Development of Power Reconstruction Method in Lead Cooled Fast Reactor Code System Mosasaur

16 Pages Posted: 9 Nov 2024

See all articles by Bin Zhang

Bin Zhang

affiliation not provided to SSRN

Lianjie Wang

affiliation not provided to SSRN

Lei Lou

affiliation not provided to SSRN

Chen Zhao

affiliation not provided to SSRN

Abstract

A power reconstruction method was researched based on the Lead cooled fast reactor (LFR) simulation code system MOSASAUR, which is focused on the neutron parameters required for thermal hydraulic analysis, fuel performance analysis and so on. In the previous version of MOSASAUR, cross-sections generation module and core simulation module have been developed, which is focused on both core steady-state and transient analyses of LFR. The equivalent one-dimensional method is utilized to generate the form factors of fuel assembly in the cross-sections generation module. The modulation method is employed to get the intra-nodal flux of the coarser mesh core simulator module. In this research, the core neutron flux distribution is expressed as the product of the axial and radial flux. The axial neutron flux distribution is represented by the cosine function, and the radial flux distribution is represented by the polynomial function. The lead bismuth fast reactor core problem based on SVBR and 70-fuel-subassembly core problem of JOYO benchmark are employed to verify the accuracy of power reconstruction calculation. Numerical results showed the good accuracy of the newly-developed power reconstruction module with MOSASAUR.

Keywords: Power reconstruction, Lead cooled fast reactor, Form factors, Modulation method, MOSASAUR

Suggested Citation

Zhang, Bin and Wang, Lianjie and Lou, Lei and Zhao, Chen, Development of Power Reconstruction Method in Lead Cooled Fast Reactor Code System Mosasaur. Available at SSRN: https://ssrn.com/abstract=5015580 or http://dx.doi.org/10.2139/ssrn.5015580

Bin Zhang (Contact Author)

affiliation not provided to SSRN ( email )

Lianjie Wang

affiliation not provided to SSRN ( email )

Lei Lou

affiliation not provided to SSRN ( email )

Chen Zhao

affiliation not provided to SSRN ( email )

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