Neutron scattering evaluation and experimental arrangement optimization method based on energy spectrum distortion factor
The method of evaluating neutron scattering based on the energy spectrum distortion factor solves the problem of quantitative comparison of scattering sources in the measurement of transient fission neutron spectrum, optimizes the experimental setup, and improves the measurement accuracy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XI AN JIAOTONG UNIV
- Filing Date
- 2026-05-09
- Publication Date
- 2026-07-31
AI Technical Summary
Existing technologies lack a unified quantitative evaluation index for transient fission neutron spectrum measurements, making it difficult to rank different scattering sources and optimize experimental setups, leading to increased measurement uncertainty.
A neutron scattering assessment method based on the energy spectrum distortion factor was adopted. The energy spectrum distortion factor index was established through Monte Carlo simulation to screen low scattering experimental setup schemes and optimize experimental parameters to reduce the scattering background.
It enables quantitative evaluation and optimized ranking of different scattering sources, improves the accuracy of transient fission neutron spectrum measurement, and reduces the influence of scattering background.
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Figure CN122488198A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of nuclear data measurement, radiation detection and neutron transport analysis, and in particular to a method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor, which is used for quantitative assessment of neutron scattering background and optimization of experimental setup under transient fission neutron spectrum measurement conditions. Background Technology
[0002] Prompt Fission Neutron Spectrum (PFNS) is one of the most important fundamental nuclear data sets. Its accurate measurement is crucial for fast neutron reactor design, nuclear safety criticality calculations, accelerator-driven nuclear waste transmutation system design, defense applications, and research on nuclear fission mechanisms. It is especially important for actinide nuclides, particularly... 238 The PFNS measurement results of nuclides such as U are directly related to the accuracy of related nuclear process calculations and model evaluation results.
[0003] During PFNS measurements, neutrons undergo elastic or inelastic scattering with the walls, floor, fission chamber shell, target substrate, gaskets, entrance window, detector surrounding structures, and shielding in the experimental environment, resulting in neutron downscattering. This effect causes the neutron energy spectrum obtained at the detection location to deviate from the true fission neutron energy spectrum, typically manifesting as a decrease in high-energy counts and an increase in low-energy counts, thus significantly increasing the uncertainty of PFNS measurements.
[0004] In existing technologies, empirical measures are typically employed to suppress the scattering background of PFNS measurements, such as those described in the article "Measurement of the 239In the article "Pu(n,f) prompt fission neutron spectrum from 10 keV to 10 MeV induced by neutrons of energy 1–20 MeV", the authors created a deep pit below the experimental region, increased the distance between the detector and the wall, and placed the detector only on the half away from the ground. In the article "A multiple parallel-plate avalanche counter for fission-fragment detection", the authors visually evaluated the energy spectra under different conditions on the same graph to optimize the materials of the PPAC. In the article "Prompt fission neutron energy spectra induced by fast neutrons", boron- or lithium-containing shields were used to shield scattered neutrons. In the article "Low-energy neutron spectrometer and its application for..." 252 In the article "Cfneutron spectrum measurements," shadow cones are used for background subtraction, etc. The article "The need for precise and well-documented experimental data on prompt fission neutron spectra from neutron-induced fission of..." further elaborates on this. 239 In Pu, simulations show that some traditional shielding or background subtraction methods may introduce new problems such as slowed scattering, multiple scattering, or oversubtraction of real fission events, thereby further deteriorating the measurement results.
[0005] However, most existing studies remain at the level of qualitative comparison, usually relying on visual judgment by plotting energy spectra under different conditions on the same graph. There is a lack of unified quantitative evaluation indicators and parameter optimization methods for experimental design. In particular, for multiple scattering sources such as walls, ground, PPAC shell, target substrate, gasket, incident window, source neutron scattering background, and shielding, existing techniques are difficult to classify and prioritize.
[0006] Therefore, it is necessary to propose a method that can be used to uniformly and quantitatively evaluate different scattering sources in the PFNS measurement process and guide the optimization of experimental setup, so as to reduce the scattering background and improve the accuracy of PFNS measurements. Summary of the Invention
[0007] To overcome the problems existing in the prior art, the present invention aims to provide a method for neutron scattering assessment and experimental setup optimization based on the energy spectrum distortion factor. Based on Monte Carlo simulation, a newly constructed energy spectrum distortion factor index is used to transform the qualitative analysis of the impact of fission neutron energy spectrum scattering into a quantitative evaluation. This method can be used to screen low-scattering experimental setup schemes and improve the measurement accuracy of transient fission neutron spectrum. It also solves the problems in the prior art where it is difficult to uniformly quantify and compare the scattering sources of PFNS measurements, it is difficult to determine the priority optimization objects for different experimental stages, and traditional shielding and setup methods lack quantitative basis.
[0008] To achieve the above objectives, the present invention adopts the following technical solution: A method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor includes the following steps: Step 1: Establish a Monte Carlo transport model for the scattering source to be evaluated; The Monte Carlo transport model includes only the target scattering source and the detector array. The scattering source includes at least one of the following: wall and ground, PPAC shell, target substrate, gasket, incident window, and neutron shield. The neutron shield is only used in actual experimental setups when the energy spectrum distortion factor F decreases after its addition.
[0009] Step 2: Set the experimental parameters for the target scattering source or detector array; The experimental parameters include at least one of the following: the type of material from which the target scattering originates, the thickness of the structure, the radius of the detector array, the distance between the center of the detector array and the wall, and the parameters of the shield.
[0010] Step 3, obtain the true fission neutron energy spectrum R(E) The actual fission neutron energy spectrum is obtained by recording the initial neutron energy corresponding to each event using a primary particle generator.
[0011] The method of obtaining the energy is as follows: register an energy reading function in the primary particle generator source file of Geant4, and then reference it when recording the data of each step in the step source file of Geant4, so as to obtain the real transient fission neutron energy corresponding to each event.
[0012] The actual fission neutron energy spectrum adopts the Maxwellian spectrum approximation. The source terms are set on multiple parallel circular surfaces, each with an equal emission probability. The emission directions are isotropic or approximately isotropic. The source terms refer to the neutron sources generated by the primary particle generator.
[0013] Step 4: Obtain the energy spectrum S(E) of the fission neutrons after scattering; The energy spectrum S(E) of the fission neutron after scattering is obtained through the Step function of Geant4, with the volume limited to the logical volume of the detector during the acquisition process. Step 5: Calculate the spectrum distortion factor F based on the actual fission neutron energy spectrum R(E) and the scattered fission neutron energy spectrum S(E); The formula for calculating the energy spectrum distortion factor F is: Among them, E min and E max These represent the lower and upper limits of the energy range to be evaluated, respectively. Alternatively, by normalizing the area of the actual fission neutron energy spectrum R(E) and the scattered fission neutron energy spectrum S(E), the normalized actual fission neutron energy spectrum R can be obtained. N (E) and the normalized scattering fission neutron energy spectrum S N (E), at this point, the spectral distortion factor F is calculated using the following formula: .
[0014] Step 6: Compare the energy spectrum distortion factor F under different experimental parameter conditions, and sort the scattering sources in descending order of F. The top one or several scattering sources are identified as priority optimization targets. Step 7: For the priority optimization target, change the experimental parameters of the target scattering source or detector array, and repeat steps 3 to 6 to establish the correspondence between the energy spectrum distortion factor and the parameters under different experimental parameters. Step 8: Select the parameter combination that minimizes the spectral distortion factor or makes it lower than the preset threshold as the low scattering experimental setup.
[0015] Compared with the prior art, the beneficial effects of the present invention (1) This invention proposes a new index for evaluating the degree of neutron scattering, namely the energy spectrum distortion factor, which can accurately describe the difference between the real fission energy spectrum and the energy spectrum after environmental scattering. Using the energy spectrum distortion factor, by adopting a single scattering source isolation modeling method, the scattering degree of different scattering sources such as walls and ground, PPAC shell, target substrate, gasket, and incident window on PFNS can be uniformly compared and ranked, and priority optimization objects can be identified. The larger the energy spectrum distortion factor, the stronger the scattering degree of PFNS, and the more the corresponding scattering source should be optimized.
[0016] (2) This invention scans parameters such as material, thickness, detector radius and distance from the wall, changes experimental parameters, obtains the relationship graph of energy spectrum distortion factor and parameter, finds the parameter corresponding to the point with the smallest energy spectrum distortion factor in the graph (or the point where the energy spectrum distortion factor changes less with the parameter), which is the optimal value, and provides a basis for optimizing the PFNS experimental setup.
[0017] (3) By comparing the magnitude of the energy spectrum distortion factor before and after the addition of the shield, the present invention can identify the negative optimization risk caused by an unreasonable shield and avoid the situation where the PFNS scattering deteriorates due to an unreasonable shield design.
[0018] In summary, this invention constructs a unified energy spectrum distortion factor index, which can transform the qualitative analysis of neutron downscattering in PFNS measurements into a quantitative evaluation. It can be used for PFNS measurement system design, scattering background analysis, uncertainty assessment, and related neutron shielding research. Attached Figure Description
[0019] Figure 1 This is a flowchart of the method of the present invention.
[0020] Figure 2 This is a schematic diagram illustrating the principle of the energy spectrum distortion factor.
[0021] Figure 3 This is a schematic diagram of the wall and floor scattering assessment model.
[0022] Figure 4 This is a schematic diagram showing the position of the detector center relative to the PPAC center.
[0023] Figure 5 This is a comparison diagram of the energy spectrum after scattering from the wall and the ground with the true spectrum.
[0024] Figure 6 A sorting diagram of the energy spectrum distortion factors corresponding to different scattering sources.
[0025] Figure 7 This is a graph showing the variation of the energy spectrum distortion factor for different materials used in the PPAC shell.
[0026] Figure 8 The graph shows the variation of the energy spectrum distortion factor under different thicknesses of the PPAC shell.
[0027] Figure 9 This is a graph showing the variation of the energy spectrum distortion factor under different equivalent thicknesses of the wall and the ground.
[0028] Figure 10 This is a graph showing the variation of the energy spectrum distortion factor for different wall and floor materials.
[0029] Figure 11The graph shows the variation of the energy spectrum distortion factor under different target substrate materials.
[0030] Figure 12 The graph shows the variation of the energy spectrum distortion factor under different Mylar substrate thicknesses.
[0031] Figure 13 The graph shows the variation of the energy spectrum distortion factor under different aluminum substrate thicknesses.
[0032] Figure 14 This is a graph showing the variation of the energy spectrum distortion factor under different gasket materials.
[0033] Figure 15 This is a graph showing the variation of the energy spectrum distortion factor under different radial thicknesses of the gasket.
[0034] Figure 16 The graph shows the variation of the energy spectrum distortion factor under different detector array radii.
[0035] Figure 17 This is a graph showing the variation of the energy spectrum distortion factor at different distances between the center of the detector array and the wall.
[0036] Figure 18 This is a geometric schematic diagram of a neutron shield.
[0037] Figure 19 The graph shows the variation of the energy spectrum distortion factor under different shielding thicknesses.
[0038] Figure 20 The graph shows the variation of the energy spectrum distortion factor at different B4C concentrations. Detailed Implementation
[0039] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. It should be understood that the following embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.
[0040] Reference Figure 1 , Figure 2 A method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor, characterized by the following steps: A method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor includes the following steps: Step 1: Establish a Monte Carlo transport model for the scattering source to be evaluated; The Monte Carlo transport model includes only the target scattering source and the detector array. The scattering source includes at least one of the following: wall and ground, PPAC shell, target substrate, gasket, incident window, and neutron shield.
[0041] Step 2: Set the experimental parameters for the target scattering source and the detector array. The experimental parameters include at least one of the following: the type of material from which the target scattering originates, the thickness of the structure, the radius of the detector array, the distance between the center of the detector array and the wall, and the parameters of the shielding body. Step 3, obtain the true fission neutron energy spectrum R(E) The actual fission neutron energy spectrum is obtained by recording the initial neutron energy corresponding to each event using a primary particle generator.
[0042] The method of obtaining the energy is as follows: register an energy reading function in the primary particle generator source file of Geant4, and then reference it when recording the data of each step in the step source file of Geant4, so as to obtain the real transient fission neutron energy corresponding to each event.
[0043] The actual fission neutron energy spectrum adopts the Maxwellian spectrum approximation. The source terms are set on multiple parallel circular surfaces, each with an equal emission probability. The emission direction is isotropic or approximately isotropic. The source terms refer to the neutron source generated by the primary particle generator. Specifically, it is to restore the experimental results as accurately as possible. 238 In the case of U fission, the source term is located on 10 parallel circular surfaces, corresponding to 10 parallel target sheets during fission. During the simulation, the probability of neutrons being emitted from any circular surface is equal. The x-coordinate of the first circular surface is -90mm relative to the center of the PPAC, and the spacing between different circular surfaces is 20mm.
[0044] Step 4: Obtain the energy spectrum S(E) of the fission neutrons after scattering; The energy spectrum S(E) of the fission neutron after scattering is obtained through the Step function of Geant4, with the volume limited to the logical volume of the detector during the acquisition process. Step 5: Calculate the spectrum distortion factor F based on the actual fission neutron energy spectrum R(E) and the scattered fission neutron energy spectrum S(E); The formula for calculating the energy spectrum distortion factor F is: Among them, E min and E max These represent the lower and upper limits of the energy range to be evaluated, respectively. Alternatively, by normalizing the area of the actual fission neutron energy spectrum R(E) and the scattered fission neutron energy spectrum S(E), the normalized actual fission neutron energy spectrum R can be obtained. N (E) and the normalized scattering fission neutron energy spectrum S N (E), at this point, the spectral distortion factor F is calculated using the following formula: Step 6: Compare the energy spectrum distortion factor F under different experimental parameter conditions, and sort the scattering sources in descending order of F. The top one or several scattering sources are identified as priority optimization targets. Step 7: For the priority optimization target, change the experimental parameters of the target scattering source and detector array, and repeat steps 1 to 6 to establish the correspondence between the energy spectrum distortion factor and the parameters under different experimental parameters; Different experimental parameters of the target scattering source or detector array will cause the fission neutron source to scatter to different degrees. The neutron energy spectrum after scattering is recorded by the detector array. Each time the scattered neutron energy is recorded, the corresponding real fission neutron energy can be obtained by referring to the energy readout function in step 3.
[0045] Step 8: Select the parameter combination that minimizes the spectral distortion factor or makes it lower than the preset threshold as the low scattering experimental setup.
[0046] For neutron shielding, the neutron shielding is only used in actual experimental setups when the energy spectrum distortion factor F decreases after the addition of the neutron shielding.
[0047] Example 1: Evaluation of PFNS Scattering from Walls and Floors To clearly observe the degree of scattering of the transient fission neutron spectrum by the wall and the ground, this embodiment only places the wall, the ground, and the detector array in the geometric model to avoid interference from other experimental steps with the scattering evaluation results.
[0048] Reference Figure 3 In one specific embodiment, the dimensions of the experimental hall can be set to 18.245 m in the north-south direction, 11.405 m in the east-west direction, and 8.732 m in height; the walls and floor are made of concrete, with a certain equivalent thickness on the outer side. A coordinate system is established with the geometric center of the experimental hall as the origin, with the east as the positive x-axis, the north as the positive y-axis, and the vertically upward as the positive z-axis. The DT neutron source is located against the wall, the PPAC is set in front of the neutron source, and the detector array is distributed in a hemispherical shape with the PPAC as the center.
[0049] Reference Figure 4 The detector array consists of 12 lithium-glass detectors, 4 in the inner ring and 8 in the outer ring. Each detector is a cylinder with a diameter of 100 mm and a thickness of 20 mm, and its axis is aligned with the line connecting the center of the detector and the center of the PPAC. The semi-apex angle φ of the cone of the inner ring detector can be 45°, and that of the outer ring detector can be 90°. The distance D between the array center and the wall can be 20 cm, and the array radius R can be 50 cm.
[0050] Because of direct simulation of 14 MeV neutron bombardment 238 Since U has a relatively low fission efficiency, this embodiment uses a Maxwellian spectrum approximation instead of PFNS. To approximate the actual emission of a multilayer fission target, the neutron source is placed on 10 parallel circular surfaces, with equal emission probabilities on each surface. The source is uniformly distributed within the circular surfaces, and the emission direction is isotropic. The actual fission neutron energy is recorded by the primary particle generator, and the neutron energy entering the detector is recorded by the stepping process.
[0051] In a specific simulation, the number of particles is 1×10. 8 The area-normalized comparison was performed between the scattered PFNS and the true Maxwellian spectrum. (Refer to...) Figure 5 The results show that in the energy ranges of 3.1–14 MeV and 1.5–2 MeV, the scattered energy spectrum is lower than the true spectrum; while in the energy ranges of 0–1.5 MeV and 2–3.1 MeV, the scattered energy spectrum is higher than the true spectrum, with an increase of approximately 50% in local regions, such as near 1 MeV. The calculated energy spectrum distortion factor F = 31.6238%, with a statistical error of approximately 0.4316%. This indicates that the wall and ground surfaces exert significant scattering distortion on the PFNS.
[0052] Example 2: Scattering assessment and ranking of different PPAC components In this embodiment, to compare the scattering effects of different PPAC structural components on PFNS, the PPAC shell, target substrate, gasket, and Kapton membrane incident window were modeled separately, without placing walls or the ground, and the other conditions were the same as in Embodiment 1.
[0053] The PPAC shell can be modeled as a cylindrical shell with an inner diameter of 110 mm and a thickness of 3 mm, made of aluminum; the target substrate can be set as 10 cylindrical thin sheets with a diameter of 75 mm and a thickness of 100 μm, made of stainless steel, with an adjacent spacing of 20 mm; the gasket can adopt a cylindrical shell structure, made of standard plastic; the Kapton entrance window is set at both ends of the PPAC, with a thickness of 25 μm.
[0054] Reference Figure 6 Simulation results show that the spectral distortion factor corresponding to the PPAC shell is 33.3794%, the target substrate is 27.7871%, the gasket is 18.6510%, and the Kapton film incident window is 17.0753%. Combining the results from the wall and floor in Example 1, the ranking of multiple scattering sources is: PPAC shell > wall and floor > target substrate > gasket > Kapton film incident window. Therefore, the PPAC shell and the wall / floor can be identified as the priority optimization targets.
[0055] Example 3: PPAC Shell Parameter Optimization In this embodiment, only the material and thickness of the PPAC shell are changed, while the other conditions remain unchanged.
[0056] Reference Figure 7 When the outer shell material is aluminum, titanium, and stainless steel, simulation results show that the corresponding energy spectrum distortion factors are all in the range of about 30% to 45%, with aluminum being the lowest, titanium being slightly higher by about 3%, and stainless steel being about 10% higher. Therefore, aluminum is the preferred outer shell material.
[0057] Reference Figure 8 Furthermore, when the outer shell material is aluminum and the thickness increases from 1 mm to 5 mm, the energy spectrum distortion factor increases approximately linearly within the range of about 32% to 35%, with an increase rate of about 0.5% / mm. Therefore, under the premise of satisfying airtightness and mechanical properties, reducing the thickness of the aluminum outer shell is beneficial to reducing PFNS scattering distortion.
[0058] Example 4: Optimization of Wall and Floor Parameters In this embodiment, the equivalent thickness and material of the wall and floor are varied.
[0059] Reference Figure 9 When the equivalent thickness of the wall and the ground changes from 1 m to 3 m, the energy spectrum distortion factor remains almost unchanged, both being approximately 31%. Therefore, in subsequent related simulations, the equivalent thickness can be simplified to 1 m to reduce the computational load.
[0060] Reference Figure 10 When the material was replaced by B4C or boron-containing polyethylene with 25% B4C, the results showed that compared with concrete, B4C reduced the energy spectrum distortion factor by about 1%, and 25% boron-containing polyethylene reduced it by about 3%. This indicates that the moderation plus absorption scheme is superior to the simple absorption scheme, but further evaluation is still needed in combination with specific structures and distances.
[0061] Example 5: Optimization of Target Substrate and Gasket Parameters In this embodiment, titanium, aluminum, stainless steel, and Mylar film were used as the target substrate materials for comparison, with an initial thickness of 100 μm for each. (Refer to...) Figure 11 The results showed that stainless steel had the highest energy dispersive spectral distortion factor, approximately 27%; titanium was approximately 24%; and both Mylar film and aluminum were approximately 23%, with aluminum being slightly lower. Therefore, aluminum or Mylar is the preferred substrate material.
[0062] Furthermore, the Mylar thickness can be reduced from 100 μm to 2 μm, or the aluminum substrate thickness can be changed from 150 μm to 50 μm, as per [reference needed]. Figure 12-13 The results all showed that the distortion factor changed very little, indicating that within the μm range, the change in substrate thickness had a limited effect on improving PFNS scattering.
[0063] For gasket materials, standard plastics, alumina, silicon carbide, Teflon plastics, and aluminum were compared and contrasted. Figure 14 The results showed that the energy spectrum distortion factors for each material were all approximately 18%, with little difference, except that aluminum and silicon carbide were slightly lower. Further changes were made to the radial thickness of the gasket from 0.5 mm to 2.5 mm, referring to... Figure 15 The results showed that the distortion factor increased approximately linearly, with an increase rate of about 0.6% / mm. Therefore, compared to changing the material, reducing the radial thickness of the gasket is more beneficial for reducing scattering.
[0064] Example 6: Optimization of Detector Array Radius In this embodiment, the experimental parameters of the target scattering source are based on Examples 2 to 5, with the radius variation changed. The detector array radius is increased from 20 cm to 70 cm, and the number of simulated particles is adjusted according to the square relationship of the radius to keep the statistical counts under different radius conditions comparable.
[0065] Reference Figure 16 The results show that as the array radius increases, the spectral distortion factor decreases from approximately 41% to approximately 37%, and the rate of decrease gradually slows down, with the gain starting to weaken significantly around approximately 60 cm. Therefore, the detector array radius is preferably not less than approximately 60 cm.
[0066] Example 7: Optimization of the distance between the center of the detector array and the wall In this embodiment, the experimental parameters of the target scattering source are based on Examples 1 to 5. The radius of the detector array is fixed at 50 cm, and the distance between the center of the detector array and the wall is changed to 10 cm, 30 cm, 50 cm, 100 cm, 200 cm and 300 cm respectively.
[0067] Reference Figure 17 The results show that as the distance from the wall increases, the energy spectrum distortion factor decreases from approximately 55% to approximately 39%, exhibiting an overall exponential decreasing trend. After approximately 100 cm, the benefit of further increasing the distance slows significantly, with a decrease rate of approximately 1% / m. Therefore, without considering efficiency reduction, the optimal distance between the center of the detector array and the wall is approximately 100 cm.
[0068] Example 8: Pre-evaluation and screening of neutron shielding bodies In this embodiment, to prevent scattered neutrons outside the flight path of fission neutrons from entering the detector, an attempt is made to set up a neutron shield around the detector array. Considering that the energy of scattered neutrons is usually close to that of fission neutrons, a direct approach is adopted. 6 Li, 10 B-type absorbers have limited effectiveness in absorbing fast neutrons, so a combination of moderation and absorption is preferred.
[0069] The experimental parameters for the target scattering source are based on Examples 2 to 5, using a boron-containing polyethylene frustum shell structure as the shield. To ensure that the flight path of fission neutrons is not obstructed, the minimum angle between the generatrix of the frustum shell and its base surface needs to be determined based on the geometric relationship between the circumscribed sphere of the fission target and the detector sphere; refer to Figure 18 In one embodiment, the minimum included angle can be approximately 5.5°, and the height of the frustum shell can be 5 cm.
[0070] Based on the moderating length theory, taking polyethylene as an example, the average moderating length required for fast neutrons to slow down from approximately 2 MeV to the thermal region can be estimated to be about 8.8 cm; taking B4C as an example, the thickness required for thermal neutron absorption can be estimated to be on the order of magnitude. Therefore, in actual simulations, the shielding effect can be evaluated by changing the thickness of boron-containing polyethylene and the concentration of B4C.
[0071] Reference Figure 19 The results showed that when the B4C content was fixed at 25%, the energy spectrum distortion factor increased instead of decreasing as the thickness of the boron-containing polyethylene increased from 0 cm to 10 cm; (Refer to...) Figure 20 When the thickness is fixed at 1 cm, although the distortion factor decreases with increasing B4C concentration, it is still higher than the result without a shield. This indicates that placing a hydrogen-containing boron-containing polyethylene shield directly near the detector array not only fails to reduce the energy spectrum distortion factor, but also increases it due to additional slowing and scattering effects.
[0072] Therefore, this invention further proposes that any neutron shield in the PFNS measurement system should be pre-evaluated using the method of this invention before actual use, and should only be used if simulation results show that it can reduce the energy spectrum distortion factor.
[0073] The above embodiments are merely preferred embodiments of the present invention. Those skilled in the art can make various modifications and substitutions without departing from the concept of the present invention, and all such modifications and substitutions should fall within the protection scope of the present invention. The Monte Carlo transport program is not limited to Geant4, and other software platforms with neutron transport and scattering simulation capabilities can also be used; the real fission neutron spectrum is not limited to the Maxwellian spectrum, and standard database spectra, theoretical model spectra, or verified reference experimental spectra can also be used.
Claims
1. A method for evaluating neutron scattering and optimizing experimental setup based on energy spectrum distortion factor, characterized in that, Includes the following steps: Step 1: Establish a Monte Carlo transport model for the scattering source to be evaluated; Step 2: Set the experimental parameters for the target scattering source or detector array; Step 3, obtain the true fission neutron energy spectrum R(E) Step 4: Obtain the energy spectrum S(E) of the fission neutrons after scattering; Step 5: Calculate the spectrum distortion factor F based on the actual fission neutron energy spectrum R(E) and the scattered fission neutron energy spectrum S(E); Step 6: Compare the energy spectrum distortion factor F under different experimental parameter conditions, and sort the scattering sources in descending order of F. The top one or several scattering sources are identified as priority optimization targets. Step 7: For the priority optimization target, change the experimental parameters and repeat steps 3 to 6 to establish the correspondence between the energy spectrum distortion factor and the parameters under different experimental parameters; Step 8: Select the parameter combination that minimizes the spectral distortion factor or makes it lower than the preset threshold as the low scattering experimental setup.
2. The method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, The Monte Carlo transport model includes only the target scattering source and the detector array. The scattering source includes at least one of the following: wall and ground, PPAC shell, target substrate, gasket, incident window, and neutron shield. The neutron shield is only used in actual experimental setups when the energy spectrum distortion factor F decreases after its addition.
3. The method for neutron scattering evaluation and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, The experimental parameters of the target scattering source include at least one of the material type and structural thickness of the target scattering source; the experimental parameters of the detector array include at least one of the radius of the detector array, the distance between the center of the detector array and the wall, and the shielding parameters.
4. The method for neutron scattering evaluation and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, The true fission neutron energy spectrum in step 3 is obtained by recording the initial neutron energy corresponding to each event in the primary particle generator. The method of obtaining the energy is as follows: register an energy reading function in the primary particle generator source file of Geant4, and then reference it when recording the data of each step in the step source file of Geant4, so as to obtain the true transient fission neutron energy corresponding to each event.
5. The method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, The real fission neutron energy spectrum described in step 3 is approximated by the Maxwellian spectrum. The source terms are set on multiple parallel circular surfaces with equal emission probabilities on each surface. The emission directions are isotropic or approximately isotropic. The source terms refer to the neutron sources generated by the primary particle generator.
6. The method for neutron scattering assessment and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, The fission neutron energy spectrum S(E) after scattering in step 4 is obtained through Geant4's Step function, with the volume limited to the logical volume of the detector during the acquisition.
7. The method for neutron scattering evaluation and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, The formula for calculating the energy spectrum distortion factor F in step 5 is as follows: Among them, E min and E max These represent the lower and upper limits of the energy range to be evaluated, respectively.
8. The method for neutron scattering evaluation and experimental setup optimization based on energy spectrum distortion factor according to claim 1, characterized in that, In step 5, when calculating the spectral distortion factor F, the area of the true fission neutron energy spectrum R(E) and the scattered fission neutron energy spectrum S(E) is first normalized to obtain the normalized true fission neutron energy spectrum R. N (E) and the normalized scattering fission neutron energy spectrum S N (E), at this point, the spectral distortion factor F is calculated using the following formula: 。