Method for quickly identifying hot spots of divertor of fusion device under circulating thermal load

Abstract

The invention provides a method for quickly identifying hot spots of a divertor of a fusion device under a cyclic thermal load. The method comprises the following steps of: recording surface temperature distribution and an average value once by using an infrared thermal imager every N / 5 cycles; calculating absorption heat flux density through coolant inlet and outlet temperature difference, and screening effective heat load data; monitoring inlet flow, temperature and pressure; setting a relative percentage threshold as a standard acceptance factor AC; the average temperature of each tungsten block is firstly compared integrally, then local highest temperature comparison is carried out on abnormal blocks, and finally global analysis is carried out. The relative temperature rise acceptance factor is introduced based on the minimum average temperature, and the judgment statistical significance is improved; dynamically calculating the heat flux density to ensure the loading effectiveness; the method is suitable for divertor delivery testing and fusion reactor in-situ monitoring, rapid and automatic hot spot identification is achieved, and the testing efficiency and accuracy are improved.

Description

Technical Field

[0001] This invention relates to the field of nuclear fusion, and more specifically to a method for rapid identification of hot spots in the divertor of a fusion device under cyclic thermal load. Background Technology

[0002] The high-power steady-state operation of fusion devices is inextricably linked to the structural safety and reliability of the divertor. However, the deterioration of the divertor's heat transfer performance and material damage under high heat loads can reduce its ability to remove particles and heat flux. Therefore, it is essential for the development of divertor target plates to conduct heat transfer and material performance tests on divertors using high heat load testing platforms such as electron guns. Current hot spot identification methods are mainly based on recorded peak heat flux and highest surface temperature. These parameters may be affected by the complexity of temperature distribution and data sampling errors, leading to distorted results and making it difficult to accurately assess issues such as divertor heat transfer performance degradation and surface hot spots. Currently, there is no accurate and effective hot spot identification method, resulting in a lack of accurate judgment of test data in existing high heat load tests. The hot spot identification method described in this patent not only ensures that the heat load meets the requirements throughout the entire cycle test process but also improves the accuracy of hot spot identification in both local and global ranges. This method is not only applicable to high heat load tests but can also be used for in-situ calculation of divertor heat load during fusion device operation. Summary of the Invention

[0003] To address the problems in existing high-heat-load testing of divertors in fusion devices, such as the lack of effective data post-processing methods, reliance on single peak parameters for hot spot identification which is susceptible to interference, and difficulty in accurately assessing the effectiveness of heat load loading and the degradation of sample heat transfer performance, this invention provides a rapid identification method for hot spots in divertors of fusion devices under cyclic heat load, enabling the determination of the divertor's operating status under cyclic heat load.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A rapid identification method for hot spots in a divertor of a fusion device under cyclic heat load includes the following steps:

[0006] Step 1: Record the surface temperature distribution image and average surface temperature value of the sample every N / 5 cycles using an infrared thermal imager. The infrared images and average temperature data are used to characterize the changes in the surface temperature distribution and average temperature of the sample with the number of cycles; N is the total number of cycles.

[0007] Step 2: Calculate the heat flux density absorbed by the sample using the temperature difference between the inlet and outlet of the coolant, and characterize the change of the heat flux density absorbed by the sample surface with the number of cycles using the calculated value;

[0008] Step 3: By reading sensor data, observe the changes in inlet flow rate, temperature, and pressure over time to determine whether the inlet coolant conditions meet the requirements;

[0009] Step 4: Set the standard acceptance factor AC to provide a reference standard for subsequent hot spot determination;

[0010] Step 5: Identify hot spots on the surface of the tested sample. Compare the average temperature of each tungsten surface with the sample with the lowest average temperature to determine whether hot spots exist.

[0011] If hot spots appear on the selected tungsten surface, local hot spot identification is performed on a single tungsten surface; the difference between the highest temperature of the tungsten surface and the average temperature of the test surface is compared to determine whether local hot spots exist.

[0012] If no hot spots appear on the selected tungsten surface, global hot spot identification is performed on the entire test surface; the difference between the highest temperature of the tungsten surface and the average temperature of the test surface is compared to determine whether there are local hot spots.

[0013] Furthermore, in step 1, the frame rate of the infrared thermal imager is not less than 30Hz, and the temperature measurement accuracy is better than ±1℃.

[0014] Furthermore, in step 2, the inlet and outlet temperature difference is obtained by measuring temperature sensors installed at the inlet and outlet of the sample cooling channel.

[0015] Furthermore, the coolant used is deionized water.

[0016] Furthermore, N represents the total number of heat load cycles.

[0017] Furthermore, in step 2, the criterion for determining whether the fluctuation of the absorbed heat flux density is within the target heat flux density range is as follows: in each heat load cycle of t1 seconds on and t2 seconds off, the time period with the highest heat flux density value is selected. If the average heat load during this time period is not less than 90% of the nominal heat load, then the heat load loading is determined to meet the requirements.

[0018] Furthermore, in step 4, the standard acceptance factor is set as a relative percentage threshold.

[0019] Furthermore, the specific steps for hot spot evaluation are as follows: compare the average surface temperature of each tungsten surface in the nth cycle with the corresponding value of the lowest average temperature among all samples, and calculate the percentage value of the difference between the two relative to the lowest average temperature.

[0020] Furthermore, in step 5, the highest temperature and the lowest average temperature of the tungsten surface are selected for overall hot spot identification. When the percentage value exceeds the standard acceptance factor, it is determined that a hot spot appears in the sample in the nth cycle, and local hot spot identification needs to be carried out. Otherwise, overall hot spot identification needs to be carried out.

[0021] Furthermore, the description of local hot spot identification compares the highest temperature and average temperature of the hot spot tungsten surface. When the percentage value exceeds the standard acceptance factor, it is determined that the sample not only has an overall hot spot but also local hot spots on the surface in the nth cycle. Conversely, the tungsten surface only has an overall hot spot and no local hot spots.

[0022] Furthermore, the global hot spot identification describes comparing the highest temperature of the hot spot tungsten surface with the average temperature of the entire test surface. When the percentage value exceeds the standard acceptance factor, it is determined that the sample has a local hot spot on the tungsten surface in the nth cycle; otherwise, the tungsten surface only has an overall hot spot and no local hot spot.

[0023] Beneficial effects:

[0024] 1. This invention introduces a relative temperature rise acceptance factor based on the "sample with the lowest average temperature", which avoids misjudgment caused by absolute temperature measurement error or randomness of local hot spots, making hot spot judgment more statistically significant and practical in engineering.

[0025] 2. This invention utilizes the temperature difference between the inlet and outlet of the coolant to dynamically calculate the absorbed heat flux density, and combines the screening and averaging of effective heat flux data within the cycle to ensure that the applied heat load truly reflects the target operating conditions and eliminates interference from load fluctuations or sensor noise.

[0026] 3. This invention can be used not only for high heat load acceptance testing of divertor components before they leave the factory, but also for in-situ heat load monitoring and hot spot early warning during the operation of fusion devices. It has good versatility and engineering promotion value.

[0027] 4. Based on the automatic acquisition and analysis process of infrared imaging and sensor data, this invention reduces manual intervention and realizes "rapid identification" and "objective evaluation" of hot spots, which meets the needs of batch testing of large-scale divertor components. Attached Figure Description

[0028] Figure 1 This is a flowchart of a method for rapid identification of hot spots in a divertor of a fusion device under cyclic heat load, according to the present invention.

[0029] Figure 2 This is a schematic diagram of the hot spot area on the surface of the divertor. Detailed Implementation

[0030] 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 accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0031] like Figure 1 As shown, the rapid identification method for hot spots in a divertor of a fusion device under cyclic heat load according to the present invention includes the following steps:

[0032] Step 1: Using an infrared thermal imager, record the surface temperature distribution image and average surface temperature value of the sample every N / 5 cycles. The infrared images and average temperature data are used to characterize the changes in the surface temperature distribution and average temperature of the sample with the number of cycles. N is the total number of cycles.

[0033] Step 2: Calculate the heat flux density absorbed by the sample using the temperature difference between the inlet and outlet of the coolant. Use the calculated value to characterize the change in the heat flux density absorbed by the sample surface with the number of cycles.

[0034] Sample absorption power q abs =Q·c·ΔT / A, where Q is the coolant mass flow rate, c is the specific heat capacity, ΔT is the temperature difference between the inlet and outlet of the sample, and A is the area of ​​the sample's heat load loading surface. The heat load cycle parameters are set to t1 seconds on and t2 seconds off, and the inlet and outlet water temperatures are recorded using thermocouples with a sampling rate of t. The effective absorbed heat load in the nth heat cycle should be characterized by the t1+1 points with the highest heat flux density between two consecutive heat load loading cycles (nth and n+1th cycles). The average value of the t1+1 heat loads is taken as the average effective absorbed heat load for this cycle. It is then determined whether the loaded absorbed heat load and the average effective absorbed heat load are within the target heat load range.

[0035] Step 3: By reading sensor data, observe the changes in inlet flow rate, temperature, and pressure over time to determine if the inlet coolant conditions meet the requirements. If they do, hot spot determination can proceed; otherwise, the divertor's operating status needs to be checked, and the experiment repeated.

[0036] Step 4: Set the acceptance standard factor AC to provide a reference standard for subsequent hot spot determination.

[0037] Step 5: Evaluate the hot spots on the surface of the tested samples, and compare the difference between the average temperature of each sample and the sample with the lowest average temperature to determine whether hot spots exist and whether the hot spots are acceptable.

[0038] The sample surfaces are numbered, and the temperature acceptance factor T of the surface of the m-th sample during the nth cycle is determined.criteria (m,n)=(T m -T min ) / T min T m T is the average surface temperature of the m-th sample during the nth cycle. min The average temperature in the nth cycle is the lowest average surface temperature of the sample. If T criteria If (m, n) is greater than the acceptance standard factor AC, then a hot spot has appeared on the sample block; otherwise, no hot spot has appeared.

[0039] If hot spots appear on the selected tungsten surface, local hot spot identification is performed on a single tungsten surface; the difference between the highest temperature of the tungsten surface and the average temperature of the test surface is compared to determine whether local hot spots exist.

[0040] If no hot spots appear on the selected tungsten surface, global hot spot identification is performed on the entire test surface; the difference between the highest temperature of the tungsten surface and the average temperature of the test surface is compared to determine whether there are local hot spots.

[0041] Example:

[0042] 1. Test Background: A divertor prototype (containing 6 independent cooling channels) for a fusion reactor needs to undergo high-heat load acceptance testing. The test uses an electron beam heat source to simulate the steady-state heat flux of 10 MW / m² experienced by the divertor during fusion reactor operation. 2 The test plan involves N=1000 long-duration thermal cycles (each lasting 10 seconds), with infrared thermal images and coolant data collected during each cycle.

[0043] 2. Data Collection:

[0044] The surface temperature field of the sample was recorded in real time using an infrared thermal imager (frame rate 30Hz, accuracy ±1℃); a high-precision PT100 temperature sensor was installed at the inlet and outlet of each cooling channel with a sampling frequency of 1Hz; the coolant was deionized water with a constant flow rate of 24t / h and the inlet temperature was maintained at 30℃.

[0045] 3. Heat load level verification, taking the first 400 cycles as an example: record the temperature difference between the coolant inlet and outlet, and calculate the instantaneous absorbed heat flux density. If the average heat load during the effective heat flux duration of 10 seconds in the first 400 cycles reaches 9.2 MW / m², then... 2 (i.e., ≥90% of the design heat load), then the average heat load of this experiment is determined to be 9.2 MW / m². 2 .

[0046] 4. Set the standard acceptance factor for hot spots to AC=20%.

[0047] 5. Overall hot spot identification.

[0048] For each valid cycle, the temperature distribution of each tungsten surface is extracted and the average value is calculated. If, in the 300th cycle, the 6th tungsten surface among all tungsten blocks has the lowest average temperature, then the hot spot acceptance factor T of the 1st tungsten surface is determined. criteria1 (6, 300)=[T ave (1, 300)-T ave (6, 300)] / T ave (6, 300). If T criteria If (6, 300) > 20%, then hot spots have appeared on the first tungsten surface, and local hot spot identification is required on the first tungsten surface; otherwise, global hot spot identification is required on the first tungsten surface.

[0049] Localized hot spot identification:

[0050] If the highest temperature of the first tungsten surface is T in the 300th cycle... max (1, 300), then T criteria2 (1, 300)=[T max (1, 300)-T ave [(1, 300)] / T ave (1, 300). If T criteria2 If (1, 300)>20%, then the first tungsten surface not only has overall hot spots but also local hot spots on the surface; otherwise, the first tungsten surface only has overall hot spots and no local hot spots.

[0051] Global hotspot identification:

[0052] If the average temperature of the entire test surface is T in the 300th cycle... ave (300), the highest temperature of the first tungsten surface is T. max (1, 300), then T criteria3 (1, 300)=[T max (1, 300)-T ave ] / T ave (300). If T criteria3 If (1, 300)>20%, then a local hot spot appears on the first tungsten surface; otherwise, no hot spot appears on the first tungsten surface.

[0053] In summary, although the sample passed the initial thermal load test, its thermal response deteriorated after long-term cycling. Based on this method, the risk of hot spots can be predicted in advance, thus avoiding thermal failure during operation in the fusion device.

[0054] like Figure 2 The diagram shows a hot spot area on the surface of the divertor.

[0055] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements 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 fast identification of hot spot in divertor of fusion device under cyclic heat load, characterized in that, The method comprises the following steps: Step 1: record the surface temperature distribution image and the surface average temperature value of the sample every N / 5 cycles by using an infrared thermal imager, and the surface temperature distribution and the average temperature change with the cycle number are characterized by the infrared image and the average temperature data, wherein N is the total cycle number; Step 2: calculate the heat flux density absorbed by the sample by using the temperature difference between the inlet and outlet of the coolant, and the heat flux density change with the cycle number is characterized by the calculated value; Step 3: read the sensor data to check the change of the inlet flow, temperature and pressure with time, so as to determine whether the inlet coolant condition meets the requirements; Step 4: set a standard acceptance factor AC, which provides a reference standard for the subsequent hot spot judgment; Step 5: perform overall hot spot identification on the measured sample surface, compare the average temperature of each tungsten surface with the lowest average temperature of all samples, and determine whether there is a hot spot; If a hot spot appears on the selected tungsten surface, perform local hot spot identification on the single tungsten surface; Compare the highest temperature of the tungsten surface with the average temperature of the test surface to determine whether there is a local hot spot; If no hot spot appears on the selected tungsten surface, perform global hot spot identification on the overall test surface; Compare the highest temperature of the tungsten surface with the average temperature of the test surface to determine whether there is a local hot spot.

2. The method according to claim 1, wherein, In step 1, the frame rate of the infrared thermal imager is not less than 30 Hz, and the temperature measurement accuracy is better than ±1℃.

3. The method of claim 1, wherein the method further comprises: In step 2, the temperature difference between the inlet and outlet is measured by temperature sensors installed at the inlet and outlet positions of the sample cooling channel.

4. The method of claim 1, wherein the method further comprises: The coolant is deionized water.

5. The method of claim 1, wherein the method further comprises: N is the total number of thermal load cycles.

6. The method of claim 1, wherein the method further comprises: In step 2, the judgment standard of whether the fluctuation of the heat flux density is within the target heat flux density range is that in each t1 second on and t2 second off thermal load cycle, the highest heat flux density value is selected in the t1 time period, and if the average thermal load in this period is not less than 90% of the nominal thermal load, it is determined that the thermal load loading meets the requirements.

7. The method of claim 1, wherein the method further comprises: In step 4, the standard acceptance factor is set as a relative percentage threshold.

8. The method of claim 1, wherein the method further comprises: The specific steps of the hot spot judgment are: compare the surface average temperature of each tungsten surface in the nth cycle with the corresponding value of the lowest average temperature in all samples, and calculate the percentage value of the difference relative to the lowest average temperature; Develop overall hot spot identification by comparing the highest temperature of the tungsten surface with the lowest average temperature, when the percentage value exceeds the standard acceptance factor, it is determined that the sample has a hot spot in the nth cycle, and local hot spot identification is carried out, otherwise overall hot spot identification is carried out.

9. The method of claim 1, wherein the method further comprises: In step 5, the local hot spot identification compares the highest temperature of the hot spot tungsten surface with the average temperature, which includes: when the percentage value exceeds the standard acceptance factor, it is determined that the sample has not only an overall hot spot but also a local hot spot on the tungsten surface in the nth cycle, otherwise the tungsten surface only has an overall hot spot but no local hot spot.

10. The method of claim 1, wherein the method further comprises: In step 5, the global hot spot identification compares the maximum temperature of the hot spot tungsten surface to the average temperature of the entire test surface, including: when the percentage value exceeds the standard acceptance factor, it is determined that the sample in the nth cycle has a local hot spot on the tungsten surface, otherwise, the tungsten surface only has a global hot spot and does not have a local hot spot.

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