Monte Carlo simulation-based waste solidification barrel nuclide rapid measurement method

Abstract

The invention provides a waste solidification barrel nuclide rapid measurement method based on Monte Carlo simulation, and the method comprises the following steps: S1, carrying out Monte Carlo simulation on a waste solidification barrel, a detector and a collimator, and obtaining a detector efficiency curve; contents in the waste solidification barrel are uniform; s2, efficiency scale verification is carried out through the uncured radioactive wastewater, and a detector efficiency curve is corrected; s3, collecting the measurement energy spectrum of the waste solidification barrel to be measured, and obtaining the count of corresponding nuclides; and S4, measuring the activity concentration of the waste solidification barrel to be measured through the corrected detector efficiency curve and nuclide counting. The method has the characteristics of simplicity, safety, high efficiency, good applicability and the like, and the measurement time can be remarkably shortened while the measurement precision is kept.

Description

Technical Field

[0001] The invention relates to the technical field of nuclear waste treatment, and in particular to a method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation. Background Art

[0002] Nuclear reactors will generate radioactive gases (aerosols), radioactive liquids and radioactive solids during operation, maintenance and decommissioning. For environmental protection and economic considerations, different wastes will be treated with appropriate processes or methods to minimize radioactive waste and costs. Treated radioactive waste is usually temporarily stored in special waste barrels or storage boxes, and when the time and conditions are right, it will be transported to a specially built radioactive waste disposal site for storage by special vehicles.

[0003] The current methods for measuring the nuclide information of radioactive waste packages mainly include segmented gamma scanning (SGS), tomographic gamma scanning (TGS), etc. In the SGS method, the waste package is raised or lowered by controlling the electromechanical platform, or the waste package remains stationary, and the detector is raised or lowered. The detector with a collimator is used to detect the gamma ray energy spectrum emitted by the decay of the contents of a certain section in the axial direction of the waste package and absorbed and weakened by itself, thereby realizing segmented measurement of the waste package. This method is suitable for the measurement of relatively low-density materials. If it is used for the measurement of medium and high density materials, the error may be large.

[0004] TGS does not directly measure the gamma rays emitted by the decay of the contents of the waste package. Instead, it is equipped with a strong gamma radiation source. The rays emitted by the source are absorbed or weakened when passing through the waste package after being collimated, and the gamma energy spectrum of the transmitted waste package is measured using a collimated detector. The scanning method of TGS is more complicated than that of SGS. The strong gamma radiation source and the detector must be synchronized in both the axial and radial directions, and always maintain a spatial relationship facing each other. Through multi-angle gamma ray scanning and tomography technology, the TGS method achieves three-dimensional reconstruction of the internal structure of the waste package. The measurement results are more accurate than the SGS method and have a wider range of applications, but the system is expensive, complex and takes a long time to measure. The TGS measurement system usually uses a high-purity germanium spectrometer, which requires a special refrigeration device and contains a high-activity transmission source, which has high requirements for measurement site conditions and personnel.

[0005] For scenarios where the amount of radioactive waste resin and evaporation residual solids generated is small, the cycle is not fixed, and the site conditions are restrictive, the use of the SGS method and the TGS measurement system has the problems of high cost and complex measurement. Summary of the invention

[0006] The present invention proposes a rapid measurement method for nuclides in waste solidification barrels based on Monte Carlo simulation, which solves the technical problems of high measurement cost and complex measurement process of existing nuclide measurement methods.

[0007] In order to solve the above technical problems, the present invention provides a method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation, comprising the following steps:

[0008] Step S1: performing Monte Carlo simulation on the waste solidification barrel, the detector and the collimator to obtain a detector efficiency curve; the contents in the waste solidification barrel are uniform;

[0009] Step S2: verifying the efficiency calibration by using unsolidified radioactive wastewater to calibrate the detector efficiency curve;

[0010] Step S3: collecting the measurement spectrum of the waste solidification barrel to be measured, and obtaining the count of the corresponding nuclide;

[0011] Step S4: measuring the activity concentration of the waste solidification barrel to be measured by using the corrected detector efficiency curve and the counting 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; an optical glass is arranged at the rear end of the lanthanum bromide scintillation detector, the side is 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, and a 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, and the shielding sleeve is made of a tungsten alloy material with a wall thickness of 20 mm.

[0015] Preferably, when performing Monte Carlo simulation, the collimating hole extends from the entrance to the inside of the collimator, and is in the shape of a rectangular parallelepiped and a trapezoidal platform respectively.

[0016] Preferably, when performing Monte Carlo simulation, the energy spectrum data obtained by measuring the actual radiation source using an actual detector is used, and the calculated energy spectrum of the Monte Carlo simulation is broadened by fitting according to the functional relationship between the half-width and the energy.

[0017] Preferably, the functional relationship between the half-height width and the energy is expressed as:

[0018]

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

[0020] Preferably, the source distance is set to 5 cm, and 60 Co. 137 The actual measurement is carried out on a Cs standard point source, and the calculated values ​​of the Monte Carlo simulation are verified by the actual measurement data.

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

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

[0023] The beneficial effects of the present invention include at least: based on the analysis of the characteristics of solidified barrel waste, the present invention proposes a simple, efficient, and low-site condition measurement method, constructs a set of measurement devices, simplifies and optimizes the SGS or TGS method by combining Monte Carlo simulation calculations with on-site measurements, removes the machinery and motors used for rotation and lifting and their control parts, and the highly active transmitted radiation source, and only uses a single detector equipped with a collimator to measure and obtain the gamma energy spectrum at an appropriate distance and height outside the solidified barrel, and uses Monte Carlo simulation calculations to obtain the detection efficiency corresponding to different energies. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of a method flow chart of an embodiment of the present invention;

[0025] Figure 2 A schematic diagram of a detector crystal and an inclusion model according to an embodiment of the present invention;

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

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

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

[0029] Figure 6 Schematic diagram of full energy peak fitting curves of different energies according to an embodiment of the present invention;

[0030] Figure 7 Schematic diagram of the energy spectrum before and after broadening according to an embodiment of the present invention;

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

[0032] Fig. 9 Schematic diagram of the curing barrel source term efficiency curve of an embodiment of the present invention;

[0033] Fig.10A schematic diagram of a Monte Carlo model at different source detection distances according to an embodiment of the present invention;

[0034] Fig.11 A schematic diagram showing comparison between simulation calculation and experimental measurement values ​​at different source detection distances according to an embodiment of the present invention;

[0035] Fig.12 A schematic diagram showing a comparison between a measured spectrum and a simulated spectrum of a standard source according to an embodiment of the present invention;

[0036] Fig.13 Schematic diagram of the curing barrel source term efficiency curve at different distances according to an embodiment of the present invention;

[0037] Fig.14 Schematic diagram of the source term efficiency curve of the waste liquid barrel at different distances according to an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of the present invention.

[0039] The waste resin and evaporation residue cement solidification adopts a barrel mixing process with step-by-step feeding and repeated lifting and lowering of planetary stirring paddles to ensure uniform mixing of the components. Visual inspection of the cross-section of the actual solidified body after cutting shows that the solidified body targeted by this embodiment is evenly distributed inside. At the same time, destructive multi-point sampling inspection can also confirm this feature.

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

[0041] Example 1

[0042] like Figure 1 As shown, an embodiment of the present invention provides a method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation, comprising the following steps:

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

[0044] Specifically, in this embodiment, after actual measurement, the waste barrel wall thickness is 1.2mm, the inner diameter is 560mm, the height is 900mm, the barrel bottom thickness is 2mm, the height from the ground is 20mm, the height of the cement solidified body in the barrel is 810mm, the barrel cover is 50mm away from the top surface of the solidified body, and there is air in the middle. The material composition of the cement solidified body is adjusted according to the solidification formula, and the density of the cement solidified body is calculated by deducting the weight of the waste barrel, the diameter and height of the cement solidified body. After measurement and calculation, the density of the steam residue solidified body and the waste resin solidified body is 1.76g / cm 3 .

[0045] The selection of detectors mainly considers energy resolution, detection efficiency, environmental adaptability, ease of use, economy and other aspects. The alternative types are the commonly used sodium iodide scintillation detectors, lanthanum bromide scintillation detectors, high-purity germanium semiconductor detectors, cadmium zinc telluride semiconductor detectors, etc. Radiochemical analysis data show that the radioactive wastewater produced during the operation of nuclear reactors mainly contains 60 Co. 58 Co. 54 Mn, 137 The main decay branch energies of γ-radioactive nuclides such as Cs are 0.662MeV, 0.811MeV, 0.835MeV, 1.173MeV, 1.332MeV, etc. Therefore, the energy resolution of the detector is preferably less than 4% of the detector, and it can effectively measure the rays within 1.5MeV. Sodium iodide and cadmium zinc telluride detectors cannot meet the requirements at the same time. Considering the on-site temperature and humidity, convenience of use and economy, this embodiment selects lanthanum bromide scintillation detector.

[0046] Since the radioactivity of the solid body is generally strong, large-sized detector crystals are not required. In addition, a collimator is required. Smaller detector crystals can reduce the size and weight of the shielding and collimator. Therefore, the smallest commercially available size that is easily available is selected, that is, 38.1mm in diameter and 38.1mm in height.

[0047] Since the incident photons may interact multiple times in the scintillator crystal, the MgO reflective layer and aluminum shell wrapped around the detector crystal are taken into consideration to obtain a more accurate γ energy spectrum. However, the photomultiplier tubes, high-voltage distribution circuit boards, front-end amplifiers and other components behind the scintillation photon exit surface of the crystal have low effective atomic numbers, low equivalent densities, and are far away from the scintillator. The possibility of scattered photons or annihilation photons generated by the interaction with γ rays re-entering the detector crystal is extremely small and is not considered. Therefore, this embodiment ignores these parts when performing Monte Carlo modeling.

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

[0049] In order to effectively shield the influence of the radiation in the surrounding environment on the measurement, the detector is placed in a cylindrical shielding sleeve with a wall thickness of 20 mm and a tungsten alloy material with a density of 18.1 g / cm 3 Compared with lead materials, tungsten alloy materials of the same thickness have better shielding effectiveness and better mechanical strength.

[0050] The structural design of the collimator in this embodiment mainly considers two aspects: allowing the radiation emitted by the solid body to hit the detector crystal as much as possible, while eliminating as many non-target radiation from the direction of the solid body as possible. Considering that the side cross-section of the waste barrel is a rectangle, the collimator opening is also set to a rectangle. The size of the collimator opening is related to the source-detection distance. In order to expand the scope of application, two specifications of 10mm and 15mm are designed. The collimator is designed as a two-stage structure, with a square outer side and a trapezoidal inner side, so as to increase the proportion of radiation emitted by the solid body that enters the detection crystal. The detailed structure of the collimator is shown in the figure below. Figure 3 As shown, it can be placed horizontally or vertically.

[0051] At the same time, based on the consideration that the opening selection of the front-end collimator can change with the measurement object, it was decided to use a split processing technology for the collimator, while ensuring that the thickness of the collimator meets the predetermined shielding thickness requirements. The entire detector is covered by a tungsten alloy collimator and shielding body, and the extension line of the collimation hole is positioned on the diameter and focus of the circle. The depth of the collimation hole is 40mm, the first 20mm of the collimation hole is designed as a rectangular parallelepiped, and the back 20mm is designed as a trapezoidal table. The horizontal width of the front edge is 12.5mm, and the horizontal width of the back edge is 38mm. The model finally established using Monte Carlo software is as follows Figure 4 shown.

[0052] In Monte Carlo simulation, the propagation path of each photon is determined by random sampling. The simulation starts at a specific source point and combines the laws of physics and different cross sections to track the photons until their energy is completely absorbed or escapes the system boundary. Each collision event in the simulation may cause photon scattering or generate new secondary particles. The newly generated particles will be tracked and recorded for subsequent analysis until the history of all particles is completely processed. The transport process is as follows: Figure 5 Through Monte Carlo simulation, the detector efficiency curve of this embodiment can be obtained.

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

[0054] Specifically, in order to quantitatively calculate the activity concentration of the contents of the solidified barrel, efficiency calibration must be performed. The common method is the shell source method, but it requires the use of multiple linear radioactive sources. The actual application process is inconvenient, and there are certain differences from the actual body source situation. Moreover, it is difficult for the energy points to cover the low, medium and high full energy range. Considering that radioactive wastewater can be easily obtained at the measurement site, this embodiment uses actual radioactive wastewater to verify the efficiency calibration. Specifically, a laboratory high-purity germanium spectrometer is used to directly measure the radioactive wastewater in the Marin Cup to obtain its nuclide composition and activity concentration, which are also used as body source term data. The method proposed in this article is used for simulation calculations, which are compared and verified with the direct measurement data. The experimental measurement values ​​and simulation calculation values ​​are shown in Table 1. The calibration certificate of the laboratory high-purity germanium spectrometer used for this measurement shows that the expanded uncertainty (k=2) of the full-energy peak efficiency of 0.662MeV, 1.173MeV and 1.332MeV is 3.0%, 3.2% and 3.2%, respectively. As can be seen from Table 1, for 60 For the two characteristic energy rays of Co, the calculated values ​​by the proposed method are close to the experimental measured values. Except for the source-detector distance of 8 cm, the maximum deviation is within 6%. After 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 deviation between experimental and calculated values ​​of energy efficiency at different locations

[0056]

[0057] Step S3: Collect the measurement spectrum of the waste solidification barrel to be measured, and obtain the count of the corresponding nuclide.

[0058] Step S4: Measure the activity concentration of the waste solidification barrel to be measured through the corrected detector efficiency curve and the counting of nuclides.

[0059] The nuclide measurement method of this embodiment is simple, safe, efficient and has good applicability. It can significantly shorten the measurement time while maintaining the measurement accuracy. The performance and measurement results of the system are comprehensively evaluated by combining the detection efficiency curve simulation, the activity concentration calculation and experimental measurement of different measurement objects. The system meets the use requirements in terms of time efficiency and activity concentration measurement accuracy, and can be used for rapid measurement and analysis of waste solidification barrels in nuclear waste management.

[0060] Example 2

[0061] The purpose of waste barrel nuclide measurement and analysis is to obtain the type and activity of γ-radioactive nuclides, which can be obtained from the full energy peak and its area of ​​the γ spectrum. From a physical point of view, this is the intrinsic peak detection efficiency, that is, the pulse count within the full energy peak and the number of rays emitted by the measurement target. Therefore, efforts should be made to obtain the γ spectrum.

[0062] Monte Carlo program MCNP can obtain multi-channel gamma spectrum by using pulse amplitude counting card F8 and combining with energy boxes that are reasonably divided. Since MCNP can only simulate the electron pair effect, Compton effect and photoelectric effect of gamma rays and matter, and does not consider the statistical fluctuations of scintillation, photomultiplier tube photoelectric conversion and electron multiplication, the energy spectrum shape obtained in this way usually shows that the extreme value appears at the characteristic energy, that is, only at one energy point, which is several times or even several orders of magnitude higher than the data of adjacent points, while the actual gamma spectrometer should have a peak with a certain width at the characteristic energy.

[0063] Therefore, this embodiment uses the energy spectrum data obtained by measuring the actual radiation source with the actual detector, and according to the functional relationship between the half-width and the energy, obtains the parameters in the functional relationship through the least square method, curve fitting, etc. for widening. The functional relationship used is:

[0064]

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

[0066] Specifically, by using 60 Co. 137 The energy spectrum is obtained by actual measurement of Cs standard source, and then the full-energy peak resolution (FWHM) of the detector at different energies is calculated with the help of Gaussian fitting of MATLAB tool, such as Figure 6 shown.

[0067] Substitute the fitted data into the formula The simultaneous equations give Gaussian broadening coefficients a = -0.01920, b = 0.05251, c = -0.22181. Write the MCNP model file, and the MCNP simulation calculation energy spectrum before and after broadening is as follows: Figure 7 As shown, by comparison, it can be clearly seen that the fluctuation of the energy spectrum after broadening processing is greatly reduced, and it is more similar to the shape of the energy spectrum measured by the actual detector, which helps to improve the accuracy of the activity concentration calculation of the solidification barrel.

[0068] Example 3

[0069] This embodiment performs detection efficiency simulation calculation and experimental verification on the method of Embodiment 1.

[0070] Before simulating and measuring objects with large volume and density such as solidification barrels, it is necessary to use simple objects to preliminarily verify the proposed method. Set the source distance to 5cm, select several energy point sources covering the low, medium and high energy ranges for simulation calculation, and select 60 Co. 137 Actual measurement of Cs standard point source, whose energy range covers the main nuclides contained in radioactive waste barrels 60 Co. 137 Cs, 54 Mn, etc., the comparison between simulation calculation and experimental measurement results is shown in Figure 8 As shown. Figure 8 It can be seen that the data obtained from simulation calculations and experimental measurements are very consistent at the same energy point, indicating that the model and calculation method are credible and reliable.

[0071] On the basis of the agreement between the point source simulation calculation and the experimental measurement, all the contents of the solidification barrel are set as source items, that is, uniformly distributed volume sources, with energies ranging from 0.06MeV to 1.5MeV. The full energy peak efficiency of the corresponding energy is obtained by simulation calculation. The relative error of the Monte Carlo simulation calculation is less than 1%. The results are as follows Fig. 9 shown.

[0072] from Fig. 9 It can be seen that the curve of volume source detection efficiency of cement solidification body is similar to the first half of the curve of point source detection efficiency mentioned above. It increases first and then decreases with the increase of energy, but the detection efficiency begins to increase again when the energy increases to a certain value. After careful analysis and research, it is believed that this is due to the large volume and high density of the contents of the solidification barrel, which causes a very serious self-absorption phenomenon. When the ray energy reaches a certain value, the proportion of the number of rays that overcome the self-absorption effect and enter the detector increases. The increasing trend even exceeds the trend of the interaction cross section between the gamma ray and the detector crystal decreasing with the increase of gamma energy, thus showing a law of increasing with the increase of energy. To verify this analysis, the contents of the solidification barrel are replaced by water from cement solidification body and then calculated again. The change laws of the two are exactly the same, but the detection efficiency of water is higher. This is because the equivalent atomic number and density of water are smaller than those of cement solidification body, and the self-absorption effect is weaker than that of cement solidification body.

[0073] Example 4

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

[0075] When MCNP modeling is performed, it takes a lot of time and effort to manually construct detector crystals, packaging materials, and shells, and it is prone to errors. In order to reduce duplication of work and improve efficiency, this embodiment uses a TRN conversion card to automatically convert and configure the model. This method can set multiple identical detectors in different positions in the model, such as Fig.10As shown, the data of multiple detectors can be obtained simultaneously in one calculation, which greatly saves the calculation time.

[0076] During on-site measurement, the central axis of the detector was 42 cm from the ground, so that it was at the center height of the solidified body; the horizontal distance between the front end surface of the detector and the cylindrical surface of the solidifying barrel gradually increased from 8 cm to 32 cm, with a step length of 8 cm. Before the formal measurement, the on-site environmental γ energy spectrum was measured for 1 hour as a basis for background subtraction.

[0077] Fig.11 The data obtained from simulation calculation and field measurement are given. The simulation calculation data is the full energy peak detection efficiency corresponding to 1.332MeV when the source-detection distance is 24cm, and the field measurement data is the full energy peak net count rate corresponding to 1.332MeV when the source-detection distance is 24cm. Fig.11 It can be seen that with the increase of the source detection distance, the data of the simulation calculation and the field measurement are monotonically decreasing, and the relative difference between the two at the same energy is small. The simulation calculation is consistent with the field measurement, which further confirms the credibility and reliability of the method proposed in the present invention.

[0078] Example 5

[0079] Detection efficiency is the core indicator to ensure accurate calculation of radionuclide activity, and directly affects the precision and accuracy of the measurement of nuclide activity in waste barrels. To verify the performance of the method of the present invention, the following experiments were carried out in this embodiment: ① The detector modeling was verified by using the standard source measurement method; ② The model efficiency curve simulation experiment was set up at different distances; ③ The activity concentration measurement verification experiment was carried out using a radioactive waste liquid barrel source; ④ The activity concentration calculation results were verified by combining solid body samples.

[0080] 1. Standard source simulation verification

[0081] Nuclide analysis and measurement system based on LaBr3 detector. The measurement object is laboratory 60 Co and 137 Cs standard source, first position the radiation source at a distance of 5 cm from the detector, and ensure that each radiation source is facing the geometric center of the front end of the detector to ensure that the radiation received by the detector is uniform, and measure for 15 minutes each.

[0082] The standard source measurement model under the same conditions was established by MCNP, and the F8 card was used for recording, and the count was set to 10. 9 , the comparison between simulation calculation and experimental measurement results is as follows Fig.12As shown. After normalization, the simulation results and experimental measurement data are highly consistent in the full energy peak corresponding to the characteristic energy of the region of interest, but there are large differences in the low-energy and high-energy regions. There are two main reasons: one is the influence of ambient background radiation in the actual measurement, which is not taken into account in the Monte Carlo simulation calculation; the other is that the actual detector crystal contains trace amounts of radioactive nuclides 138 La, which will produce background noise in the energy spectrum, is not taken into account in Monte Carlo simulations. 138 The influence of La emitted rays.

[0083] Since energy spectrum analysis is based on the information of the total energy peak, and the main nuclides contained in the research object are usually 60 Co. 137 Cs, 54 Mn, etc., trace amounts contained in the environmental background and detector crystals 138 La will not have an observable effect on the full energy peaks corresponding to the characteristic rays of these nuclides, so it can be ignored in engineering. Overall, the simulation results are ideal, proving the accuracy of the detector model.

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

[0085] On the basis of standard source simulation calculation, the solidified body in the solidification barrel is set as the source term, that is, a uniformly distributed volume source. The energy is selected from 0.04MeV to 1.5MeV. The corresponding Monte Carlo model is established, and the full-energy peak efficiency of the corresponding energy is obtained by simulation calculation.

[0086] like Fig.13 As shown in the figure, the volume source detection efficiency curve of the solidified body increases first and then decreases with the increase of energy, but the detection efficiency begins to increase again when the energy increases to a certain value. This is due to the self-absorption phenomenon caused by the large volume and high density of the contents of the solidified barrel. When the ray energy reaches 500keV, the proportion of the number of rays that overcome the self-absorption and enter the detector increases. The increasing trend even exceeds the trend of the interaction cross section between the gamma ray and the detector crystal decreasing with the increase of gamma energy, thus showing a law of increasing with the increase of energy. By comparing and analyzing the efficiency curves at different measurement distances, it can be observed that the efficiency curve shows a downward trend with the increase of distance. This trend is due to the decrease in the number of particles entering the collimator with the increase of measurement distance, which leads to a decrease in efficiency.

[0087] After replacing the cement solidified body with water, recalculate the content of the curing barrel. Fig.14 The change rules of the two are exactly the same. However, the detection efficiency of water is higher, because the equivalent atomic number and density of water are smaller than those of cement solidification, and the self-absorption effect is weaker than that of cement solidification.

[0088] In view of the similarity between water and solidified bodies in the efficiency calibration curve, it is considered theoretically feasible to use the waste liquid barrel model as a substitute for measurement verification when verifying the solidification barrel model. In actual operation, it is not necessary to specifically solidify the residual liquid or waste resin, sample and prepare cement solidified body samples, and perform maintenance operations. Instead, the radioactive waste liquid can be directly measured and verified using this method after being placed in the waste barrel. After confirming that the experimental results meet expectations, the solidification barrel can be used for further verification, which not only saves the time cost brought by solidification and maintenance, but also allows for flexible adjustment of the plan during the experiment.

[0089] 3. Waste liquid barrel experimental verification

[0090] 3.1 Experimental methods

[0091] The verification method adopts the direct measurement method, that is, after sampling the waste stream, the laboratory HPGe spectrometer is used to directly measure the activity concentration information of the waste, which serves as the benchmark value for the experimental verification of this method. The main steps are as follows:

[0092] (1) First, prepare a 200L empty solidification barrel and transfer the waste liquid into the barrel through the sampling system to ensure that the liquid level in the barrel is consistent with the solidification body.

[0093] (2) Use a pipette to draw the waste liquid into a dedicated Marlin cup and use a calibrated laboratory HPGe spectrometer measurement system to directly measure and obtain the radionuclide composition and activity concentration of the waste liquid.

[0094] (3) On-site measurement: Obtain the energy spectrum measurement results of the waste liquid barrel using detectors at different distances.

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

[0096] 3.2 Field measurement

[0097] Carry out environmental background measurement and instrument energy calibration, install the collimator to the front of the detector, and ensure that the detection window of the collimator is aligned with the center of the detector. Place the detector horizontally, with its central axis facing the central axis of the curing barrel, and the two are perpendicular. The central axis of the detector is 42cm from the ground, so that it is at the center height of the contents of the curing barrel and starts measurement.

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

[0099] 3.3 Source term laboratory analysis

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

[0101] The collected energy spectrum data was analyzed using the gamma vision software equipped 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 represents the activity concentration of the nuclide to be measured, V represents the volume of the sample to be measured, t is the effective measurement time, ε nuclide corresponds to the energy efficiency scale, P is the probability of gamma rays being generated when the radioactive nuclide decays (branching ratio), N net Indicates the net count.

[0104] From the experimental source analysis data, it is found that 54 Mn and 58 The content of Co is very small, about 60 1 / 14 and 1 / 25 of Co. 60 Co. 54 Mn and 58 The half-life of Co is 5.28 years, 312 days and 71 days respectively. In actual work, it usually takes 1 to 3 years for the waste liquid to be received, processed, solidified and then transferred out of the warehouse. 54 Mn and 58 The remaining percentage of Co is much less 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] According to the detection efficiency curve calculated by Monte Carlo simulation and the waste liquid barrel energy spectrum data obtained by field measurement, the waste liquid activity concentration measured under different distance conditions and its deviation from the experimental spectrometer measurement results are calculated as shown in Table 2.

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

[0108]

[0109]

[0110] In general, as the distance increases, the deviation between the calculated and measured values ​​of the activity concentration decreases first and then increases slightly. At a distance of 16 cm to 48 cm, the deviation remains in a relatively low range, i.e., -6.65% to 6.27%. At a closer distance of 8 cm, the deviation is the largest, but it does not exceed 15%. The overall model can meet the measurement requirements well, and the calculated results are close to the actual values, providing a reliable basis for the measurement and verification of solidified samples.

[0111] 4. Experimental verification of cured samples

[0112] 4.1 Experimental methods

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

[0114] During the operation of the cement curing line, a barrel of solidified material is randomly selected for sampling and the relevant number is recorded. The sample and the curing barrel are then placed in a constant temperature and humidity environment for curing. The waste barrel after curing is placed in a predetermined measurement position, and the gamma energy spectrum of the barrel is measured using the waste curing barrel measurement system. By obtaining the overall energy spectrum data of the barrel and combining it with the detector efficiency calibration curve generated by simulation, the activity concentration of the curing barrel can be calculated. In order to verify the correctness of the efficiency calibration curve, the simulation calculation results are compared with the activity concentration measured by the curing sampling.

[0115] 4.2 Source term laboratory analysis

[0116] The sample is measured by gamma spectrum through the HPG detector to obtain the spectrum data of the nuclides in the sample. Since the sample is taken out during the solidification process and the physical and chemical properties are basically consistent with the final solidified body, the measured activity concentration can better represent the overall activity level of the solidified body. 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 solid body, 60 Co was taken as the main research object for calculation.

[0117] 4.3 On-site measurement and result analysis

[0118] The activity concentration results obtained by actual measurement and simulation efficiency calculation of the curing barrel are shown in Table 3. At a distance of 8 cm, the maximum deviation is 21.60%. This deviation may be due to the detector entering the nonlinear response region when measuring at close range, especially when facing high-intensity radiation sources such as solidified bodies. This means that the detector may over-respond, resulting in a higher net count rate than expected, and the measured value of the activity concentration is much higher than the calculated value. At a distance of 16 cm, the deviation is reduced to 10.05%. Although the error is still large, it is significantly lower than that at 8 cm, indicating that the response of the detector tends to be stable and the match between the measured and calculated values ​​has improved. At the measurement distances of 24 cm, 32 cm, 40 cm, and 48 cm, the deviations are 3.17%, -2.05%, -5.02%, and -9.13%, respectively, indicating that the mid-distance measurement provides more reliable measurement results overall.

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

[0120]

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

[0122] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. Only the preferred embodiments of the present invention are expressed. The description is more specific and detailed, but it cannot be understood as limiting the scope of the present invention. As long as there is no contradiction in the combination of these technical features, they should be considered as within the scope of this specification.

[0123] It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these modifications and improvements all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A rapid measurement method for radionuclides in waste solidification barrels based on Monte Carlo simulation, characterized in that: The following steps are involved: Step S1: performing Monte Carlo simulation on the waste solidification barrel, the detector and the collimator to obtain a detector efficiency curve; the contents in the waste solidification barrel are uniform; Step S2: verifying the efficiency calibration by using unsolidified radioactive wastewater to calibrate the detector efficiency curve; Step S3: collecting the measurement spectrum of the waste solidification barrel to be measured, and obtaining the count of the corresponding nuclide; Step S4: measuring the activity concentration of the waste solidification barrel to be measured through the corrected detector efficiency curve and the counting of nuclides.

2. According to claim 1, a method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation is characterized in that: When performing Monte Carlo simulation, the detector used is a lanthanum bromide scintillation detector.

3. The method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation according to claim 2 is characterized in that: The lanthanum bromide scintillation detector is a cylinder; an optical glass is arranged at the rear end of the lanthanum bromide scintillation detector, the side is 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 reflection layer is filled between the aluminum shell and the lanthanum bromide scintillation detector, wherein A2 is smaller than A1.

4. The method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation according to claim 3 is characterized by: The lanthanum bromide scintillation detector is placed in a cylindrical shielding sleeve, and the shielding sleeve is made of a tungsten alloy material with a wall thickness of 20 mm.

5. The method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation according to claim 4 is characterized in that: When performing Monte Carlo simulation, the collimating hole extends from the entrance to the inside of the collimator, and is in the shape of a rectangular parallelepiped and a trapezoidal platform respectively.

6. The method for rapid measurement of radionuclides in waste solidification barrels based on Monte Carlo simulation according to claim 1 is characterized in that: When performing Monte Carlo simulation, the energy spectrum data obtained by measuring the actual radiation source using an actual detector is used. Based on the functional relationship between the half-width and energy, the calculated energy spectrum of the Monte Carlo simulation is broadened by fitting.

7. The method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation according to claim 6 is characterized by: The expression of the functional relationship between the half-height width and energy is: Where a, b and c represent Gaussian broadening coefficients, and E represents ray energy.

8. The method for rapid measurement of nuclides in waste solidification barrels based on Monte Carlo simulation according to claim 1 is characterized in that: Set the source distance to 5cm, select 60 Co. 137 The actual measurement is carried out using a Cs standard point source, and the calculated values ​​of the Monte Carlo simulation are verified by the actual measurement data.

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

10. The method for rapid measurement of radionuclides in waste solidification barrels based on Monte Carlo simulation according to claim 1 is characterized in that: During the operation of the cement curing line, a barrel of solidified body is randomly selected for sampling and actual measurement. The calculated value of Monte Carlo simulation is verified by the solidification sampling measurement data.

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