The study of the nuclear equation of state (EoS) is one of the primary goals of experimental and theoretical heavy-ion physics. The comparison of recent high-statistics data from the STAR Collaboration with transport models provides a unique possibility to address this topic in a yet-unexplored energy domain. Employing the microscopic N -body parton-hadron-quantum-molecular dynamics transport approach, which allows us to describe the propagation and interactions of hadronic and partonic degrees of freedom, including cluster and hypernucleus formation and dynamics, we investigate the influence of different EoS on bulk observables, the multiplicity, p T , and rapidity distributions of protons, Λ s and clusters up to A = 4, as well as their influence on the collective flow. We explore three different EoS: two static EoS, dubbed “soft” and “hard,” which differ in the compressibility modulus, as well as a soft momentum-dependent EoS. We find that a soft momentum-dependent EoS reproduces most baryon and cluster observables, including the flow observables, quantitatively; however, hard EoS show a similar trend.
Nucleosynthesis reaction networks leading to p nuclei involve a combination of different types of photo-disintegration and capture reactions, as well as beta + decays or electron captures. Photodisintegration reactions involving alpha particles present a particular interest as they serve as branching points of the reaction networks. The cross sections of these reactions depend crucially on the alpha-nucleus interaction. The alpha-optical model potential (AOMP) is determined mostly by means of experimental differential elastic scattering distributions. Several previous studies have focused on the case of 144Sm, an intriguing p nucleus that is semimagic with 82 neutrons. This work presents new experimental data on alpha elastic and inelastic scattering on 148Sm, its closest stable isotope. Isotopic effects on the description of the AOMP are studied, as well as their consequences on the prediction of alpha-induced reaction cross sections at astrophysical energies. It is shown that the isotopic ratio for (alpha, gamma) cross sections can be multiplied up to a factor of two when these effects are included.
The FALSTAFF spectrometer designed to detect fission fragments in direct kinematics, is a key instrument for advancing the understanding of neutron-induced fission in the MeV energy range. It employs a 2V–2EV technique, combining time-of-flight measurements with Secondary Electron Detectors (SeDs) and calorimetry in an axial ionization chamber, to determine fragment velocities and residual energies on an event-by-event basis. Preliminary results of the measurements performed at the Neutron For Science (NFS) facility of GANIL/SPIRAL2 over a neutron energy range of 0.5–40 MeV, are discussed.
France's nuclear reactor fleet forms a substantial component of its electricity generation mix, making load-following operation of nuclear power plants essential to balance supply and demand on the grid. This need for flexibility has increased due to the growing share of intermittent renewable energy sources. In response, active research is directed toward optimizing load-following reactor control.This work addresses this challenge by solving a bi-objective unit-commitment problem, employing metamodels that approximate the physical constraints simulated by ALGO, a load-following simulator based on APOLLO3 (R) for the neutronics parts and on its own modeling of the mode 'G' and of the secondary circuit. One evaluation by these metamodels runs up to eight orders of magnitude faster than one evaluation with ALGO while maintaining, with the best models, average relative errors below 2%. The generation time of their learning database was three orders of magnitude lower than solving a three-reactor unit-commitment problem once with ALGO on 96 h of simulated operation.The best performing metamodel was a histogram-based gradient boosting regression tree using at least 53 h of operational history as input for the best Pareto front estimation. This approach offers a practical solution for optimizing load-following operations across a fleet of reactors based on technical criteria related to increasing the safety and operational margins.Beyond the baseline optimization, we also explore methods to iteratively specialize the metamodel to better fit a target fleet-level power profile by coupling metamodel-assisted optimization with selective reevaluation of data points by ALGO. This process incrementally augments the training and testing databases. The coupled approach allowed us to improve the hypervolume of the initially obtained Pareto front by up to 83% with a single test. This work also gave us insights into general principles to follow for the dispatch of a fleet of nuclear power plants.
