YAN Shiyu, YANG Xiaohua, LIU Zhiming, et al. Research on benchmark derivation techniques in verification of steady state nuclear reactor core design programs[J]. 2019, 51(11): 160-166.
DOI:
YAN Shiyu, YANG Xiaohua, LIU Zhiming, et al. Research on benchmark derivation techniques in verification of steady state nuclear reactor core design programs[J]. 2019, 51(11): 160-166.DOI: 10.11918/j.issn.0367-6234.201901149.
Research on benchmark derivation techniques in verification of steady state nuclear reactor core design programs
Verification is one of the necessary steps to ensure the quality of nuclear power software
and benchmark calculation is an important mean of nuclear power software verification. The traditional methods of obtaining benchmark data mainly include independent experiments
collecting operation data of nuclear power plants
joining international experimental research programs
and purchasing data of international benchmarks. However
they have the problems of high cost and long cycle. In order to provide more benchmarks for the verification of steady state nuclear reactor core design programs
a benchmark derivation technique based on metamorphic testing principle is proposed in this paper. First
the technology established the framework of benchmark derivation
whose main idea is to directly calculate and solve the related input and output parameters of the original benchmark according to the parameters and relations of the metamorphic relationship
so as to obtain the derived benchmark (new test cases). Furthermore
aiming at the characteristic that the benchmark problems can input the data of the program under test in the form of a fixed format input card
an automatic derivation algorithm for benchmark questions was designed and a benchmark automatic derivation system was developed to improve the efficiency of derivation. Finally
the two-dimensional and three-dimensional benchmarks of the steady state neutron diffusion program were demonstrated as examples. Results show that the technology can automatically generate two-dimensional and three-dimensional derivative benchmarks in a single or batch way
which not only generates data accurately and efficiently