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Nucleon-ion and ion-ion collisions at non relativistic bombarding energies can be described by means of Monte Carlo approaches, such as those based on the Quantum Molecular Dynamics (QMD) model. We have developed a QMD code, to simulate the…

Nuclear Theory · Physics 2008-09-14 M. V. Garzelli

The propagation of uncertainties in reaction cross sections and rates of neutron-, proton-, and alpha-induced reactions into the final isotopic abundances obtained in nucleosynthesis models is an important issue in studies of…

High Energy Astrophysical Phenomena · Physics 2025-01-07 T. Rauscher , N. Nishimura , G. Cescutti , R. Hirschi , A. St. J. Murphy , C. Travaglio

Virtual experiments (VEs), a modern tool in metrology, can be used to help perform an uncertainty evaluation for the measurand. Current guidelines in metrology do not cover the many possibilities to incorporate VEs into an uncertainty…

Applications · Statistics 2024-04-18 Finn Hughes , Manuel Marschall , Gerd Wübbeler , Gertjan Kok , Marcel van Dijk , Clemens Elster

The potential for mis-modeling of $\nu_{\mu}$/$\nu_{e}$, $\bar{\nu}_{\mu}$/$\bar{\nu}_{e}$ and $\nu_{e}$/$\bar{\nu}_{e}$ cross section ratios due to nuclear effects is quantified by considering model spread within the full kinematic phase…

High Energy Physics - Phenomenology · Physics 2023-04-06 T. Dieminger , S. Dolan , D. Sgalaberna , A. Nikolakopoulos , T. Dealtry , S. Bolognesi , L. Pickering , A. Rubbia

A Monte Carlo-based Bayesian inference model is applied to the prediction of reactor operation parameters of a PWR nuclear power plant. In this non-perturbative framework, high-dimensional covariance information describing the uncertainty…

In this work, we study the uncertainty of nuclear model parameters for neutron induced ^{56}Fe reactions in fast neutron region by using the Total Monte Carlo method. We perform a large number of TALYS runs and compare the calculated…

Aims. Numerical test-particle simulations are a reliable and frequently used tool to test analytical transport theories and to predict mean-free paths. The comparison between solutions of the diffusion equation and the particle flux is used…

High Energy Astrophysical Phenomena · Physics 2016-02-17 R. C. Tautz , J. Bolte , A. Shalchi

We present a simple comparative framework for testing and developing uncertainty modeling in uncertain marching cubes implementations. The selection of a model to represent the probability distribution of uncertain values directly…

Human-Computer Interaction · Computer Science 2024-09-16 Robert Sisneros , Tushar M. Athawale , David Pugmire , Kenneth Moreland

As the sensitivity and uncertainty analysis of nuclear system can provide more confident bounds for the Best-estimate Prediction used to assess the performance and safety of nuclear plant, the uncertainty and sensitivity analysis has been a…

Applied Physics · Physics 2017-04-24 JiaYi Xu , Xu Bo Ma , Fan Lu , Yi Xue Chen

The measurement of the beta asymmetry parameter in nuclear beta decay is a potentially very sensitive tool to search for non V-A components in the charge-changing weak interaction. To reach the required precision (percent level) all effects…

Automated vehicles require the ability to cooperate with humans for smooth integration into today's traffic. While the concept of cooperation is well known, developing a robust and efficient cooperative trajectory planning method is still a…

Multiagent Systems · Computer Science 2022-11-15 Philipp Stegmaier , Karl Kurzer , J. Marius Zöllner

Uncertainties of fission fraction is an important uncertainty source for the antineutrino flux prediction in a reactor antineutrino experiment. A new MC-based method of evaluating the covariance coefficients between isotopes was proposed.…

High Energy Physics - Experiment · Physics 2017-01-04 X. B. Ma , R. M. Qiu , Y. X. Chen

The issue of how epistemic uncertainties affect the outcome of Monte Carlo simulation is discussed by means of a concrete use case: the simulation of the longitudinal energy deposition profile of low energy protons. A variety of…

Computational Physics · Physics 2010-12-16 Maria Grazia Pia , Marcia Begalli , Anton Lechner , Lina Quintieri , Paolo Saracco

Recent work has provided the means to rigorously determine properties of super-hadronic matter from experimental data through the application of broad scale modeling of high-energy nuclear collisions within a Bayesian framework. These…

Nuclear Theory · Physics 2016-03-23 Evan Sangaline , Scott Pratt

The effects of the nuclear structure uncertainties on the description of processes induced by coherent scattering of neutrinos on nuclei are investigated. A reference calculation based on a specific nuclear model is defined and the cross…

Nuclear Theory · Physics 2020-05-06 G. Co' , M. Anguiano , A. M. Lallena

Aleatoric uncertainty quantification seeks for distributional knowledge of random responses, which is important for reliability analysis and robustness improvement in machine learning applications. Previous research on aleatoric uncertainty…

Machine Learning · Computer Science 2022-06-10 Ziyi Huang , Henry Lam , Haofeng Zhang

Sources of uncertainty are reviewed for calculated atomic and molecular data that are important for plasma modeling: atomic and molecular structure and cross sections for electron-atom, electron-molecule, and heavy particle collisions. We…

Based on Monte Carlo approach and conventional error analysis theory, taking the heaviest doubly magic nucleus $^{208}$Pb as an example, we firstly evaluate the propagated uncertainties of universal potential parameters for three typical…

Nuclear Theory · Physics 2021-02-02 Zhen-Zhen Zhang , Hua-Lei Wang , Hai-Yan Meng , Min-Liang Liu

Nuclear reactions induced by muon neutrino with energies in the range from 0.2 to 1.5 GeV in Monte Carlo calculations framework in the intra-nuclear cascade model are studied. This study was done by comparison between the available…

New physics contributions to the (anti)neutrino-nucleon elastic scattering process can be constrained by precision measurements, with controlled Standard Model uncertainties. In a large class of new physics models, interactions involving…

High Energy Physics - Phenomenology · Physics 2024-05-24 Oleksandr Tomalak , Minerba Betancourt , Kaushik Borah , Richard J. Hill , Thomas Junk