Method for solving nuclide migration governing equation on basis of hybrid computation architecture

Abstract

The invention discloses a method for solving a nuclide migration governing equation on basis of a hybrid computation architecture. The method comprises the following steps of reading parameters, wherein computation parameters, boundary conditions and computational grid files are read in; generating matrixes, wherein a rigidity sparse matrix, a time evolution sparse matrix and loading vectors are generated, corresponding sparse matrixes are generated, and a later rigidity sparse matrix and a later time evolution sparse matrix are generated; carrying out circulation computation for solution, wherein a finite difference method is used for carrying out the circulation computation, a Jacobi iteration method is adopted in a circulation process for solving a matrix equation of AX=B, and the obtained solution vector Z is the nuclide concentration field datum of the time point. According to the method, data matrixes in a higher grid body number scale can be stored, and solving speed is higher.

Description

technical field [0001] The invention relates to a method, in particular to a method for solving nuclide migration control equations based on a hybrid computing architecture. Background technique [0002] As of 2012, 15 nuclear reactors have been put into operation in my country, and another 26 are under construction. In order to solve the increasingly approaching nuclear waste disposal problem, my country has clearly proposed to build an underground laboratory for nuclear waste disposal in 2020, and build nuclear waste in 2050. Underground repository. The development of nuclear waste disposal will directly affect and restrict the planning and development of my country's nuclear industry and national defense forces. [0003] How to effectively and safely dispose of nuclear waste not only affects the development and future of the country, but also has a direct impact on individuals and society. The most notable examples are the Chernobyl nuclear power plant accident in the for...

AI Technical Summary

Problems solved by technology

The disadvantage of this technique is: under a certain scale of grid body data (less than 100,000), the time consumption and The memory consumption is acceptable. Once this range is exceeded, due to the physical capacity limitation of the memory, data will be repeatedly exchanged between the memory and the hard disk during the entire solution process, reducing the solution speed, and due to the limitation of CPU computing power and design purpose, Time-consuming floating-point operations will be unacceptable to users

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