Isotope abundance determination method, program product, electronic equipment and storage medium

Abstract

The invention discloses an isotope abundance determination method, a program product, electronic equipment and a storage medium. The isotope abundance determination method comprises the following steps: acquiring energy spectrum data of rays emitted by a to-be-detected sample and collected by a nuclear radiation detector; the set elements in the to-be-detected sample comprise a first isotope and a second isotope; based on first energy at a characteristic peak of a first isotope and second energy at a characteristic peak of a second isotope in the energy spectrum data, determining first relative detection efficiency at the first energy and second relative detection efficiency at the second energy by using a relative detection efficiency curve model; the relative detection efficiency curve model comprises a first part and a second part, the first part represents an incidence relation between a reaction cross section of interaction of rays and the nuclear radiation detector and relative detection efficiency, and the second part is a power series expansion formula of a relative detection efficiency curve; determining the atomic number ratio of the first isotope to the second isotope based on the first relative detection efficiency and the second relative detection efficiency; and determining the abundance of the isotope in the sample to be detected according to the atomic number ratio.

Description

Technical Field

[0001] The present invention relates to the technical field of radioactive substance measurement, and in particular, to a method for determining isotope abundance, a program product, an electronic device, and a storage medium. Background Art

[0002] The γ-ray spectrometry analysis method based on the relative detection efficiency technology, also known as the relative detection efficiency method, can directly collect data on the γ-ray spectrum of a sample, establish a relative detection efficiency curve model corresponding to the measurement conditions, and then accurately calculate the isotope abundance in the sample.

[0003] The establishment of the relative detection efficiency curve model is the technical core of the relative detection efficiency method. In the process of analyzing the isotope abundance of nuclear materials, the accuracy of the relative detection efficiency curve expression will directly affect the calculation of the relative efficiency between different characteristic peaks, and thus affect the abundance analysis result. The traditional relative detection efficiency curve model is usually an empirical model that describes the shape of the relative efficiency curve using forms such as power functions and logarithmic power functions. The disadvantage is that the physical meaning of the parameters in the model cannot be explained, and the analysis accuracy and reliability of isotope abundance information cannot be known. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method for determining isotope abundance, a program product, an electronic device, and a storage medium, aiming to improve the accuracy and reliability of the analysis process of isotope abundance information.

[0005] The technical solution of the embodiments of the present invention is implemented as follows:

[0006] On the one hand, embodiments of the present invention provide a method for determining isotope abundance, the method comprising:

[0007] Obtaining energy spectrum data of rays emitted by a sample to be measured collected by a nuclear radiation detector; the set elements in the sample to be measured include a first isotope and a second isotope;

[0008] Based on a first energy at a characteristic peak of the first isotope and a second energy at a characteristic peak of the second isotope in the energy spectrum data, determining a first relative detection efficiency at the first energy and a second relative detection efficiency at the second energy by using a relative detection efficiency curve model; the relative detection efficiency curve model includes a first part and a second part, the first part characterizing the correlation between the reaction cross-section of the interaction between rays and the nuclear radiation detector and the relative detection efficiency, and the second part being a power series expansion formula of the relative detection efficiency curve;

[0009] Based on the first relative detection efficiency and the second relative detection efficiency, determining the atomic number ratio of the first isotope and the second isotope;

[0010] Determine the abundances of the isotopes in the sample to be measured according to the ratio of the number of atoms.

[0011] In the above solution, before determining the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy by using the relative detection efficiency curve model based on the first energy of the ray energy peak emitted by the first isotope and the second energy of the ray energy peak emitted by the second isotope in the energy spectrum data, the method further includes:

[0012] Determine the net peak area of each characteristic peak in the energy spectrum data;

[0013] Determine the model parameters of the relative detection efficiency curve model based on the ratio of the net peak area of each characteristic peak to the corresponding branching ratio.

[0014] In the above solution, the determining the net peak area of each characteristic peak in the energy spectrum data includes:

[0015] Determine the background area of each characteristic peak;

[0016] Subtract the background area from the total area of each characteristic peak to obtain the net peak area of each characteristic peak.

[0017] In the above solution, the determining the ratio of the number of atoms of the first isotope and the second isotope based on the first relative detection efficiency and the second relative detection efficiency includes:

[0018] Determine the ratio of the number of atoms of the first isotope and the second isotope according to the net peak area of the characteristic peak corresponding to the first energy, the net peak area of the characteristic peak corresponding to the second energy, the branching ratio of the characteristic peak corresponding to the first energy, the branching ratio of the characteristic peak corresponding to the second energy, the first relative detection efficiency and the second relative detection efficiency.

[0019] In the above solution, the determining the abundances of the isotopes in the sample to be measured according to the ratio of the number of atoms includes:

[0020] Determine the abundance of the first isotope based on the ratio of the number of atoms, the mass number of the first isotope and the mass number of the second isotope.

[0021] In the above solution, the determining the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy by using the relative detection efficiency curve model based on the first energy at the characteristic peak of the first isotope and the second energy at the characteristic peak of the second isotope in the energy spectrum data includes:

[0022] Based on the first energy at the first characteristic peak of the first isotope, determine the first relative detection efficiency at the first energy through the relative detection efficiency curve model;

[0023] Based on the second energy at the second characteristic peak of the second isotope, determine the second relative detection efficiency at the second energy through the relative detection efficiency curve model; the first characteristic peak and the second characteristic peak are preset characteristic peaks.

[0024] In the above solution, the sample to be measured is a uranium sample, the first isotope is uranium 235, and the second isotope is uranium 238.

[0025] On the other hand, an embodiment of the present application further provides a computer program product, including a computer program, which when executed by a processor, implements the steps of the above isotope abundance determination method.

[0026] On the other hand, an embodiment of the present invention provides an electronic device, including a processor and a memory, the processor and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the steps of the isotope abundance determination method provided in the first aspect of the embodiment of the present invention.

[0027] On the other hand, an embodiment of the present invention provides a computer-readable storage medium, including: the computer-readable storage medium stores a computer program. The computer program, when executed by a processor, implements the steps of the isotope abundance determination method provided in the first aspect of the embodiment of the present invention.

[0028] In an embodiment of the present invention, energy spectrum data of rays emitted by a sample to be measured collected by a nuclear radiation detector is obtained; the set elements in the sample to be measured include a first isotope and a second isotope. Based on a first energy at a characteristic peak of the first isotope and a second energy at a characteristic peak of the second isotope in the energy spectrum data, a first relative detection efficiency at the first energy and a second relative detection efficiency at the second energy are determined by using a relative detection efficiency curve model. The relative detection efficiency curve model includes a first part and a second part. The first part characterizes the correlation between the reaction cross-section of the interaction between the rays and the nuclear radiation detector and the relative detection efficiency, and the second part is a power series expansion formula of the relative detection efficiency curve. Based on the first relative detection efficiency and the second relative detection efficiency, the atomic number ratio of the first isotope and the second isotope is determined; according to the atomic number ratio, the abundances of the isotopes in the sample to be measured are determined. In an embodiment of the present invention, by using a relative detection efficiency curve model established by combining a typical empirical model of a detector efficiency curve with a microscopic cross-section analytical formula of the interaction between rays and matter, accurate calibration of the relative efficiency curve is realized, and the problems that the physical meaning of the parameters in the empirical model cannot be explained and the dependence on information such as the sample form and measurement conditions in the physical analytical formula are solved. This method can be used for analyzing the isotope abundances in nuclear materials, which helps to improve the accuracy and reliability of isotope abundance analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 FIG. is a schematic flowchart of an implementation of a method for determining isotope abundances provided by an embodiment of the present invention;

[0030] Figure 2 FIG. is a schematic diagram of a typical shape of a relative detection efficiency curve model provided by an embodiment of the present invention;

[0031] Figure 3 FIG. is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0033] Isotopes refer to the same element with the same number of protons but different numbers of neutrons in the atomic nucleus. They have the same chemical properties but different physical properties. Isotope relative abundance refers to the relative content of various isotopes of a certain element existing in nature.

[0034] International nuclear safeguards, also known as nuclear safeguards, refer to the international verification mechanism established and implemented by the International Atomic Energy Agency (IAEA) as authorized by international treaties. It is a very important part of the international nuclear non-proliferation regime. International nuclear safeguards mainly include technical measures such as physical protection, containment and surveillance, unattended and remote monitoring, and nuclear material accounting and inspection systems.

[0035] In the measurement of nuclear waste, detection and verification of fissile materials, it is necessary to analyze the nuclide or isotope composition of samples. Gamma-ray spectrometry is one of the commonly used non-destructive analysis methods in safeguards verification. This method mainly analyzes the isotopic abundance of samples by measuring the energy and intensity of gamma rays emitted by different isotopes incident on the detector. The gamma-ray spectrometry analysis method based on relative efficiency technology, also known as the relative efficiency method, can directly collect data from the gamma spectrum of the sample, establish a relative efficiency curve model corresponding to the measurement conditions, and then accurately calculate the isotopic abundance of the sample. It has the characteristics of not requiring prior calibration, fast analysis speed, and no special requirements for the geometric shape and chemical form of the sample to be measured. Therefore, it has a wide range of applications in on-site inspections of nuclear safeguards.

[0036] For example, in uranium samples, usually, except 235 U and 238 U, the content of other isotopes is extremely low. Therefore, the uranium enrichment (i.e., 235 U abundance) only depends on the ratio of the number of 235 U and 238 U atoms. The uranium enrichment calculation method based on the relative efficiency method mainly analyzes the energy region in the range of 120 - 1001 keV in the uranium spectrum. Its core is to fit the relative detection efficiency curve of the sample using multiple characteristic gamma rays of 235 U in the low-energy region and characteristic gamma rays of the decay daughters of 238 U in the medium- and high-energy regions, and then calculate the uranium enrichment. During the measurement of uranium enrichment, whether the relative efficiency curve of the complete region from the low-energy region to the high-energy region can be accurately fitted will directly affect the calculation of the relative efficiency between different characteristic peaks, and thus affect the measurement result of enrichment.

[0037] The establishment of the relative efficiency curve model is the technical core of the relative efficiency method. During the analysis of the isotopic abundance of nuclear materials, the accuracy of the relative efficiency curve expression will directly affect the calculation of the relative efficiency between different characteristic peaks, and thus affect the isotopic abundance analysis results. There are two traditional relative efficiency curve models. The first is an empirical model that describes the shape of the relative efficiency curve using forms such as power functions and logarithmic power functions according to the geometric shape of the relative efficiency curve. The advantage of this model is that it is relatively convenient to use and can achieve good fitting results for common detection systems. However, the disadvantage of this model is that the physical meaning of the parameters in the model cannot be explained, and the fitting effect for detection systems beyond the software application range cannot be guaranteed and needs further verification. The second model is a physical model obtained based on the principle of the interaction between high-purity germanium detectors and γ photons. The accuracy of the fitting result of this model depends on the understanding of the sample morphology and measurement conditions, as well as the need for an expected estimate of the detection efficiency and calibration factor of the detector; but its advantage is that it can include the physical principle of the interaction between rays and matter to a certain extent in the relative efficiency curve model, and the final obtained model will also be more in line with physical laws.

[0038] In view of the disadvantages of the above related technologies, the embodiments of the present invention provide an isotopic abundance determination method, which can improve the accuracy and reliability of the analysis process of isotopic abundance information. To illustrate the technical solutions described in the present invention, specific embodiments are used for illustration below.

[0039] Figure 1 is a schematic flowchart of the implementation of an isotopic abundance determination method provided by an embodiment of the present invention. The execution subject of the isotopic abundance determination method is an electronic device, and the electronic device includes a desktop computer, a laptop computer, a server, etc. Among them, the server can be a physical device or a virtualized device deployed in the cloud. Refer to Figure 1 , the isotopic abundance determination method includes:

[0040] S101, obtaining energy spectrum data of rays emitted by a sample to be measured collected by a nuclear radiation detector; the set elements in the sample to be measured include a first isotope and a second isotope.

[0041] Among them, the nuclear radiation detector can be a high-purity germanium detector, which is a detector used to measure radiation particles. It is made based on a high-purity germanium crystal and measures the energy and position of radiation particles through an electric field and electronic equipment.

[0042] The sample to be measured can be a radioactive sample, such as a uranium sample, and the uranium sample includes isotopes 235 U and 238The radionuclide in the sample to be measured emits rays, and the nuclear radiation detector can collect energy spectrum data of the rays emitted by the radionuclide in the sample to be measured.

[0043] By using a high-resolution γ spectrometer to perform γ energy spectrum acquisition on the sample to be measured, the resolvability of each characteristic peak in the energy spectrum is ensured.

[0044] For example, when analyzing the γ energy spectrum of the uranium sample to be measured, by obtaining the 235 U, 238 characteristic γ energy peaks of 235 U (including the 143.7 keV, 163.3 keV, 185.7 keV, and 205.3 keV characteristic γ energy peaks related to 238 U, and the 258.3 keV, 742.8 keV, 766.4 keV, and 1001 keV characteristic γ energy peaks related to 238 U).

[0045] S102. Based on the first energy at the characteristic peak of the first isotope and the second energy at the characteristic peak of the second isotope in the energy spectrum data, use the relative detection efficiency curve model to determine the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy; the relative detection efficiency curve model includes a first part and a second part, the first part characterizes the correlation between the reaction cross-section of the interaction between the ray and the nuclear radiation detector and the relative detection efficiency, and the second part is the power series expansion formula of the relative detection efficiency curve;

[0046] Among them, the first energy at the characteristic peak of the first isotope and the second energy at the characteristic peak of the second isotope. Here, the characteristic peaks can be multiple pairs of pre-selected characteristic peaks, and the relative detection efficiency at multiple characteristic peaks can be measured.

[0047] For example, for the uranium sample to be measured, the first energy of the first isotope 235 U is 185.7 keV, and the second energy of the second isotope 238 U is 1001 keV.

[0048] The relative detection efficiency curve model of this embodiment is established based on the typical empirical model of the detection efficiency curve of the detector and combined with the microscopic cross-section analytical formula of the interaction between γ rays and matter. It realizes the accurate calibration of the relative efficiency curve, solves the problem that the physical meaning of the parameters in the empirical model cannot be explained, and the dependence problem of the physical analytical formula on information such as the sample form and measurement conditions. This method can be used to analyze isotope abundance information such as uranium enrichment in nuclear materials, which helps to improve the accuracy and reliability of the analysis process.

[0049] For example, the expression of the relative detection efficiency curve model is as follows:

[0050]

[0051] Among them, A1, B1, A2, c0, c1, c2, and c3 are model fitting parameters. The first half of this model is composed of a combination and adjustment of several terms in the physical expression of the reaction cross-section of γ-ray interacting with matter. The B1 / E term comes from the far-end asymptote of the reaction cross-section of the photoelectric effect. The variation trend of this reaction cross-section with energy is that it first decreases rapidly according to the E -7 / 2 power, then slows down, and finally varies according to the E -1 power; A1E and respectively come from the low-energy and high-energy approximation formulas of the Compton scattering reaction cross-section. A1 and A2 determine the influence contribution of Compton events to the relative detection efficiency curve. The Compton scattering cross-section decreases with the increase of photon energy, changing slowly at low energy and rapidly at high energy. The second half of the formula comes from the power series expansion of the typical relative detection efficiency formula. c0, c1, c2, and c3 are the coefficients of the first three terms of the power series expansion respectively.

[0052] According to the relative detection efficiency curve model, by substituting the specific energies at the characteristic peaks of each isotope, the corresponding relative detection efficiency can be obtained.

[0053] According to the above formula, by substituting the first energy and the second energy into the formula for calculation, the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy can be obtained.

[0054] Let the energy of a certain characteristic γ energy peak emitted by the first isotope i be E j , and the energy of a certain characteristic γ energy peak emitted by isotope k be E l , then their relative efficiencies at the corresponding energies are respectively:

[0055]

[0056] S103. Based on the first relative detection efficiency and the second relative detection efficiency, determine the atomic number ratio of the first isotope and the second isotope.

[0057] According to the basic principle of abundance calculation by relative efficiency calibration technology, the atomic number ratio of isotopes i and k in the sample can be expressed as:

[0058]

[0059] Among them, is the peak area of the γ energy peak j with energy E j emitted by isotope i, is the peak area of the γ energy peak l emitted by another isotope k; and are their respective decay constants; N i and N k are their respective numbers of atomic nuclei; is the branching ratio corresponding to energy peak j, is the branching ratio corresponding to energy peak l.

[0060] According to the above formulas 2 and 3, substituting the relative detection efficiency calculated by formula 2 into formula 3, the atomic number ratio of the first isotope and the second isotope can be obtained.

[0061] The detection efficiency ratio of two energy peaks of the same nuclide can be directly obtained from the net count of the energy spectrum and the branching ratio data. Assume that the nuclide emits a total of m rays, and all these m rays are detected by the detector, and these ray peaks are relatively isolated from each other (without interference from other energy peaks) and cover a large energy region, then the corresponding net peak count can be directly obtained from the energy spectrum. If the detection efficiency of a certain ray, for example, the k-th ray, is selected as the reference value, the relative detection efficiencies of the other m - 1 energy peaks are calculated, then an RE~E curve is plotted and a functional expression describing this curve is fitted.

[0062] It should be noted that although the relative detection efficiency curve is made from multiple rays of a certain nuclide, it reflects the variation relationship of the detection efficiency with energy and has nothing to do with the nuclide type. Therefore, after solving the functional expression of the relative detection efficiency curve, the relative detection efficiency values of energy peaks with different energies can be obtained, and then the atomic number ratio of the corresponding nuclide can be solved.

[0063] S104. Determine the abundance of the isotope in the sample to be measured according to the atomic number ratio.

[0064] After obtaining the atomic number ratio of the first isotope and the second isotope in the sample, it can be used to further calculate the isotope abundance or enrichment degree in the sample.

[0065] For example, taking a uranium sample as an example, 235 The U abundance calculation formula is:

[0066]

[0067] where E w is 235 the enrichment degree of U (i.e., 235 the U abundance), m 235 and m 238 respectively represent 235 U and 238 U's mass numbers, N 235 and N 238 respectively represent 235 U and 238 U's atomic numbers, and finally the 235 in the sample is obtained.U abundance.

[0068] In an embodiment of the present invention, energy spectrum data of rays emitted by a sample to be measured collected by a nuclear radiation detector is obtained; the set elements in the sample to be measured include a first isotope and a second isotope. Based on a first energy at a characteristic peak of the first isotope and a second energy at a characteristic peak of the second isotope in the energy spectrum data, a first relative detection efficiency at the first energy and a second relative detection efficiency at the second energy are determined by using a relative detection efficiency curve model. The relative detection efficiency curve model includes a first part and a second part. The first part characterizes the correlation between the reaction cross-section of the interaction between the ray and the nuclear radiation detector and the relative detection efficiency, and the second part is a power series expansion formula of the relative detection efficiency curve. Based on the first relative detection efficiency and the second relative detection efficiency, the atomic number ratio of the first isotope and the second isotope is determined; and based on the atomic number ratio, the abundance of the isotopes in the sample to be measured is determined. In an embodiment of the present invention, by using a relative detection efficiency curve model established by combining a typical empirical model of a detector efficiency curve with a microscopic cross-section analytical formula of the interaction between a ray and a substance, accurate calibration of the relative efficiency curve is achieved, and the problems that the physical meaning of the parameters in the empirical model cannot be explained and the dependence on information such as the sample form and measurement conditions in the physical analytical formula are solved. This method can be used to analyze the isotope abundance in nuclear materials, which helps to improve the accuracy and reliability of isotope abundance analysis.

[0069] In one embodiment, before determining the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy based on the first energy of the ray energy peak emitted by the first isotope and the second energy of the ray energy peak emitted by the second isotope in the energy spectrum data by using the relative detection efficiency curve model, the method further includes:

[0070] Determine the net peak area of each characteristic peak in the energy spectrum data;

[0071] Based on the ratio of the net peak area of each characteristic peak to the corresponding branching ratio, determine the model parameters of the relative detection efficiency curve model.

[0072] For the expression form of the above formula 2 of the relative detection efficiency curve model, specific data needs to be substituted to solve the model parameters. The problem to be solved can be expressed as:

[0073]

[0074] where y i is the i-th measured data, that is, the result obtained by dividing the net peak area peak i by its corresponding branching ratio; is the i-th predicted data. The characteristic gamma peaks and branching ratios of common radionuclides are known quantities and can be obtained by querying relevant technologies.

[0075] The objective function for determining the model parameters is defined as:

[0076] F(A1,B1,A2,c0,c1,c2,c3) =

[0077] min‖‖M(E)-(A1E + B1 / E + A2lnE / E + c0 + c1lnE + c2(lnE) 2 + c3(lnE) 3 )‖‖ 2

[0078] = min‖‖R(E)‖‖ 2 Equation 6

[0079] Substitute the relative detection efficiency data to be fitted (the result obtained by dividing the net peak area peak i by its corresponding branching ratio) into this objective function, and use the non-linear least squares fitting algorithm to iterate it. Finally, obtain the specific expression form of the relative detection efficiency curve model, denoted as Its expression is:

[0080]

[0081] where A, B, C, D, F, G, H are the best fitting parameters obtained by iteration.

[0082] In one embodiment, determining the net peak area of each characteristic peak in the energy spectrum data includes:

[0083] Determine the background area of each characteristic peak;

[0084] Subtract the background area from the total area of each characteristic peak to obtain the net peak area of each characteristic peak.

[0085] Perform integral peak background technology processing, peak width calibration, peak shape calibration, and single peak fitting on each characteristic peak to determine the net peak area of each characteristic energy peak.

[0086] The trapezoidal background subtraction method can be used to subtract the background from all characteristic peaks to be analyzed in the energy spectrum. Determine the parameters of the background function by measuring the background on both sides of the spectrum segment, so as to use the determined background function to describe the background in the entire energy peak region. The subtraction method is shown in Equation 8:

[0087]

[0088] where B(x) is the background count of the x-th channel; m, n are the left and right boundary channels; b m and bn are the background counts on the left and right sides respectively; y i 、y j is the count of the i-th and j-th tracks.

[0089] The peak shape function is expressed in the form of a Gaussian function plus a tailing function to describe the characteristic peak shape. The formula is:

[0090]

[0091] in:

[0092] ε is a unit step function, and the model is defined as:

[0093]

[0094] H represents the peak height of the tail, B is used to control the slope of the front tail, and α is the tail parameter, which is used to describe the overall shape of the tail.

[0095] The calculation of the net peak area requires the integration of the peak shape function, namely:

[0096]

[0097] In one embodiment, determining the ratio of the number of atoms of the first isotope to the number of atoms of the second isotope based on the first relative detection efficiency and the second relative detection efficiency includes:

[0098] Determine the ratio of the number of atoms of the first isotope and the second isotope based on the net peak area of the characteristic peak corresponding to the first energy, the net peak area of the characteristic peak corresponding to the second energy, the branching ratio of the characteristic peak corresponding to the first energy, the branching ratio of the characteristic peak corresponding to the second energy, the first relative detection efficiency and the second relative detection efficiency.

[0099] As shown in Formula 3, the ratio of the number of atoms of the first isotope to that of the second isotope can be obtained by substituting the relative detection efficiency calculated by Formula 2 into Formula 3.

[0100] In one embodiment, determining the abundance of the isotopes in the sample to be tested based on the ratio of the atomic numbers includes:

[0101] The abundance of the first isotope is determined based on the ratio of the atomic numbers, the mass number of the first isotope, and the mass number of the second isotope.

[0102] As shown in formula 4, the abundance of the first isotope can be calculated based on the ratio of the atomic numbers.

[0103] In one embodiment, based on the first energy at the characteristic peak of the first isotope and the second energy at the characteristic peak of the second isotope in the energy spectrum data, determining the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy by using a relative detection efficiency curve model includes:

[0104] Based on the first energy at the first characteristic peak of the first isotope, determining the first relative detection efficiency at the first energy through the relative detection efficiency curve model;

[0105] Based on the second energy at the second characteristic peak of the second isotope, determining the second relative detection efficiency at the second energy through the relative detection efficiency curve model; the first characteristic peak and the second characteristic peak are preset characteristic peaks.

[0106] Here, the first characteristic peak and the second characteristic peak form a pair of characteristic peaks for calculating the atomic number ratio. Multiple pairs of characteristic peaks can be selected, so as to calculate multiple atomic number ratios, and the final atomic number ratio is comprehensively obtained by combining multiple atomic number ratios.

[0107] In one embodiment, the sample to be measured is a uranium sample, the first isotope is 235 U, and the second isotope is 238 U.

[0108] In one embodiment, taking a uranium sample as an example, calculating the uranium enrichment content ( 235 U abundance), the implementation process is as follows:

[0109] 1. Use a high-resolution γ spectrometer to collect γ energy spectrum data of the sample and complete the calculation of the net peak area of the characteristic peak.

[0110] Use a high-resolution γ spectrometer to perform γ energy spectrum collection on the uranium sample to be measured. During the measurement, keep the detector dead time less than 10%. When the net peak area reaches more than 10000, select 6 times the full width at half maximum of the energy peak around the peak value as m and n respectively. After obtaining the energy spectrum, use the trapezoidal background subtraction method to subtract the background. Fit the energy spectrum after background subtraction using a fitting model.

[0111] In the calculation of uranium enrichment, the 11 characteristic peaks for which the net peak area needs to be calculated respectively represent 235 143.76 keV, 163.36 keV, 185.715 keV, 205.311 keV of U and 258.26 keV, 742.83 keV, 766.4 keV, 880.47 keV, 883.24 keV, 945.95 keV, 1001.03 keV of 238U. The obtained peak areas are denoted as A1, A2... A11.

[0112] 2. Calculate the relative detection efficiency.

[0113] Using the fitted relative detection efficiency curve model (such as Equation 7), calculate 235 U and 238 the relative detection efficiency at the energy of the characteristic γ energy peak emitted by U.

[0114] At this time, the typical shape of the relative detection efficiency curve model is as Figure 1 shown.

[0115] 3. Calculate 235 U and 238 the ratio of the number of atoms of U.

[0116] Substitute the calculated relative detection efficiency into Equation 3 to obtain 235 U and 238 the ratio of the number of atoms of U.

[0117] 4. Calculate the uranium enrichment.

[0118] Substitute the ratio of the number of atoms into Equation 4 to finally obtain the 235 U enrichment in the sample.

[0119] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0120] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0121] It should be noted that the technical solutions described in the embodiments of the present invention can be arbitrarily combined without conflict.

[0122] In addition, in the embodiments of the present invention, "first", "second", etc. are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence.

[0123] The embodiment of the present application also provides an isotope abundance determination device. This device corresponds to the above isotope abundance determination method, and each step in the embodiment of the above isotope abundance determination method is also fully applicable to the embodiment of this device. This device includes:

[0124] An acquisition module, configured to acquire the energy spectrum data of the rays emitted by the sample to be measured collected by the nuclear radiation detector; the set elements in the sample to be measured include a first isotope and a second isotope;

[0125] A first determination module, configured to determine a first relative detection efficiency at the first energy and a second relative detection efficiency at the second energy by using a relative detection efficiency curve model based on the first energy at a characteristic peak of the first isotope and the second energy at a characteristic peak of the second isotope in the energy spectrum data; the relative detection efficiency curve model includes a first part and a second part, the first part characterizes the correlation between the reaction cross-section of the interaction between the ray and the nuclear radiation detector and the relative detection efficiency, and the second part is a power series expansion formula of the relative detection efficiency curve;

[0126] A second determination module, configured to determine the atomic number ratio of the first isotope and the second isotope based on the first relative detection efficiency and the second relative detection efficiency;

[0127] A third determination module, configured to determine the abundance of the isotope in the sample to be measured according to the atomic number ratio.

[0128] In practical applications, the acquisition module, the first determination module, the second determination module, and the third determination module can be implemented by a processor in an electronic device, such as a central processing unit (CPU, Central Processing Unit), a digital signal processor (DSP, Digital Signal Processor), a microcontroller unit (MCU, Microcontroller Unit), or a field-programmable gate array (FPGA, Field-Programmable Gate Array), etc.

[0129] It should be noted that: when the isotope abundance determination device provided in the above embodiment determines the isotope abundance, only the division of the above modules is used as an example. In practical applications, the above processing can be allocated to different modules according to needs, that is, the internal structure of the device is divided into different modules to complete all or part of the above-described processing. In addition, the isotope abundance determination device provided in the above embodiment and the isotope abundance determination method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0130] The above isotope abundance determination device may be in the form of an image file, and after the image file is executed, it can run in the form of a container or a virtual machine to implement the isotope abundance determination method described in this application. Of course, it is not limited to the form of an image file, and any software form that can implement the isotope abundance determination method described in this application is within the protection scope of this application.

[0131] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiments of the present application, the embodiments of the present application further provide an electronic device. Figure 3 It is a schematic diagram of the hardware composition structure of the electronic device according to the embodiments of the present application. As Figure 3 shown, the electronic device includes:

[0132] A communication interface capable of interacting with other devices such as network devices.

[0133] A processor, connected to the communication interface to implement information interaction with other devices, and when used to run a computer program, execute the method provided by one or more technical solutions on the electronic device side. And the computer program is stored on the memory.

[0134] Of course, in actual application, each component in the electronic device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus, and a status signal bus. However, for the sake of clear illustration, in Figure 3 all kinds of buses are labeled as the bus system.

[0135] The above-mentioned electronic device can be in the form of a cluster, such as a cloud computing platform. The so-called cloud computing platform is a business form that uses computing virtualization, network virtualization, and storage virtualization technologies to organize multiple independent server physical hardware resources into pooled resources. It is a software-defined resource structure based on the development of virtualization technology, and can provide resource capabilities in the form of virtual machines, containers, etc. By eliminating the fixed relationship between the hardware and the operating system, relying on the network connectivity for unified resource scheduling, and then providing the required virtual resources and services, it is a new type of IT and software delivery model, with characteristics such as flexibility, elasticity, distribution, multi-tenancy, and on-demand.

[0136] The memory in the embodiments of the present application is used to store various types of data to support the operation of the electronic device. Examples of these data include: any computer program for operating on the electronic device.

[0137] It can be understood that the memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory), an electrically erasable programmable read-only memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), a ferromagnetic random access memory (FRAM, ferromagnetic random access memory), a flash memory (FlashMemory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM, Compact Disc Read-OnlyMemory); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM, RandomAccessMemory), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as a static random access memory (SRAM, Static Random Access Memory), a synchronous static random access memory (SSRAM, Synchronous Static RandomAccess Memory), a dynamic random access memory (DRAM, Dynamic Random Access Memory), a synchronous dynamic random access memory (SDRAM, SynchronousDynamic RandomAccess Memory), a double data rate synchronous dynamic random access memory (DDRSDRAM, Double Data Rate Synchronous Dynamic RandomAccess Memory), an enhanced synchronous dynamic random access memory (ESDRAM, Enhanced Synchronous Dynamic RandomAccess Memory), a synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), a direct rambus random access memory (DRRAM, Direct Rambus RandomAccess Memory). The memory described in the embodiments of the present application is intended to include but not limited to these and any other suitable types of memory.

[0138] The method disclosed in the embodiments of the present application can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor or the instructions in the form of software. The above-mentioned processor may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. Combining the steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, and this storage medium is located in the memory. The processor reads the program in the memory and combines its hardware to complete the steps of the foregoing method.

[0139] Optionally, when the processor executes the program, it implements the corresponding processes implemented by the electronic device in the various methods of the embodiments of the present application. For the sake of brevity, it will not be elaborated here.

[0140] In an exemplary embodiment, the embodiments of the present application further provide a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, such as a first memory storing a computer program. The above computer program can be executed by the processor of the electronic device to complete the steps of the foregoing method. The computer-readable storage medium may be a FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM, etc.

[0141] In several embodiments provided by the present application, it should be understood that the disclosed devices, electronic devices, and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined, or integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0142] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0143] In addition, in each embodiment of the present application, all the functional units may be integrated into one processing unit, or each unit may be separately taken as one unit, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0144] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments. The foregoing storage medium includes: various media such as removable storage devices, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0145] Alternatively, if the above-mentioned integrated units of the present application are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present application, in essence or the part that contributes to the related technology, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present application. The foregoing storage medium includes: various media such as removable storage devices, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0146] In an exemplary embodiment, the embodiments of the present application also provide a computer program product, including a computer program, which can be executed by a processor of an electronic device to complete the steps of the isotope abundance determination method in the embodiments of the present application.

[0147] It should be noted that the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0148] In addition, in the examples of the present application, "first", "second", etc. are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence.

[0149] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the said claims.

Claims

1. A method for determining isotope abundance, characterized in that, The method includes: Obtaining energy spectrum data of rays emitted by a sample to be measured collected by a nuclear radiation detector; the set elements in the sample to be measured include a first isotope and a second isotope; Based on a first energy at a characteristic peak of the first isotope and a second energy at a characteristic peak of the second isotope in the energy spectrum data, using a relative detection efficiency curve model to determine a first relative detection efficiency at the first energy and a second relative detection efficiency at the second energy; the relative detection efficiency curve model includes a first part and a second part, the first part characterizes the correlation between the reaction cross-section of the interaction between the ray and the nuclear radiation detector and the relative detection efficiency, and the second part is a power series expansion formula of the relative detection efficiency curve; Based on the first relative detection efficiency and the second relative detection efficiency, determining the atomic number ratio of the first isotope and the second isotope; According to the atomic number ratio, determining the abundance of isotopes in the sample to be measured.

2. The method according to claim 1, wherein Before using the relative detection efficiency curve model to determine the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy based on the first energy of the ray energy peak emitted by the first isotope and the second energy of the ray energy peak emitted by the second isotope in the energy spectrum data, the method further includes: Determining the net peak area of each characteristic peak in the energy spectrum data; Based on the ratio of the net peak area of each characteristic peak and the corresponding branching ratio, determining the model parameters of the relative detection efficiency curve model.

3. The method according to claim 2, characterized in that, The determining the net peak area of each characteristic peak in the energy spectrum data includes: Determining the background area of each characteristic peak; Subtracting the background area from the total area of each characteristic peak to obtain the net peak area of each characteristic peak.

4. The method according to claim 1, wherein The determining the atomic number ratio of the first isotope and the second isotope based on the first relative detection efficiency and the second relative detection efficiency includes: According to the net peak area of the characteristic peak corresponding to the first energy, the net peak area of the characteristic peak corresponding to the second energy, the branching ratio of the characteristic peak corresponding to the first energy, the branching ratio of the characteristic peak corresponding to the second energy, the first relative detection efficiency and the second relative detection efficiency, determining the atomic number ratio of the first isotope and the second isotope.

5. The method according to claim 1, wherein The determining the abundance of isotopes in the sample to be measured according to the atomic number ratio includes: Based on the atomic number ratio, the mass number of the first isotope and the mass number of the second isotope, determining the abundance of the first isotope.

6. The method according to claim 1, wherein The using the relative detection efficiency curve model to determine the first relative detection efficiency at the first energy and the second relative detection efficiency at the second energy based on the first energy at the characteristic peak of the first isotope and the second energy at the characteristic peak of the second isotope in the energy spectrum data includes: Based on the first energy at the first characteristic peak of the first isotope, determining the first relative detection efficiency at the first energy through the relative detection efficiency curve model; Based on the second energy at the second characteristic peak of the second isotope, determine the second relative detection efficiency at the second energy through the relative detection efficiency curve model; the first characteristic peak and the second characteristic peak are preset characteristic peaks.

7. The method according to claim 1, wherein The sample to be measured is a uranium sample, the first isotope is uranium-235, and the second isotope is uranium-238.

8. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, the steps of the isotope abundance determination method according to any one of claims 1-7 are implemented.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the isotope abundance determination method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to execute the isotope abundance determination method according to any one of claims 1 to 7.

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