In the realm of nuclear physics and energy research, a team of scientists from the Université Paris-Saclay in France has made strides in understanding the dynamics of nuclear fission, a process critical to nuclear energy production. The researchers, Alice Bernard, David Regnier, Junah Newsome, Paul Carpentier, Noël Dubray, and Nathalie Pillet, have developed a new method to predict the probability distribution functions (pdf) of certain fission observables, shedding light on the fluctuations that occur during this process.
Nuclear fission, the process by which a heavy nucleus splits into two smaller fragments, is a cornerstone of nuclear energy. Understanding the dynamics of this process is crucial for optimizing nuclear reactors and ensuring their safe operation. The researchers have focused on developing a Monte Carlo method, a statistical technique used to understand the behavior of complex systems, to investigate the fluctuations in fission observables.
The team’s work builds on recent advances in nuclear energy density functional frameworks (EDF), which have allowed for the computation of pdfs for observables such as particle number and angular momentum of the fragments. However, predicting the pdf of other observables, such as the total kinetic energy of the fragments, has remained a challenge. The researchers’ new method aims to address this gap by determining the complete pdf of a new category of observables from a Bogoliubov vacuum projected onto good particle number.
The method relies on sampling nucleonic configurations in coordinate and intrinsic-spin representation. The researchers assessed the feasibility and convergence properties of the method and applied it to states representative of the scission of an actinide, a group of metallic elements that includes uranium and plutonium, commonly used in nuclear reactors. They analyzed fluctuations in fragment shapes, inter-fragment Coulomb and nuclear interaction, as well as the corresponding torques.
The findings suggest that a significant fraction of the fluctuation of several measured fission observables is already present within the mean-field picture. This insight could have practical applications for the energy sector, particularly in the design and operation of nuclear reactors. By better understanding the fluctuations in fission observables, engineers and scientists can optimize reactor performance, improve safety measures, and enhance the overall efficiency of nuclear energy production.
The research was published in the journal Physical Review C, a leading publication in the field of nuclear physics. The study represents a significant step forward in the understanding of nuclear fission dynamics and highlights the potential of advanced computational methods in addressing complex challenges in the energy sector.
This article is based on research available at arXiv.