DOI: 10.57760/sciencedb.j00186.00018
title: Dataset of design algorithms for neutron-focusing supermirrors
title: 中子聚焦超镜设计算法数据集

description: This dataset contains all kinds of neutron focusing supermirror design algorithms used in the design of neutron focusing super-mirror, and the methods for comparing the design results of various algorithms, as well as the data generated in the design and comparison process. Various neutron supermirror design algorithms refer to the previous literature, and the corresponding design process is realized by writing Python code. The method for comparing the design results of various algorithms is original in my paper, and also is realized by writing Python code by myself. All data are calculated and generated using Python code written by ourselves. This dataset includes the code and the data that support the findings of Selection diagram of design algorithms for neutron-focusing supermirrors. Refer to our github webpage for details: https://github.com/MoWenbo19/Neutron-Supermirror.The SMlib.py file is a common function package for neutron supermirror algorithm, which contains the implementation process of eight neutron super-mirror design algorithms, the calculation of neutron super-mirror reflectivity (including the consideration of film roughness, film thickness non-uniformity, material absorption and other factors), and the calculation of coating thickness distribution on curved surfaces.The calculation process folder contains the calculation process files for the results, pictures, etc. in the paper:(1) First use ABC parameter selection. py, GRB parameter selection_ Parallel. py and Mas parameter selection_ Parallel. py calculates the initial design parameters of the three design algorithms for reflection performance comparison, and the results are arranged in the supermirror algorithm design parameter.xlsx table. Each row represents the design parameters of the three algorithms when the supermirror with m value shown in the second column is to be designed. The average reflectivity of the three algorithms under the initial design parameters is shown in Figure 2. The corresponding calculation and drawing code is the initial condition average reflectivity. py file, and the results are saved as Rmean0.npy file.(2) Then use ThicknessDistribution_ The New-ROC.py file calculates the film thickness distribution under different ROC, and saves the results in the ROC folder. The results of ROC=50, 80 and 160mm are shown in Figure 4, and the corresponding calculation and drawing code is the thickness range. py file.(3) Next, select the normalized point position of the film thickness, as shown in Figure 5. The corresponding calculation and drawing code thickness selects. py file.(4) The next step is to calculate the neutron intensity Q distribution, as shown in Figure 6. The corresponding calculation and drawing code is IQ customization_ Points. py file.(5) Next, calculate the influence of film thickness nonuniformity on the average reflectivity of the three algorithms. The calculation process code is ROC-m_ 1d_ double_ 3. py file, in which the results without considering the neutron intensity Q distribution are saved as R_ mean_ 3. npy file, the result of considering neutron intensity Q distribution is saved as R_ mean_ IQ_ 3. npy file. The comparison and selection of the average reflectivity of the three algorithms are shown in Figures 7 and 10. The corresponding calculation and drawing codes are selected for different uniformity algorithms_ Encrypt the grid. py file.(6) Then analyze the influence of thickness nonuniformity on the reflectivity curves of the three algorithms, as shown in Figures 8 and 9. The corresponding calculation and drawing codes are thickness change comparison. py file and subsection comparison. py file. Figure 11. The corresponding calculation and drawing code is thickness change comparison. py file .(7) Next, compare the influence of film thickness nonuniformity and neutron intensity Q distribution on the reflectivity of the algorithm, as shown in Figure 12. The corresponding calculation and drawing codes are selected for different uniformity algorithms_ Encrypt the grid. py file.(8) Next, the thickness of each layer in the supermirror multilayer film structure designed by three algorithms is compared, as shown in Figure 13. The corresponding calculation and drawing code is a segmented comparison. py file.(9) Finally, the film number allocation strategies of the three algorithms are compared, as shown in Figure 14. The corresponding calculation and drawing code is a segmented comparison. py file.
description: This dataset contains all kinds of neutron focusing supermirror design algorithms used in the design of neutron focusing super-mirror, and the methods for comparing the design results of various algorithms, as well as the data generated in the design and comparison process. Various neutron supermirror design algorithms refer to the previous literature, and the corresponding design process is realized by writing Python code. The method for comparing the design results of various algorithms is original in my paper, and also is realized by writing Python code by myself. All data are calculated and generated using Python code written by ourselves. This dataset includes the code and the data that support the findings of Selection diagram of design algorithms for neutron-focusing supermirrors. Refer to our github webpage for details: https://github.com/MoWenbo19/Neutron-Supermirror.The SMlib.py file is a common function package for neutron supermirror algorithm, which contains the implementation process of eight neutron super-mirror design algorithms, the calculation of neutron super-mirror reflectivity (including the consideration of film roughness, film thickness non-uniformity, material absorption and other factors), and the calculation of coating thickness distribution on curved surfaces.The calculation process folder contains the calculation process files for the results, pictures, etc. in the paper:(1) First use ABC parameter selection. py, GRB parameter selection_ Parallel. py and Mas parameter selection_ Parallel. py calculates the initial design parameters of the three design algorithms for reflection performance comparison, and the results are arranged in the supermirror algorithm design parameter.xlsx table. Each row represents the design parameters of the three algorithms when the supermirror with m value shown in the second column is to be designed. The average reflectivity of the three algorithms under the initial design parameters is shown in Figure 2. The corresponding calculation and drawing code is the initial condition average reflectivity. py file, and the results are saved as Rmean0.npy file.(2) Then use ThicknessDistribution_ The New-ROC.py file calculates the film thickness distribution under different ROC, and saves the results in the ROC folder. The results of ROC=50, 80 and 160mm are shown in Figure 4, and the corresponding calculation and drawing code is the thickness range. py file.(3) Next, select the normalized point position of the film thickness, as shown in Figure 5. The corresponding calculation and drawing code thickness selects. py file.(4) The next step is to calculate the neutron intensity Q distribution, as shown in Figure 6. The corresponding calculation and drawing code is IQ customization_ Points. py file.(5) Next, calculate the influence of film thickness nonuniformity on the average reflectivity of the three algorithms. The calculation process code is ROC-m_ 1d_ double_ 3. py file, in which the results without considering the neutron intensity Q distribution are saved as R_ mean_ 3. npy file, the result of considering neutron intensity Q distribution is saved as R_ mean_ IQ_ 3. npy file. The comparison and selection of the average reflectivity of the three algorithms are shown in Figures 7 and 10. The corresponding calculation and drawing codes are selected for different uniformity algorithms_ Encrypt the grid. py file.(6) Then analyze the influence of thickness nonuniformity on the reflectivity curves of the three algorithms, as shown in Figures 8 and 9. The corresponding calculation and drawing codes are thickness change comparison. py file and subsection comparison. py file. Figure 11. The corresponding calculation and drawing code is thickness change comparison. py file .(7) Next, compare the influence of film thickness nonuniformity and neutron intensity Q distribution on the reflectivity of the algorithm, as shown in Figure 12. The corresponding calculation and drawing codes are selected for different uniformity algorithms_ Encrypt the grid. py file.(8) Next, the thickness of each layer in the supermirror multilayer film structure designed by three algorithms is compared, as shown in Figure 13. The corresponding calculation and drawing code is a segmented comparison. py file.(9) Finally, the film number allocation strategies of the three algorithms are compared, as shown in Figure 14. The corresponding calculation and drawing code is a segmented comparison. py file.