatile section, and the heavy low volatile section are 0.84, 0.77, and 0.70, respectively. Therefore, the in-situ correction amount for each component segment is:

[0260] N j,corr = N j,obs / η j ;

[0261] The in-situ correction amount for the light volatile section is:

[0262] N 1,corr = 0.21 / 0.84 = 0.25 mg;

[0263] The in-situ correction for the intermediate volatile section is:

[0264] N 2,corr = 0.27 / 0.77 = 0.35 mg;

[0265] The in-situ correction for the heavy, low-volatile section is:

[0266] N 3,corr = 0.28 / 0.70 = 0.40 mg;

[0267] The total in-situ correction amount for lubricating oil cracking products is:

[0268] N org,corr = ΣN j,corr = 0.25 + 0.35 + 0.40 = 1.00 mg;

[0269] Therefore, by using multi-internal-standard segmented correction, the gas phase detection amount, condensate recovery amount, pipe wall adsorption amount, and residual amount can all be included in the calculation to restore the true amount of lubricating oil cracking simulant added to the supercritical carbon dioxide standard sample. If only the gas phase detection amount is used, the total amount detected is only 0.32 mg, which will significantly underestimate the in-situ total amount.

[0270] In this embodiment, the mass closure deviation during the calibration stage is determined by the following formula:

[0271] ε cal,j = |n 0,j - (n g,j + n c,j+ n a,j + n f,j + n r,j )| / n 0,j × 100%;

[0272] When expressed in mass form, n is converted to the corresponding mass. Calibration results show that the closure deviations after segmented recovery for the light volatile section, medium volatile section, and heavy low volatile section are approximately 16%, 22.9%, and 30%, respectively. Among these, the closure deviation for the light volatile section is relatively low and can be used for quantitative correction; the closure deviations for the medium volatile section and the heavy low volatile section, due to significant agglomeration, adsorption, and residual losses, are still within the acceptable range for calibration of complex organic mixtures, but their uncertainty should be reflected in the fidelity rating.

[0273] Example 4: Based on Example 1, Example 4 provides a specific example of reference correction and leakage detection for non-condensable gases.

[0274] This embodiment illustrates an auxiliary reference correction method for non-condensable or weakly condensable gases during supercritical carbon dioxide sampling. The non-condensable or weakly condensable gases are not the core target of sampling distortion caused by changes in the solubility of supercritical carbon dioxide in this invention, but can be used for dead volume dilution, leakage contamination, flow rate integral error, instrument drift, and determination of sampling path validity.

[0275] In this embodiment, argon is used as a stable reference gas, and oxygen and nitrogen are used as the gases to be calibrated. 50 μmol / mol argon (CO2), 10 μmol / mol oxygen (CO2), and 100 μmol / mol nitrogen (CO2) are added to a supercritical carbon dioxide standard sample. The standard sample is then passed through the calibration sampling path and analyzed by a gas chromatograph. The results show that the measured concentration of argon is 45 μmol / mol CO2, the measured concentration of oxygen is 7.2 μmol / mol CO2, and the measured concentration of nitrogen is 103 μmol / mol CO2. Since argon undergoes minimal condensation, adsorption, and reaction loss during sampling, it can be used as a reference component for dead volume dilution and detection response deviation.

[0276] The reference correction factor is determined by the following formula:

[0277] β = C ref,0 / C ref,m ;

[0278] Among them, C ref,0 C represents the theoretical concentration of argon gas. ref,m This represents the measured concentration of argon gas. Substitute the data:

[0279] β = 50 / 45 = 1.11;

[0280] The oxygen correction concentration is:

[0281] C(O2,corr) = β · C(O2,m) = 1.11 × 7.2 = 8.0 μmol / mol CO2;

[0282] The nitrogen correction concentration is:

[0283] C(N2,corr) = β · C(N2,m) = 1.11 × 103 = 114.3 μmol / mol CO2;

[0284] If the nitrogen correction concentration is significantly higher than the theoretical addition concentration, while the oxygen correction concentration is lower than the theoretical addition concentration, it indicates that air ingress and oxygen consumption may occur simultaneously in the sampling path or system. Air ingress leads to an increase in nitrogen levels, while oxygen may be partially consumed at high-temperature walls, on residual active metal surfaces, or during the oxidation of organic matter. In this case, the non-condensable gas correction result can be used not only for concentration correction but also to determine whether there are leaks, wall reactions, or reactive contaminants in the sampling path.

[0285] In this embodiment, if the nitrogen level is still higher than the preset threshold after argon reference correction, it is determined that there is a risk of air contamination in the sampling system; if the oxygen level is significantly lower than the corresponding concentration of nitrogen calculated based on the air ratio, it is determined that there may be oxygen consumption in the sampling path or system. In this case, the result of this non-condensable gas detection can be used for leak identification and sampling path effectiveness evaluation, but it should not be directly used as a quantitative result of the original oxygen content of the system's working fluid. It needs to be further confirmed by combining blank path calibration and repeated sampling results.

[0286] Example 5: Based on Example 1, Example 5 provides a specific implementation case for actual sample correction based on a tabular sampling distortion calibration matrix.

[0287] This embodiment illustrates the application method of tabular sampling distortion calibration matrix in actual supercritical carbon dioxide system sampling and detection.

[0288] A sampling path is set up in a supercritical carbon dioxide test loop. The sampling point operates at 20 MPa and 200 °C. The sampling path includes a high-pressure sampling valve, a first-stage pressure-reducing element, a heat tracing pipeline, a cooling section, a separation and collection unit, and a gas phase detection unit. Using the methods of Examples 1 and 2, a tabular sampling distortion calibration matrix corresponding to this sampling path has been established, as shown in Table 4.

[0289]

[0290] During the actual sampling process, the trace water analyzer, total hydrocarbon analyzer, gas chromatograph, and condensate measurement unit obtained the following test results:

[0291] The effective detection concentration of moisture after blank background subtraction, desorption tailing back calculation and adsorption loss correction is 32 μmol / mol CO2;

[0292] The gas phase detection result for the light volatile section was 0.18 mg / kg CO2;

[0293] The combined observed value of the gas phase and condensed phase in the intermediate volatile section was 0.28 mg / kg CO2;

[0294] The combined observed value of the condensed phase, flushing recovery, and residual recovery in the heavy, low-volatile section was 0.21 mg / kg CO2;

[0295] The argon reference correction factor β is 1.05.

[0296] According to Table 3, the actual operating conditions fall within the calibration range of 18–22 MPa and 180–220 ℃, and the corresponding recovery rates can be obtained directly by reference or interpolation. The overall effective moisture recovery rate R is calculated. p,eff,w = 0.87, then the in-situ water concentration is:

[0297] C(0,w) = 32 / 0.87 = 36.8 μmol / mol CO2;

[0298] If the overall effective recovery rate of the light volatile section is η1 = 0.84, then its in-situ correction is:

[0299] N 1,corr = 0.18 / 0.84 = 0.214 mg / kg CO2;

[0300] If the overall effective recovery rate of the intermediate volatility section is taken as η2 = 0.77, then its in-situ correction is:

[0301] N 2,corr = 0.28 / 0.77 = 0.364 mg / kg CO2;

[0302] If the overall effective recovery rate of the heavy, low-volatile section is taken as η3 = 0.70, then its in-situ correction is:

[0303] N 3,corr = 0.21 / 0.70 = 0.300 mg / kg CO2;

[0304] The total in-situ correction amount for organic impurities is:

[0305] N org,corr= 0.214 + 0.364 + 0.300 = 0.878 mg / kg CO2;

[0306] If the sampling distortion calibration and correction method of this invention is not used, and the detected values ​​after sampling are simply summed, the total amount of organic impurities is:

[0307] 0.18 + 0.28 + 0.21 = 0.67 mg / kg CO2;

[0308] After correction using the method of this invention, the total in-situ organic impurities were 0.878 mg / kg CO2, indicating that this sampling route systematically underestimates organic impurities. This underestimation mainly originates from condensation, adsorption, and residues in the medium-volatility section and the heavy low-volatility section during pressure reduction, cooling, and pipe wall contact processes.

[0309] Based on the calibration quality closure deviation, effective recovery rate, internal standard recovery deviation, and blank background stability of the matched calibration line, this moisture detection is classified as Grade B, which can be used for quantitative correction; the light and medium volatile sections are also classified as Grade B; the heavy low volatile section is classified as Grade C based on the worst-case indicator because the effective recovery rate is close to the boundary between Grade B and Grade C and the quality closure deviation is large. It can be used for trend judgment and semi-quantitative evaluation, and it is recommended to flush the pipeline or shorten the sampling path before the next sampling.

[0310] As can be seen from this embodiment, the tabular sampling distortion calibration matrix can transform complex sampling path distortion information into queryable, interpolable, and reusable correction parameters, enabling the actual detection results to be further transformed from "post-sampling detection values" into "in-situ concentrations in the system loop," thereby improving the data comparability between different sampling points, different operating conditions, and different detection batches.

[0311] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for calibrating and correcting sampling distortion of trace impurities in supercritical carbon dioxide working fluid, characterized in that, Includes the following steps: S1: Determine the type of the target trace impurity, the sampling path to be calibrated, and the object to be calibrated; S2: Divide the sampling path into several functional segments and obtain the sampling path parameters for each functional segment; S3: Under calibration conditions, based on the target trace impurity type, obtain a supercritical carbon dioxide standard sample with a known addition amount or known in-situ concentration of that type; S4: Use supercritical carbon dioxide that is free of the target trace impurities or whose target trace impurity content is lower than the preset threshold to perform blank calibration on the sampling path to be calibrated, record and obtain the blank deduction amount of the sampling path under blank conditions. S5: Introduce the supercritical carbon dioxide standard sample into the sampling path to be calibrated to obtain the segmented detection quantity of each functional segment; S6: Based on the segmented detection amount and combined with the blank deduction amount, the transmission throughput and segmented effective recovery rate of the target trace impurities in each functional segment are obtained through the mass closure relationship, so as to obtain the recovery rate of the sampling path in a comprehensive manner. S7: By adjusting the state parameters, target trace impurity parameters, and sampling path parameters of the supercritical carbon dioxide standard sample, and repeating steps S3-S6, various detection and calculation results under different conditions are obtained, thereby establishing a tabular sampling distortion calibration matrix. S8: During actual sampling, the actual sampling conditions are matched with the tabular sampling distortion calibration matrix to find suitable sampling conditions, and the corresponding detection and calculation results are output for correction.

2. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 1, characterized in that, In step S1: The identified target trace impurities include: moisture, light hydrocarbons, heavy hydrocarbons, lubricating oil cracking products and oxygen-containing organic matter, trace components that are soluble, condensable, easily adsorbed or easily undergo partition changes, as well as non-condensable or weakly condensable gases. The sampling path to be calibrated is the entire path that the sample travels from the sampling point in the supercritical carbon dioxide system loop to the inlet of the detection instrument, including one or more of the following: sampling valve, pressure reducing element, transmission pipeline, heat tracing pipeline, cooling section, filter element, separation unit, collection unit, pretreatment unit for detection and inlet of the detection instrument; The calibration targets include one or more of the following during the sampling process: changes in carbon dioxide density, changes in solubility, valve retention, tube wall adsorption, condensation, filtration retention, separation loss, dead volume dilution, changes in pretreatment recovery rate, and detection response drift of the target trace impurities.

3. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 1, characterized in that, Step S2 further includes the following steps: Based on the sampling path parameters of each functional segment, a segmented state trajectory of the target trace impurity in the sampling path is established. Establish the degree of change in carbon dioxide density D in the k-th functional segment. k The calculation model is used to simultaneously establish the solubility margin M of the i-th type of target trace impurity in the k-th functional segment. k,i Computational model; When D k Exceeding the preset threshold, or M k,i If the value is less than the preset threshold, it is determined that there is a risk that the target trace impurities may precipitate, condense, adsorb, or redistribute between phases due to the decrease in carbon dioxide density, the decrease in solubility, or the change in phase path.

4. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 1, characterized in that, The specific steps of step S6 include: Based on the segmented detection quantities, the existence state of the target trace impurities after sampling is divided into gas phase, condensed phase, adsorbed phase, cut-off phase, residual phase, and unrecovered loss; wherein, for the i-th type of target trace impurity, the material balance relationship in its calibration process is: n 0,i = n g,i + n c,i + n a,i + n f,i + n r,i + n lost,i In the formula, n 0,i n represents the known amount or equivalent in-situ amount of the i-th target trace impurity in a supercritical carbon dioxide standard sample; g,i For gas phase detection quantity; n c,i n represents the amount of condensed phase recovered. a,i n represents the amount of material adsorbed and recovered from the pipe wall or component. f,i For the amount of material to be filtered or retained for recovery; n r,i For pretreatment or other residual recovery amounts; n lost,i This refers to the amount of unrecovered losses. Based on material balance, the distribution ratio of the target trace impurity in different phases or positions is obtained: F g,i = n g,i / n 0,i ;F c,i = n c,i / n 0,i ;F a,i = n a,i / n 0,i In the formula, F g,i F c,i F a,i These represent the distribution ratios of the i-th target trace impurity in the gas phase, condensed phase, and adsorbed phase, respectively. Subsequently, the transport throughput and segmented effective recovery rate of the i-th target trace impurity in the k-th functional segment were calculated: T k,i = n out,k,i / n in,k,i E k,i = (n out,k,i + n rec,k,i ) / n in,k,i In the formula, T k,i E represents the transport throughput of the i-th target trace impurity in the k-th functional segment. k,i n represents the segmented effective recovery rate of the i-th target trace impurity in the k-th functional segment; in,k,i For the i-th type of target trace impurity mass entering the k-th functional segment; n out,k,i For the i-th type of target trace impurity mass leaving the k-th functional segment and entering the next functional segment or detection unit; n rec,k,i The target trace impurity quantity included in the correction amount is the amount of the i-th type of trace impurity that is recovered in the k-th functional segment through agglomerate collection, filtration retention, tube wall flushing, thermal desorption, solvent extraction, or pre-detection treatment. Considering the throughput and effective recovery rate of each functional segment, when the target trace impurity passes through each functional segment continuously in gaseous form without measurable agglomeration, adsorption, retention, or residual recovery, the gas-phase transport recovery rate of the entire sampling path is: R g,i = T 1,i · T 2,i · …… · T m,i When the target trace impurity undergoes aggregation, adsorption, retention, residue, or phase separation recovery during the sampling path, the overall effective recovery rate of the entire sampling path is R. p,eff,i =(n g,i + n c,i + n a,i + n f,i + n r,i ) / n 0,i .

5. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 1, characterized in that, Step S7 further includes a step of correcting the detection quantity based on the target trace impurity type, based on the tabulated sampling distortion calibration matrix: When the target trace impurity is moisture, the adsorption capacity, adsorption rate, desorption rate, response hysteresis time and tailing integral of the sampling path for moisture are obtained through blank purging, calibration of water-containing standard samples and recovery of dried samples. In actual moisture detection, the output value of the trace moisture analyzer is corrected based on the background of blank water release before sampling, the rise time of the current moisture detection curve, the stable plateau, the integral response, and the desorption tail after sampling, to obtain the corrected effective moisture detection quantity: n w,corr = n w,m -n b,w + n des,w + n ads,w In the formula, n w,corr This is the corrected effective moisture detection amount; n w,m The water content measured by a trace water analyzer; n b,w Water content for blank background; n des,w For sampling path desorption tail back calculation; n ads,w This is an estimate of the amount of sample that was adsorbed by the tube wall or components during the sampling process and did not enter the detector.

6. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 1, characterized in that, Step S7 further includes a step of correcting the detection quantity based on the target trace impurity type, based on the tabulated sampling distortion calibration matrix: When the target trace impurity is an organic target trace impurity, it is divided into at least two component segments according to the carbon number range, boiling point range, polarity, volatility, supercritical carbon dioxide solubility, or wall adsorption tendency of the target trace impurity. For different component segments, internal standards with similar boiling point range, carbon number range, polarity, supercritical carbon dioxide solubility, and wall adsorption tendency were selected. During actual sampling, multiple internal standards are added to the sampling branch or standard sample in known amounts, so that they and the target trace impurities go through the same sampling path, in order to obtain the real-time recovery rate of the internal standards and the overall effective recovery rate of the component segment. Based on the real-time recovery rate and the overall effective recovery rate, the observed recovery amount and in-situ correction amount of each component segment are obtained, and the total correction amount of the final organic target trace impurities is further obtained.

7. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 1, characterized in that, Step S7 further includes a step of correcting the detection quantity based on the target trace impurity type, based on the tabulated sampling distortion calibration matrix: When the target trace impurity is a non-condensable or weakly condensable gas, corrections are made based on the reference component or standard gas to account for dead volume dilution, leakage contamination, flow integral deviation, wall reaction loss, and detection drift, resulting in a reference correction factor: β = C ref,0 / C ref,m In the formula, β is the reference correction factor; C ref,0 The theoretical or calibrated concentration of the reference component; C ref,m This represents the measured concentration of the reference component. The detection concentration of non-condensable or weakly condensable gases is corrected using a reference correction factor: C g,corr = β · C g,m In the formula, C g,corr For corrected concentrations of non-condensable or weakly condensable gases; C g,m This represents the measured concentration of the gas.

8. A method for calibrating and correcting sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to any one of claims 1 to 7, characterized in that, The specific correction steps in step S8 include: S801: During the actual operation of a supercritical carbon dioxide system, the detected values ​​and real-time sampling status parameters are obtained; S802: Based on real-time sampling status parameters, the corresponding segmented recovery rate, path recovery rate, phase distribution ratio, solubility margin, and pretreatment recovery rate are obtained by matching or interpolating from the tabular sampling distortion calibration matrix; and combined with the real-time recovery rate of the internal standard, the correction results of the reference component, the blank background subtraction results, the mass closure deviation of the matching calibration row, and the actual sampling validity judgment results, a comprehensive correction model for the target trace impurities is constructed to invert the in-situ concentration of the target trace impurities; S803: During the calibration process, the validity is determined by quality closure verification or by matching the degree of matching of parameters in the calibration row; S804: Finally, output the in-situ concentration correction results and the sampling fidelity evaluation results.

9. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 8, characterized in that, The calculation model for the sampling fidelity is as follows: F Ii = R use,i · (1-e i / 100); In the formula, F Ii R is the sampling fidelity index for the i-th target trace impurity; use,i The effective recovery rate used for evaluating the fidelity of trace impurities in this target; ε i This refers to the quality closure deviation used for fidelity evaluation.

10. The method for calibration and correction of sampling distortion of trace impurities in supercritical carbon dioxide working fluid according to claim 9, characterized in that, The grading and evaluation steps for sampling fidelity include: When R is satisfied simultaneously use,i ≥0.90, ε i If the sampling results are ≤10%, the blank background ratio is ≤10%, the actual sampling conditions are within the applicable range of the tabular sampling distortion calibration matrix, and the internal standard recovery rate deviation is ≤10% when using internal standard, the sampling results are judged to be of Class A fidelity, which can be used for in-situ concentration quantitative evaluation and can be used for direct comparison between results from different sampling points or different batches. When 0.70≤R use,i <0.90, or 10% <ε i If the sampling result is ≤30%, or 10% < blank background ratio ≤30%, or 10% < internal standard recovery deviation ≤30% when using internal standard, and the actual sampling conditions are still within the applicable range of the tabular sampling distortion calibration matrix, the sampling result is determined to be of Class B fidelity, which can be used for in-situ concentration correction and engineering quantitative evaluation, but the uncertainty range or fidelity description should be given at the same time. When 0.50≤R is satisfied use,i <0.70, or 30% < ε i If the sampling result is ≤50%, or the blank background ratio is greater than 30%, or the internal standard recovery rate deviation is greater than 30% when using internal standards, or the actual sampling conditions are close to the applicable boundary of the tabular sampling distortion calibration matrix, the sampling result is determined to be of C-level fidelity. It is only suitable for trend judgment, semi-quantitative evaluation or auxiliary analysis of impurity sources, and should not be used as a basis for accurate quantification on its own. When R use,i If the value is less than 0.50, or the actual sampling conditions exceed the applicable range of the tabular sampling distortion calibration matrix, or the blank background is unstable and cannot be subtracted, or an internal standard is used but the internal standard is not effectively recovered, the sampling result is deemed unsuitable for in-situ concentration quantitative correction, and the sampling path should be recalibrated, the sampling path adjusted, or the pretreatment conditions optimized. When different evaluation indicators correspond to different fidelity levels, the final fidelity level shall be determined according to the lowest fidelity level among them.

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