Roy Gross, Johan Cufe, Daniele Tomatis, Erez Gilad, “Comprehensive investigation of the Ronen method in slab geometry,” Nuclear Engineering and Technology 55(2), 2023, 734-748, https://doi.org/10.1016/j.net.2022.09.026.
Greetings, fellow scientists. Today, we present our investigation of the Ronen method, a powerful tool for solving neutron transport problems. Our team, consisting of Ph.D. students Roy Gross and Johan Cufe and our Ph.D. advisors Dr. Daniele Tamotis from Newcleo SrL, Torino, Italy, and Prof. Erez Gilad from Ben-Gurion University, aimed to test the effectiveness of the Ronen Method in various scenarios.
Our comprehensive investigation focused on homogeneous and heterogeneous slab problems from the Sood benchmark, including isotropic and linearly-anisotropic problems. We exercised three finite difference implementations, which were compared to reference solutions using one and two energy groups. Our results demonstrate that the Ronen method provides significantly improved accuracy in a wide range of problems compared to other neutron diffusion methods.
We validated our findings by examining the criticality eigenvalue and the fundamental eigenfunction, i.e., the neutron flux distribution. For standard convergence tolerances, we found that the maximal deviation in criticality eigenvalue was less than ten pcm, and the maximal deviation in the spatial distribution of the flux was less than 2%, always located near sharp interfaces or vacuum boundaries.
The Ronen method has proven to be an effective tool for solving neutron transport problems with high accuracy using a fraction of the time and computer resources compared to full transport methods. We hope our findings will inspire further research in this field. Thank you for joining us on this scientific journey, and we hope our findings will help you in your own research endeavors.
* Roy Gross thanks the Israel Ministry of Energy for its support as part of the scholarship program for undergraduate and graduate students in energy-related fields, contract no. 219-11-045. Johan Cufe thanks FRAMATOME for its support as part of a collaboration agreement regarding this research, Grant number: FRA-21-002-RM.