CN116467856A - Method for processing gamma-ray detection data of radioactive waste steel box - Google Patents
Method for processing gamma-ray detection data of radioactive waste steel box Download PDFInfo
- Publication number
- CN116467856A CN116467856A CN202310325108.7A CN202310325108A CN116467856A CN 116467856 A CN116467856 A CN 116467856A CN 202310325108 A CN202310325108 A CN 202310325108A CN 116467856 A CN116467856 A CN 116467856A
- Authority
- CN
- China
- Prior art keywords
- steel box
- detector
- voxel
- waste steel
- model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 76
- 239000010959 steel Substances 0.000 title claims abstract description 76
- 238000001514 detection method Methods 0.000 title claims abstract description 72
- 238000000034 method Methods 0.000 title claims abstract description 46
- 230000005251 gamma ray Effects 0.000 title claims abstract description 27
- 239000002901 radioactive waste Substances 0.000 title claims abstract description 25
- 238000012545 processing Methods 0.000 title claims description 15
- 238000005259 measurement Methods 0.000 claims abstract description 42
- 230000000694 effects Effects 0.000 claims abstract description 36
- 238000002474 experimental method Methods 0.000 claims abstract description 24
- 238000012512 characterization method Methods 0.000 claims abstract description 20
- 238000009826 distribution Methods 0.000 claims abstract description 11
- 230000008569 process Effects 0.000 claims description 16
- 239000000463 material Substances 0.000 claims description 15
- 239000002699 waste material Substances 0.000 claims description 13
- 238000012937 correction Methods 0.000 claims description 11
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims description 10
- 239000011159 matrix material Substances 0.000 claims description 8
- 238000004422 calculation algorithm Methods 0.000 claims description 7
- 239000004698 Polyethylene Substances 0.000 claims description 5
- -1 polyethylene Polymers 0.000 claims description 5
- 229920000573 polyethylene Polymers 0.000 claims description 5
- 239000002245 particle Substances 0.000 claims description 4
- 239000002023 wood Substances 0.000 claims description 4
- 230000008859 change Effects 0.000 claims description 3
- 206010067623 Radiation interaction Diseases 0.000 claims description 2
- 230000002285 radioactive effect Effects 0.000 abstract description 25
- 239000002910 solid waste Substances 0.000 abstract description 21
- 238000004458 analytical method Methods 0.000 abstract description 18
- 238000003672 processing method Methods 0.000 abstract description 5
- 238000000342 Monte Carlo simulation Methods 0.000 abstract description 4
- 238000011109 contamination Methods 0.000 abstract description 2
- 239000000523 sample Substances 0.000 description 10
- 238000010586 diagram Methods 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 6
- 229910052742 iron Inorganic materials 0.000 description 4
- 239000004973 liquid crystal related substance Substances 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 238000001228 spectrum Methods 0.000 description 4
- 238000010276 construction Methods 0.000 description 3
- 239000013078 crystal Substances 0.000 description 3
- 238000013461 design Methods 0.000 description 3
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000002591 computed tomography Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000004381 surface treatment Methods 0.000 description 2
- 239000013598 vector Substances 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- FYYHWMGAXLPEAU-UHFFFAOYSA-N Magnesium Chemical compound [Mg] FYYHWMGAXLPEAU-UHFFFAOYSA-N 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 239000004411 aluminium Substances 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- 230000002238 attenuated effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 239000005304 optical glass Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000003904 radioactive pollution Methods 0.000 description 1
- 238000004055 radioactive waste management Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000005316 response function Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/16—Measuring radiation intensity
- G01T1/20—Measuring radiation intensity with scintillation detectors
- G01T1/202—Measuring radiation intensity with scintillation detectors the detector being a crystal
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/36—Measuring spectral distribution of X-rays or of nuclear radiation spectrometry
- G01T1/362—Measuring spectral distribution of X-rays or of nuclear radiation spectrometry with scintillation detectors
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01T—MEASUREMENT OF NUCLEAR OR X-RADIATION
- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/36—Measuring spectral distribution of X-rays or of nuclear radiation spectrometry
- G01T1/38—Particle discrimination and measurement of relative mass, e.g. by measurement of loss of energy with distance (dE/dx)
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E30/00—Energy generation of nuclear origin
- Y02E30/30—Nuclear fission reactors
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- High Energy & Nuclear Physics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Algebra (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Operations Research (AREA)
- Geometry (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- Evolutionary Computation (AREA)
- Chemical & Material Sciences (AREA)
- Crystallography & Structural Chemistry (AREA)
- Measurement Of Radiation (AREA)
Abstract
The invention relates to a radioactive waste steel box gamma ray detection data processing method, which constructs physical geometry of a detector by using simulation software through a Monte Carlo method and performs detector characterization by combining experiments. And constructing relevant data of the box body, the medium and the environment, calculating the projection of each voxel detector under the conditions of different densities and different nuclide distribution, and obtaining a voxel detection efficiency library. And carrying out activity reconstruction by combining the voxel detection efficiency library, thereby realizing the real-time voxel activity reconstruction work of the steel box in the experiment. The method disclosed by the invention can support the rapid measurement, reconstruction and analysis of the retired steel box before warehouse entry, can analyze the contents of various elements and isotopes in the steel box, provides more accurate data for the final treatment of the steel box, accurately identifies and measures the types and activities of nuclides in the steel box so as to evaluate the contamination degree, and provides necessary data support for the detection and warehouse entry of the low-medium-level radioactive solid waste steel box.
Description
Technical Field
The invention belongs to the field of radioactivity measurement, and particularly relates to a radioactive waste steel box gamma-ray detection data processing method.
Background
With the rapid development of nuclear industry, radioactive wastes are continuously generated and accumulated, so that a great pressure is generated for industrial production and facility operation, and various radioactive wastes are needed to be safely and timely treated properly to achieve the aim of safety development. In laws and regulations such as "radioactive pollution control method" and "radioactive waste management regulation", it is clearly specified that the disposal of general medium-low radioactive solid waste is performed by performing a near-surface treatment after a process transformation process such as sorting, compression, and preparation, and in "near-surface treatment regulation of low-level and horizontal radioactive solid waste", it is clearly required that the waste disposal needs to have a record of the whole process. Therefore, before radioactive waste is disposed of, it is required to accurately identify and measure the species and activity contained therein to evaluate and make corresponding measures for disposal.
The radioactive solid waste comes mainly from 3 aspects of post-treatment plants, nuclear power plant operation and nuclear facility decommissioning. These radionuclide wastes are often contained in special barrels or boxes where radionuclide class, distribution and medium class recordings are not sufficiently detailed and are generally non-uniform so that analysis using conventional sampling methods is difficult. The nondestructive analysis method (NDA) can be used for measuring and analyzing the whole nuclear waste, and compared with the destructive analysis method, the nondestructive analysis method can shorten the analysis time and can not generate secondary radioactive waste, and is an effective analysis method, wherein gamma energy spectrum measurement, analysis and counting are most commonly used.
The early detection method for the radioactive solid steel box design mainly adopts methods of integral measurement, step-by-step measurement of a neutron flat panel detector, correction by using overlapping volume proportion after gamma ray detection, and the like, but the methods have certain limitations, such as smaller measurable box type, incapability of containing more hydrogen organic matters in the interior, larger measurement result error, and the like. The gamma-ray CT detection device obtains a radioactivity distribution image through scanning measurement and radioactivity reconstruction by utilizing the principle of emission type computer tomography (Emission Computed Tomography, ECT), has the advantages of high measurement accuracy, no dependence on the type of internal medium, less limitation on the shape of measurable wastes and the like, and is widely used for detecting various wastes at present. The Monte Carlo (MC) method has the advantages of time and cost saving, simplicity, high accuracy and the like, adopts MC analog calculation to establish a physical model of the radioactive solid waste steel box detection system by combining CT principle and gamma ray energy spectrum measurement, and can calculate voxel dividing efficiency of the radioactive solid waste steel box under different medium types, densities and different gamma ray energy conditions. The length, width and height of a common FA-IV radioactive solid waste steel box are respectively close to 1.5m, and are limited by the influence of transmissivity, so that the conventional TCT scheme cannot be adopted for inspection analysis and correction.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a radioactive waste steel box gamma ray detection data processing method, which combines the traditional CT principle, MC simulation and discretization measurement analysis method, firstly adopts the Monte Carlo method to construct a measurement system model, generates a voxel detection efficiency library for a measurement object as a priori parameter, combines elements in the voxel detection efficiency library to generate a calculation matrix, and then completes matrix calculation according to an iterative algorithm to finally complete data reconstruction and analysis of the nuclide activity of the steel box, can complete voxel discrete measurement and analysis for the steel box with difficult measurement, is beneficial to realizing rationalization and precision of measurement of the radioactive solid waste steel box, directly acquires the data in the voxel efficiency library for calculation after the data is measured, greatly shortens the reconstruction time, does not depend on other software and networks, and directly completes report output on site.
In order to achieve the above purpose, the invention adopts the technical scheme that: a method for processing gamma-ray detection data of a radioactive waste steel box, the method comprising the steps of:
s1, a detector model is established according to a detector structure, and detector characterization is carried out by combining experimental results;
s2, building an object model to be detected and a physical process model according to the structure of the object to be detected and the characteristics of a measurement system, and obtaining a voxel detection efficiency library;
and S3, carrying out activity reconstruction by combining the voxel detection efficiency library, so as to carry out voxel activity reconstruction of the steel box in real time in an experiment.
Further, in step S1, a detector model is built by using monte carlo simulation software according to the detector structure on the NaI detector drawing.
In step S1, a standard point source is used for experiment, and the detector is characterized by an experiment characterization platform and combining with an experiment result.
Further, in step S1, the deviation of the experimental value and the calculated value under different radii is measured by using the root mean square error RMSE, the relationship between the radius of the sensitive volume and the root mean square error is obtained by using data fitting, and the value of the symmetry axis of the curve is selected as the detector characterization result R.
Further, in the step S1, during the experiment, the NaI detector is used for measuring the actual waste steel box, the vertical distance between the detector and the surface of the steel box is determined according to the dead time, the collimation depth, the opening shape and the size of the collimator are set, the current voxel with the detection range of the detector and the projection graph on the surface of the steel box being opposite is the surface closest to the detector, the influence of the background and other voxels on the measurement result is smaller than a preset value, and the collimation thickness of the collimator is determined according to the mechanical bearing of the system.
Further, in step S2, the object model to be measured is a waste steel box model and a collimator model, and the physical process model includes a medium model, an environment model and a radiation interaction model.
Further, in step S2, the voxel detection efficiency library is obtained by calculating the projections of each voxel detector under the conditions of different nuclides, different densities and different nuclide distributions.
Further, step S2 comprises the sub-steps of:
s21: establishing a steel box model, filling specific materials into the current measurement voxels, performing step progression on the density in a certain range, selecting nuclides and proper energy peaks thereof, and obtaining the efficiency of the detector on the current voxels under the nuclide energy when each density of the specific materials is obtained;
s22: filling the same specific material for the left voxel and the current measured voxel, synchronizing density change, selecting the same nuclide and the proper energy peak value thereof as in the step S21, and placing the nuclide and the proper energy peak value thereof on the left voxel so as to obtain the efficiency of the detector for the left and right adjacent voxels under the energy of the nuclide when each density of the specific material is obtained;
s23: and obtaining the efficiency of the detector on the upper and lower adjacent voxels under the nuclide energy by using the same method, and sorting the calculated efficiency value into a voxel detection efficiency library.
Further, in step S3, an ART algorithm is used to perform iterative solution on the constructed matrix equation of the inter-voxel crosstalk correction equation, so as to perform activity reconstruction.
Further, the specific material filled in step S21 is any one of wood chips, iron chips, and polyethylene particles.
The beneficial technical effects of the invention are as follows: model construction of geometric, material and physical processes of the whole measurement system is realized, a voxel detection efficiency library is generated, and an inter-voxel crosstalk correction equation is formed through the voxel detection efficiency library and experimental data, so that inter-voxel crosstalk correction in the detection process is completed; the method can realize off-line reconstruction and analysis of the waste steel box, realize synchronization of experimental reconstruction and analysis, greatly improve the measurement and analysis efficiency of the engineering site steel box, and can also be applied to the nuclide identification and activity measurement of other low-level horizontal radioactive solid waste containers.
Drawings
Fig. 1 is a schematic view of a monte carlo CT projection according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a NaI detector monte carlo simulation in accordance with an embodiment of the present invention;
FIG. 3 is a schematic view of a gamma measurement device for a FA-IV type solid waste steel tank according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a probe characterization process according to an embodiment of the present invention;
FIG. 5 is an overall schematic diagram of a characterization probe system according to an embodiment of the invention;
FIG. 6 is a schematic diagram of a detector and collimator model according to an embodiment of the invention;
FIG. 7 is a diagram illustrating a collimator detection effect according to a first embodiment of the present invention;
FIG. 8 is a schematic flow chart of a reconstruction algorithm according to a first embodiment of the present invention;
FIG. 9 is a schematic diagram of placement of an experimental medium according to a second embodiment of the present invention;
fig. 10 is a schematic diagram of uniform voxel segmentation according to a second embodiment of the present invention;
fig. 11 is a top view of a reconstructed single voxel for each location of 32 point sources as shown in embodiment two of the present invention.
Detailed Description
The invention is further described below with reference to the drawings and detailed description.
Example 1
The embodiment of the invention provides a method for processing gamma-ray detection data of a radioactive waste steel box, which comprises the following steps:
s1, a detector model is built according to the detector structure, and detector characterization is conducted by combining experimental results.
As shown in fig. 1, using monte carlo simulation software, a detector model as shown in fig. 2 is built according to the detector structure on the NaI detector drawing.
As shown in FIG. 3, the standard point source is used for experiment, the detector is characterized by an experiment characterization platform and an experiment result, and the error of the characterization result is less than or equal to 5%.
As shown in FIG. 4, in the characterization process, the standard point source is utilized for parameter adjustmentAnd (7) integrating and confirming. The standard point source used at this time is 60 Co、 137 Cs has a nominal activity of 5.43×10 4 Bq (2022, 8, 10 days), 7.65X10 3 Bq (2022, 8, 10 days), the source probe distance is respectively measured for three times when 5cm, 10 cm and 15cm, and the energy spectrum is obtained and recorded by adopting special energy spectrum analysis software. Meanwhile, MC software is used for establishing a detector model, the radius of a cylinder of a NaI detector sensitivity body is respectively 2cm, 2.3cm, 2.5cm, 2.6cm, 2.7cm, 2.8cm and 3cm, the detection efficiency under the same conditions as the characterization experiment is simulated and calculated, the deviation of experimental values and calculated values under different radiuses is measured by using root mean square error RMSE, a relation between the sensitive volume radius and the root mean square error is obtained by using binomial fitting, the symmetry axis of the curve is R= 2.48072cm, the error between the simulated value and the experimental value is the smallest at the moment, and the obtained detector parameter value is shown in the table 1.
RMSE＝p 1 ×R 2 +p 2 ×R+p 3
p 1 ＝0.005834，
p 2 ＝-0.028945，
p 3 ＝0.036230，
R 2 ＝0.942548
TABLE 1 simulation parameters for NaI detector MC
| Parameters (parameters) | MC simulation parameters/mm |
| Radius of crystal | 24.8072 |
| Length of crystal | 49 |
| Thickness of aluminium shell | 1.5 |
| Thickness of magnesium powder | 1 |
| Optical glass thickness | 4 |
The characterization results are shown in tables 2-4.
Table 2 6 NaI probe point source characterization results
TABLE 3 actual and simulated values of efficiency
TABLE 4 Crystal radius and RMSE
The six detectors for characterization are respectively 2E-HD, 2F-HD, 30-HD, 31-HD, 32-HD and 33-HD, after the model is adjusted, the relative deviation between the measurement results of the six detectors and the simulation result is less than 5%, the modeling requirement is met, and the characterization results of the detectors are shown in figure 5.
As shown in fig. 6, the actual waste steel bin was measured using a NaI detector, and the vertical distance of the detector from the steel bin surface was determined based on the dead time. And selecting proper collimation depth, opening shape and size, so that the current voxel with the detection range of the detector opposite to the projection graph on the surface of the steel box is the surface closest to the detector, the background and other voxels have the smallest influence on the measurement result, and determining the collimation thickness according to the mechanical bearing of the system to obtain the collimator detector effect schematic diagram shown in fig. 7.
S2, building an object to be detected and a physical process model according to the structure of the object to be detected and the characteristics of a measurement system, and obtaining a voxel detection efficiency library.
After the characterization of the geometric parameters of the detector is completed, a waste steel box model, a collimator model and a measurement geometric model are established, wherein the measurement geometric model comprises a medium model, an environment model and a ray interaction model.
And calculating the projections of each voxel detector under the conditions of different nuclides, different densities and different nuclide distribution to obtain a voxel detection efficiency library.
And (3) establishing a steel box model, filling specific materials into the current measurement voxels, performing step progression on the density in a certain range, and selecting nuclides and proper energy peaks thereof. The detector's efficiency for the current voxel at the nuclide energy when the densities of the particular material are obtained. And (3) filling the same specific material for the left voxel and the current measured voxel, and selecting the same nuclide and the proper energy peak value thereof in the last step to be placed in the left voxel. The detector's efficiency for left and right adjacent voxels at the nuclide energy when the densities of the particular material are obtained. And obtaining the efficiency of the detector on the upper and lower adjacent voxels under the nuclide energy by using the same method, and sorting the calculated efficiency value into a voxel detection efficiency library.
Most radioactive solid wastes release gamma rays, and the nuclide types and activities in the gamma rays can be qualitatively and quantitatively analyzed through energy and intensity measurement of the gamma rays and nuclide library comparison and detection efficiency scale conversion, so that the purpose of waste identification is achieved. The principle of the gamma ray detection data processing method of the low-medium level radioactive solid waste steel box is based on the traditional CT theory. Assuming that the detector measures the intensity of a characteristic gamma ray at a certain measuring position of a certain object as I e Can be regarded as the inside of the object to be measuredThe radioactivity f at this energy is on a straight line perpendicular to the detector end face, and the attenuated integral projection g is expressed as formula (1).
Where E is the energy of the radiation, the origin of the coordinate system xOy is defined at the center of the rotational scan of the detector, l= (x, y), θ is the rotation angle of the detector, and t is the distance between the center line of the detector and the origin.
The total attenuation a of the radiation emitted by point (x, y) to the detector can be expressed as equation (2).
Wherein, (xd, yd) is the center coordinate of the front end face of the detector, and mu is the linear attenuation coefficient of the measured substance.
In the detection of the radioactive waste bin, characteristic gamma rays are collimated and then are input into a detector, and the detector and a detector object cannot be regarded as point sources to carry out simplified treatment due to the tubular structure design of the collimator and the detection distance limitation. Meanwhile, in order to realize the full coverage of the surface of the radioactive solid waste steel box, the detector is designed to have wider visual field. On the other hand, the condition of the medium in the steel box is complex, the radioactive source is regarded as a point source to bring larger error, the radioactive source is treated as a body source, and the efficiency response of the detector has obvious difference for different body source positions. Therefore, the traditional delta response function and line integral projection theory are not applicable any more, and according to the characteristics and structural parameters of radioactive waste detection, the system design parameters, performance indexes and the like of the gamma-ray CT have certain differences from gamma-ray CT applied to other fields such as medicine and the like, and the gamma-ray CT needs to be corrected by considering a space angle. Thus, parameters are added to the algorithm to correct the spatial angle, where the radioactivity projection obtained by the detector can be represented by the following equation (3), where Ω (r, θ, t) represents the spatial angle correction parameter.
Wherein, the liquid crystal display device comprises a liquid crystal display device,
r＝(x,y,z)#(4)
the attenuation a can be expressed as equation (5),
omega is the solid angle of point (x, y, z) to the detector. Epsilon is the detection efficiency and is related to the geometry, physical properties and the relative position of the point to the detector, so that geometrical corrections are usually required in the reconstruction.
The measured radioactive intensity distribution f and its CT projection g are discretized into vectors f, g, respectively, and the above projection relationship can be expressed as a matrix form (6).
g＝Hf#(6)
Wherein H is a system matrix, its elements
Where i, j are the element labels of the image and projection vectors f, g, respectively. Considering that the distance between the measured object and the detector is relatively far, the attenuation term a does not change significantly in the voxel space Vi, so h ij Can be approximately expressed as
h i，j ＝ε i，j a i，j #(8)
Wherein, the liquid crystal display device comprises a liquid crystal display device,
and (3) performing a step-by-step scanning process on the radioactive solid waste steel box by using a detector, performing discretization processing on the formula (3) to obtain a formula (10), and deforming the formula (10) to obtain a voxel-to-voxel crosstalk correction equation matrix (11).
D(E)＝F(E)·S(E)#(10)
Wherein F (E) is detection efficiency, which comprises intrinsic detection efficiency, geometric detection efficiency and sample self-absorption of the detector, D (E) is detector counting rate of gamma rays emitted by the bulk source sample, and S (E) is radionuclide activity at corresponding positions.
As shown in fig. 8, in this embodiment, the radioactivity of the steel box is assumed to be a special "image", the steel box is artificially divided into 2×5×3 voxels, and the characteristic ray count rate obtained by experimental measurement is taken as "image" raw data in combination with the voxel detection efficiency library in step S3, and the activity to be solved is taken as a target image. And calling corresponding data to construct a detection efficiency equation E after the measurement is completed.
Wherein e ij The probability density value of the j-th detector sampling point at the i-th voxel activity is represented by the above example, where N is 30 in this embodiment, and represents a total of 30 voxel spaces, and M is the number of detectors. The voxel detection efficiency library establishment process considers the probability of all voxel densities and nuclides contained as much as possible according to the actual steel box condition to be detected. The counting rate of the measuring result of the detector in one complete analysis process of the measuring system is marked as C= { C i I=1, 2,3, …, N }, the initial value of the nuclide activity is noted as I i ＝I i (0) ,(i＝1,2,3,…,N)。
S3, carrying out activity reconstruction by combining the voxel detection efficiency library, thereby realizing real-time voxel activity reconstruction work of the steel box in an experiment.
When the activity reconstruction is carried out, the constructed inter-voxel crosstalk correction equation matrix is needed to be solved, an ART algorithm is used for carrying out iterative solution on the equation, the method is suitable for image reconstruction of a discrete-discrete model, and is also called a Kaczmarz method, the main idea of the algorithm is to endow an initial value to a reconstructed image, projection data is obtained according to forward projection, then the actually measured projection data and estimated data are corrected, the corrected result is back projected to update the image, and the reconstructed image can be obtained after repeated iteration until the iteration termination condition is met.
The iteration equation is as follows:
and the iterative process essentially comprises the steps of correcting a calculation result by using the difference between the actually measured projection value and the estimated projection value, so as to perform optimal estimation of each voxel activity, and finally providing activity estimated values of all voxels to be reconstructed, thereby realizing quantitative analysis on nuclide distribution in the whole radioactive solid waste steel box.
When the above example is accepted and a steel box model is established, discretization treatment is carried out on the radioactive solid waste steel box, and the radioactive solid waste steel box is divided into 2X 5X 3 voxels in total, so that the requirement of spatial resolution of radioactive hot spots is met. The calculation analysis is performed for the contribution system of the opposite voxels and the adjacent voxels to the current nuclide detection efficiency, and the result is shown in table 5.
TABLE 5 critical values for impact on voxel crosstalk (scrap iron as medium)
As can be seen from the data in the table, when the medium density reached 0.78g/cm 3 When the detection efficiency of the 661keV characteristic gamma rays to the voxels is less than 1%; when the density of the medium reaches 0.81g/cm 3 In the time of this, the process is carried out, 60 the influence of Co-generated characteristic gamma rays on the detection efficiency of voxels is less than 1%, and the density of actual solid waste steel box media generated by retirement is about 1-2 g/cm in combination with reality 3 Thus, in this embodiment, the effect of the object voxel on the current voxel detection efficiency is negligible in doing the current voxel detection efficiency synthesis, mainly interfering with voxels from its top, bottom, left and right neighbors. Upper part,The results of contributions of the lower, left and right adjacent voxels to the current voxel detection efficiency are shown in table 6.
TABLE 6 voxel detection efficiency at other locations and current layer duty cycle
Example two
In this example, for the FA-VI steel boxes used in the 101 pile work, the filling sample selected was wood dust (sample density 0.14 g.cm -3 ) Polyethylene particles (sample density 0.55g cm) -3 ) Scrap iron (sample density 0.11g cm) -3 ) Because the medium density used by the limitation of the experimental conditions is smaller than the actual steel box medium level, when the experiment is carried out, the construction experiment is carried out by using the current voxel and the upper, lower, left and right adjacent voxels, and the construction schematic diagram is shown in fig. 9. Experiment using standard point sources 137 Cs, activity 1.297×10 7 (2022, 9 and 13 days), 137 the single-point measurement time of the Cs source is respectively set to be 200s, 300s and 300s, so that the counting is enough, and the spectrum resolution result is accurate.
During the experiment, since the basic assumption of steel box measurement is that the density distribution and activity distribution of each voxel are uniform, 4×8×1 microcubes of each voxel are seen, and 1 source uniformly distributed in the voxels is approximately seen as 32 point sources uniformly distributed in the center of 4×8×1 microcubes as shown in fig. 10. When the count rate of each point source is denoted as ci, the count rate of the entire voxel is denoted as the following equation (14), and the activity reconstruction of the voxel is completed.
The relative deviation of the measurement results is expressed as formula (15):
the measurement results are shown in the following table 7 after being synthesized, and the measurement results are shown in fig. 11.
Table 7 steel box experimental results
| Media name | Density of medium/g.cm -3 | Reconstructing activity results/Bq | Relative deviation/% |
| Sawdust | 0.14 | 1.44E+07 | 11.03 |
| Polyethylene | 0.55 | 1.47E+07 | 13.34 |
| Scrap iron | 0.11 | 1.36E+07 | 4.86 |
After model establishment, initializing a voxel detection efficiency library and device parameter configuration, completing the efficiency correction and compensation of solid waste steel box measurement voxels, and performing FA-IV radioactive solid waste steel box detection platformVerification experiments of different media (wood chips, scrap iron and polyethylene particles) are carried out, and the results show that the relative deviation between the surface activity reconstruction result of radioactive waste and the calibration activity of a radioactive source is less than 30%, the measurement result meets engineering requirements, and the detection configuration realizes that the surface hotspot resolution is better than that of the radioactive sourceTechnical requirements of (2).
According to the embodiment, the gamma-ray detection data processing method for the radioactive waste steel box disclosed by the invention is characterized by constructing the physical geometry of the detector by using simulation software through a Monte Carlo method and carrying out detector characterization by combining experiments. And constructing relevant data of the box body, the medium and the environment, calculating the projection of each voxel detector under the conditions of different densities and different nuclide distribution, and obtaining a voxel detection efficiency library. And carrying out activity reconstruction by combining the voxel detection efficiency library, thereby realizing the real-time voxel activity reconstruction work of the steel box in the experiment. The method disclosed by the invention can support the rapid measurement, reconstruction and analysis of the retired steel box before warehouse entry, can analyze the contents of various elements and isotopes in the steel box, provides more accurate data for the final treatment of the steel box, accurately identifies and measures the types and activities of nuclides in the steel box so as to evaluate the contamination degree, and provides necessary data support for the detection and warehouse entry of the low-medium-level radioactive solid waste steel box.
The method according to the present invention is not limited to the examples described in the specific embodiments, and those skilled in the art can obtain other embodiments according to the technical solution of the present invention, which also belong to the technical innovation scope of the present invention.
Claims (10)
1. A method for processing gamma-ray detection data of a radioactive waste steel box, the method comprising the steps of:
s1, a detector model is established according to a detector structure, and detector characterization is carried out by combining experimental results;
s2, building an object model to be detected and a physical process model according to the structure of the object to be detected and the characteristics of a measurement system, and obtaining a voxel detection efficiency library;
and S3, carrying out activity reconstruction by combining the voxel detection efficiency library, so as to carry out voxel activity reconstruction of the steel box in real time in an experiment.
2. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 1, wherein: in the step S1, a detector model is built by using Monte Carlo simulation software according to the detector structure on the drawing of the NaI detector.
3. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 2, wherein: in the step S1, a standard point source is used for experiment, and the detector is characterized by combining an experiment result through an experiment characterization platform.
4. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 3, wherein: in the step S1, the root mean square error RMSE is used for measuring the deviation of experimental values and calculated values under different radiuses, the relation between the radius of the sensitive volume and the root mean square error is obtained by using data fitting, and the value of the symmetry axis of the curve is selected as a detector characterization result R.
5. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 4, wherein: in the step S1, an NaI detector is used for measuring an actual waste steel box in an experiment, the vertical distance between the detector and the surface of the steel box is determined according to the dead time, the collimation depth, the opening shape and the size of a collimator are set, the current voxel with the detection range of the detector and the projection graph of the surface of the steel box being opposite is the surface of the detector, the influence of the background and other voxels on the measurement result is smaller than a preset value, and the collimation thickness of the collimator is determined according to the mechanical bearing of the system.
6. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 5, wherein: in step S2, the object model to be measured is a waste steel box model and a collimator model, and the physical process model includes a medium model, an environment model and a radiation interaction model.
7. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 6, wherein: in step S2, the voxel detection efficiency library is obtained by calculating the projections of each voxel detector under the conditions of different nuclides, different densities and different nuclide distribution.
8. A method of processing radioactive waste steel box gamma-ray detection data as set forth in claim 7, wherein step S2 comprises the sub-steps of:
s21: establishing a steel box model, filling specific materials into the current measurement voxels, performing step progression on the density in a certain range, selecting nuclides and proper energy peaks thereof, and obtaining the efficiency of the detector on the current voxels under the nuclide energy when each density of the specific materials is obtained;
s22: filling the same specific material for the left voxel and the current measured voxel, synchronizing density change, selecting the same nuclide and the proper energy peak value thereof as in the step S21, and placing the nuclide and the proper energy peak value thereof on the left voxel so as to obtain the efficiency of the detector for the left and right adjacent voxels under the energy of the nuclide when each density of the specific material is obtained;
s23: and obtaining the efficiency of the detector on the upper and lower adjacent voxels under the nuclide energy by using the same method, and sorting the calculated efficiency value into a voxel detection efficiency library.
9. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 8, wherein: and in the step S3, iterative solution is carried out on the constructed inter-voxel crosstalk correction equation matrix equation by using an ART algorithm so as to carry out activity reconstruction.
10. A method for processing gamma-ray detection data of a radioactive waste steel box according to claim 8, wherein: the specific material filled in step S21 is any one of wood chips, iron chips and polyethylene particles.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310325108.7A CN116467856A (en) | 2023-03-29 | 2023-03-29 | Method for processing gamma-ray detection data of radioactive waste steel box |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310325108.7A CN116467856A (en) | 2023-03-29 | 2023-03-29 | Method for processing gamma-ray detection data of radioactive waste steel box |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116467856A true CN116467856A (en) | 2023-07-21 |
Family
ID=87178137
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310325108.7A Pending CN116467856A (en) | 2023-03-29 | 2023-03-29 | Method for processing gamma-ray detection data of radioactive waste steel box |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116467856A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116736361A (en) * | 2023-05-16 | 2023-09-12 | 中国工程物理研究院材料研究所 | Method for correcting non-uniformity of space detection efficiency of radioactive waste measurement system |
| CN116858214A (en) * | 2023-09-04 | 2023-10-10 | 中国医学科学院放射医学研究所 | Radionuclide distribution drawing system and drawing method |
-
2023
- 2023-03-29 CN CN202310325108.7A patent/CN116467856A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116736361A (en) * | 2023-05-16 | 2023-09-12 | 中国工程物理研究院材料研究所 | Method for correcting non-uniformity of space detection efficiency of radioactive waste measurement system |
| CN116858214A (en) * | 2023-09-04 | 2023-10-10 | 中国医学科学院放射医学研究所 | Radionuclide distribution drawing system and drawing method |
| CN116858214B (en) * | 2023-09-04 | 2024-04-26 | 中国医学科学院放射医学研究所 | Radionuclide distribution drawing system and drawing method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116467856A (en) | Method for processing gamma-ray detection data of radioactive waste steel box | |
| CN109541675B (en) | Chromatography gamma scanning voxel efficiency calibration method based on point source space efficiency function | |
| CN103308534B (en) | Chromatographic gamma scanning measurement method | |
| Svärd et al. | Applicability of a set of tomographic reconstruction algorithms for quantitative SPECT on irradiated nuclear fuel assemblies | |
| CN111158037B (en) | Nuclear facility solid waste package radioactivity evaluation method and system | |
| Biard | Quantitative analysis of the fission product distribution in a damaged fuel assembly using gamma-spectrometry and computed tomography for the Phébus FPT3 test | |
| Agarwal et al. | Algebraic reconstruction technique combined with Monte Carlo method for weight matrix calculation in gamma ray transmission tomography | |
| Krings et al. | Reconstruction of the isotope activity content of heterogeneous nuclear waste drums | |
| JP2015219046A (en) | Radioactive waste radioactivity measuring method and radioactive waste radioactivity measuring device | |
| CN111180018B (en) | Nuclear facility solid waste package radioactivity evaluation method and system | |
| Mauring et al. | InSiCal–A tool for calculating calibration factors and activity concentrations in in situ gamma spectrometry | |
| KR102394944B1 (en) | Apparatus for measuring and amending activity concentration density of radioactive material and operation calibration methode thereof | |
| KR102437787B1 (en) | Shield inspection equipment of hot cell shield by using Co-60 source | |
| CN113552608B (en) | SGS efficiency scale function model, construction method, scale method and application | |
| Holcombe et al. | Determination of the rod-wise fission gas release fraction in a complete fuel assembly using non-destructive gamma emission tomography | |
| Chen et al. | Research of γ-ray 3D scanning detection and analysis system | |
| CN112558135B (en) | Nuclear facility waste bag radioactivity characteristic detection system and method | |
| Nakazawa et al. | The Efficiency Calibration of Non-Destructive Gamma Assay Systems Using Semi-Analytical Mathematical Approaches-10497 | |
| Li et al. | Study of γ-Ray Spectrum Measurement Analysis Algorithm of Radioactive Solid Waste Steel Boxes | |
| Beddingfield et al. | Distributed source term analysis, a new approach to nuclear material inventory verification | |
| Han et al. | Influence of different path length computation models and iterative reconstruction algorithms on the quality of transmission reconstruction in Tomographic Gamma Scanning | |
| JP2635860B2 (en) | Radioactivity evaluation method for solidified radioactive waste | |
| CN115267873B (en) | Method, system, terminal and medium for measuring and analyzing deposition source item of reactor | |
| Bronson et al. | The application of mathematical modeling for commercial nuclear instrument design, development, and calibration | |
| JP2018189551A (en) | Waste measurement device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |