Monte Carlo simulation method for moving body dose based on data field segmentation

Abstract

The invention discloses a Monte Carlo simulation method for moving body dose based on data field segmentation. The method includes the steps of: a) acquiring calculated input parameter, b) forming a body bounding box on the basis of a tree structure of an entity so as to acquire a body discrete state sequence, c) segmenting particle track data into a sensitive data field and a non-sensitive data field based on the body bounding box, d) alternately processing circulating simulations of the two data fields, processing a relative state transition of particles when entering or exiting the sensitive data field, delivering the particles in the same model, dividing each of the particles entering the sensitive data field split into two particles respectively of the weights of 1 / m and 1-1 / m, and then delivering the two particles respectively in two data fields, and e) acquiring the precise dose change of the human body in movements through a linear interpolation. The method can be used for accurately calculating dose changes of the moving body and every organ, and is high in speed and widely applicable to fields such as maintenance and assembling, roaming and nuclear detection under the circumstances of radiation shield and nuclear radiation.

Description

technical field [0001] The invention relates to a Monte Carlo dose calculation method for a mobile human body based on data field segmentation in the fields of radiation shielding, maintenance assembly and roaming in nuclear radiation environments, and nuclear detection. Background technique [0002] Radiation shielding, maintenance assembly and roaming in nuclear radiation environment, nuclear detection and other fields evaluate the radiation dose of the human body and its various organs are important topics. Dose calculation methods are generally divided into analytical methods and Monte Carlo methods. The analytical method has the advantages of fast and high calculation accuracy for problems with relatively regular geometry and material distribution, but it has large errors or cannot be solved for complex problems; the Monte Carlo method is not limited by the geometry and materials of the problem, and can be used in all areas Maintain high accuracy, but at the cost of ca...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that: since the space occupied by the moving human body is relatively small relative to the entire radiation field, a large number of repeated calculations will be performed on the non-moving field that occupies most of the space, resulting in a serious time-consuming calculation process; It does not consider the influence of the human body on the radiation field during the movement process and the influence of this moment on the particle transport process at the next moment due to the interaction between the particles and the human body.

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