Method for rapid measurement of nuclides in waste canister based on monte carlo simulation

Abstract

The application provides a waste solidification barrel nuclide rapid measurement method based on Monte Carlo simulation, and comprises the following steps: step S1: performing Monte Carlo simulation on a waste solidification barrel, a detector and a collimator to obtain a detector efficiency curve; the content in the waste solidification barrel is uniform; step S2: verifying the efficiency calibration by using un-solidified radioactive waste water, and correcting the detector efficiency curve; step S3: collecting a measurement spectrum of a waste solidification barrel to be measured, and obtaining the count of a corresponding nuclide; and step S4: measuring the activity concentration of the waste solidification barrel to be measured by using the corrected detector efficiency curve and the count of the nuclide. The method has the characteristics of simplicity, safety, high efficiency and good applicability, and can significantly shorten the measurement time while maintaining the measurement precision.

Description

Technical Field

[0001] This invention relates to the field of nuclear waste treatment technology, specifically to a rapid method for measuring radionuclides in waste solidification containers based on Monte Carlo simulation. Background Technology

[0002] Nuclear reactors generate radioactive waste, including radioactive gases (aerosols), radioactive liquids, and radioactive solids, during operation, maintenance, and decommissioning. For environmental protection and economic reasons, different types of waste are treated using appropriate processes or methods to minimize radioactive waste and costs. Treated radioactive waste is typically temporarily stored in specially designed waste containers or storage boxes, and then transported to a specially constructed radioactive waste disposal site by dedicated transport vehicles when conditions are suitable.

[0003] Currently, the main methods used to measure the nuclide information of radioactive waste packages include segmented gamma-ray scanning (SGS) and tomographic gamma-ray scanning (TGS). In the SGS method, the waste package is raised or lowered by controlling an electromechanical platform, or the waste package is kept stationary while the detector rises and falls. A detector with a collimator detects the gamma-ray energy spectrum emitted by the decaying contents of a segment of the waste package along its axial direction, after which the gamma rays are absorbed and weakened by the package itself. This allows for segmented measurement of the waste package. This method is suitable for measuring low-density materials; however, the error may be significant when used for medium- to high-density materials.

[0004] TGS does not directly measure the gamma rays emitted by the decay of the contents of the waste package. Instead, it uses a high-intensity gamma-ray source. The emitted rays are collimated and absorbed or attenuated as they pass through the waste package. A collimated detector is then used to measure the gamma-ray spectrum transmitted through the waste package. TGS scanning is more complex than SGS. The high-intensity gamma-ray source and detector must be synchronized in both the axial and radial directions, maintaining a perfectly aligned spatial relationship. Through multi-angle gamma-ray scanning and tomographic imaging, the TGS method achieves three-dimensional reconstruction of the internal structure of the waste package. The measurement results are more accurate than those of the SGS method and have a wider range of applications, but the system is expensive, complex, and time-consuming. TGS measurement systems typically use high-purity germanium spectrometers, require specialized cooling devices, and contain high-activity transmission sources, placing high demands on measurement site conditions and personnel.

[0005] For scenarios where the generation of radioactive waste resin and distillation residue solids is small, the cycle is not fixed, and site conditions are limiting, both the SGS method and the TGS measurement system are expensive and complex to measure. Summary of the Invention

[0006] This invention proposes a rapid method for measuring radionuclides in waste solidification bins based on Monte Carlo simulation, which solves the technical problems of high measurement cost and complex measurement process in existing radionuclide measurement methods.

[0007] To address the aforementioned technical problems, this invention provides a rapid method for measuring radionuclides in waste solidification bins based on Monte Carlo simulation, comprising the following steps:

[0008] Step S1: Perform Monte Carlo simulation on the waste solidification bucket, detector, and collimator to obtain the detector efficiency curve; the contents of the waste solidification bucket are uniform.

[0009] Step S2: Verify the efficiency of the detector by using unsolidified radioactive wastewater to correct the efficiency curve.

[0010] Step S3: Collect the energy spectrum of the solidification container of the waste to be measured and obtain the count of the corresponding nuclides;

[0011] Step S4: Measure the activity concentration of the solidification container of the waste to be measured by using the corrected detector efficiency curve and the count of nuclides.

[0012] Preferably, when performing Monte Carlo simulation, the detector is a lanthanum bromide scintillation detector.

[0013] Preferably, the lanthanum bromide scintillation detector is a cylinder; the rear end of the lanthanum bromide scintillation detector is provided with optical glass, the sides are wrapped with an aluminum shell with a thickness of A1 mm, and the rear end is wrapped with an aluminum shell with a thickness of A2 mm. An MgO reflective layer is filled between the aluminum shell and the lanthanum bromide scintillation detector, wherein A2 is smaller than A1.

[0014] Preferably, the lanthanum bromide scintillation detector is placed in a cylindrical shielding sleeve, which is made of tungsten alloy material with a wall thickness of 20 mm.

[0015] Preferably, during Monte Carlo simulation, the collimation hole extends from the entrance into the collimator, and is successively a cuboid shape and a trapezoidal platform.

[0016] Preferably, when performing Monte Carlo simulation, energy spectrum data obtained by measuring the actual radioactive source using an actual detector is used, and the calculated energy spectrum of Monte Carlo simulation is broadened by fitting based on the functional relationship between half-width at half maximum (HWHM) and energy.

[0017] Preferably, the expression for the functional relationship between half-width at half maximum (FWHM) and energy is:

[0018]

[0019] In the formula, a, b, and c represent Gaussian broadening coefficients, and E represents the ray energy.

[0020] Preferably, the source distance is set to 5cm, and the selected... 60 Co、 137 We conducted actual measurements using the Cs standard point source and verified the calculated values ​​from the Monte Carlo simulation using the actual measurement data.

[0021] Preferably, a TRN converter card is used to set up several detectors at different positions in the Monte Carlo simulation, and the calculated values ​​of the Monte Carlo simulation are verified by the corresponding actual measurement data.

[0022] Preferably, during the operation of the cement curing line, a barrel of cured material is randomly selected for sampling and actual measurement, and the calculated value of the Monte Carlo simulation is verified by the curing sampling measurement data.

[0023] The beneficial effects of this invention include at least the following: Based on the analysis of the characteristics of solidification barrel waste, this invention proposes a simple, efficient measurement method with low requirements for site conditions. A measurement device is constructed, which simplifies and optimizes the SGS or TGS method by combining Monte Carlo simulation calculations and on-site measurements. The mechanical and motor components and their control parts used for rotation and lifting, as well as the highly active transmission radiation source, are removed. Only a single detector equipped with a collimator is used to measure and obtain the γ energy spectrum at an appropriate distance and height around the solidification barrel. The detection efficiency corresponding to different energies can be obtained by Monte Carlo simulation calculations. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present invention;

[0025] Figure 2 This is a schematic diagram of the detector crystal and its enclosure model according to an embodiment of the present invention;

[0026] Figure 3 This is a schematic diagram of the collimator structure according to an embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram of the 3D perspective structure of the Monte Carlo modeling in an embodiment of the present invention;

[0028] Figure 5 This is a schematic diagram of Monte Carlo simulation of radiation transport according to an embodiment of the present invention;

[0029] Figure 6 This is a schematic diagram of fitting curves of the full-energy peaks at different energies in an embodiment of the present invention;

[0030] Figure 7 This is a schematic diagram of the energy spectrum before and after broadening in an embodiment of the present invention;

[0031] Figure 8 This is a schematic diagram comparing the point source efficiency of an embodiment of the present invention;

[0032] Figure 9 This is a schematic diagram of the source efficiency curve of the curing barrel according to an embodiment of the present invention;

[0033] Figure 10This is a schematic diagram of the Monte Carlo model under different source detection distances according to an embodiment of the present invention;

[0034] Figure 11 This is a schematic diagram comparing simulated calculations and experimental measurements under different source detection distances according to an embodiment of the present invention;

[0035] Figure 12 This is a schematic diagram comparing the standard source measurement spectrum and the simulated spectrum in an embodiment of the present invention;

[0036] Figure 13 This is a schematic diagram of the source efficiency curves of the curing barrel at different distances according to an embodiment of the present invention;

[0037] Figure 14 This is a schematic diagram of the source efficiency curves of the waste liquid tank at different distances according to an embodiment of the present invention. Detailed Implementation

[0038] 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 protection scope of the present invention.

[0039] The solidification of waste resin and residual liquid cement adopts a step-by-step feeding and planetary stirring paddle in-tank stirring process to ensure uniform mixing of components. Visual inspection of the cross-section after cutting the actual solidified body shows that the solidified body targeted in this embodiment has a uniform internal distribution. At the same time, destructive multi-point sampling inspection can also confirm this feature.

[0040] In view of the uniform mixing of internal components of cement solidified body, the present invention simplifies and optimizes the SGS or TGS method, removes the mechanical and motor parts and their control parts used for rotation and lifting, and the highly active transmission radiation source, and only uses a single detector equipped with a collimator to measure and obtain the γ energy spectrum at an appropriate distance and height outside the solidification barrel. The detection efficiency corresponding to different energies can be obtained by Monte Carlo simulation calculation, as shown in Example 1.

[0041] Example 1

[0042] like Figure 1 As shown, this embodiment of the invention provides a rapid method for measuring radionuclides in waste solidification bins based on Monte Carlo simulation, comprising the following steps:

[0043] Step S1: Perform Monte Carlo simulation on the waste solidification bucket, detector, and collimator to obtain the detector efficiency curve.

[0044] Specifically, in this embodiment, actual measurements show that the waste bin has a wall thickness of 1.2 mm, an inner diameter of 560 mm, a height of 900 mm, a bottom thickness of 2 mm, a distance of 20 mm from the ground, and a height of 810 mm for the cement solidified body inside. The distance between the bin lid and the top surface of the solidified body is 50 mm, with air in between. The material composition of the cement solidified body is adjusted according to the solidification formula, and its density is calculated by subtracting the weight of the waste bin, the diameter of the cement solidified body, and its height. Measurements show that the density of both the solidified residual liquid and the solidified waste resin is 1.76 g / cm³. 3 .

[0045] The selection of detectors mainly considers factors such as energy resolution, detection efficiency, environmental adaptability, ease of use, and cost-effectiveness. Alternative types include commonly used sodium iodide scintillation detectors, lanthanum bromide scintillation detectors, high-purity germanium semiconductor detectors, and zinc-cadmium telluride semiconductor detectors. Radiochemical analysis data indicates that the radioactive wastewater generated during nuclear reactor operation mainly contains... 60 Co、 58 Co、 54 Mn, 137 Cs and other gamma-ray radionuclides have major decay branches with energies of 0.662 MeV, 0.811 MeV, 0.835 MeV, 1.173 MeV, and 1.332 MeV. Therefore, the detector's energy resolution should ideally be less than 4%, and it should be able to effectively measure radiation up to 1.5 MeV. Sodium iodide and cadmium zinc telluride detectors cannot simultaneously meet these requirements. Considering the ambient temperature and humidity, ease of use, and cost-effectiveness, this embodiment selects a lanthanum bromide scintillation detector.

[0046] Since solidified bodies are generally highly radioactive, large detector crystals are not required. In addition, collimators are needed, and smaller detector crystals can reduce the size and weight of shielding and collimators. Therefore, the smallest commercially available size that is readily available is chosen, namely 38.1 mm in diameter and 38.1 mm in height.

[0047] Since incident photons may interact multiple times within the scintillator crystal, the MgO reflective layer and aluminum shell surrounding the detector crystal are considered to obtain a more accurate gamma spectrum. However, the effective atomic numbers and equivalent densities of components such as the photomultiplier tube, high-voltage distribution circuit board, and preamplifier board beyond the scintillator photon exit surface are low, and they are far from the scintillator. The possibility of scattered or annihilated photons generated by their interaction with gamma rays re-entering the detector crystal is extremely small, so they are not considered. Therefore, these parts are ignored in the Monte Carlo modeling of this embodiment.

[0048] The lanthanum bromide scintillation detector crystal in this embodiment has a diameter of 38.1 mm and a height of 38.1 mm. The outer shell is constructed of an aluminum cylinder with a length of 40.1 mm, a front-end thickness of 1 mm, and a side thickness of 2 mm. A 1 mm thick MgO reflective layer is filled between the cylindrical outer shell and the crystal. The rear end is optical glass with a thickness of 2 mm. Figure 2 As shown.

[0049] To effectively shield the measurement from the influence of ambient radiation, this embodiment places the detector inside a cylindrical shielding sleeve with a wall thickness of 20 mm, made of tungsten alloy with a density of 18.1 g / cm³. 3 Compared with lead materials, tungsten alloy materials of the same thickness have better shielding effectiveness and better mechanical strength.

[0050] In this embodiment, the collimator's structural design primarily considers two aspects: ensuring that as many rays emitted by the solidified body as possible reach the detector crystal, while simultaneously eliminating as many non-target rays as possible from the direction of the solidified body. Considering the rectangular cross-section of the waste bin, the collimator opening is also rectangular. The collimator opening size is related to the source-detector distance; to broaden its applicability, two specifications, 10mm and 15mm, are designed. The collimator is designed as a two-section structure, with a square outer section and a trapezoidal inner section, to increase the proportion of rays emitted by the solidified body that reach the detector crystal. The detailed structure of the collimator is as follows... Figure 3 As shown, it can be placed in both horizontal and vertical positions.

[0051] Meanwhile, considering that the selection of the collimator opening can vary depending on the object being measured, it was decided to adopt a split manufacturing process for the collimator. This ensures that the collimator thickness meets the predetermined shielding thickness requirements. The entire detector exterior is covered by a tungsten alloy collimator and shield. The extension line of the collimation aperture is positioned at the diameter and focal point of a circle. The collimation aperture depth is 40mm. The first 20mm of the collimation aperture is designed as a cuboid shape, and the last 20mm is designed as a trapezoidal truncated cone. The horizontal width of the leading edge is 12.5mm, and the horizontal width of the trailing edge is 38mm. The final model built using Monte Carlo software is as follows... Figure 4 As shown.

[0052] In the Monte Carlo simulation, the propagation path of each photon is determined through random sampling. The simulation begins at a specific source point and tracks photons using physical laws and different cross-sections until their energy is completely absorbed or they escape from the system boundary. Each collision event during the simulation may result in photon scattering or the generation of new secondary particles. These newly generated particles are tracked and recorded for subsequent analysis until the history of all particles has been fully processed. The transport process is as follows: Figure 5 As shown. The detector efficiency curve of this embodiment can be obtained through Monte Carlo simulation.

[0053] Step S2: Verify the efficiency using unsolidified radioactive wastewater to calibrate the detector efficiency curve.

[0054] Specifically, to quantitatively calculate the activity concentration of the contents of the solidification container, efficiency calibration is necessary. A common method is the shell-source method, but this requires multiple linear radioactive sources, which is inconvenient in practical application and differs from actual volume sources. Furthermore, it's difficult to cover the entire energy range (low, medium, and high). Considering the ease of obtaining radioactive wastewater at the measurement site, this embodiment uses actual radioactive wastewater for efficiency calibration verification. Specifically, a laboratory high-purity germanium spectrometer is used to directly measure the radioactive wastewater in the Marin cup, obtaining its nuclide composition and activity concentration, which also serves as source term data for the volume source. The proposed method is used for simulation calculations, which are compared and verified with the direct measurement data. The experimental and simulated values ​​are shown in Table 1. The calibration certificate of the laboratory high-purity germanium spectrometer used in this measurement shows that the expanded uncertainty (k=2) for the full-energy peak efficiency at 0.662 MeV, 1.173 MeV, and 1.332 MeV is 3.0%, 3.2%, and 3.2%, respectively. As can be seen from Table 1, for… 60 The two characteristic energy rays of Co are calculated by the method in this paper and the experimental measurements are close. Except for the 8cm source-probe distance condition, the maximum deviation is within 6%. Even considering the uncertainty of the laboratory high-purity germanium spectrometer, the maximum deviation does not exceed 6.8%. The measurement deviation can meet the relevant requirements for waste transfer.

[0055] Table 1: Relative deviations between experimental and calculated energy efficiency values ​​at different locations

[0056]

[0057] Step S3: Collect the energy spectrum of the solidification container of the waste to be measured and obtain the count of the corresponding nuclides.

[0058] Step S4: Measure the activity concentration of the solidification container of the waste to be measured by using the corrected detector efficiency curve and the count of nuclides.

[0059] The nuclide measurement method in this embodiment is simple, safe, efficient, and widely applicable, significantly reducing measurement time while maintaining measurement accuracy. The system's performance and measurement results were comprehensively evaluated by combining detection efficiency curve simulation, activity concentration calculation for different measurement objects, and experimental measurements. The system meets the requirements for both time efficiency and activity concentration measurement accuracy, and can be applied to the rapid measurement and analysis of solidified waste containers in nuclear waste management.

[0060] Example 2

[0061] The purpose of radionuclide measurement and analysis in waste bins is to obtain the types and activities of gamma radionuclides, which can be obtained from information such as the full-energy peak and its area in the gamma spectrum. From a physical perspective, this is the intrinsic peak detection efficiency, i.e., the pulse count within the full-energy peak and the number of rays emitted by the target being measured. Therefore, efforts should be made to obtain the gamma spectrum.

[0062] The Monte Carlo program MCNP can obtain multichannel gamma spectra by using the pulse amplitude counter card F8 and combining it with a properly divided energy box. Since MCNP can only simulate the pair production, Compton effect, and photoelectric effect of gamma rays interacting with matter, it does not consider the statistical fluctuations of processes such as scintillation, photomultiplier tube photoelectric conversion, and electron multiplication. The resulting energy spectrum usually shows an extreme value at the characteristic energy, i.e., only one energy point, which is several times or even several orders of magnitude higher than the data of adjacent points. However, a real gamma spectrometer should show a peak with a certain width at the characteristic energy.

[0063] Therefore, this embodiment uses energy spectrum data obtained from actual detector measurements of actual radioactive sources. Based on the functional relationship between half-width at half-maximum (FWHM) and energy, the parameters in the functional relationship are obtained through methods such as least squares and curve fitting for broadening. The functional relationship used is as follows:

[0064]

[0065] In the formula, a, b, and c represent Gaussian broadening coefficients, and E represents the ray energy.

[0066] Specifically, by using 60 Co、 137 The energy spectrum was obtained through actual measurements using a Cs standard source. Then, using Gaussian fitting with MATLAB tools, the full-energy peak resolution (FWHM) of the detector at different energies was calculated. Figure 6 As shown.

[0067] Substitute the fitted data into the formula Solving the system of equations, we obtain the Gaussian broadening coefficients a = -0.01920, b = 0.05251, and c = -0.22181. These are then written into the MCNP model file. The MCNP simulation energy spectra before and after broadening are as follows: Figure 7 As shown in the comparison, it can be clearly seen that the fluctuations of the energy spectrum after the broadening process are greatly reduced, and the shape of the energy spectrum is more similar to that measured by the actual detector, which helps to improve the accuracy of the calculation of the activity concentration of the curing barrel.

[0068] Example 3

[0069] This embodiment simulates and experimentally verifies the detection efficiency of the method in Embodiment 1.

[0070] Before performing simulations and measurements on objects with large volume and density, such as curing barrels, it is necessary to conduct preliminary verification of the proposed method using simpler objects. With a source distance of 5cm, several point sources covering low, medium, and high energy ranges were selected for simulation calculations. 60 Co、 137 Actual measurements of the Cs standard point source show that its energy range covers the main nuclides contained in radioactive waste containers. 60 Co、 137 Cs、 54 Mn, etc., comparison between simulation calculations and experimental measurement results, for example Figure 8 As shown. From Figure 8 It can be seen that the data obtained from simulation calculations and experimental measurements are in excellent agreement at the same energy point, indicating that the model and calculation method are credible and reliable.

[0071] Based on the good agreement between point source simulation calculations and experimental measurements, all contents of the curing tank were set as source terms, i.e., uniformly distributed volume sources with energies ranging from 0.06 MeV to 1.5 MeV. The simulation calculations yielded the full-energy peak efficiency for the corresponding energies. The relative error of the Monte Carlo simulation calculations was less than 1%, as shown in the results below. Figure 9 As shown.

[0072] from Figure 9 It can be seen that the volume source detection efficiency curve of the cement-solidified body follows a similar pattern to the first half of the point source detection efficiency curve mentioned above. It initially increases with increasing energy and then decreases, but the detection efficiency begins to increase again when the energy reaches a certain value. Careful analysis suggests that this is because the large volume and high density of the contents of the solidification container cause severe self-absorption. When the radiation energy reaches a certain value, the proportion of radiation entering the detector to overcome self-absorption increases significantly, even exceeding the trend of decreasing cross-section of the gamma-ray interaction with the detector crystal with increasing gamma energy. Therefore, the efficiency increases with increasing energy. To verify this analysis, the contents of the solidification container were replaced with water, and the calculations were performed again. The patterns were completely consistent, but the detection efficiency for water was slightly higher. This is because water has a smaller equivalent atomic number and density than cement-solidified body, resulting in weaker self-absorption.

[0073] Example 4

[0074] This embodiment performs source detection distance simulation calculations and experimental verification on the method of Embodiment 1.

[0075] In MCNP modeling, manually constructing detector crystals, packaging, and casings is time-consuming, labor-intensive, and prone to errors. To reduce repetitive work and improve efficiency, this embodiment uses a TRN transformation card to automatically convert and configure the model. This method allows multiple identical detectors to be placed in different locations within the model, such as... Figure 10As shown, this allows data from multiple detectors to be obtained simultaneously in a single calculation, greatly saving computation time.

[0076] During on-site measurement, the detector's central axis was 42cm from the ground, placing it at the center height of the solidified body. The horizontal distance between the detector's front face and the solidified barrel's cylindrical surface gradually increased from 8cm to 32cm, with a change step of 8cm. Before formally conducting the measurement, the ambient gamma spectrum was measured for 1 hour as the basis for background subtraction.

[0077] Figure 11 Data obtained from simulation calculations and field measurements are presented. The simulation calculation data represents the full-energy peak detection efficiency at 1.332 MeV with a source-probe distance of 24 cm, while the field measurement data represents the net count rate of the full-energy peak at 1.332 MeV with a source-probe distance of 24 cm. Figure 11 It can be seen that as the source distance increases, both the simulation calculation and the field measurement data decrease monotonically, and the relative difference between the two at the same energy is small. The simulation calculation and the field measurement are in good agreement, which further confirms the credibility and reliability of the method proposed in this invention.

[0078] Example 5

[0079] Detection efficiency is a core indicator for ensuring accurate calculation of radionuclide activity, directly affecting the precision and accuracy of radionuclide activity measurement in waste containers. To verify the performance of the method of this invention, the following experiments were conducted in this embodiment: ① Verification of detector modeling using a standard source measurement method; ② Simulation experiments with model efficiency curves at different distances; ③ Verification experiments using a radioactive waste liquid barrel source for activity concentration measurement; ④ Verification of the activity concentration calculation results using a solidified sample.

[0080] 1. Standard source simulation verification

[0081] This study uses a radionuclide analysis measurement system built based on a LaBr3 detector. The measurement object is a laboratory-grade radionuclide. 60 Co and 137 For the Cs standard source, the radiation sources are first positioned 5 cm away from the detector, ensuring that each radiation source is directly facing the geometric center of the front face of the detector to ensure that the radiation received by the detector is uniform. Each source is measured for 15 minutes.

[0082] A standard source measurement model under the same conditions was established using MCNP, and F8 cards were used for recording, with the count set to 10. 9 The results of simulation calculations and experimental measurements are compared, for example Figure 12As shown, after normalization, the simulation results and experimental measurement data show a high degree of agreement between the energy corresponding to the region of interest and the full-energy peak at the characteristic energy. However, there are significant differences in the low-energy and high-energy regions. This is mainly due to two reasons: first, the influence of ambient background radiation exists during actual measurements, which the Monte Carlo simulation did not consider; second, the actual detector crystal contains trace amounts of radioactive nuclides. 138 La introduces background noise into the energy spectrum, which Monte Carlo simulations did not consider. 138 The effect of La emitted rays.

[0083] Since energy spectrum analysis relies on information from full-energy peaks, and the main nuclides contained in the research object are usually... 60 Co、 137 Cs、 54 Mn, etc., environmental background and trace elements contained in the detector crystal 138 La does not have an observable effect on the full-energy peaks corresponding to the characteristic rays of these nuclides, so it can be disregarded in engineering. Overall, the simulation results are ideal, proving the accuracy of the detector model.

[0084] 2. Simulation experiment of efficiency curves at different distances

[0085] Based on the standard source simulation calculation, the solidified body inside the curing barrel is set as the source term, that is, a uniformly distributed volume source. The energy is selected from 0.04MeV to 1.5MeV, and the corresponding Monte Carlo model is established to simulate and calculate the full-energy peak efficiency of the corresponding energy.

[0086] like Figure 13 As shown, the bulk source detection efficiency curve of the solidified body initially increases and then decreases with increasing energy, but the detection efficiency begins to increase again when the energy reaches a certain value. This is because the large volume and high density of the contents of the solidified container cause self-absorption. When the X-ray energy reaches 500 keV, the proportion of X-rays that overcome the self-absorption effect and enter the detector increases more and more, and its increasing trend even exceeds the trend of the interaction cross section between the γ-ray and the detector crystal decreasing with increasing γ-ray energy, thus showing a law of increasing with increasing energy. Comparative analysis of the efficiency curves at different measurement distances shows that the efficiency curve shows a decreasing trend with increasing distance. This trend is because the number of particles entering the collimator decreases with increasing measurement distance, thus leading to a decrease in efficiency.

[0087] After replacing the cement solidification tank with water, the calculation is repeated as follows: Figure 14 The variation patterns of the two are completely consistent. However, the detection efficiency for water is higher because water has a smaller equivalent atomic number and density than cement solidified bodies, and its self-absorption effect is weaker.

[0088] Given the similarity of the efficiency calibration curves for water and solidified bodies, it is theoretically feasible to use a waste liquid tank model as a substitute for measurement verification when validating the solidification tank model. In practice, it is not necessary to specifically solidify the residual liquid or waste resin, sample and prepare small samples of cement solidified bodies, and perform curing. Instead, the radioactive waste liquid can be placed in a waste tank and the method can be directly used for measurement verification. After confirming that the experimental results meet expectations, the solidification tank can be used for further verification. This not only saves the time and cost of solidification and curing but also allows for flexible adjustments to the plan during the experiment.

[0089] 3. Experimental verification of waste liquid tank

[0090] 3.1 Experimental Methods

[0091] The validation method employs a direct measurement approach, whereby waste stream samples are taken and the activity concentration information of the waste is directly measured using a laboratory HPGe spectrometer. This measurement serves as the baseline value for the experimental validation of this method. The main steps are as follows:

[0092] (1) First, prepare a 200L empty curing tank. Use a sampling system to retrieve the waste liquid and transport it into the tank to ensure that the liquid level in the tank is consistent with the level of the solidified body.

[0093] (2) Use a pipette to draw up the waste liquid and put it into a special marin cup. Use a calibrated laboratory HPGe spectrometer to directly measure the nuclide composition and activity concentration of the waste liquid.

[0094] (3) On-site measurement of energy spectrum of the waste liquid tank by detectors at different distances.

[0095] (4) The efficiency curve obtained by Monte Carlo simulation was used as the efficiency calibration curve for on-site energy spectrum measurement. The activity concentration of the waste liquid was calculated and compared with the laboratory analysis data.

[0096] 3.2 On-site measurement

[0097] Conduct environmental background measurements and calibrate the instrument's energy. Install the collimator at the front of the detector, ensuring the collimator's detection window is aligned with the detector's center. Place the detector horizontally, aligning its central axis with the central axis of the curing container, ensuring they are perpendicular. The detector's central axis should be 42cm above the ground. Begin measurement at the center height of the contents of the curing container.

[0098] During the measurement, the horizontal distance between the detector and the curing barrel was systematically adjusted, gradually increasing from 8cm to 48cm, with each adjustment step being 8cm, and the measurement time for each set distance was 180s.

[0099] 3.3 Source Term Laboratory Analysis

[0100] The laboratory gamma spectrometer is an ORTEC GEM-C5970-LB HPGe spectrometer, which has passed the testing and calibration laboratory's verification.

[0101] The acquired energy spectrum data were analyzed using the gamma vision software provided with the spectrometer. The measurement time was 30 minutes, and the activity concentration of the radionuclide was calculated according to the formula:

[0102]

[0103] Among them, a c V represents the activity concentration of the analyte, V represents the volume of the sample, t is the effective measurement time, ε represents the energy efficiency scale corresponding to the nuclide, P is the probability (branching ratio) of gamma rays produced during the decay of the radionuclide, and N... net This indicates the net count.

[0104] Analysis of experimental source data revealed that the waste liquid contained... 54 Mn and 58 The content of Co is very low, approximately [missing information]. 60 1 / 14 and 1 / 25 of Co, 60 Co、 54 Mn and 58 The half-lives of Co are 5.28 years, 312 days, and 71 days, respectively. However, in actual work, the time from receiving the waste liquid to processing, solidification, and finally handover is generally 1 to 3 years. At the time of waste handover, the solidified body contains... 54 Mn and 58 The remaining percentage of Co is much smaller than 60 Co, therefore, the research mainly focuses on 60 The relevant activity of Co.

[0105] 3.4 On-site Measurement and Result Analysis

[0106] Based on the detection efficiency curve obtained from the Monte Carlo simulation and the energy spectrum data of the waste liquid tank obtained from the field measurement, the activity concentration of the waste liquid measured under different distance conditions and its deviation from the experimental spectrometer measurement results are shown in Table 2.

[0107] Table 2: 60 Co activity concentration measurement and calculation results

[0108]

[0109]

[0110] Overall, with increasing distance, the deviation between the calculated and measured activity concentration values ​​initially decreased and then slightly increased. Between 16 cm and 48 cm, the deviation remained within a low range, from -6.65% to 6.27%. The deviation was largest at a closer distance of 8 cm, but still did not exceed 15%. The overall model effectively met the measurement requirements, and the calculated results closely approximate the actual values, providing a reliable basis for the measurement verification of solidified samples.

[0111] 4. Experimental verification of cured samples

[0112] 4.1 Experimental Methods

[0113] Considering the issue of uniformity in the cured body, source sampling is generally considered to be the most representative method for overall activity. Therefore, this embodiment selects a method of sampling and measuring during the curing process to ensure the representativeness and accuracy of the measurement results.

[0114] During the operation of the cement curing line, a sample of the cured material was randomly selected and its number recorded. The sample and the curing container were then placed in a constant temperature and humidity environment for curing. After curing, the waste container was placed at a predetermined measurement location, and a gamma-ray spectrometry (γ-ray spectroscopy) measurement was performed on the container using a waste curing container measurement system. By acquiring the overall γ-ray spectral data of the container and combining it with the simulated detector efficiency calibration curve, the activity concentration of the curing container could be calculated. To verify the accuracy of the efficiency calibration curve, the simulation results were compared with the activity concentration measured from the cured sample.

[0115] 4.2 Source Term Laboratory Analysis

[0116] The energy spectrum data of the nuclides in the sample were obtained by gamma-ray spectroscopy measurement using an HPG detector. Since the sample was taken during the curing process and its physicochemical properties are essentially consistent with the final cured body, the measured activity concentration can well represent the overall activity level of the cured body. In the sample... 60 Co、 54 Mn and 58 The activity concentration ratio of Co is approximately 27.4:1.4:1. Therefore, when calculating the activity concentration of the solidified body, it is still based on... 60 Co is the main object of study for calculation.

[0117] 4.3 On-site measurement and result analysis

[0118] The activity concentration results obtained from actual measurements and simulated efficiency calculations of the curing tank are shown in Table 3. At a distance of 8 cm, the maximum deviation was 21.60%. This deviation may stem from the detector entering the nonlinear response region during close-range measurements, especially when facing high-intensity radiation sources such as the cured material. This means the detector may over-respond, resulting in a higher net count rate than expected, leading to measured activity concentration values ​​significantly higher than calculated values. At a distance of 16 cm, the deviation decreased to 10.05%. Although the error is still relatively large, it is significantly lower than at 8 cm, indicating that the detector response is stabilizing and the match between measured and calculated values ​​is improving. At measurement distances of 24 cm, 32 cm, 40 cm, and 48 cm, the deviations were 3.17%, -2.05%, -5.02%, and -9.13%, respectively, indicating that mid-range measurements generally provide relatively reliable results.

[0119] Table 3: 60 Co activity concentration measurement and calculation results

[0120]

[0121] In summary, the method provided in Example 1 meets the requirements in terms of both time efficiency and activity concentration measurement accuracy, and can be applied to the rapid measurement and analysis of waste solidification containers in nuclear waste management.

[0122] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; only preferred embodiments of the present invention are illustrated. The descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. As long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0123] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this invention should be determined by the appended claims.

Claims

1. A rapid method for measuring radionuclides in waste solidification bins based on Monte Carlo simulation, characterized in that: Includes the following steps: Step S1: Perform Monte Carlo simulation on the waste solidification bucket containing cement solidification body, detector and collimator to obtain the detector efficiency curve; the contents of the waste solidification bucket are uniform; Step S2: Verify the efficiency of the detector by using unsolidified radioactive wastewater to correct the efficiency curve. Step S3: Collect the energy spectrum of the solidification container of the waste to be measured and obtain the count of the corresponding nuclides; Step S4: Measure the activity concentration of the solidification container of the waste to be measured using the corrected detector efficiency curve and the nuclide count; When performing Monte Carlo simulations, the detector used is a lanthanum bromide scintillation detector; The lanthanum bromide scintillation detector is cylindrical; the rear end of the lanthanum bromide scintillation detector is provided with optical glass, the sides are wrapped with an aluminum shell with a thickness of A1 mm, and the rear end is wrapped with an aluminum shell with a thickness of A2 mm. The space between the aluminum shell and the lanthanum bromide scintillation detector is filled with an MgO reflective layer, wherein A2 is smaller than A1. The lanthanum bromide scintillation detector is placed in a cylindrical shielding sleeve, which is made of tungsten alloy material with a wall thickness of 20 mm. During Monte Carlo simulation, the collimation aperture extends from the entrance into the collimator, in the form of a cuboid shape followed by a trapezoidal platform.

2. The rapid radionuclide measurement method for waste solidification bins based on Monte Carlo simulation according to claim 1, characterized in that: When performing Monte Carlo simulations, energy spectrum data obtained from actual radioactive sources are measured using actual detectors. Based on the functional relationship between half-width at half maximum (HWHM) and energy, the calculated energy spectrum of the Monte Carlo simulation is broadened by fitting.

3. The rapid radionuclide measurement method for waste solidification bins based on Monte Carlo simulation according to claim 2, characterized in that: The expression for the functional relationship between half-width at half-maximum and energy is: In the formula, a, b, and c represent Gaussian broadening coefficients, and E represents the ray energy.

4. The rapid radionuclide measurement method for waste solidification bins based on Monte Carlo simulation according to claim 1, characterized in that: Set the source distance to 5cm and select... 60 Co、 137 We conducted actual measurements using the Cs standard point source and verified the calculated values ​​from the Monte Carlo simulation using the actual measurement data.

5. The rapid radionuclide measurement method for waste solidification bins based on Monte Carlo simulation according to claim 1, characterized in that: A TRN converter card was used to set up several detectors at different positions in the Monte Carlo simulation, and the calculated values ​​of the Monte Carlo simulation were verified by the corresponding actual measurement data.

6. The rapid radionuclide measurement method for waste solidification bins based on Monte Carlo simulation according to claim 1, characterized in that: During the operation of the cement curing line, a barrel of cured material was randomly selected for sampling and actual measurement. The calculated values ​​of the Monte Carlo simulation were verified by using the measurement data from the cured sample.

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