Uncertainty Analysis of Radioactive Material Activity in 200L Steel Barrel by On-site Object Counting System Yi Yi, Wang Dezhong, Li Houwen, Liu Cheng, Qian Nan, Wang Bin Abstract: Monte Carlo method is used to evaluate the uncertainty of measurement results caused by the random distribution of radioactive materials in the activity of 200L steel drum of Qinshan Third Nuclear Power Co., Ltd. on the field object counting system (ISOCS). Monte Carlo method is adopted. The deviation of the ISOCS measurement results for the 4 degree density packing and 10 kinds of nuclide in the steel drum was simulated and corrected for the ISOCS measurement. Key words: activity measurement; random distribution; Monte Carlo method; on-site object counting system; standard steel drum According to the “Regulations on Near-surface Disposal of Low- and Medium-level Radioactive Solid Wastes†and the relevant standards and requirements of NUS Pediatrics, in the process of disposal of radioactive waste, its classification should be judged according to its activity level. Therefore, the activity measurement of solid waste is An important part of the process. According to the requirements of environmental impact assessment, Qinshan No. 3 Nuclear Power Co., Ltd. uses the in situ object counting system (ISOCS) to measure the activity inside the standard 200L steel drum for storing compressible medium and low radioactive solid waste. ISOCS can accurately measure the activity of the sample under the premise that the distribution of radioactive material in the sample is known. When measuring the actual waste barrel, it is found that the material of the filling in the barrel is unknown, the source of the waste is many, and the distribution of medium and low radioactive materials is random, so that the distribution of radioactive materials in the barrel is unknown. Therefore, in actual measurement, the radioactive material in the barrel is generally assumed. Evenly distributed. This will result in a certain degree of uncertainty in the measurement results due to the inconsistent distribution of radioactive materials in the actual barrel. In this work, Monte Carlo method is used to study the uncertainty of measurement results caused by random distribution of radioactive materials, and a correction method is proposed to improve the accuracy of actual waste barrel activity measurement. 1 principle Before using ISOCS for measurement, the detector is first characterized. After the user inputs the geometric data of the source, the passive efficiency scale is completed by the calibration software. The calibration software uses the method of simulation calculation to obtain the detection efficiency of the environmental sample and realize the passive calibration, so that the accurate quantitative γ analysis measurement result can be obtained in the measurement. It can be seen that in the actual measurement, only when the condition of the sample to be tested is accurately timed can be obtained. Accurate measurement results. However, in actual measurement, due to the unknown situation in the waste bin, the conditions of the sample to be tested, such as the material distribution in the barrel, the material composition and the distribution of radioactive materials in the barrel, are difficult to determine accurately. The study found that when the waste barrel is measured while rotating at a constant speed, it can be approximated that the material in the barrel is evenly distributed. Therefore, the measurement deviation caused by the difference in the actual distribution of the material in the barrel and the assumed uniform distribution can be reduced by measuring the uniform rotation of the waste barrel at the time of measurement, and the measurement requirements are met. In addition, since the actual filling in the barrel is generally cotton, chemical fiber products such as gloves, masks, scorpions, plastic bags, etc., the absorption of γ ray by the material mainly depends on its linear attenuation coefficient μ, and some chemical fiber materials obtained by table lookup and calculation are obtained. The difference in μ under the same density conditions is not large. Therefore, when considering the gamma ray absorption effect of various materials in the barrel, these materials can be regarded as the same equivalent simulation material within a certain error range. In the actual measurement, the equivalent simulation material is used to replace the various filler materials in the barrel to meet the ISOCS passive efficiency calibration requirements, and more accurate measurement results are obtained. Due to the factors such as the energy of μ and γ ray, the type of absorbing material, the density Ï of the absorbing material, and the thickness h of the ray passing through the material, the gamma rays emitted by different nuclides at different positions in the barrel are absorbed when passing through different density materials. Different conditions, in the actual measurement, because the distribution of radioactive materials in the barrel is unknown and is assumed to be evenly distributed, there will be some uncertainty in the measurement results due to the actual distribution of radioactive materials and assumptions. In this work, the Monte Carlo method is used to simulate the calculation of the radioactive materials in the barrel when they are randomly distributed and uniformly released, and the gamma rays are absorbed by the fillings in different density barrels, and then the actual measurement is evaluated by analyzing the results. Uncertainty of measurement results under the model. 2 simulation material selection Since the linear attenuation coefficient of polyethylene and various cotton and chemical fiber materials in the actual filling is the closest, it is first assumed to be an equivalent simulation material to replace the filler in the actual waste barrel, and is verified by calculation and actual. 2.1 Simulation calculation First, the MCNP program was used to simulate the calculation of the uniform distribution density in the waste bin of 0.058 g.cm3 (uncompressed) and the count rate measured by the detector when the radioactive source was in different positions in the barrel. The gamma ray energy of the main representative nuclide in the low-level solid waste in the nuclear power plant is basically between 80 and 1700 keV, and the characteristic energy peak of the gamma ray of Eu is more distributed in the range of 121 to 1470 keV. This nuclides serve as radionuclide nuclei in models and experiments. The size of the detector in the model is the size of the ISOCS GC1518 probe, as shown in Figure 1. The size of the waste bin is the same as the standard 200L steel drum of the nuclear power plant. The geometric position distribution of each device is shown in Figure 2. The central axis of the detector is aligned with the central axis of the barrel; the angle of the detector collimator covers the entire barrel; the source is placed on the center plane of the barrel, that is, at six points in Figure 2, with an interval of 46.6 mm. Figure 1 High-purity germanium detector in MCNP simulation calculation model Figure 2 Geometric relative positional relationship of each device in the simulation calculation 2.2 Experimental verification Under the same experimental conditions as the MCNP model, such as device geometry, device geometry position and source position distribution, using ISOCS GC1518 probe, the γ-ray density of the γ-rays with an activity of 1.85×107 Bq is 0.058. The count rate after the actual filling of the nuclear power plant in g/cm3. By analyzing the deviation between the count rate calculated by MCNP simulation and the count rate measured in the experiment (Table 1), it is judged whether the assumption of using polyethylene as a simulation material is credible within a certain error range. It can be seen from the data in Table 1 that the energy count rate deviations of each point calculated and experimentally obtained are small, both less than 9.7%, mostly within 5%. Even considering the inherent statistical error (about 5%) and the inevitable error in the MCNP simulation calculation, it can be considered that the deviation of the rate is small. Therefore, it can be considered that within a certain error range, the assumption that polyethylene is used as a dummy material instead of the actual filler is credible. Table 1 Simulation material verification data (slightly - China Steel Barrel Packaging Network) 3 Determination of the degree of uncertainty in the measurement results After the selection of the simulated materials, MCNP was used to study whether the fillings in the waste bins were of different density materials, and the measurement results were unanimous because of the random distribution of radionuclides. 3.1 Uniform analysis of radioactive materials In the actual measurement of specific nuclide, firstly, the filling efficiency and the radioactive material are evenly distributed, and the passive efficiency scale is used to obtain the detection efficiency η, and then the measurement result rate C is calculated by η to obtain the activity measurement result I. , the relationship is: C=IηY......(1) Where: Y is the branch ratio of the corresponding nuclide. The C collected by the detector is constant, and Y is a constant. Therefore, under different model conditions, the calculated different measurement results I are due to the different detection efficiencies of each model. Therefore, the detection efficiency under different models is first calculated. The geometry of the device in the model of the simulation calculation, the geometric positional relationship of the device, and the position distribution of the source are the same as those in the simulation material selection calculation. According to the actual measurement situation of the nuclear power plant, eight representative nuclei with characteristic energy peaks between 86,788 and 1,691 keV were selected. In addition, considering that the density of the filler in the actual low-level waste bin is generally 0.1 to 0.8 g/cm3, the case where the material density in the barrel is 0.1, 0.3, 0.5, and 0.8 g/cm3, respectively. The results of the simulation calculation are listed in Table 2. Table 2 Detection efficiency of different densities and different nuclei when radioactive materials are evenly distributed (slightly - China Steel Barrel Packaging Network) 3.2 Distribution of point source of radioactive materials In practice, the radioactive material in the barrel is evenly distributed, and the extreme case of non-uniform distribution is the point source distribution, that is, all the radioactive materials are concentrated in a point in the barrel. By the formula: C=-IηY......(2) It can be seen that when C and Y are determined, the measurement results I (k = 1, 2, 3, ... 8) corresponding to different positions change as the measurement efficiency η changes. Therefore, in order to calculate the deviation of the measurement results caused by the uniform distribution hypothesis under extreme conditions, it is necessary to first use MCNP to calculate the measurement efficiency of the point source at different positions in the barrel. Since the barrel rotates at a constant speed and the center axis of the probe is aligned with the center axis of the barrel, the time efficiency is the same when the source is at the same radius or position symmetrically about the center plane of the barrel. Therefore, select 9 as shown in Figure 3. Point source location calculation. Figure 3 Schematic diagram of point source distribution 3.3 Measurement result correction factor Define the correction factor for the measurement results as: G=I1/I2......(3) Comparing equations (1) and (2), it can be seen that, in the case of the same measured count rate C, the correction coefficient of the measurement result is: G=η1/η2......(3) Among them, the corresponding correction coefficient when the density inside the barrel is 0.1g/cm33 is listed in Table 3. The corresponding average correction factors for other density conditions are listed in Table 4. Table 3 Correction factor (slightly - China Steel Barrel Packaging Network) Table 4 Average correction factor (slightly - China Steel Barrel Packaging Network) Through the analysis of the data in Table 4, it is found that the density is small. If it is 0.1g/cm3, the correction coefficient is close to 1, that is, the actual measurement result of ISOCS has little deviation from the total activity of the source, and there is no need to correct it; the density is 0.3g. At /cm3, the measurement results of each nuclide at each position are larger than those at 0.1 g/cm3, but still small, acceptable; at a density of 0.5 g/cm3, the high-energy regions such as Sb, Co, Co, and Zr correspond to nuclide. The deviation of the measurement results is small, the other nuclide deviations are large, and the measurement results need to be corrected. When the density is 0.8g/cm3, the deviation of each nuclide measurement result is large, and all need to be corrected. The revised method is to divide the ISOCS measurement result of the hypothesis by the average correction coefficient of each density obtained to obtain a relatively more accurate measurement result. 3.4 Radioactive materials are published randomly To describe the measurement of the random distribution of radioactive material in the actual barrel, the activity measurement results when several point sources are randomly selected in the barrel are calculated. The activity measurement result has the following relationship with the measurement count rate: (slightly - China Steel Barrel Packaging Network) 10 point sources are randomly selected from 15 locations in the bucket, and 8 nuclei randomly select 8×10×4 random numbers. The point source activity is (slightly - China Steel Barrel Packaging Network). The measurement deviations are listed in Table 5. Table 5 Measurement deviations when radioactive materials are randomly distributed (slightly - China Steel Barrel Packaging Network) It can be seen from Table 5 that after the correction result is corrected by the correction coefficient, the measured value is more accurate. When the density is high, the correction effect is more obvious. Taking 0.8g/cm3 as an example, the deviation between the measured value and the accurate value after correction is reduced by about 20% compared with the deviation before the correction. The corrected measured values ​​are more accurate under various density conditions, especially the measured values ​​of the nuclide corresponding to the high energy region are more accurate, mostly within 5%. The above research shows that after using this method to correct the measured value, the bias value of the measured value and the accurate value is significantly reduced, and the effect is remarkable. 4 Conclusion The research results show that when using IOSCS to measure 200L waste steel drums with different activity standards in actual production, the measurement results are more accurate and credible under low density, and when the density increases, the measurement results show significant deviation. The overall deviation increases as the ray characteristic energy decreases, especially when the energy is near 122 keV, the deviation is maximized. Through the research of this project, the accuracy of Qinshan Phase III ISOCS measurement of steel drum waste can be further improved to meet the measurement requirements of solid waste. References (slightly - China Steel Barrel Packaging Network) Note: The part of this article that shows “slightly†is due to the difficulty of editing the webpage. If a friend needs the full text, please contact China Steel Barrel Packaging Network. SHANDONG CAIFENG INTERNATIONAL TRADING Co., Ltd. , https://www.zihcaifeng.com
Uncertainty Analysis of Radioactive Material Activity in 200L Steel Barrel by On-site Object Counting System