With the advancement of nuclear technology applications, the demand for irradiation resources continues to grow. As China's primary civilian irradiation platform, optimizing the utilization of in-core irradiation resources in the minjiang test reactor (MJTR) necessitates precise core physics calculations. Prolonged operation of the MJTR has led to neutron irradiation-induced accumulation of neutron-absorbing poisons in the beryllium reflector and control rod followers, which exacerbates deviations in fuel management simulations.

This study aims to quantify the beryllium-derived poison inventory, evaluate its impact on core neutronics, and mitigate computational inaccuracies.

The MJTR 28-1 core was selected as the research object. A dynamic beryllium poison accumulation model was established based on its geometric configuration, operational characteristics, and beryllium-neutron interaction mechanisms. Then, the Monte Carlo N-Particle (MCNP) code was applied to neutron transport simulation. Key parameters, including thermal neutron flux distribution uniformity, reactivity effects, and neutron spectrum hardening in the active core and irradiation channels, were analyzed. Finally, experimental validation was conducted through cold subcriticality measurements and axial thermal neutron flux profiling in channels 2# and 4#.

Simulation results show that accumulated beryllium poison leads to a reactivity difference of 0.032 45 between poison-free and fully decayed scenarios, and spectrum hardening occurs in the active core and irradiation channels, evidenced by elevated epithermal-to-thermal neutron ratios. Thermal neutron flux homogeneity improves in the active zone due to enhanced neutron moderation. Cold subcriticality calculation deviation is reduced to approximately 1.5β_eff. Simulated axial flux distributions in 2# and 4# channels align closely with experimental data, demonstrating the fidelity of beryllium poison accumulation model.

Incorporating beryllium poison dynamics into core physics simulations significantly enhances computational accuracy. This refinement enables precise irradiation dose forecasting for samples, thereby improving the operational safety and economic efficiency of the MJTR. The methodology provides a paradigm for neutronics modeling in research reactors with beryllium-based components.