相关论文: A Bayesian-Neural-Network Prediction for Fragment …
The Bayesian neural network (BNN) method is used to construct a predictive model for fragment prediction of proton induced spallation reactions with the guidance of a simplified EPAX formula. Compared to the experimental data, it is found…
Large-scale computations of fission properties play a crucial role in nuclear reaction network calculations simulating rapid neutron-capture process (r-process) nucleosynthesis. Due to the large number of fissioning nuclei contributing to…
One of considered nowadays scenarios of proton - nucleus reaction is spallation. Its motivation is based on experimental final-state observations of one heavy nucleus, a small number of light fragments and numerous individual nucleons. It…
Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction…
Accurate modeling of neutron-induced (n,p) reaction cross sections is essential for diverse applications in nuclear physics, including reactor design, nuclear astrophysics, and radionuclide production. However, experimental data are often…
We exploit the great potential offered by Bayesian Neural Networks (BNNs) to directly decipher the internal composition of neutron stars (NSs) based on their macroscopic properties. By analyzing a set of simulated observations, namely NS…
Activation cross sections of proton induced nuclear reactions on palladium were measured up to 80 MeV by using the stacked foil irradiation technique and gamma ray spectrometry. The beam intensity, the incident energy and the energy…
Mostly for the purpose of applications for the energy and the environment and for the design of sources of neutrons or exotic nuclides, intense research has been dedicated to spallation, induced by protons or light projectiles at incident…
Bayesian neural network (BNN) approach is employed to improve the nuclear mass predictions of various models. It is found that the noise error in the likelihood function plays an important role in the predictive performance of the BNN…
Besides their intrinsic nuclear-structure value, nuclear mass models are essential for astrophysical applications, such as r-process nucleosynthesis and neutron-star structure. To overcome the intrinsic limitations of existing…
We investigate the prompt emission of few intermediate-mass fragments in spallation reactions induced by protons and deuterons in the 1 GeV range. Such emission has a minor contribution to the total reaction cross section, but it may…
The dynamics of high-energy proton-induced spallation reactions on target nuclides of $^{136}$Xe, $^{59}$Ni, $^{56}$Fe, $^{208}$Pb, $^{184}$W, $^{181}$Ta, $^{197}$Au and $^{112}$Cd, are investigated with the quantum molecular dynamics…
The production cross sections of various fragments from proton-induced reactions on $^{56}$Fe and $^{27}$Al have been analyzed by the Quantum Molecular Dynamics (QMD) plus Statistical Decay Model (SDM). It was found that the mass and charge…
Use of deuteron-induced spallation reactions at intermediate energies has recently been proposed for transmutation of several long-lived fission products (LLFPs). In the design study of a transmutation system using a deuteron primary beam,…
A method is proposed for the experimental measurement of neutron separation energies for nuclei far from stability. The procedure is based on determining cross sections for the production of nuclei, by projectile fragmentation, for which…
In this study, a Bayesian Network (BN) is considered to represent a nuclear plant mechanical system degradation. It describes a causal representation of the phenomena involved in the degradation process. Inference from such a BN needs to…
Spallation neutron production in proton induced reactions on Al, Fe, Zr, W, Pb and Th targets at 1.2 GeV and on Fe and Pb at 0.8, and 1.6 GeV measured at the SATURNE accelerator in Saclay is reported. The experimental double-differential…
Fission product yields are key infrastructure data for nuclear applications in many aspects. It is a challenge both experimentally and theoretically to obtain accurate and complete energy-dependent fission yields. We apply the Bayesian…
We present a statistical-model description of fission, in the framework of compound-nucleus decay, which is found to simultaneously reproduce data from both heavy-ion-induced fusion reactions and proton-induced spallation reactions at…
The limits of the nuclear landscape are determined by nuclear binding energies. Beyond the proton drip lines, where the separation energy becomes negative, there is not enough binding energy to prevent protons from escaping the nucleus.…