Wilcox, T. A. | Search NASA

DOE OSTI2016

MCNP 6.2.0 Delayed-Particle Production Improvements

Development began on a delayed-particle physics package for the Monte Carlo Radiation transport code MCNPX in 2004 incorporating the CINDER90 depletion code and delayed particle libraries. When MCNP5 was merged with MCNPX to form MCNP6 in 2010, this delayed-particle capability was passed on and has been continuously improved in subsequent versions of MCNP6. Today, the delayed-particle feature in MCNP6 allows for the production of delayed neutrons, gammas, betas, and alpha particles. Future development includes the addition of delayed-positron production in the next release of MCNP6. Delayed particles can be sampled with MCNP using the ACT card in conjunction with the FISSION and NONFISS keywords. The user can specify one or more of the four available delayed-particle types mentioned above on one or both of the FISSION and NONFISS keywords. If a delayed-particle type is selected on the FISSION keyword, then delayed production of that particle from fission products and their progeny will be produced. Likewise, if a delayed-particle type is selected on the NONFISS keyword then delayed production of that particle from non-fission interactions and spontaneous decay will be produced. In some cases, the sheer number of delayed particles that can be produced from nuclear reactions and spontaneous decay (i.e. hundreds of delayed gamma lines when spontaneous fission is possible) can make it difficult to achieve converged solutions in an efficient and timely manner. Truncation methods are the simplest form of variance reduction and can be used to decrease convergence times by limiting calculations to the phase space of interest. This paper introduces several such truncation methods that allow the user to restrict the number of possible delayed particles available for sampling to only those of interest in the problem. It is important to stress that the use of any truncation method should be verified by first assessing the impact of the truncated particles (i.e. by disabling the truncation) for one or more baseline cases. In addition to these new methods, a new delayed-gamma sampling algorithm implemented in MCNP 6.2.0 is introduced. Comparisons to ENDF data and analytical benchmarking with the new algorithm show a substantial improvement in accuracy over previous versions. New improvements to the delayed-particle capability have been added to MCNP 6.2.0. These improvements include an updated treatment of the THRESH keyword which omits delayed-particle lines below a set amplitude, and addition of the PECUT and HLCUT keywords which allow the user to truncate delayed-particles lines based on energy and half-life, respectively. The delayed-gamma sampling algorithm has also been improved to allow exact energy sampling. Comparisons of MCNP calculations directly to ENDF data and analytical benchmarks have verified the significant improvement in the new delayed gamma sampling algorithm. (authors)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Predicting Future Solar Modulation and Implementation in MCNP6

The application of detecting low level radiation in the field requires quantification of the natural radiation background specific to that location. This background is made up two primary components: naturally decaying radionuclides in the soil and atmosphere known as terrestrial background, and the particle cascades caused by high energy cosmic radiation interacting within the earth's atmosphere known as cosmic background. The terrestrial component dominates the background spectrum below approximately 2 MeV, however, the cosmic component comprises the entirety of the high-energy spectrum. Furthermore, the terrestrial component is relatively constant for a given location while the cosmic component is heavily dependent on solar activity, an effect known as solar modulation. Annual values of the solar modulation parameter, φ, have been determined since 1936, and their fluctuations are seen to be roughly sinusoidal over time. If one wished to predict or simulate the outcome of an experiment in the future, a prediction for the solar modulation would be necessary to accurately determine the cosmic background contribution. The previous version 6.1.1 of MCNP contained solar modulation data for 46 years between 1960 and 2005. This data was updated with newer solar modulation data, from I. G. Usoskin et al., which reports solar modulation data for an additional 33 years between 1936 and 2014. In order to use past solar modulation data to predict cosmic background radiation fluctuations for dates beyond 2014 an algorithm was developed to forecast future solar modulation data based on the sinusoidal behavior exhibited in recorded data. This algorithm was implemented into MCNP 6.1.2 to be used for cosmic background simulations and tested against benchmark data to assess its accuracy. (authors)

54 ENVIRONMENTAL SCIENCES↗