James Robert Tutt

135 Cs/ 137 Cs measurements were performed on a set of debris samples from the first nuclear test, Trinity. Debris from several locations around ground zero of the event were purified and analyzed for 135 Cs/ 137 Cs by thermal ionization mass spectrometry (TIMS). The Cs-isotopic measurements presented here are the first high precision TIMS 135 Cs/ 137 Cs measurements of trinitite from variable locations and cooling histories relative to ground zero. Our measurements show a large fractionation from the predicted fission yields, all with a relative enrichment in 137 Cs. 135 Cs/ 137 Cs ratios indicate that condensation times varied between different debris forms, however they are not consistent with an unfractionated decay to Cs from independent fission products. Variations in 135 Cs/ 137 Cs ratios are observed with relative distance from ground zero as well as 135 Cs/ 137 Cs heterogeneities between different trinitite lithologies within a single sample.

The delayed-gamma (DG) line-emission (line) sampling was first introduced into MCNPX in 2005. At the time, storage demands for problems with large numbers of DG lines was a major concern. In order to accommodate large amounts of line data while keeping the memory footprint of such a problem from exceeding memory limits, complicated logic was included to sift through various storage options. In mid-2015 concerns arose over the adequacy of the MCNP6 DG source option (inherited from MCNPX) with line sampling for modeling high-fidelity problems. One indication that there was a problem came when studying the MCNP6 produced DG spectra of U-238 and its progeny using high-fidelity spectroscopic tallies when compared to DG line amplitudes directly from ENDF/B-VII.1 emission data. Despite producing a correct integral number of gammas, the comparison to ENDF data showed a broadening in the energy lines and a reduction in the amplitude of more prominent lines. It was later found that the cause of this broadening was one of the memory-saving techniques used to store DG line data when problems required many DG lines. Specifically, the DG lines were integrated into fine energy bins for sampling. When a DG line was to be sampled, a random number would be used to choose which energy bin to sample based on emission probability. Once chosen, a second random number was used to perform nearest-line sampling in that bin. The integration of lines led to an oversampling of low-probability lines, especially when in close proximity to high-probability lines. This treatment also caused a similar issue with the time-dependent behavior of DG line emission which occurred when low-probability lines were sampled near high probability lines with the former decay constant being used. The effect on time-dependent gamma production was demonstrated in analytic benchmarks performed by Weldon et al.. To address these issues a new gamma line storage and sampling treatment was introduced in 2015. This new treatment, stores gamma emission data in a line-by-line CDF which is sampled directly, thereby resolving both the line-broadening issue, and the time-dependence issue as was demonstrated by Tutt el al.. In addition, the new DG sampling treatment was written to use dynamically dimensioned storage arrays as opposed to large fixed-dimensioned arrays, as in the former treatment, and also makes more efficient use of line data that is stored by reducing or eliminating repeated data. As a result, storage arrays are generated only for DG data relevant to the problem being executed. The result should be a reduction in both memory requirements and runtime. However, these reductions could not be realized until the logic for the old treatment could be removed. This paper provides an update on recent work which has focused on the removal of the old DG sampling logic and attempts to quantify the memory reduction and speed up of selected problems.

The general-purpose Monte Carlo radiation-transport code MCNP6{sup TM} came from the integration of MCNP5{sup TM} and MCNPX{sup TM}. The most recent release of MCNP, version 6.2.0, is scheduled for release in early 2017, which includes a variety of bug fixes and new features to the code. MCNP traditionally models nuclear reactions using Monte Carlo sampling techniques on measured and modeled cross-sectional data contained within ACE (A Compact Evaluated Nuclear Data File) libraries. In addition to reaction cross-sections, ACE libraries contain information relating to the production of secondary particles, such as secondary neutrons and photons. For example, an incident neutron on a nucleus can produce a nuclear reaction in the form (n, M{sub n}n'), where n is the incident neutron and M{sub n} is the number of secondary neutrons n' produced. Using this notation, different reactions can be described based on their neutron multiplicity, such as neutron capture (M{sub n} = 0), elastic and inelastic scattering (M{sub n} = 1), and reactions with multiple secondary neutrons (M{sub n} > 1). Accounting for secondary γ-rays emitted from the residual nuclei, this reaction can further be generalized as n, Mnn'M to describe a reaction producing M{sub n} neutrons and M -rays. These values M{sub n} and M are referred to as the neutron and multiplicities, respectively. ACE libraries contain the cross-sectional data for each reaction, and their corresponding statistically averaged multiplicities for neutrons and photons, M-bar{sub n} and M-bar{sub γ}. However, there are several limitations to reaction sampling using ACE libraries. First, the data contained within ACE libraries is limited by the accuracy of the model and/or experiment, which out of necessity can greatly simplify the true physics behind a reaction. For example, the value M{sub γ} in a (n, M{sub n}n'M{sub γ}γ) reaction is determined by the statistically averaged multiplicity M-bar{sub γ} instead of a distribution. Consequently, MCNP, unable to produce a continuous distribution, will utilizes a binary sampling around M-bar{sub γ}. While this sampling method provides a statistically average M{sub γ} over a large simulation, it is an inaccurate representation of an individual reaction and its corresponding secondary particles. Secondary neutrons are affected in a similar manner, such that different kinds of secondary neutrons can be sampled from the same interaction (eg., an inelastic neutron with an [n, 2n] neutron). Lastly, the random sampling technique for secondary particles remains completely independent of the sampled reaction, eliminating the ability to correlate secondary particles for a given reaction. To supplement these data libraries, additional codes and models describing certain nuclear reactions are employed. These codes can fill in the information missing from ACE, provide a better model to the true physics distribution, and can provide true correlated secondary particles, which has many useful applications in research and industry.

Secondary electrons in the form of delta-rays, also referred to as knock-on electrons, have been a feature of MCNP for electron and positron transport for over 20 years. While MCNP6 now includes transport for a suite of heavy-ions and charged particles from its integration with MCNPX, the production of delta-rays was still limited to electron and positron transport. In the newest release of MCNP6, version 6.2.0, delta-ray production has now been extended for all energetic charged particles. The basis of this production is the analytical formulation from Rossi and ICRU Report 37. This paper discusses the MCNP6 heavy charged-particle implementation and provides production results for several benchmark/test problems.

Characterization of delayed-particle signatures is of the utmost importance for detecting, identifying, and quantifying special nuclear material (SNM). Various non-destructive assay (NDA) techniques used in nuclear material safeguards rely on characteristic gamma-ray or neutron emissions to infer properties of a material. The all-particle, all-energy Monte-Carlo radiation transport code MCNP6 is capable of simulating delayed-particle signatures from SNM in addition to modeling the transport of emitted particles to a detector or other instrument. In some cases, NDA techniques require the measurement of low probability emissions from a given material. In physical scenarios, this problem can be bypassed by longer count-times or may be simply irrelevant due to the mass, and therefore the total activity, of the material being measured. However, when applying the Monte-Carlo method to such scenarios, sampling of low probability emissions requires a large number of histories to converge to a statistically acceptable solution. To address this issue, the delayed-neutron and gamma energy biasing feature was introduced in MCNP6 by H. Armstrong et al. in 2013 which allows the user to set up energy windows in which delayed-particle emission sampling can be adjusted. For delayed-gamma sampling, this biasing method was based on the bin-wise structure of gamma emission data for both the multi-bin gamma and line-emission sampling modes. Recent improvements have been made to the line-emission sampling algorithm which upgrade the previous mini-bin sampling treatment to an exact energy-line treatment. This upgrade was not compatible with the biasing method implemented by H. Armstrong et al. due to the sampled data no longer having a bin-wise structure in line-emission mode. For this reason the delayed-gamma energy biasing feature has been rewritten to support the exact line-sampling treatment. This paper provides a description of the delayed-gamma energy biasing (DGEB) feature in MCNP6 as well as results and discussion for a gamma-ray spectroscopy example used to demonstrate the biasing utility. (authors)

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)