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DOE OSTI2016

The MCNP6 Analytic Criticality Benchmark Suite

Analytical benchmarks provide an invaluable tool for verifying computer codes used to simulate neutron transport. Several collections of analytical benchmark problems [1-4] are used routinely in the verification of production Monte Carlo codes such as MCNP® [5,6]. Verification of a computer code is a necessary prerequisite to the more complex validation process. The verification process confirms that a code performs its intended functions correctly. The validation process involves determining the absolute accuracy of code results vs. nature. In typical validations, results are computed for a set of benchmark experiments using a particular methodology (code, cross-section data with uncertainties, and modeling) and compared to the measured results from the set of benchmark experiments. The validation process determines bias, bias uncertainty, and possibly additional margins. Verification is generally performed by the code developers, while validation is generally performed by code users for a particular application space. The VERIFICATION_KEFF suite of criticality problems [1,2] was originally a set of 75 criticality problems found in the literature for which exact analytical solutions are available. Even though the spatial and energy detail is necessarily limited in analytical benchmarks, typically to a few regions or energy groups, the exact solutions obtained can be used to verify that the basic algorithms, mathematics, and methods used in complex production codes perform correctly. The present work has focused on revisiting this benchmark suite. A thorough review of the problems resulted in discarding some of them as not suitable for MCNP benchmarking. For the remaining problems, many of them were reformulated to permit execution in either multigroup mode or in the normal continuous-energy mode for MCNP. Execution of the benchmarks in continuous-energy mode provides a significant advance to MCNP verification methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Criticality Calculations with MCNP6 - Practical Lectures

These slides are used to teach MCNP (Monte Carlo N-Particle) usage to nuclear criticality safety analysts. The following are the lecture topics: course information, introduction, MCNP basics, criticality calculations, advanced geometry, tallies, adjoint-weighted tallies and sensitivities, physics and nuclear data, parameter studies, NCS validation I, NCS validation II, NCS validation III, case study 1 - solution tanks, case study 2 - fuel vault, case study 3 - B&W core, case study 4 - simple TRIGA, case study 5 - fissile mat. vault, criticality accident alarm systems. After completion of this course, you should be able to: Develop an input model for MCNP; Describe how cross section data impact Monte Carlo and deterministic codes; Describe the importance of validation of computer codes and how it is accomplished; Describe the methodology supporting Monte Carlo codes and deterministic codes; Describe pitfalls of Monte Carlo calculations; Discuss the strengths and weaknesses of Monte Carlo and Discrete Ordinants codes; The diffusion theory model is not strictly valid for treating fissile systems in which neutron absorption, voids, and/or material boundaries are present. In the context of these limitations, identify a fissile system for which a diffusion theory solution would be adequate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Validation of MCNP6 Version 1.0 with the ENDF/B-VII.1 Cross Section Library for Uranium Metal, Oxide, and Solution Systems on the High Performance Computing Platform Moonlight

In this document, the code MCNP is validated with ENDF/B-VII.1 cross section data under the purview of ANSI/ANS-8.24-2007, for use with uranium systems. MCNP is a computer code based on Monte Carlo transport methods. While MCNP has wide reading capability in nuclear transport simulation, this validation is limited to the functionality related to neutron transport and calculation of criticality parameters such as k eff .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

(U) Differences in the Use of Isotopic $χ$ Vectors Demonstrated with an Analytic k ∞ Problem (And Verification of SENSMG and MCNP6’s KSEN)

Comparisons of responses and first-order sensitivities of responses to the neutron fission spectrum ( χ ) have been done using different transport methods. Kodeli and Slavič compared sensitivities from Monte Carlo, deterministic, and method of characteristics of k eff in the SNEAK-7 benchmark, and the agreement was reasonable. Yamamoto compared deterministic and Monte Carlo sensitivities of k - and α -eigenvalues to the fission χ , but only for material (i.e. single-isotope) values of the fission χ . Haeck et al. compared Monte Carlo and deterministic sensitivities of k eff to the fission χ of individual isotopes for several benchmarks, and the agreement was excellent (except, strangely, for U-236). Kiedrowski and Brown compared Monte Carlo and analytic sensitivities of k ∞ to the fission χ in analytic problems, but only for material values of the fission χ .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Recalculation of Soil Bulk Density Used in the Scorpius MCNP6 Model

The soil composition used in the Scorpius MCNP6.2 (Ref. 1) model was recently recalculated. Originally, it was “determined using the United States Geological Survey (USGS) Mercury Core Library and the Nevada National Security Site U.S. Geological Survey Databases (NNSS USGS) and Nevada National Security Site Petrographic, Geochemical, and Geophysical Database (NNSS PGG),” but the details had been lost. Reference 2 documents the updated soil composition determination. Reference 2 estimated the grain density of the soil instead of the bulk density. This report corrects that error. I am indebted to Garrett Euler (EES-17) for reading Ref. 2, pointing out its errors, and guiding me through the correct calculations. This report is organized as follows. For completeness, the composition calculations from Ref. 2 are repeated: Sec. II discusses the data that are reported in the PGG Access database, and Sec. III uses the data in the PGG Access database to compute the composition of the soil. Section IV estimates the bulk density of the soil. Section V evaluates the soil wall thickness in the Scorpius model. Section VI estimates the effect of the soil density change on previously calculated results. Section VII presents a summary and conclusions. Input files and output files are listed in appendices.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Recent MCNP6 ® Code Developments and Improvements for Nuclear Engineering Applications [Slides]

The Los Alamos MCNP Monte Carlo radiation transport code has been the international gold standard for particle transport applications for over three decades. Many developments to the code have taken place with several significant new feature additions, major improvements, and enhancements to existing features. With significant institutional and programmatic investment in the code since the time of the last public release in 2018, important code development and infrastructure modernization has taken place and remains a high priority for all ongoing efforts across the code development team.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

MCNP6 Developments: A 2022-23 Year in Review [Slides]

A separate MCNP6.3 V&V document reports on all the default calculations for all test suites is touched on. This report does not include the subcritical multiplication benchmark suite. After some additional clean-up and finalizing the post-processing and documentation steps, the subcritical multiplication benchmark suite will be released in the next version of our vnvstats repository. We tested the new HDF5 PTRAC feature in MCNP6.3 and found encouraging outcomes. Identical results coming out of the simulation with respect to the legacy PTRAC results. The overall runtime for all simulations is reduced by ~20% with the new HDF5 PTRAC capability. We consider giving the new HDF5 PTRAC features a try and using it for all subcritical multiplication and any other relevant (PTRAC) calculations.

97 MATHEMATICS AND COMPUTING↗