A method for calculating high-temperature liquid sodium-metal oxide corrosion interface thermal resistance

Abstract

The application discloses a high-temperature liquid sodium-metal oxidation corrosion interface thermal resistance calculation method, relates to the technical field of material performance calculation methods, and has the following steps: H1, material characterization is carried out on a high-temperature liquid sodium-oxidation corrosion sample, and oxidation layer thickness, porosity and pore layer thickness corrosion characteristics are quantified; H2, a nonlinear regression method is used for fitting, and an oxidation corrosion rate model of the metal sample oxidation layer thickness, porosity and pore layer thickness is derived and established; H3, oxidation layer thermal resistance and pore layer thermal resistance are calculated; and H4, interface thermal resistance net increment caused by oxidation corrosion is calculated. The application has the beneficial effects that the limitations of pure theoretical derivation or empirical estimation are overcome; the oxidation layer thickness, porosity and pore layer thickness mathematical model has practical basis; the thermal resistance contribution of the oxidation layer and the pore layer is distinguished; the method can be used for heat transfer performance evaluation and life prediction of a sodium heat pipe, and solves the problem that the prior art can only qualitatively describe corrosion influence and cannot provide engineering calculation basis.

Description

Technical Field

[0001] This invention relates to the field of material property calculation methods, specifically a method for calculating the thermal resistance of the interface between high-temperature liquid sodium and metal oxidation corrosion. Background Technology

[0002] In the field of solar thermal power generation, sodium heat pipes are used as the core temperature equalization component of the absorber, eliminating local overheating by significantly reducing the temperature difference on the absorber surface, thereby improving the system operating temperature and photoelectric conversion efficiency. Furthermore, sodium heat pipes can also be used for thermal management of coupled high-temperature molten salt thermal storage systems or battery energy storage cabinets, enabling long-distance, efficient transfer of industrial waste heat and highly safe passive heat dissipation for energy storage devices. However, under high-temperature operating conditions, liquid sodium and the metal shell material of sodium heat pipes undergo oxidation corrosion. Corrosion leads to the formation of oxides on the metal surface and the formation of pores and cracks extending along grain boundaries within the matrix. These corrosion products significantly increase the solid-liquid interface thermal resistance, reduce the heat transfer efficiency of the heat pipe, and threaten structural safety. Current technology lacks an engineering method that can quantitatively calculate the interface thermal resistance based on measurable corrosion parameters (temperature, oxygen content, time), making it difficult to meet the practical needs of sodium heat pipe heat transfer performance evaluation and lifespan prediction. Therefore, it is urgent to establish an engineering method based on measurable corrosion parameters that can quantitatively calculate the thermal resistance of the high-temperature liquid sodium-metal oxide corrosion interface, so as to provide a scientific basis for the heat transfer performance evaluation, life prediction and structural optimization design of sodium heat pipes.

[0003] To address the aforementioned issues, this invention provides a method for calculating the interfacial thermal resistance of high-temperature liquid sodium-metal oxide corrosion interface. It establishes a quantitative evolution model of corrosion characteristics, distinguishes the thermal resistance contributions of the oxide layer and the pore layer, and achieves engineering-based quantitative calculation of interfacial thermal resistance, providing a reliable basis for the analysis of the heat transfer performance and life prediction of sodium heat pipes. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a material performance calculation method to address the shortcomings of the prior art, thereby solving the problems that the thermal resistance performance analysis in the prior art lacks engineering practicality, the required mathematical model has poor accuracy, and the thermal resistance contribution of the oxide layer and the pore layer is not distinguished.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for calculating the thermal resistance of a high-temperature liquid sodium-metal oxidation corrosion interface, comprising the following steps: H1. Material characterization of high-temperature liquid sodium-oxidation corrosion samples was performed to quantify corrosion characteristics such as oxide layer thickness, porosity, and pore layer thickness. Material characterization included: (1) The morphological changes of the metal surface after oxidation and corrosion were observed by imaging the metal surface with SEM; (2) The elemental composition of the corroded metal sample was analyzed by X-ray EDS; (3) Characterize the elemental composition, layer thickness, and layer structure of the metal samples by GD-OES; H2. Based on the experimental data in step H1, a nonlinear regression method was used to fit and derive an oxidation corrosion rate model for the oxide layer thickness, porosity, and pore layer thickness of the metal sample. H3. Calculate the thermal resistance of the oxide layer and the thermal resistance of the porous layer; H4. Calculate the net increase in interfacial thermal resistance due to oxidation and corrosion.

[0006] Furthermore, in step H2, the thickness of the oxide layer of the metal sample... Porosity and pore layer thickness The mathematical model for the oxidation corrosion rate is:

[0007] in, δ 1 represents the oxide layer thickness in μm, and c[O] represents the oxygen content in the liquid sodium in ppm. T Temperature is expressed in Kelvin (K). t c This indicates the duration of oxidation and corrosion, expressed in hours (h). Indicates porosity. δ 2 represents the thickness of the porous layer, in μm.

[0008] Further, in step H2, porosity is calculated using statistical methods. The mathematical model is obtained based on the following formula:

[0009] in, Porosity at each time point,  α This represents the average ratio of each pore to the deepest pore in the image; A o This represents the pore area, in meters (m²). 2 ; A The area of ​​a metal cross-section is expressed in m². 2 .

[0010] Furthermore, in step H3, the thermal resistance of the oxide layer... R 1 and thermal resistance of the pore layer R 2. The calculation formula is:

[0011] in, R 1 represents the thermal resistance of the oxide layer, in meters (m). 2 K / W; δ 1 indicates the oxide layer thickness, in μm; λ oxide This represents the thermal conductivity of the oxide, expressed in W / (m·K). R 2 represents the thermal resistance of the porous layer, in meters (m). 2 ·K / W, δ 2 indicates the thickness of the porous layer, in μm. A o This represents the pore area, in meters (m²). 2 , A The area of ​​a metal cross-section is expressed in m². 2 , λ The value represents the thermal conductivity of the metal sample, expressed in W / (m·K).

[0012] Further, in step H4, the net increase in interfacial thermal resistance caused by oxidation corrosion is expressed as the sum of the thermal resistance of the oxide layer and the thermal resistance of the pore layer, minus the thermal resistance of the uncorroded metal substrate corresponding to the thickness of the pore layer. The calculation formula is as follows:

[0013] in, R co This represents the net increase in interfacial thermal resistance due to oxidation and corrosion, expressed in meters (m). 2 K / W; R 1 represents the thermal resistance of the oxide layer, in meters (m). 2 K / W; R 2 represents the thermal resistance of the porous layer, in meters (m). 2 K / W; δ 2 indicates the thickness of the porous layer, in μm; λ This represents the thermal conductivity of a metallic sample, expressed in W / (m·K).

[0014] Furthermore, in step H1, before performing SEM imaging on the oxidized and corroded metal sample, the longitudinal cross-section of the metal sample is imaged, and the cross-section is processed using the inlay polishing method.

[0015] Further, in step H1, after obtaining the metal surface image through SEM, the morphological features are converted into statistically significant particle area and quantity data by utilizing the grayscale difference between oxide particles and the metal matrix in the SEM image. Then, the particles in the image are filtered by grayscale range, which is set to 140~195.

[0016] Further, in step H1, during the SEM imaging process, the area and length of the oxide layer in the image are calculated to obtain the average thickness of the oxide layer. The number of pixels occupied by the oxide layer and pores is counted and converted proportionally using a given scale to obtain the area of ​​the oxide layer and the area occupied by the pores, which are then converted into the oxide layer thickness, porosity, and thickness affected by pores.

[0017] Further, in step H1, phase analysis of the metal sample surface is performed using X-ray diffraction technology. The experimental data is smoothed, background subtracted, and peak position corrected to ensure the accuracy and resolvability of the diffraction pattern. By identifying and comparing the diffraction peaks, the phases present on the metal surface are identified based on the standard PDF card database of the International Data Center for Diffraction. The position and concentration changes of different elements in the metal sample are analyzed using EDS mapping. The cross-section of the metal sample after oxidation and corrosion is detected using elemental spectra to analyze the elemental composition and distribution of the oxide layer and pores, and elemental detection is performed on the cracks and pores diffused along the grain boundaries of the metal sample matrix.

[0018] Furthermore, the metal sample is 316 stainless steel, and is applicable to the calculation of the thermal resistance of the oxidation corrosion interface under the following conditions: temperature range of 500℃ to 850℃, liquid sodium oxygen content range of 10ppm to 100ppm, and corrosion time range of 20 hours to 1200 hours.

[0019] Compared with the prior art, the beneficial effects of the present invention are: 1. Based on systematic experimental data: This invention is based on systematic oxidation corrosion experimental data of 316 stainless steel material in the range of 500-850 ℃, 10-100ppm oxygen content, and 20-1200 hours. The mathematical model parameters are derived from the real high-temperature liquid sodium environment, which overcomes the limitations of pure theoretical derivation or empirical estimation without experimental verification.

[0020] 2. An evolution model for quantitative corrosion characteristics was established: Based on SEM cross-sectional image analysis and pixel statistics, this invention established a quantitative evolution mathematical model for three key corrosion characteristics: oxide layer thickness, porosity, and pore layer thickness. This mathematical model is based on experimental data and is the first of its kind in this application.

[0021] 3. The thermal resistance contributions of the oxide layer and the porous layer are distinguished: This invention decomposes the oxidation corrosion interface into an oxide layer and a porous layer, and calculates the thermal resistance of each separately. The thermal resistance of the oxide layer takes into account the characteristics of oxide materials with low thermal conductivity; the thermal resistance of the porous layer takes into account the weakening effect of porosity on thermal conductivity.

[0022] 4. Quantitative calculation of interfacial thermal resistance is achieved: Based on measurable corrosion parameters, this invention quantitatively provides the net increase in interfacial thermal resistance caused by oxidative corrosion. This calculation method can be directly used for the heat transfer performance evaluation and life prediction of sodium heat pipes, solving the problem that existing technologies can only qualitatively describe the effects of corrosion and cannot provide engineering calculation basis. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the overall structure of the experimental system of the present invention; Figure 2This is a schematic diagram of the experimental body structure of the experimental system of the present invention; Figure 3 This is a schematic diagram of the pressure-holding container structure of the experimental system of the present invention; Figure 4 This is a schematic diagram of the sample container structure of the experimental system of the present invention; Figure 5 This is a schematic diagram of the gas path system connection of the experimental system of the present invention; Figure 6 This is a schematic diagram of the wire mesh liquid absorption core of the experimental system of the present invention; Figure 7 This is a design and manufacturing diagram of the sample container for the present invention. Figure 8 This is a design and manufacturing drawing of the pressure-holding container of the present invention. Figure 9 This is the main flowchart of the experimental method steps of the present invention; Figure 10 This is the main flowchart of the interface thermal resistance calculation method of the present invention; Figure 11 Flowchart of the logical relationship for the invention of the interface thermal resistance calculation method; Figure 12 Cross-sectional view of a polished metal sample after being embedded with the interface thermal resistance calculation method of this invention; Figure 13 This is a scanning electron microscope image of the interface thermal resistance calculation method of the present invention; Figure 14 Particle identification diagram for the invention of interfacial thermal resistance calculation method; Figure 15 This is a verification diagram of the oxide layer thickness of 316 stainless steel in Experiment 3 of this invention; Figure 16 This is a diagram verifying the porosity of 316 stainless steel in the experiment of this invention. Figure 17 This is a verification diagram of the porosity layer depth of 316 stainless steel in this invention. Figure 18 This is a comparison chart of the predicted and experimental values ​​of the thermal resistance of oxidative corrosion of 316 stainless steel in this invention.

[0024] In the diagram: 1. Experimental body; 11. Pressure holding container; 111. Sealing cap; 1111. Gas connection tube; 1112. Thermocouple connection tube; 112. Open container; 113. Metal spiral wound gasket; 12. Sample container; 121. Hollow bolt; 122. Nut; 123. Annular gasket; 124. Wire mesh wick; 13. Positioning disc; 2. Gas system; 21. Vacuum system; 211. Vacuum gauge; 212. Vacuum pump; 213. First control valve; 22. Argon system; 221. Argon cylinder; 222. Pressure gauge; 223. Second control valve; 224. Third control valve; 3. Heating coil; 4. Thermocouple; 5. Controller; 6. DC power supply. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1: A high-temperature liquid sodium-metal oxidation corrosion experimental system, see attached figure. Figure 1-6 The experimental system includes an experimental body 1, a gas path system 2, a heating coil 3, multiple thermocouples 4, a controller 5, and a DC power supply 6. The experimental body 1 includes a pressure-holding container 11, two or more independent sample containers 12, and a positioning disk 13. Each sample container 12 consists of a hollow bolt 121 with an upper opening, a nut 122 matching the hollow bolt 121, an annular washer 123, and a wire mesh suction core 124 placed inside the hollow bolt 121. The materials used for each sample container 12 can be different. The drive thread of the hollow bolt 121 is an NTP 1 / 2 type thread structure. The metal sample is placed on the wire mesh suction core 124 and arranged close to the inner wall of the hollow bolt 121. During the experiment, sodium is also placed inside the hollow bolt 121. The wire mesh suction core 124, the metal sample, and the sample container 12 are all made of the same material; specifically, the different metal samples are 304 stainless steel, 316 stainless steel, or molybdenum. The inner wall of the pressure-holding container 11 has multiple protrusions. The positioning disk 13 has multiple positioning holes evenly distributed on the protrusions, and the suspended hollow bolt 121 is placed in the positioning holes. The gas system 2 is connected to the pressure holding container 11. The heating coil 3 is wound around the outer surface of the pressure holding container 11. The thermocouple 4 is inserted into the pressure holding container 11. The controller 5 is connected to the thermocouple 4 and the DC power supply 6 respectively. The DC power supply 6 is also connected to the heating coil 3.

[0027] The wire mesh wick 124 is a key component inside the hollow bolt (simulating a sodium heat pipe) that drives liquid reflux. It maintains the internal circulation of the hollow bolt 121 through capillary action. The rate and extent of the oxidation and corrosion reaction in the hollow bolt 121 are largely controlled by the ratio of the metal sample surface area to the liquid sodium volume. The surface area of ​​the metal sample inside the hollow bolt 121 includes the total surface area of ​​the inner wall of the hollow bolt 121 and the total surface area of ​​the wire mesh wick 124. The wire mesh wick 124 in the hollow bolt 121 has a large surface area, significantly increasing the contact area between the metal sample and the liquid sodium. During operation, the wire mesh wick 124 is wetted by the liquid sodium, further increasing the contact area between the metal sample and the liquid sodium. Therefore, to more accurately reflect the actual operating state of a sodium heat pipe, a wire mesh wick 124 is placed inside the sample container. (Refer to Appendix) Figure 6 The wire mesh wick 124 is composed of four layers of metal mesh, and two types of wire mesh wicks 124, namely 100 mesh and 400 mesh, are placed in different sample containers 12.

[0028] In specific implementation, the pressure holding container 11 is made of 304 stainless steel. The sealing cover 111 of the pressure holding container 11 and the open container 112 are connected by a flange structure. The flange structure position is sealed with a metal spiral wound gasket 113. The flange bolt material is high temperature resistant metal A286 660A.

[0029] Furthermore, a gas connection pipe 1111 and a thermocouple connection pipe 1112 are connected through the sealing cover 111. The thermocouple connection pipes 1112 are evenly distributed to monitor the temperature at different points, especially at the upper, middle and lower positions of the pressure holding container 11. The number of thermocouple connection pipes 1112 matches the number of thermocouples 4. The thermocouples 4 are N-type thermocouples, and their installation position is inside the thermocouple connection pipes 1112, 200 mm away from the sealing cover. The junction of the thermocouples 4 and the thermocouple connection pipes 1112 is sealed with a metal ferrule and sealant.

[0030] Furthermore, the heating coil 3 is wound around the outer surface of the open container 112. The heating coil 3 is a nickel alloy resistance type. A ceramic shell is installed around the heating coil 3. A heat insulation layer is arranged around the ceramic shell. The ceramic shell enhances the thermal shock resistance of the heating coil, and the heat insulation layer reduces heat loss and maintains temperature stability.

[0031] Furthermore, the DC power supply 6 has a rated output voltage of 0~600 V and an output current of 0~6 A. The maximum output power is 3.6 kW. The DC power supply 6 is connected to the controller 5 via the Modbus communication protocol and its power status is controlled via an SSCOM serial port data debugger. The DC power supply 6 is supplied by Vetex (WSD60H06).

[0032] Further, see attached document. Figure 5The gas system 2 includes a vacuum system 21 and an argon system 22. The vacuum system 21 includes a vacuum gauge 211, a vacuum pump 212, and a first control valve 213. The vacuum pump 212 is connected to the gas connection pipe 1111 through a metal pipeline. The gas connection pipe 1111 and the metal pipeline are sealed at the junction. The first control valve 213 and the vacuum gauge 211 are installed on the metal pipeline between the vacuum pump 212 and the gas connection pipe 1111. The vacuum gauge 211 is close to the gas connection pipe 1111, and the first control valve 213 is close to the vacuum pump 212.

[0033] Further, see attached document. Figure 5 The argon system 22 includes an argon cylinder 221, a pressure gauge 222, a second control valve 223, and a third control valve 224. The second control valve 223 is installed on a metal pipeline between the first control valve 213 and the vacuum gauge 211. The metal pipeline between the second control valve 223 and the vacuum gauge 211 is connected at both ends by a T-connector, and the other end is connected to the argon cylinder 221 through a metal pipeline. The third control valve 224 and the pressure gauge 222 are installed on the metal pipeline between the T-connector and the argon cylinder 221. The pressure gauge 222 is installed close to the argon cylinder 221, and the third control valve 224 is installed close to the T-connector.

[0034] Furthermore, the experimental body 1 operates within a temperature range of 500°C to 850°C.

[0035] Example 2: A test method for preparing sodium-stainless steel oxidation corrosion samples, comprising the following steps: S1. Design and manufacture of the experimental body: The wire mesh suction core 124, the metal sample, and the sample container 12 itself in the same sample container 12 of the experimental body 1 are all made of the same material. A total of 3 sample containers 12 made of different materials were compared, namely 304 stainless steel, 316 stainless steel, and molybdenum. The physical structure of one of them is shown in the attached document. Figure 7 The pressure-holding container 11 is shown in the attached document. Figure 8 ; S2. Double sealing test of the experimental body: The sealing test was carried out on the pressure holding container 11 and the sample container 12 respectively; S3. Material Contents in Sample Containers: Different sample containers 12 contain different combinations of liquid sodium with varying oxygen content, different metal samples, and different 124-mesh wire wicks. This includes 18 different experimental combinations, meaning a single experiment will yield 18 sodium-stainless steel oxidation corrosion metal samples. The number of sample containers 12 and their arrangement in the positioning disk 13 are shown in the appendix. Figure 2 Or attached Figure 3 The specific experimental combinations are shown in Table 1.

[0036] Table 1. Test combination methods for preparing sodium-stainless steel oxidation corrosion samples (I) ; Another set of reserved experimental combinations was designed (generally, this can be omitted), and the specific combination methods are shown in Table 2.

[0037] Table 2 Test combinations for preparing sodium-stainless steel oxidation corrosion samples (II) ; In the actual experiments above, the specifications of sample container 12 were an inner diameter of 14 mm and a tube length of 50 mm. The surface area / sodium volume of the metal sample corresponding to the wire mesh wicks 124 (no mesh), 100 mesh, and 400 mesh were 0.41 m², respectively. -1 20.0 m -1 27.6 m -1 The four layers of the selected wire mesh absorbent core are placed into the sample container to form a porous capillary structure layer.

[0038] S4. Conduct high-temperature liquid sodium-stainless steel oxidation corrosion experiments; S5. Obtain sodium-stainless steel oxidation corrosion samples; S6. Comparative analysis of the performance of different corroded metal samples: The performance of oxidized and corroded metal samples under different experimental combinations was analyzed by calculating the interfacial thermal resistance.

[0039] Further, in steps S1 and S2, hollow bolts 121 and nuts 122 with different types of threads, as well as different annular washers 123, are designed and manufactured. The reliability analysis and judgment of the sealing structure of the sample container 12 are conducted using a weighing method. That is, the final weight of a poorly sealed container will differ from the standard weight. Since the experiment must maintain a leak-free liquid sodium level and ensure that the oxygen concentration is not affected by liquid sodium leakage, the sealing performance of the experimental setup is a key technical issue. Sample containers 12 with poor sealing will be eliminated, and ultimately 18 sample containers 12 that meet the material requirements and have good sealing performance will be selected. The pressure-holding container 11 is tested using conventional sealing test methods.

[0040] Furthermore, in step S2, the reliability test of the sealing structure is specifically demonstrated by: using three sealing methods for sample container 12—insertion fit with cured adhesive, M-type thread seal, and NPT thread seal—the sample container 12 containing liquid sodium is heated sequentially and weighed, and the method with the best sealing performance is selected. In practice, this experiment underwent multiple tests. The test results using the NPT thread seal showed that the mass change rate within 60 hours was within ±0.5% (measurement accuracy ±0.01%), which is considered to indicate no leakage within 60 hours.

[0041] Furthermore, in steps S1 and S4, the formula for calculating the axial length between two adjacent cylindrical steel wires of the wire mesh absorbent core 124 is as follows:

[0042] in, l AB The length of the axis between two adjacent cylindrical steel wires of the wire mesh absorbent core 124 is expressed in meters (m). M The mesh spacing is in meters (m). d The radius of the steel wire is in meters (m).

[0043] The above formulas yielded wire mesh liquid absorber 124 with an axis length (aperture) of 0.15 mm (100 mesh) and 0.038 mm (400 mesh), respectively.

[0044] Further, in step S3, the metal sample, which has been ultrasonically cleaned and dried with anhydrous ethanol, is weighed and filled into sample container 12 inside a glove box. A specific mass of metallic sodium is calculated and cut, melted at 150 °C, and then a corresponding mass of sodium peroxide powder is added. The mixture is kept for 10 minutes to ensure all the sodium peroxide powder dissolves into the liquid sodium. The prepared oxygen-containing liquid sodium is then filled into the sample container, cooled, and sealed. The steps of adding sodium and sodium peroxide are repeated to prepare a series of liquid sodiums with different oxygen contents. The preparation of liquid sodium, the metal sample, and the filling of liquid sodium into sample container 12 are all completed inside the glove box, ensuring that the sample container is not affected by any "uncleanliness."

[0045] Furthermore, in step S3, when preparing liquid sodium with different oxygen contents, the water vapor content in the glove box is kept less than 0.5 ppm and the oxygen content is less than 1 ppm.

[0046] Furthermore, in step S3, the formula for calculating the mass of sodium peroxide added is as follows:

[0047] in, c [O] represents the concentration of liquid sodium oxygen, in ppm; m o The mass of oxygen is expressed in kg. m Na The mass of sodium is expressed in kg; m Na 2 O 2 represents the mass of sodium peroxide, in kg; M O This represents the molar mass of oxygen, expressed in kg / mol. M Na 2 O 2 The value represents the molar mass of sodium peroxide, expressed in kg / mol.

[0048] Further, in step S4, during the high-temperature liquid sodium-metal oxidation corrosion experiment, the sample container 12 containing oxygen-containing liquid sodium and the metal sample obtained in step S3 is fixed inside the pressure holding container 11. The pressure holding container 11 is externally connected to the gas system 2 pipeline, and air is vented using the vacuum pump 212 while argon gas is introduced; after the air is completely removed, the heating coil 3 is activated, and active venting is used during the heating and holding stages to maintain the relative pressure inside the pressure holding container 11 and stabilize the temperature at the target value (the temperature change rate is maintained at ±0.5 ℃ / h, which is considered temperature stability); heating is stopped after the predetermined corrosion time is reached, and pressure stability is maintained by gas replenishment during the cooling stage; finally, the metal sample is removed after the sample container 12 and the pressure holding container 11 have cooled to room temperature.

[0049] Further, in step S4, before starting the heating coil 3, the working process of the gas system 2 is as follows: First, the vacuum pump 212 is used to evacuate the pressure holding container 11. After the pressure drops to 50 Pa, the vacuum pump 212 is turned off, and the argon cylinder 221 is opened to fill the pressure holding container 11 with argon gas, so that the pressure inside the pressure holding container 11 rises to 150 kPa. This cycle is repeated three times to ensure that there is no residual air inside the pressure holding container 11. After the last argon filling, the pressure inside the pressure holding container 11 is 50 kPa.

[0050] Furthermore, in step S5, the specific method for removing impurities from the metal sample after experimental corrosion is as follows: open sample container 12 in the glove box and take out the metal sample. Use anhydrous ethanol to clean the residual sodium on the surface of the metal sample. After confirming that there are no residual impurities on the surface of the metal sample and that all the anhydrous ethanol on the surface of the metal sample has evaporated, seal the metal sample to obtain various sodium-stainless steel oxidation corrosion samples of different samples.

[0051] Example 3: Definition: The interface refers to the contact surface between the high-temperature liquid sodium and the inner wall of the metal tube shell in a sodium heat pipe. Due to oxidation and corrosion, additional thermal resistance is formed at this solid-liquid interface, thus hindering the transfer of heat between the wall and the liquid sodium. Therefore, it is necessary to calculate the interfacial thermal resistance.

[0052] A method for calculating the thermal resistance of the interface between high-temperature liquid sodium and metal oxidation corrosion, referenced Figure 10 and Figure 11 The method includes the following steps: H1. Material characterization of high-temperature liquid sodium-oxidation corrosion samples was performed to quantify corrosion characteristics such as oxide layer thickness, porosity, and pore layer thickness. Material characterization included: (1) The morphological changes of the metal surface after oxidation and corrosion were observed by imaging the metal surface with a scanning electron microscope (SEM). (2) The elemental composition of the corroded metal sample was analyzed by an energy dispersive X-ray spectrometer (EDS). (3) Characterize the elemental composition, layer thickness, and layer structure of the metal sample by glow discharge optical emission spectrometry (GD-OES); H2. Based on the experimental data in step S1, a nonlinear regression method was used to fit and derive a mathematical model of the oxidation corrosion rate of the metal sample oxide layer thickness, porosity, and pore layer thickness. H3. Calculate the thermal resistance of the oxide layer and the thermal resistance of the porous layer; H4. Calculate the net increase in interfacial thermal resistance due to oxidation and corrosion.

[0053] Furthermore, in step H2, the thickness of the oxide layer of the metal sample... Porosity and pore layer thickness The mathematical model for the oxidation corrosion rate is:

[0054] in, δ 1 indicates the oxide layer thickness, in μm. c [O] indicates the oxygen content in liquid sodium, expressed in ppm. T Temperature is expressed in Kelvin (K). t c This indicates the duration of oxidation and corrosion, expressed in hours (h). Indicates porosity. δ 2 represents the thickness of the porous layer, in μm.

[0055] Furthermore, in step H2, within the observation range, due to the varying shapes of the pores in the oxidized and corroded metal samples—some approximating spherical shapes, while others exhibiting elongated shapes at grain boundaries—and considering the complexity of pore shapes caused by intergranular corrosion, statistical methods are used to calculate the porosity. The mathematical model is obtained based on the following formula:

[0056] in, Porosity at each time point,  α This represents the average ratio of each pore to the deepest pore in the image; A o This represents the pore area, in meters (m²). 2 ; A The area of ​​a metal cross-section is expressed in m². 2This formula is used to calculate the porosity at each time point. The overall porosity is obtained by fitting the porosity calculated at each time point using this formula. The mathematical model.

[0057] Furthermore, in step H3, the thermal resistance of the oxide layer... R 1 and thermal resistance of the pore layer R 2. The calculation formula is:

[0058] Oxide layer thickness Porosity and pore layer thickness Substituting the mathematical model of the oxidation corrosion rate into the above equation, we can further simplify to obtain the following formula:

[0059] in, R 1 represents the thermal resistance of the oxide layer, in meters (m). 2 K / W; δ 1 indicates the oxide layer thickness, in μm; λ oxide This represents the thermal conductivity of the oxide, expressed in W / (m·K). R 2 represents the thermal resistance of the porous layer, in meters (m). 2 ·K / W, δ 2 indicates the thickness of the porous layer, in μm. A o This represents the pore area, in meters (m²). 2 , A The area of ​​a metal cross-section is expressed in m². 2 , λ The thermal conductivity of the metal sample is expressed in W / (m·K). The thermal conductivity of the oxide layer is referenced to that of conventional ternary metal oxides (0.1~1 W / (m·K)), and is 0.5 W / (m·K) at 700℃.

[0060] Further, in step H4, the net increase in interfacial thermal resistance caused by oxidation corrosion is expressed as the sum of the thermal resistance of the oxide layer and the thermal resistance of the pore layer, minus the thermal resistance of the uncorroded metal substrate corresponding to the thickness of the pore layer. The calculation formula is as follows:

[0061] in, R co This represents the net increase in interfacial thermal resistance due to oxidation and corrosion, expressed in meters (m). 2 K / W; R 1 represents the thermal resistance of the oxide layer, in meters (m). 2 K / W; R2 represents the thermal resistance of the porous layer, in meters (m). 2 K / W; δ 2 indicates the thickness of the porous layer, in μm; λ The value represents the thermal conductivity of the metal sample, expressed in W / (m·K).

[0062] Furthermore, in step H1, before SEM imaging of the oxidized and corroded metal sample, a longitudinal cross-sectional image of the metal sample is created, and the cross-section is processed using a mosaic polishing method. The purpose of this technical solution is to prepare a cross-sectional metal sample suitable for SEM observation. Only through high-resolution cross-sectional images acquired by SEM can the oxide layer thickness and pore layer depth be measured.

[0063] Further, in step H1, after acquiring the metal surface image via SEM, the morphological features are converted into statistically significant particle area and quantity data by utilizing the grayscale difference between oxide particles and the metal matrix in the SEM image. Then, a grayscale range is used to filter particles in the image, with the grayscale range set to 140~195. The principle of grayscale range filtering is that all pixels in the image have a certain brightness value. Pure black is defined as 0, pure white as 255, and brightness values ​​between black and white are represented by 0~255. Pixels with a certain range of grayscale values ​​are selected to identify areas within that brightness range. When the grayscale range is set to 140~195, the boundaries of particles can be distinguished relatively well. Combined with manual correction, particles can be selected more accurately, and the area of ​​each particle can be counted.

[0064] Furthermore, in step H1, during the SEM imaging process, since the thickness of the oxide layer is not uniform, it is necessary to calculate the area and length of the oxide layer in the image to obtain the average thickness of the oxide layer. The number of pixels occupied by the oxide layer and pores is counted, and the ratio is converted using a given scale to obtain the area of ​​the oxide layer and the area occupied by the pores, which are then converted into the oxide layer thickness, porosity, and thickness affected by pores.

[0065] Further, in step H1, X-ray diffraction analysis (XRD) is used to analyze the phase composition of the metal sample surface. The experimental data is smoothed, background subtracted, and peak position corrected to ensure the accuracy and resolvability of the diffraction pattern. By identifying and comparing the diffraction peaks, the phases present on the metal surface are identified based on the standard PDF card database of the International Centre for Diffraction Data (ICDD). The position and concentration changes of different elements in the metal sample are analyzed by EDS mapping. The cross-section of the metal sample after oxidation and corrosion is detected using elemental spectra to analyze the elemental composition and distribution of the oxide layer and pores, and elemental detection is performed on the cracks and pores diffused along the grain boundaries of the metal sample matrix.

[0066] Furthermore, the metal sample is 316 stainless steel, and is applicable to the calculation of the thermal resistance of the oxidation corrosion interface under the following conditions: temperature range of 500℃ to 850℃, liquid sodium oxygen content range of 10ppm to 100ppm, and corrosion time range of 20 hours to 1200 hours.

[0067] Example 4: Based on Examples 1-3, specifically using 316 stainless steel as an example, the experiment was conducted under complex oxidation corrosion conditions with a total duration of 2000 hours. Oxidation corrosion was carried out at 600℃, 700℃ and 850℃ for 20h, 400h and 1580h respectively. Among them, experimental value 1 and experimental value 2 correspond to oxidation corrosion under the conditions of 100 mesh wire and 400 mesh wire, respectively.

[0068] As attached Figure 13 As shown, the metal surface after oxidation and corrosion generates a large number of particles. In scanning electron microscopy imaging, the particles exhibit a bright appearance. Therefore, the particles in the image are screened using grayscale range.

[0069] As attached Figure 14 As shown, when the grayscale range is set to 140~195, the boundaries of particles can be distinguished well for particle identification on the surface of metal samples. Combined with manual correction, particles can be accurately selected and the area of ​​each particle can be counted.

[0070] To evaluate the accuracy of the oxidation corrosion rate model, the oxide layer thickness, porosity, and pore layer thickness of metal samples under long-term complex oxidation corrosion conditions were analyzed, and the results compared with those predicted by the oxidation corrosion rate model are shown in the attached figure. Figure 15-17As shown, the predicted values ​​of oxide layer thickness, porosity, and pore layer thickness from the model agree well with the experimental values. Compared with experimental values ​​1 and 2, the prediction errors for oxide layer thickness are 34.75% and -0.50%, respectively; for porosity, 3.37% and -7.26%, respectively; and for pore layer thickness, -6.43% and -9.45%, respectively. This indicates that the oxidation corrosion rate model based on this experiment can predict the actual oxidation corrosion situation.

[0071] The calculated values ​​of the net increase in interfacial thermal resistance caused by oxidation corrosion in Example 3 were compared with the experimental values. The comparison results are shown in the appendix. Figure 18 It can be seen that the mathematical model can predict the thermal resistance caused by oxidation and corrosion relatively accurately, but there are still some cases where the error is large, especially when the oxidation and corrosion time is short and the oxygen content is low. Due to the small oxide layer thickness, the prediction error of the oxide layer thickness is too large, which will eventually lead to a large prediction error of the thermal resistance. Therefore, in the experiment, the experimental time and oxygen content are two key experimental settings.

[0072] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for calculating the thermal resistance of a high-temperature liquid sodium-metal oxidation corrosion interface, characterized in that, The method includes the following steps: H1. Material characterization of high-temperature liquid sodium-oxidation corrosion samples was performed to quantify corrosion characteristics such as oxide layer thickness, porosity, and pore layer thickness. Material characterization included: (1) The morphological changes of the metal surface after oxidation and corrosion were observed by imaging the metal surface with SEM; (2) The elemental composition of the corroded metal sample was analyzed by X-ray EDS; (3) Characterize the elemental composition, layer thickness, and layer structure of the metal samples by GD-OES; H2. Based on the experimental data in step H1, a nonlinear regression method was used to fit and derive an oxidation corrosion rate model for the oxide layer thickness, porosity, and pore layer thickness of the metal sample. H3. Calculate the thermal resistance of the oxide layer and the thermal resistance of the porous layer; H4. Calculate the net increase in interfacial thermal resistance due to oxidation and corrosion.

2. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 1, characterized in that, In step H2, the thickness of the oxide layer of the metal sample Porosity and pore layer thickness The mathematical model for the oxidation corrosion rate is: ， in, δ 1 indicates the oxide layer thickness, in μm. c [O] indicates the oxygen content in liquid sodium, expressed in ppm. T Temperature is expressed in Kelvin (K). t c This indicates the duration of oxidation and corrosion, expressed in hours (h). Indicates porosity. δ 2 represents the thickness of the porous layer, in μm.

3. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 2, characterized in that, In step H2, porosity is calculated using statistical methods. The mathematical model is obtained based on the following formula: ， in, Porosity at each time point,  α This represents the average ratio of each pore to the deepest pore in the image; A o This represents the pore area, in meters (m²). 2 ; A The area of ​​a metal cross-section is expressed in m². 2 .

4. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 3, characterized in that, In step H3, the thermal resistance of the oxide layer R 1 and thermal resistance of the pore layer R 2. The calculation formula is: ， in, R 1 represents the thermal resistance of the oxide layer, in meters (m). 2 K / W; δ 1 indicates the oxide layer thickness, in μm; λ oxide This represents the thermal conductivity of the oxide, expressed in W / (m·K). R 2 represents the thermal resistance of the porous layer, in meters (m). 2 ·K / W, δ 2 indicates the thickness of the porous layer, in μm. A o This represents the pore area, in meters (m²). 2 , A The area of ​​a metal cross-section is expressed in m². 2 , λ The value represents the thermal conductivity of the metal sample, expressed in W / (m·K).

5. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 4, characterized in that, In step H4, the net increase in interfacial thermal resistance caused by oxidation corrosion is expressed as the sum of the thermal resistance of the oxide layer and the thermal resistance of the porous layer, minus the thermal resistance of the uncorroded metal substrate corresponding to the thickness of the porous layer. The calculation formula is as follows: ， in, R co This represents the net increase in interfacial thermal resistance due to oxidation and corrosion, expressed in meters (m). 2 K / W; R 1 represents the thermal resistance of the oxide layer, in meters (m). 2 K / W; R 2 represents the thermal resistance of the porous layer, in meters (m). 2 K / W; δ 2 indicates the thickness of the porous layer, in μm; λ This represents the thermal conductivity of a metallic sample, expressed in W / (m·K).

6. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 1, characterized in that, In step H1, before performing SEM imaging on the oxidized and corroded metal sample, a longitudinal cross-section of the metal sample is imaged, and the cross-section is processed using the inlay polishing method.

7. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 6, characterized in that, In step H1, after obtaining the metal surface image through SEM, the morphological features are converted into statistically significant particle area and quantity data by utilizing the grayscale difference between oxide particles and the metal matrix in the SEM image. Then, the particles in the image are filtered by grayscale range, which is set to 140~195.

8. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 7, characterized in that, In step H1, during SEM imaging, the area and length of the oxide layer in the image are calculated to obtain the average thickness of the oxide layer. The number of pixels occupied by the oxide layer and pores is counted and converted according to a given scale to obtain the area of ​​the oxide layer and the area occupied by the pores, which are then converted into the oxide layer thickness, porosity, and thickness affected by pores.

9. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 1, characterized in that, In step H1, X-ray diffraction is used to analyze the phase composition of the metal sample surface. The experimental data is smoothed, background subtracted, and peak position corrected to ensure the accuracy and resolvability of the diffraction pattern. By identifying and comparing the diffraction peaks, the phases present on the metal surface are identified based on the standard PDF card database of the International Data Center for Diffraction. The position and concentration changes of different elements in the metal sample are analyzed by EDS-Mapping. The cross-section of the metal sample after oxidation and corrosion is detected using elemental spectra to analyze the elemental composition and distribution of the oxide layer and pores, and elemental detection is performed on the cracks and pores diffused along the grain boundaries of the metal sample matrix.

10. The method for calculating the thermal resistance of the high-temperature liquid sodium-metal oxidation corrosion interface according to claim 1, characterized in that, The metal sample is 316 stainless steel and is suitable for calculating the thermal resistance of the oxidation corrosion interface under the following conditions: temperature range of 500℃ to 850℃, liquid sodium oxygen content range of 10ppm to 100ppm, and corrosion time range of 20 hours to 1200 hours.

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