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論文

Numerical investigation of the random arrangement effect of coated fuel particles on the criticality of HTTR fuel compact using MCNP6

Ho, H. Q.; 本多 友貴; 後藤 実; 高田 昌二

Annals of Nuclear Energy, 103, p.114 - 121, 2017/05

 被引用回数:5 パーセンタイル:29.98(Nuclear Science & Technology)

This study investigated the random arrangement effect of Coated Fuel Particle (CFP) on criticality of the fuel compact of High-Temperature engineering Test Reactor (HTTR). A utility program coupling with MCNP6, namely Realized Random Packing (RRP), was developed to model a random arrangement of the CFPs explicitly for the specified fuel compact of HTTR. The criticality and neutronic calculations for pin cell model were performed by using the Monte Carlo MCNP6 code with an ENDF/B-VII.1 neutron library data. First, the reliability of the RRP model was confirmed by an insignificant variance of the infinite multiplication factor (k$$_{rm inf}$$) among 10 differently random arrangements of the CFPs. Next, the criticality of RRP model was compared with those of Non-truncated Uniform Packing (NUP) model and On-the-fly Random Packing (ORP) model which is a stochastic geometry capability in MCNP6. The results indicated that there was no substantial difference between the NUP and ORP models. However, the RRP model presented a lower k$$_{rm inf}$$ of about 0.32-0.52%$$Delta$$k/k than the NUP model. In additions, the difference of k$$_{rm inf}$$ could be increased as the uranium enrichment decreases. The investigation of the 4-factor formula showed that the difference of k$$_{rm inf}$$ was predominantly given by the resonance escape probability, with the RRP model showing the smallest value.

論文

Benchmark study on realized random packing model for coated fuel particles of HTTR using MCNP6

Ho, H. Q.; 守田 圭介*; 本多 友貴; 藤本 望*; 高田 昌二

Proceedings of 2017 International Congress on Advances in Nuclear Power Plants (ICAPP 2017) (CD-ROM), 8 Pages, 2017/04

The Coated Fuel Particle plays an important role in the excellent safety feature of the High Temperature Gas-cooled Reactor. However, the random distribution of CFPs also makes the simulation of HTGR fuel become more complicated. The Monte Carlo N-particle (MCNP) code is one of the most well-known codes for validation of nuclear systems; unfortunately, it does not provide an appropriate function to model a statistical geometry explicitly. In order to deal with the stochastic media, a utility program for the random model, namely Realized Random Packing (RRP), has been developed particularly for High Temperature engineering Test Reactor (HTTR). This utility program creates a number of random points in an annular geometry. Then, these random points will be used as the center coordinate of CFPs in the MCNP6 input file and therefore the actual random arrangement of CFPs can be simulated explicitly. First, a pin-cell calculation was carried out to validate the RRP by comparing with Statistical Geometry (STG) model of MVP code. After that, the comparison between the RRP model (MCNP) and STG model (MVP) was shown in whole core criticality calculation, not only for the annular core but also for the fully-loaded core. The comparison of numerical results showed that the RRP model and STG model differed insignificantly in the multiplication factor as expected, regardless of the pin-cell or whole core calculations. In addition, the RRP model did not make the calculation time increase a lot in comparison with the conventional regular model (uniform arrangement).

口頭

Development of realized random model for coated fuel particle of prismatic HTGR

Ho, H. Q.; 本多 友貴; 後藤 実; 高田 昌二; 石塚 悦男

no journal, , 

The Monte-Carlo MCNP code does not provide an appropriate model to simulate random arrangement of coated fuel particles (CFPs) in the fuel compact of high temperature engineering test reactor (HTTR). This study developed a MCNP model for the HTTR by using an explicit random method, namely realized random packing (RRP), to improve the accuracy of the benchmark assessment. Criticality results showed that by using the RRP model the accuracy of HTTR benchmark could be improved in comparison with the conventional uniform model.

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