Method for screening fission yield experimental data
By using Zp model fitting and deviation threshold screening, the experimental data of fission yield is processed automatically, solving the problems of large data volume and low efficiency of manual screening, and achieving efficient data screening and shortening the research cycle.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA INSTITUTE OF ATOMIC ENERGY
- Filing Date
- 2025-11-28
- Publication Date
- 2026-05-01
AI Technical Summary
In existing technologies, the amount of fission yield experimental data is large and the efficiency of manual screening is low, resulting in poor quality of scientific research results. There is a lack of automated screening methods.
The Zp model was used to fit the fission output experimental data. The model parameters were determined by the least squares method, the fission output was calculated and a deviation threshold was set, and the experimental data with deviations exceeding the threshold were automatically filtered out.
This improved the efficiency of screening experimental data on fission yield, shortened the research cycle, and provided technical support for establishing an experimental database.
Smart Images
Figure CN121958239A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of nuclear data evaluation technology, specifically relating to a method for screening experimental data on fission yield. Background Technology
[0002] Fission yield refers to the probability of a nuclear fission producing a specific product nucleus. Independent yield refers to the yield generated after fission fragments emit transient neutrons and gamma rays. These fragments then undergo beta decay, accumulating along the decay chain to a specific product nucleus; this portion is called cumulative yield. Fission yield is a crucial foundation for nuclear devices and nuclear energy research, and fission yield assessment is an important means of providing user data.
[0003] Methods for measuring fission yield include radiochemical separation gamma ray method, direct gamma ray method, mass spectrometry, kinetic energy method, etc. Currently, the International Atomic Energy Agency compiles experimental data into the EXFOR database, which contains over 20,000 data points on fission yields of 235U, 238U, and 239Pu. These experimental data contain discrepancies and errors, leading to poor quality results in scientific research based on these data (such as fission yield assessment and machine learning). Therefore, it is necessary to screen the experimental data.
[0004] There is currently no relevant work in the publicly available literature, both domestically and internationally, regarding the screening of fission yield experimental data. For example, the literature on fission yield assessment databases in the United States and Europe does not cover this aspect. Given the large volume of fission experimental data and the low efficiency of manual screening, there is an urgent need to provide a method for automatically screening fission yield experimental data. Summary of the Invention
[0005] To address the shortcomings of existing technologies, the present invention aims to provide a method for screening experimental data on fission yield. This method can effectively improve evaluation efficiency, shorten the research cycle, and provide technical support for further establishing an experimental database.
[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:
[0007] A method for screening experimental data on fission yield includes the following steps:
[0008] S1. Obtain fission output experimental data from the EXFOR database and group the experimental data;
[0009] S2. The Zp model is used to fit the experimental data of fission output for each group to determine the model parameters; the fission output is calculated based on the determined model parameters to obtain the output calculation value.
[0010] S3. Calculate the deviation between the experimental data of fission yield and the calculated value of fission yield obtained in step S2;
[0011] S4. Filter the experimental data based on the deviation obtained in step S3.
[0012] Furthermore, in the fission yield experimental data screening method described above, the grouping of experimental data in step S1 specifically involves grouping the experimental data according to the fission system and the mass chain, thereby extracting the yield data of the same fission system and the same mass chain.
[0013] Furthermore, in the fission yield experimental data screening method described above, the functional expression of the Zp model in step S2 is:
[0014] (1)
[0015] In formula (1):
[0016] y(Z) represents the charge distribution of fission product nuclei on the same mass chain, i.e., the independent yield, which is approximately Gaussian distributed; Z represents the charge number of the product nuclei.
[0017] Z0 represents the center point of the Gaussian distribution. Let Z represent the width of the Gaussian distribution, C represent the normalization constant, and F(Z) represent the parity effect of the proton-neutron pair.
[0018] Furthermore, using the fission yield experimental data screening method described above, the cumulative yield of a certain product nucleus j... The nucleus is the sum of all pioneer contributions to the j-nucleus, that is:
[0019] (2)
[0020] Represented in matrix form as follows:
[0021] Y = R·y (3)
[0022] In the formula:
[0023] Y and y represent N×1 column matrices consisting of independent output and cumulative output, respectively; N represents the number of product cores;
[0024] R represents the N-dimensional transformation matrix from independent output to cumulative output, with matrix element r(i,j)=r i→j The contribution of the independent yield of product nucleus i to nucleus j is calculated based on the branching ratio of the decay chain.
[0025] Furthermore, the fission yield experimental data screening method described above uses the least squares method to fit the experimental data, thereby determining the values of the Zp model parameters and their covariance. The Zp model parameters include the center point Z0 of the Gaussian distribution and the width of the Gaussian distribution. Normalization constant C and proton-neutron parity effect F(Z);
[0026] Then, the four model parameters obtained from the fitting are substituted into formula (1) to calculate the fission output, including independent output and cumulative output.
[0027] Furthermore, in the fission yield experimental data screening method described above, the formula for calculating the deviation between the calculated fission yield value and the corresponding experimental data in step S3 is as follows:
[0028] (4)
[0029] In equation (4):
[0030] Indicates experimental values, This represents the calculated value. Indicates the error of the experimental value. This indicates the deviation between the experimental value and the calculated value.
[0031] Furthermore, in the fission yield experimental data screening method described above, step S4 specifically includes:
[0032] The deviation threshold P0 is determined based on statistical significance.
[0033] when If the deviation exceeds the aforementioned deviation threshold P0, the experimental data is considered unreasonable and discarded, thus completing the experimental data screening.
[0034] The present invention also provides a computer program product, which includes a computer program or instructions, wherein the computer program or instructions are executed by a processor to implement the fission yield experimental data screening method as described in any of the above.
[0035] Compared with existing technologies, the fission yield experimental data screening method provided by this invention has the following beneficial effects:
[0036] This invention uses the Zp model to fit the initial experimental data to obtain fitting parameters; the calculated output value is further calculated based on the fitting parameters; then the relative deviation between the experimental data and the calculated data is compared, and experimental data with deviations greater than a set value are discarded, thereby achieving the screening of experimental data.
[0037] Applying the method provided by this invention to fission yield research can effectively improve evaluation efficiency, shorten the research cycle, and provide technical support for further establishing an experimental database. Attached Figure Description
[0038] To further illustrate the above and other advantages and features of this application, the specific embodiments of this application will be described in more detail below with reference to the accompanying drawings. The accompanying drawings, together with the following detailed description, are included in and form a part of this specification. It should be understood that these drawings only depict typical examples of this application and should not be considered as limiting the scope of this application.
[0039] Figure 1 This is a flowchart of a fission yield experimental data screening method provided in a specific embodiment of the present invention;
[0040] Figure 2 A schematic diagram of the decay chain of fission products and the β decay branching ratio for A=144;
[0041] Figure 3 Induced by thermal neutrons 235 U fission A=144 calculated and experimental values (where the solid line is the cumulative output calculated by the Zp model, the dashed line is the calculated independent output, and the scatter plots are experimental data). Detailed Implementation
[0042] Exemplary embodiments of this application will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of actual implementations are described in the specification. However, it should be understood that many implementation-specific decisions must be made in the development of any such actual embodiment to achieve the developer's specific goals, such as complying with constraints related to the system and business, and these constraints may vary depending on the implementation. Furthermore, it should be understood that while development work can be very complex and time-consuming, such development work is merely a routine task for those skilled in the art who benefit from the content of this application.
[0043] It should also be noted that, in order to avoid obscuring this application with unnecessary details, only the equipment structure and / or processing steps closely related to the solution according to this application are shown in the accompanying drawings, while other details that are not closely related to this application are omitted.
[0044] The embodiments or examples disclosed below are used to implement this application. To simplify the disclosure of this application, the components and methods of specific examples are described below. Of course, they are merely examples and are not intended to limit this application.
[0045] To address the problems mentioned in the background art regarding the large volume of fission experiment data and the low efficiency of manual screening, this invention provides a method for screening fission yield experiment data. Figure 1 A flowchart of the method is shown, which includes the following steps:
[0046] S1. Obtain fission output experimental data from the EXFOR database and group the experimental data.
[0047] This invention groups experimental data according to the fission system and the mass chain, thereby extracting the yield data of the same fission system and the same mass chain.
[0048] S2. The Zp model is used to fit the experimental data of fission output for each group to determine the model parameters; the fission output is calculated based on the determined model parameters to obtain the output calculation value.
[0049] Zp model: The charge distribution (i.e., independent yield) of fission product nuclei on the same decay chain (also known as the mass chain) approximates a Gaussian distribution.
[0050] (1)
[0051] Where Z is the charge number of the product nucleus, and Z0 is the center point of the Gaussian distribution. Let Z be the width of the Gaussian distribution, C be the normalization constant, and F(Z) be the parity effect of the proton-neutron pair.
[0052] Cumulative yield of a certain product nucleus j The nucleus is the sum of all pioneer contributions to the j-nucleus, that is: (2)
[0053] Represented in matrix form:
[0054] Y = R·y (3)
[0055] Where Y and y are N×1 column matrices composed of independent output and cumulative output, respectively, and N is the number of product cores; R is an N-dimensional transformation matrix from independent output to cumulative output, and its matrix element r(i,j) = r i→j The contribution of the independent yield of product nucleus i to nucleus j can be calculated based on the branching ratio of the decay chain. When i=j, it is its own contribution, which is equal to 1.
[0056] Figure 2 Taking A=144 as an example, the branching ratio of each β decay in the decay chain is given.
[0057] The Zp model includes four parameters: Z0, normalization constant C, Gaussian distribution width σ, and neutron-proton parity effect F(Z). In some embodiments, the present invention uses the least squares method to fit the experimental data to obtain the values of these four model parameters and their covariance; then, the fitted four model parameters are substituted into formula (1) to calculate the fission yield, including independent yield and cumulative yield.
[0058] S3. Calculate the deviation between the experimental data and the fission yield calculated in step S2.
[0059] The degree of deviation between a certain fission yield calculation value and the corresponding experimental data can be obtained by calculation formula (4):
[0060] (4)
[0061] in, These are experimental values. For calculated values, For experimental value error, This represents the weighted deviation between the experimental and calculated values.
[0062] S4. Filter the experimental data based on the deviation obtained in step S3.
[0063] As a screening criterion, when If the deviation exceeds the set deviation threshold Δ0, the experimental data is considered unreasonable. The threshold Δ0 is determined based on statistical significance. Experimental data with deviations exceeding the threshold Δ0 are discarded, thus completing the screening process.
[0064] Based on the above method steps, the present invention also provides a computer program product, which includes a computer program or instructions, and the computer program or instructions are executed by a processor to implement the fission yield experimental data screening method as described above.
[0065] In one specific embodiment, the present invention establishes the ZpFit program, which automatically calculates and judges deviations in yield experiment data, thereby efficiently completing the screening of fission yield experiment data. For example, for experimental data of a mass chain, if preliminary screening is carried out manually, it generally takes about a day, but with the ZpFit program, preliminary screening can be completed in one minute.
[0066] Example
[0067] Induced by thermal neutrons 235 Taking the experimental data screening of a mass chain with U fission A=144 as an example, the steps are as follows:
[0068] 1. Preparation of experimental data
[0069] Access the EXFOR website (https: / / www-nds.iaea.org / exfor / ) to obtain fission yield data, and organize the initial experimental data. Taking the product nuclei of thermal neutron-induced 235U fission with A=144 as an example, some yield data are as follows:
[0070] Table 1. Experimental data (partial) of A=144 product nuclei induced by thermal neutron fission of 235U.
[0071] Number of charges mass number Metastable Isomer IC Output error Neutron Energy (MEV) literature 59 144 0 C 5.26E-02 3.16E-04 2.53E-08 Bail(09)22985 59 144 0 C 5.16E-02 2.58E-03 2.53E-08 Fontenla(80)10937 59 144 0 C 3.83E-02 1.92E-03 2.53E-08 Ajitanand(78)31685 59 144 0 C 4.61E-02 2.31E-03 2.53E-08 Ajitanand(78)31685 59 144 0 C 5.60E-02 4.90E-04 2.53E-08 Diiorio(77)13359 59 144 0 C 4.97E-02 2.87E-05 2.53E-08 Asghar(77)21543 59 144 0 C 5.58E-02 2.90E-03 2.53E-08 Thierens(76)21531 59 144 0 C 5.30E-02 1.06E-03 2.53E-08 Farrar(62)13064 59 144 0 C 5.34E+00 1.35E-01 2.53E-08 Blachot(74)21736 59 144 0 C 5.54E-02 3.10E-04 2.53E-08 Maeck(78)10865 59 144 0 C 5.42E-02 2.00E-04 2.53E-08 Lisman(70)13270 54 144 0 C 1.10E-03 1.00E-04 2.53E-08 Wahl(58)13450
[0072] Table Notes:
[0073] b) IC: I represents independent output, and C represents cumulative output;
[0074] c) The references are marked with the author (year) EXFOR number, which can be obtained from the EXFOR experimental database.
[0075] 2. Use the Zp model to fit the output experimental data and calculate the output value.
[0076] The output results of running the ZpFit program are shown in Table 2 and... Figure 3 As shown.
[0077] Table 2. Partial Calculation Results of ZpFit Program
[0078]
[0079] Table Notes:
[0080] Column 1: Use ID=A*1000 + Z*10 + Isomer to label the product nuclei, where A, Z, and Isomer represent the mass number A, charge number Z, and isonuclear isoenergetic state of the product nuclei, respectively.
[0081] Column 2: IC indicates the same as Table 1
[0082] 3. Data Filtering
[0083] The criterion for data filtering is the comparison between the deviation of a single data point and a threshold. In this embodiment, the threshold is set to 50, i.e. Experimental data exceeding 50 were deemed to have excessive deviation and were discarded.
[0084] Based on the calculation results from the ZpFit program, it can be seen that the experimental data displayed in bold in Table 2 deviates significantly. Figure 3 It is also clear that the experimental data deviates significantly.
[0085] As shown in Table 2:
[0086] Balestrini (79) 21641.3 ( =1.06E+02>50), Ajitanand (78) 31685.2 ( Data with a deviation exceeding the threshold (=7.42E+01 > 50) is discarded; the remaining data... ≤50, meets the accuracy requirements, can be used, and can be used for subsequent analysis.
[0087] from Figure 3It can also be seen intuitively that the experimental data points with excessive deviations are significantly deviated from the model curve, verifying the rationality of the screening results.
[0088] 4. Database Construction
[0089] Using the above method, traverse the target fission systems (such as...) in the EXFOR database. 235 U thermal neutron fission, 238 U-Fast Neutron Fission 239 For all mass chain experimental data of Pu thermal neutron fission, repeat steps 1-3 to summarize all qualified data, forming a filtered fission yield experimental database. The database includes experimental information (fission system, product nuclear parameters, neutron energy, literature), yield values (experimental values, calculated values), and... This value is useful for subsequent research.
[0090] The fission yield experimental data screening method provided by this invention uses a Zp model to fit initial experimental data to obtain fitting parameters; based on the fitting parameters, the calculated yield value is further calculated; then, the relative deviation between the experimental data and the calculated data is compared, and experimental data with deviations greater than a set value are discarded, thereby achieving data screening. Applying the method provided by this invention to fission yield research can effectively improve evaluation efficiency, shorten the research cycle, and provide technical support for further establishing an experimental database.
[0091] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention is also intended to include these modifications and variations.
Claims
1. A method for screening experimental data on fission yield, comprising the following steps: S1. Obtain fission output experimental data from the EXFOR database and group the experimental data; S2. The Zp model is used to fit the experimental data of fission output for each group to determine the model parameters; the fission output is calculated based on the determined model parameters to obtain the output calculation value. S3. Calculate the deviation between the experimental data of fission yield and the calculated value of fission yield obtained in step S2; S4. Filter the experimental data based on the deviation obtained in step S3.
2. The fission yield experimental data screening method according to claim 1, characterized in that, The grouping of experimental data in step S1 specifically involves grouping the experimental data according to the fission system and the mass chain, thereby extracting the output data of the same fission system and the same mass chain.
3. The fission yield experimental data screening method according to claim 2, characterized in that, The functional expression of the Zp model in step S2 is: (1) In formula (1): y(Z) represents the charge distribution of fission product nuclei on the same mass chain, i.e., the independent yield, which is approximately Gaussian distributed; Z represents the charge number of the product nuclei. Z0 represents the center point of the Gaussian distribution. Let Z represent the width of the Gaussian distribution, C represent the normalization constant, and F(Z) represent the parity effect of the proton-neutron pair.
4. The fission yield experimental data screening method according to claim 3, characterized in that, Cumulative yield of a certain product nucleus j The nucleus is the sum of all pioneer contributions to the j-nucleus, that is: (2) Represented in matrix form as follows: Y = R·y (3) In the formula: Y and y represent N×1 column matrices consisting of independent output and cumulative output, respectively; N represents the number of product cores; R represents the N-dimensional transformation matrix from independent output to cumulative output, with matrix element r(i,j)=r i→j The contribution of the independent yield of product nucleus i to nucleus j is calculated based on the branching ratio of the decay chain.
5. The fission yield experimental data screening method according to claim 4, characterized in that, The experimental data were fitted using the least squares method to determine the values of the Zp model parameters and their covariance. The Zp model parameters include the center point Z0 of the Gaussian distribution and the width of the Gaussian distribution. Normalization constant C and proton-neutron parity effect F(Z); Then, the four model parameters obtained from the fitting are substituted into formula (1) to calculate the fission output, including independent output and cumulative output.
6. The fission yield experimental data screening method according to claim 5, characterized in that, The formula for calculating the deviation between the calculated fission yield and the corresponding experimental data in step S3 is as follows: (4) In equation (4): Indicates experimental values, This represents the calculated value. Indicates the error of the experimental value. This indicates the deviation between the experimental value and the calculated value.
7. The fission yield experimental data screening method according to claim 6, characterized in that, Step S4 is as follows: The deviation threshold P0 is determined based on statistical significance. when If the deviation exceeds the aforementioned deviation threshold P0, the experimental data is considered unreasonable and discarded, thus completing the experimental data screening.
8. A computer program product comprising a computer program or instructions, characterized in that, The computer program or instructions are executed by the processor to implement the fission yield experimental data screening method according to any one of claims 1-7.