Simulation method for simulated energy spectral curve

Abstract

The invention relates to a simulation method for a simulated energy spectral curve. The simulation method comprises the steps of: step S1, acquiring an actual nuclear energy spectral curve chart; step S2, and processing the actual nuclear energy spectral curve chart to obtain a simulated energy spectral curve. The simulation method for the simulated energy spectral curve obtains numerical values (ie., energy levels of nuclear energy spectra and counting rates of the energy levels) of points of the energy spectral curve through carrying out curve identification on the actual nuclear energy spectral curve chart and numeralization on the energy spectral curve, obtains a random number of each nuclear energy level through randomly and directly sampling a group of the numerical values by adopting a Monte Carlo method, so as to simulate the randomness of the nuclear decay process, finally conducts statistical processing on the random number to obtain the simulated energy spectral curve, and performs inversion on the simulated energy spectral curve and an actual energy spectral curve so as to determine the reliability and precision of a simulated nuclear signal generator.

Description

technical field [0001] The invention relates to the field of nuclear energy, in particular to a simulation method for simulating energy spectrum curves. Background technique [0002] The nuclear decay process occurs randomly in time, and the radiation (energy) released during the decay process is also random, but the statistical analysis of the time interval and energy value of its occurrence shows that the nuclear decay process has the following characteristics: The time interval approximately obeys the exponential distribution; the energy released by the nuclear decay process (that is, the energy spectrum) approximately obeys the Gaussian distribution. [0003] Based on the above characteristics of the nuclear decay process, the traditional nuclear signal generator simulates the nuclear signal characteristics with random numbers that obey different distributions, that is, simulates the statistical characteristics of nuclear signals at time intervals with random numbers tha...

AI Technical Summary

Problems solved by technology

However, it is inaccurate to simulate the statistical characteristics of the nuclear signal in amplitude only with random numbers that obey the Gaussian distribution. There is a large error between the simulated high-period distribution curve and the actual energy spectrum curve, which cannot accurately reflect the characteristics of the nuclear signal. ; At the same time, the statistical characteristics of the energy spectrum of each nuclide are not the same, so the simulation of the amplitude characteristics of different types of nuclides needs to generate Gaussian distribution random numbers with different parameters to match them, which is not practical. Difficult to achieve in the process

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