A5079340496- Nuclear reactor physics and engineering
- Nuclear Physics and Applications
- Nuclear Materials and Properties
- Graphite, nuclear technology, radiation studies
- Probabilistic and Robust Engineering Design
- Nuclear and radioactivity studies
- Radiation Detection and Scintillator Technologies
- Radiation Effects in Electronics
- Radiative Heat Transfer Studies
- Nuclear physics research studies
- Statistical Methods and Inference
- VLSI and Analog Circuit Testing
- Nuclear Engineering Thermal-Hydraulics
- Mathematical Approximation and Integration
- Particle Detector Development and Performance
- Advanced Chemical Physics Studies
- Scientific Measurement and Uncertainty Evaluation
- Semiconductor materials and devices
- Particle accelerators and beam dynamics
- Magnetic confinement fusion research
- Electron and X-Ray Spectroscopy Techniques
- Markov Chains and Monte Carlo Methods
- Superconducting Materials and Applications
- Radiation Therapy and Dosimetry
- Fault Detection and Control Systems
Los Alamos National Laboratory
2010-2021
University of Michigan
2015-2021
European Commission
2018
Joint Research Center
2018
Computational Physics (United States)
2011-2014
Los Alamos National Security (United States)
2014
University of Wisconsin–Madison
2008-2009
Fusion Academy
2008
Fusion (United States)
2008
We describe the new ENDF/B-VIII.0 evaluated nuclear reaction data library. fully incorporates IAEA standards, includes improved thermal neutron scattering and uses from CIELO project for reactions on 1H, 16O, 56Fe, 235U, 238U 239Pu described in companion papers present issue of Nuclear Data Sheets. The evaluations benefit recent experimental obtained U.S. Europe, improvements theory simulation. Notable advances include updated light nuclei, structural materials, actinides, fission energy...
MCNP6 is simply and accurately described as the merger of MCNP5 MCNPX capabilities, but it much more than sum those two computer codes. result five years effort by code development teams. These groups people, residing in Los Alamos National Laboratory's (LANL) X Computational Physics Division, Monte Carlo Codes Group (XCP-3), Decision Applications Radiation Transport Team (D-5), respectively, have combined their efforts to produce next evolution MCNP. While maintenance bug fixes will...
A Monte Carlo method is developed that performs adjoint-weighted tallies in continuous-energy k-eigenvalue calculations. Each contribution to a tally score weighted by an estimate of the relative magnitude fundamental adjoint mode, way iterated fission probability, at phase-space location contribution. The designed around power iteration such no additional random walks are necessary, resulting minimal increase computational time. implemented N-Particle (MCNP) code. These used calculate...
The CIELO collaboration has studied neutron cross sections on nuclides that significantly impact criticality in nuclear technologies - 235,238U, 239Pu, 56Fe, 16O and 1H with the aim of improving accuracy data resolving previous discrepancies our understanding. This multi-laboratory pilot project, coordinated via OECD/NEA Working Party Evaluation Cooperation (WPEC) Subgroup 40 support also from IAEA, motivated experimental theoretical work led to suites new evaluated libraries accurately...
An integrated study of compact stellarator power plants, ARIES-CS, has been conducted to explore attractive configurations and define key research development (R&D) areas. The large size mass predicted by earlier plant studies had led cost projections much higher than those the advanced tokamak plant. As such, first major goal ARIES-CS was investigate if plants can be made comparable in variants while maintaining desirable properties. fusion core components would have complex shapes...
A continuous-energy Monte Carlo method is developed to compute adjoint-based k-eigenvalue sensitivity coefficients with respect nuclear data. The implemented into MCNP6 and based upon similar methodologies used other adjoint-weighted quantities. tallies employed are explained. Verification of the performed by comparing results analytic solutions, direct density perturbations, those from software packages such as TSUNAMI-3D MONK. Results solutions agree within a few tenths percent. Direct...
Nuclear criticality safety analysis using computational methods such as a Monte Carlo method must establish, for defined area of applicability, an upper subcritical limit (USL), which is calculated multiplication factor k that can be treated actually and derived from calculational margin (combination bias uncertainty) subcriticality. Whisper, nonparametric, extreme-value based on sensitivity/uncertainty techniques the associated software are presented. Whisper uses benchmark critical...
Evaluations of nuclear reaction data for the major uranium isotopes 238U and 235U were performed within scope CIELO Project on initiative OECD/NEA Data Bank under Working Party Evaluation Co-operation (WPEC) Subgroup 40 coordinated by IAEA Nuclear Section. Both mean values covariances are evaluated from 10−5 eV up to 30 MeV. The resonance parameters re-evaluated with addition newly available existing experimental database. evaluations in fast neutron range based model calculations code...
Since the 1960s, Monte Carlo methods have been used to compute effect of perturbations on system responses and for computing sensitivity coefficients. This review article focuses 21st-century developments specific k-eigenvalue calculations. The theory correlated sampling, differential operator adjoint-based approaches their historical from 20th century are briefly summarized. Specific focus is given four recent significant developments: fission source correction using sampling methods, k...
The energy spectra of neutrons emitted promptly in the neutron-induced fission reactions 235U and 239Pu were re-evaluated for ENDF/B-VIII.0. These evaluations are based on a careful modeling all relevant physics processes, an extensive analysis experimental data detailed quantification pertinent uncertainties. Energy up to fourth chance considered both compound pre-equilibrium processes included. Also, important nuclear model parameters, such as average total kinetic fragments multiple...
Within the ARIES-CS project, design activities have focused on developing first compact device that enhances attractiveness of stellarator as a power plant. The objectives this paper are to review nuclear elements received considerable attention during process and provide perspective their successful integration into final design. Among these radial build definition, well-optimized in-vessel components satisfy ARIES top-level requirements, carefully selected engineering parameters produce an...
The evaluation of uncertainties is essential for criticality safety. This paper deals with material density and composition provides guidance on how traditional first-order sensitivity methods can be used to predict their effects. Unlike problems that deal cross-section uncertainty analysis, composition-related are often characterized by constraints do not allow arbitrary independent variations the input parameters. Their proper handling requires constrained sensitivities take into account...
We describe recent experience and results from implementing a fission matrix capability into the MCNP Monte Carlo code. The can be used to provide estimates of fundamental mode distribution, dominance ratio, eigenvalue spectrum, higher forward adjoint eigenfunctions neutron source distribution. It also accelerate convergence power method iterations basis functions for higher-order perturbation theory. higher-mode sources in determine fluxes tallies, work is underway adjoint-weighted tallies....
Recent research has focused on the development of surrogate models for radiation source localization in a simulated urban domain. We employ Monte Carlo N-Particle (MCNP) code to provide high-fidelity simulations transport within an The model is constructed location (x,y,z) as input and return estimated count rate set specified detector locations. Because MCNP are computationally expensive, we develop efficient accurate responses. construct using Gaussian processes neural networks that train...