Method for constructing a ternary gas impurity control threshold model under high temperature and inert conditions

Abstract

This invention discloses a method for constructing a ternary gas impurity control threshold model under high-temperature inert conditions. The steps are as follows: Analyze the possible types of impurity corrosion reactions that may occur in the material, and establish a two-dimensional critical partial pressure spectrum of a single impurity versus temperature; vary the impurity partial pressure under constant total pressure to determine the dominant corrosion reaction types for different ratios; select representative impurity gas proportion points in the dominant reaction region, subject the material to high-temperature corrosion reaction, and analyze the actual dominant corrosion reaction types; normalize the theoretical and actual dominant corrosion reactions to construct a ternary impurity ratio and corrosion reaction type response model; set failure critical conditions, and use the corrosion reaction type as the criterion to obtain the ternary impurity control threshold model. This invention clarifies the critical partial pressure relationship of the "oxidation-carbonization-volatilization-stabilization" region by examining the influence of different impurity combinations on the type, thickness, and diffusion depth of corrosion products on the surface of refractory alloys, and can be used to calculate the key impurity control thresholds for high-temperature alloy materials.

Description

Technical Field

[0001] This invention relates to the field of material-working fluid interface compatibility technology in nuclear energy and high-temperature power systems, and more specifically, to a method for constructing a ternary gas impurity control threshold model under high-temperature inert gaseous working fluid conditions. Background Technology

[0002] Currently, advanced nuclear energy systems and high-efficiency energy conversion systems using high-temperature inert gaseous working fluids as heat transfer media are becoming an important development direction in the energy field. High-temperature inert gases (such as helium, argon, xenon, or mixtures thereof) are the preferred working fluids for closed Brayton cycles and high-temperature gas-cooled reactors due to their excellent thermophysical properties and chemical stability. Meanwhile, to further improve thermal efficiency and achieve reactor miniaturization and long-life operation, system operating temperatures are constantly rising, with some approaching or exceeding 1500K. Under such extreme high-temperature conditions, although inert gases themselves have extremely low chemical reactivity, trace impurities such as H2O, O2, CO, and CO2 are still unavoidable in the working fluid due to process limitations and operating environment influences. These impurities, even at the ppm level, can trigger severe oxidation, carbonization, decarburization, and even evaporative corrosion reactions, especially when ultra-high temperature refractory alloys such as Mo, Nb, and W are used as structural materials, further amplifying their interfacial reactivity. Taking Mo alloys as an example, they can work stably under low oxygen partial pressure, but when the temperature exceeds 1200K, even 5ppm of H2O or O2 impurities may induce the volatilization of surface MoO3 oxides, leading to rapid material failure.

[0003] Currently, while international projects such as HTTR (Japan), HTR-PM (China), and NASA's Nuclear Thermal Propulsion Reactor (NTP) have established gaseous impurity control specifications for helium-cooled reactors, these specifications are largely based on operational experience with graphite cores and traditional high-temperature alloys (such as Ni-based alloys). Their control limits and theoretical models are not applicable to next-generation systems using refractory metal materials, operating at higher temperatures, and employing more complex working fluids. Crucially, most existing specifications are based on empirical rules or single-factor corrosion experiments, lacking a deep understanding of the synergistic reaction mechanisms among impurities. For example, under certain conditions, O2 may inhibit the carbonization of CH4, while the coexistence of CO2 and H2O may cause instability in the oxide layer, leading to material spalling. This phenomenon of "synergistic corrosion" among multiple impurities is particularly complex in ultra-high temperature environments, resulting in significant prediction biases based on traditional thermodynamic models.

[0004] In summary, existing methods for assessing material corrosion and setting impurity limits in ultra-high temperature inert gas environments cannot meet the system's requirements for long-term operational safety and material life prediction. Therefore, there is an urgent need to develop a method for constructing gaseous impurity control thresholds that is applicable to high-temperature inert gaseous working fluid environments, considers the synergistic reaction effects among multiple impurities, and combines theoretical modeling with experimental data.

[0005] In view of the above, this application is hereby submitted. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a method for constructing a ternary gas impurity control threshold model under a high-temperature inert gaseous working environment. By studying the influence of different impurity combinations on the type, thickness, and diffusion depth of corrosion products on the surface of refractory alloys, the quantitative relationship between impurity concentration, component ratio, temperature, and material reaction is clarified. A thermodynamic boundary map between temperature, impurity partial pressure, and material corrosion reaction type is constructed, and the critical partial pressure relationship of the "oxidation-carbonization-volatilization-stability" region is defined. This method can be used to calculate the key impurity control thresholds for different high-temperature alloy materials.

[0007] This invention is achieved through the following technical solution: This invention provides a method for constructing a ternary gas impurity control threshold model under high-temperature inert conditions, comprising the following steps: S1. Analyze the types of impurity corrosion reactions that may occur in alloy materials in a high-temperature inert atmosphere, and establish a two-dimensional critical partial pressure spectrum of a single impurity versus temperature; under the same total pressure, vary the partial pressure of three impurities to determine the dominant corrosion reaction types of different ternary ratio combinations, and obtain a theoretical dominant reaction region map. S2, select representative impurity gas ratio points for each dominant reaction region, and conduct high-temperature corrosion reaction on the alloy material; characterize the surface of the alloy material after corrosion and analyze the actual dominant corrosion reaction type; S3. The theoretical dominant reaction region map and the actual dominant corrosion reaction type are normalized to construct a response model of ternary impurity ratio and corrosion reaction type. Using the corrosion reaction type as the criterion and combined with the "failure critical condition" of the working condition, the ternary impurity control threshold model is derived in reverse.

[0008] This invention investigates the influence of different impurity combinations on the type, thickness, and diffusion depth of corrosion products on the surface of refractory alloys, clarifies the quantitative relationship between impurity concentration, component ratio, temperature, and material reaction, constructs a thermodynamic boundary map between temperature, impurity partial pressure, and material corrosion reaction type, and clarifies the critical partial pressure relationship of the "oxidation-carbonization-volatilization-stability" region, which can be used to calculate the key impurity control thresholds for different high-temperature alloy materials.

[0009] This invention, through the efficient synergy of multivariate experiments and theoretical modeling, overcomes the limitations of single-factor empirical rules in traditional nuclear propellant management. It can construct a highly reliable and universally applicable impurity control threshold model, significantly improving the scientific rigor, specificity, and engineering adaptability of impurity limit setting. This provides a scientific, accurate, and engineering-practical technical means for corrosion control of materials in high-temperature inert gas cooling systems. In a specific embodiment, in step S1, the types of impurity corrosion reactions include oxidation reactions, carbonization reactions, and evaporation reactions.

[0010] In a specific implementation, the method for establishing a two-dimensional critical partial pressure spectrum of a single impurity versus temperature in step S1 is as follows: ΔH for each reaction was obtained using a thermodynamic database. 0 ΔS 0 ΔG 0 data; Temperature dependence analysis of ΔG for each reaction was performed using the Gibbs minimum free energy principle; The expression for the critical reaction partial pressure is derived using the thermodynamic equilibrium equation, the critical partial pressure of impurities for each reaction is determined, and the critical partial pressure curves of a single impurity at different temperatures are established.

[0011] In a specific implementation, the method for establishing the theoretically dominant reaction region map in step S1 is as follows: By varying the partial pressures of the three impurities under constant total pressure, and substituting the ΔG expression for each reaction under each ratio combination, the reaction thermodynamic conditions under each impurity ratio are calculated. Determine the dominant corrosion reaction type for all ratio combinations and map it to the corresponding ternary coordinate points; Based on the dominant corrosion reaction type, draw a map of the theoretical dominant reaction region.

[0012] In a specific implementation, in step S2, the data characterized include the corrosion layer thickness, phase composition, surface morphology, and element diffusion depth.

[0013] This invention combines density functional theory with experimental fitting formulas to establish a relationship between the Gibbs energy model of corrosion reaction and the partial pressure function of impurities. This enables the quantification and calculability of impurity control. In engineering, the upper limit of impurity control can be directly derived from the operating temperature, providing target parameters for coolant purification systems. In a specific implementation, the criteria for determining the actual dominant corrosion reaction type in step S2 include: a) If the corrosion layer thickness is >3 μm and it is mainly composed of oxides, then it is determined that the oxidation reaction is dominant; b) If there is a distinct carbide phase of the alloy and it is enriched with C, then it is determined that the carbide reaction is dominant. c) If the corrosion morphology is pitting or surface erosion, and gaseous signals of alloy oxides or alloy species are found, it is determined that the evaporation reaction is dominant. d) If the material has minimal mass loss and the corrosion layer is discontinuous or amorphous, it is considered to be inert and stable.

[0014] In one particular implementation, the response model is constructed using multivariate regression, response surface methodology (RSM), or artificial neural network (ANN).

[0015] In a specific implementation, the response model is constructed by using the impurity partial pressure ratio and temperature as input variables, and the corrosion rate or corrosion layer thickness of the alloy material as the response output variable.

[0016] In a specific implementation method, the construction method of the ternary impurity control threshold model is as follows: Based on the output of the response model, a global simulation of the ternary impurity space is performed, and the dominant reaction region is plotted. A clear "failure critical condition" is set, and the corresponding impurity control threshold line is solved by using corrosion rate and corrosion layer thickness as criteria. By combining theoretical calculations with experimental verification results, the impurity control threshold spectrum within the ternary impurity system was accurately plotted, clarifying the precise boundaries of the oxidation-dominated region, carbonization-dominated region, evaporation-dominated region, and inert stable region.

[0017] In one specific implementation, the method for constructing the impurity control threshold model further includes step S4, iterative optimization of the impurity control threshold model: Points or boundary areas near the ternary spectrum boundary were selected as extended experimental groups to verify the accuracy of the constructed impurity threshold model prediction and ensure that the model prediction error is controlled within ±10%. If the model prediction error exceeds the specified range, supplementary experimental data collection and theoretical calculation optimization should be carried out, and the model parameters should be iterated repeatedly until the model error is within an acceptable range.

[0018] Compared with the prior art, the present invention has the following advantages and beneficial effects: 1. The method for constructing a ternary gas impurity control threshold model under high temperature inert environment provided in this embodiment of the invention clarifies the synergistic mechanism of the influence of multiple impurities on the corrosion behavior (oxidation, carbonization, evaporation) of ultra-high temperature (>1000℃) materials, and determines the critical impurity partial pressure conditions for each reaction type. 2. The method for constructing a ternary gas impurity control threshold model under high temperature and inert environment provided in this embodiment of the invention can divide the material service behavior into "oxidation-dominated zone", "carbonization-dominated zone", "evaporation-dominated zone" and "inert safety zone" by constructing a corrosion boundary map of the ternary atmosphere, and provide a safety window map based on temperature and impurity concentration for engineering design. 3. The method for constructing a ternary gas impurity control threshold model under high temperature inert environment provided in this embodiment of the invention breaks through the limitation of single-factor empirical rules in traditional nuclear working fluid management through the efficient collaboration of multivariate experiments and theoretical modeling. It can construct a highly reliable and universal impurity control threshold model, significantly improving the scientificity, pertinence and engineering adaptability of impurity limit setting, and providing a scientific, accurate and engineering-practical technical means for corrosion prevention and control of materials in high temperature inert gas cooling systems. 4. The method for constructing a ternary gas impurity control threshold model under high temperature inert environment provided in this embodiment of the invention combines density functional theory and experimental fitting formula to establish the relationship between the corrosion reaction Gibbs energy model and the impurity partial pressure function, thereby realizing the quantification and calculability of impurity control. In engineering, the upper limit of impurity control can be directly derived from the operating temperature, providing target parameters for the coolant purification system. 5. The method for constructing a ternary gas impurity control threshold model under high temperature inert environment provided in this embodiment of the invention has material independence and atmosphere adjustability. It is not only applicable to various inert gas working fluid systems such as helium, helium-xenon, and CO2, but can also be extended to new application fields such as supercritical CO2 energy conversion systems, deep space nuclear thermal propulsion systems, and aviation nuclear power systems. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments. The illustrative embodiments and descriptions of this invention are only used to explain this invention and are not intended to limit this invention.

[0020] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other embodiments, well-known materials or methods have not been specifically described in order to avoid obscuring the invention.

[0021] Throughout this specification, references to “an embodiment,” “an example,” or “an example” mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases “an embodiment,” “an example,” “an example,” or “an example” appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. The term “and / or” as used herein includes any and all combinations of one or more of the associated listed items.

[0022] The "range" disclosed in this application is defined by a lower limit and an upper limit. A given range is defined by selecting a lower limit and an upper limit, which define the boundaries of a particular range. Ranges defined in this way can include or exclude endpoints and can be arbitrarily combined; that is, any lower limit can be combined with any upper limit to form a range. For example, if ranges of 60–120 and 80–110 are listed for a specific parameter, it is understood that ranges of 60–110 and 80–120 are also expected. Furthermore, if minimum range values ​​of 1 and 2 are listed, and if maximum range values ​​of 3, 4, and 5 are listed, then the following ranges are all expected: 1–3, 1–4, 1–5, 2–3, 2–4, and 2–5. In this application, unless otherwise stated, the numerical range "a–b" represents a shortened representation of any combination of real numbers between a and b, where a and b are real numbers. For example, the numerical range "0~5" indicates that all real numbers between "0~5" have been listed in this article; "0~5" is simply a shortened representation of these numerical combinations. Furthermore, when a parameter is stated as an integer ≥2, it is equivalent to disclosing that the parameter is, for example, an integer such as 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, etc.

[0023] Unless otherwise specified, all steps in this application may be performed sequentially or randomly, preferably sequentially. For example, the method includes steps (a) and (b), indicating that the method may include steps (a) and (b) performed sequentially, or it may include steps (b) and (a) performed sequentially. For example, the method may also include step (c), indicating that step (c) may be added to the method in any order. For example, the method may include steps (a), (b), and (c), or it may include steps (a), (c), and (b), or it may include steps (c), (a), and (b), etc. Example

[0024] This invention provides a method for constructing a ternary gas impurity control threshold model under high-temperature inert conditions, comprising the following steps: S1, Theoretical calculation to construct the initial impurity threshold model S11, Corrosion Reaction Type Analysis Typical refractory metal and alloy material systems were selected to identify the types of corrosion reactions that may occur under high-temperature inert conditions. A representative O2-H2O-CO2 ternary impurity system was chosen, with Mo alloy as the research object, as detailed below: (1) Oxidation pathway: Mo+O2→MoO2 (solid state) Mo+H2O→MoO2+H2 (2) Carbonization pathway: Mo + CO2 → Mo2C + O2 (forming carbides) Mo + CO → Mo₂C + O (3) Evaporation path: MoO2(s)⇌MoO2(g) MoO2(s) + 1 / 2O2 → MoO3(g) S12, Construction of a Thermodynamic Parameter Collection and Calculation Platform (1) Using standard thermodynamic databases, such as JANAF, NIST, and FACTPS databases, obtain the ΔH for each reaction. 0 ΔS 0 ΔG 0 Data, calibrating the database's effectiveness within the target temperature range; (2) Then, using thermodynamic calculation software such as FactSage and Thermo-Calc, input the reaction equations and calculate the specific values ​​of the standard Gibbs free energy change (ΔG) of each reaction in a specific temperature range using the Gibbs minimum free energy principle, so as to clarify the thermodynamic spontaneous conditions of each reaction. (3) Derive the expression for the critical reaction partial pressure using the thermodynamic equilibrium equation, for example: ΔG=ΔG 0 +RT ln(pO2), and then the inverse solution yields pO2=exp[(ΔG-ΔG 0 ) / RT]; (4) Finally, based on the reaction thermodynamic equilibrium condition (ΔG=0), the critical partial pressure of impurities for each reaction type at different temperatures is determined, forming a two-dimensional critical partial pressure spectrum of a single impurity versus temperature, and the critical corrosion conditions are preliminarily judged. S13, ternary impurity space thermodynamic mapping (1) Define coordinate normalization rules in the ternary impurity space. x O2+ x H2O+ xCO2=1 ensures that any mixing ratio can be visualized on a triangular projection diagram, meaning that any impurity ratio can be expressed in a triangular coordinate system, and the impurity concentration (pO2, pH2O, pCO2) at any point is converted into a normalized concentration ratio. x O2, x H2O, x CO2); (2) Based on the critical partial pressure of a single impurity, the system is extended to a ternary impurity system. By varying the partial pressures of the three impurities under the same total pressure, the ΔG values ​​of each possible reaction are calculated by substituting the ΔG expression of each reaction into a large number of possible impurity ratio combinations. Based on the principle of minimum energy, the dominant reaction type (oxidation, carbonization, evaporation or inert stability) of each impurity combination point is determined. (3) Construct a data processing program to automatically identify the dominant corrosion reaction type for all ratio combinations and map it to the corresponding ternary coordinate points; (4) Based on the classification of dominant corrosion reaction types, a preliminary map of the dominant regions of theoretical ternary heterogeneous corrosion is drawn to clarify the theoretical boundaries of the oxidation-dominated region, carbonization-dominated region, evaporation-dominated region and inert stability region. (5) Finally, MATLAB or Python (Matplotlib + Numpy) is used to identify the region and smooth the boundary of the ternary heterogeneous corrosion-dominant region map. At the same time, the temperature level map (such as the maps of 1200 K, 1400 K and 1600 K) is further refined by combining the critical partial pressure calculation results.

[0025] S2. The model was validated using actual corrosion experimental data of alloy materials under atmospheres with different impurity ratios. S21, Impurity Ratio Point Design (1) Referencing the theoretical ternary heterogeneous corrosion dominant region map, select representative impurity ratio points from each dominant reaction region, with no less than 3 points selected for each region to ensure uniform distribution and comprehensive coverage of each corrosion region by experimental data; (2) Using the D-Optimal design principle, a comprehensive experimental matrix is ​​generated by considering the multi-level combination of three factors: temperature, ratio, and reaction pressure. (3) After normalizing all experimental points, a triangular coordinate layout map is formed and compared with the map of the dominant ternary heterogeneous corrosion area to verify the scientific validity of the location.

[0026] S22, Experimental Design and Corrosion Experiment Implementation (1) Experimental apparatus composition: A high-precision temperature-controlled high-temperature tubular furnace is used. The experimental section is equipped with two-point thermocouples for real-time temperature measurement, and a real-time pressure monitoring and overpressure relief device is provided to ensure the temperature inside the furnace is stable and to prevent the furnace tubes from rupturing due to overpressure. A mass flow controller (MFC) is configured to control the flow rate of the gas introduced. An online gas monitoring unit is set up for measuring the system cleaning effect before the experiment and monitoring real-time gas changes. The inlet and outlet flanges of the tubular furnace are water-cooled flanges and connected to a water chiller for cooling, which effectively avoids external air leakage and high-temperature deformation of the sealing ring. Materials that are easy to react with impurity gases or that easily release impurity gases at high temperatures are avoided in the experimental section. EP-grade electrolytic polished pipes are used in the low-temperature section to prevent gas adsorption from interfering with the experimental results.

[0027] (2) System purification steps: Before the experiment, use 99.999% high-purity He to continuously purge for no less than 3 rounds, each round lasting 30 minutes; intermittently heat the sample section to about 100°C while using a high vacuum pump to purge the system (final vacuum degree <10 Pa) to completely remove residual impurity gases in the system; use an online gas monitoring unit to monitor the exhaust concentration curve and monitor the cleaning effect of the experimental system in real time. The reaction atmosphere can only be activated when the concentrations of O2, CO2, and H2O are stably below 0.1 ppm and maintained for 20 minutes; all process gas flow rates and atmosphere composition are recorded and archived in real time to ensure data traceability.

[0028] (3) Sample preparation: Mo alloy material is selected and processed into a uniform shape to ensure consistent exposed surface area. The cutting method for ultra-high temperature refractory alloys should be turning, slow wire EDM or diamond wire cutting, and wire cutting should not be used; at the same time, alcohol cleaning should be used, and water washing should be avoided as much as possible. After drying, it is sealed in a vacuum storage tank for later use to avoid oxidation or moisture absorption.

[0029] (4) Experimental conditions: The specified temperature and flow rate were set, and the corrosion time for each impurity combination was fixed at no less than 500 hours; three parallel samples were set for each experimental group to enhance the statistical repeatability; a control group (He environment only) was set up for comparison of normalized corrosion behavior; samples were taken at regular intervals during the experiment, and changes in sample mass were recorded. After the experiment, SEM, EDS, XPS, XRD, FIB-TEM and other analytical techniques were used to quantitatively characterize the corrosion layer thickness, phase composition, surface morphology and element diffusion depth.

[0030] S23, Corrosion Product Analysis and Dominant Reaction Identification (1) Morphology and structure analysis: SEM was used to observe the surface morphology after corrosion, and EDS was used to obtain the elemental distribution information of the surface scan; XRD was used to determine the main phase composition of the corrosion layer to determine whether it is an oxide (such as MoO2, MoO3) or a carbide (Mo2C); XPS was used to analyze the chemical state change of Mo to identify the oxidation state (Mo2C). 4+ / Mo6+ ) or carbon bond (Mo-C).

[0031] (2) Interface and diffusion analysis: cross-sectional samples were prepared using FIB, and the thickness of the corrosion layer and the continuity of the interface were analyzed using TEM high resolution. Line scan EDS was used to analyze the distribution of elements along the vertical direction to determine whether oxygen or carbon penetrated into the matrix.

[0032] (3) Quantitative judgment method for the dominant type of corrosion reaction: By comparing the data obtained from different analytical techniques, the following indicators are extracted: a) If the corrosion layer thickness is >3 μm and it is mainly composed of oxides, then it is determined to be oxidation-dominated; b) If a distinct Mo2C phase is present and enriched with C, it is determined to be dominated by carbonization; c) If the corrosion morphology is pitting or surface erosion, and gaseous signals of MoO3 or Mo species are found, it is determined to be evaporation-dominated; d) If the mass loss is extremely small (<0.2 mg / cm³) 2 Discontinuous or amorphous corrosion layers can be classified as inert stable regions.

[0033] The dominant reactions of all samples were numbered for subsequent response surface model construction and ternary spectrum classification.

[0034] S3, Accurately constructing an impurity control threshold model by combining experiments and theory. Based on theoretical calculations and corrosion experiments, a combined analysis of experiments and theory was conducted to construct an impurity control threshold model with quantitative capabilities and regional determination functions, as detailed below: S31, Data Normalization and Integration (1) Compare the corrosion reaction dominant region map (such as oxidation / carbonization / evaporation boundary) obtained by theoretical calculation with the corrosion dominant behavior type determined by experiment to verify the accuracy of theoretical model. Based on experimental data, make necessary adjustments and optimizations to the theoretical model and normalize the impurity ratio (triangular coordinate transformation).

[0035] (2) The dominant corrosion reaction type of all experimental sites is numbered and classified (e.g., 1 represents oxidation-dominant, 2 represents carbonization-dominant, 3 represents evaporation-dominant, and 0 represents inert stability) to form a labeled dataset.

[0036] S32, Response Model Construction Based on experimental data, the impurity partial pressure ratio ( x O2, x H2O, xUsing CO2 and temperature as input variables, and corrosion reaction type, corrosion layer thickness, or quantitative corrosion rate as response output variables, a high-precision quantitative corrosion response model is constructed using algorithms such as multivariate regression, response surface methodology (RSM), and artificial neural network (ANN), and a mapping relationship between "impurity ratio - reaction type" or "impurity ratio - corrosion rate" is established.

[0037] S33, Boundary Determination and Generation of Ternary Impurity Control Threshold Map (1) Based on the output results of the response model, a global simulation of the entire ternary impurity space (O2-H2O-CO2) is performed, and a dominant reaction interval diagram (thermodynamic + experimental correction version) is drawn and superimposed with actual experimental points.

[0038] (2) Set clear failure critical conditions based on operating conditions (e.g., corrosion rate > 1 mg / cm). 2 • h or corrosion layer thickness > 5µm), using corrosion rate, corrosion depth, etc. as criteria, to deduce the corresponding impurity control threshold line.

[0039] (3) Combine theoretical calculations with experimental verification results to accurately draw a complete ternary impurity control threshold map, clearly define the precise boundaries of the oxidation-dominant zone, carbonization-dominant zone, evaporation-dominant zone and inert stability zone, identify the dominant zones of different corrosion reactions, and clearly delineate the allowable range and failure risk areas of the project.

[0040] S4, Model Iteration Optimization and Validation Closed Loop To ensure that the constructed threshold model has sufficient engineering applicability and prediction accuracy, a closed-loop verification and iteration mechanism needs to be established, as follows: S41, Verification Data Enlargement (1) Select points or boundary areas near the boundary of the ternary map as the extended experimental group to obtain new data to enhance the model's boundary recognition ability.

[0041] (2) Use the newly added experimental data to make “blind predictions” and compare the model prediction results with the actual corrosion reaction results and deviations.

[0042] S42, Model Error Analysis and Adjustment (1) Calculate the prediction error (such as the accuracy of reaction mechanism identification, the root mean square error of corrosion rate residuals, etc.) (2) Re-evaluate the representativeness of the thermodynamic calculation model parameters and experimental boundary points in the high deviation region, and update the model weights or subdivide the region for training.

[0043] S43, iterative iterations and stable convergence (1) Compare the updated map with the original model. If the prediction accuracy improves and the boundary becomes stable, the model is considered to have converged.

[0044] (2) If the error is still greater than 10%, continue to introduce new experimental points or adjust the modeling strategy until the model error is controlled within ±10%.

[0045] S44, Engineering Application Compatibility Verification (1) The final model is embedded into the high-temperature power system, and the corrosion risk is quickly determined by inputting the actual service atmosphere parameters.

[0046] (2) Conduct long-term operation tests in actual application scenarios, continuously track the service performance of the samples, and further feed back to iteratively correct the model until the accuracy requirements of actual engineering applications are met.

[0047] 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 constructing a ternary gas impurity control threshold model under high-temperature inert conditions, characterized in that, Includes the following steps: S1. Analyze the types of impurity corrosion reactions that may occur in Mo-based, Nb-based, or W-based refractory alloys in a high-temperature inert atmosphere. The types of impurity corrosion reactions include oxidation, carbonization, and evaporation. Establish a two-dimensional critical partial pressure spectrum of a single impurity versus temperature. Under the same total pressure, vary the partial pressures of the three impurities to determine the dominant corrosion reaction types for different combinations of the ternary ratios of O2, H2O, and CO2. Obtain a theoretical dominant reaction region map, which includes an oxidation-dominant region, a carbonization-dominant region, an evaporation-dominant region, and an inert stability region. S2, select the proportions of O2, H2O, and CO2 impurity gases in each dominant reaction region, and subject the Mo-based, Nb-based, or W-based refractory alloy material to high-temperature corrosion; characterize the surface of the refractory alloy material after corrosion, and the characterization data include corrosion layer thickness, phase composition, surface morphology, and element diffusion depth; analyze the actual dominant corrosion reaction type based on the characterization data, and the criteria for determining the actual dominant corrosion reaction type include: a) If the corrosion layer thickness is >3 μm and it is mainly composed of oxides, then it is determined that the oxidation reaction is dominant; b) If there is a distinct carbide phase of the alloy and it is enriched with C, then it is determined that the carbide reaction is dominant. c) If the corrosion morphology is pitting or surface loss, and gaseous signals of alloy oxides or alloy species are detected, it is determined that the evaporation reaction is dominant. d) If the material has minimal mass loss and the corrosion layer is discontinuous or amorphous, it is considered to be inert and stable. S3. The theoretical dominant reaction region map and the actual dominant corrosion reaction type are normalized to construct a response model of the ratio of O2, H2O and CO2 ternary impurities and the corrosion reaction type. Using the corrosion reaction type as the criterion and combined with the working condition failure critical condition that the corrosion rate, corrosion layer thickness or corrosion depth reach the preset limit, the control threshold model of O2, H2O and CO2 ternary gas impurities is deduced.

2. The method for constructing a ternary gas impurity control threshold model under high-temperature inert environment according to claim 1, characterized in that, In step S1, the specific method for establishing the two-dimensional critical partial pressure spectrum of a single impurity versus temperature is as follows: ΔH for each reaction was obtained using a thermodynamic database. 0 ΔS 0 ΔG 0 data; Temperature dependence analysis of ΔG for each reaction was performed using the Gibbs minimum free energy principle; The expression for the critical reaction partial pressure is derived using the thermodynamic equilibrium equation, the critical partial pressure of impurities for each reaction is determined, and the critical partial pressure curves of a single impurity at different temperatures are established.

3. The method for constructing a ternary gas impurity control threshold model under high-temperature inert environment according to claim 1, characterized in that, In step S1, the method for establishing the theoretically dominant reaction region diagram is as follows: Under constant total pressure, the partial pressures of O2, H2O, and CO2 are varied. For each combination of O2, H2O, and CO2 ternary ratios, the ΔG expression for each reaction is substituted into the expression to calculate the reaction thermodynamic conditions for each impurity ratio. Determine the dominant corrosion reaction type for all ternary ratios of O2, H2O, and CO2, and map them to the corresponding ternary coordinate points; Based on the dominant corrosion reaction type, a theoretical dominant reaction region diagram is drawn, including the oxidation-dominant region, carbonization-dominant region, evaporation-dominant region, and inert stability region.

4. The method for constructing a ternary gas impurity control threshold model under high-temperature inert environment according to claim 1, characterized in that, The response model is constructed using multivariate regression, response surface methodology, or artificial neural networks.

5. The method for constructing a ternary gas impurity control threshold model under high-temperature inert environment according to claim 4, characterized in that, The specific method for constructing the response model is as follows: The partial pressure ratios of impurities O2, H2O, and CO2, and temperature were used as input variables; The corrosion reaction type, corrosion rate, or corrosion layer thickness of the alloy material are used as response output variables. A mapping relationship was established between the ratio of ternary impurities O2, H2O and CO2, temperature and the corrosion reaction type of refractory alloys.

6. The method for constructing a ternary gas impurity control threshold model under high-temperature inert environment according to claim 5, characterized in that, The specific method for constructing the ternary impurity control threshold model is as follows: Based on the output of the response model, a global simulation of the ternary impurity space of O2, H2O and CO2 is performed, and the dominant reaction region is plotted. Define clear failure critical conditions, using corrosion rate, corrosion layer thickness or corrosion depth as criteria, and solve the corresponding O2, H2O and CO2 impurity control threshold lines in reverse; By combining theoretical calculations with experimental verification results, we accurately plotted the impurity control threshold spectrum within the ternary impurity system of O2, H2O, and CO2, and clarified the precise boundaries of the oxidation-dominant region, carbonization-dominant region, evaporation-dominant region, and inert stability region.

7. The method for constructing a ternary gas impurity control threshold model under high-temperature inert environment according to claim 6, characterized in that, It also includes step S4, iterative optimization of the impurity control threshold model: Points or boundary areas near the boundaries of the O2, H2O and CO2 ternary spectra were selected as extended experimental groups to verify the accuracy of the constructed impurity threshold model prediction and ensure that the model prediction error is controlled within ±10%. If the model prediction error exceeds the specified range, supplementary experimental data collection and theoretical calculation optimization are carried out, and the model parameters are iterated repeatedly until the model error is within an acceptable range.