Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “MCNP6”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Comparative studies of actinide and sub-actinide fission cross section calculation from MCNP6 and TALYS

Comparative studies of actinide and sub-actinide fission cross section calculation from MCNP6 and TALYS have been conducted. In this work, fission cross section resulted from MCNP6 prediction will be compared with result from TALYS calculation. MCNP6 with its event generator CEM03.03 and LAQGSM03.03 have been validated and verified for several intermediate and heavy nuclides fission reaction data and also has a good agreement with experimental data for fission reaction that induced by photons, pions, and nucleons at energy from several ten of MeV to about 1 TeV. The calculation that induced within TALYS will be focused mainly to several hundred MeV for actinide and sub-actinide nuclides and will be compared with MCNP6 code and several experimental data from other evaluator.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

MCNP6 Status and plans for criticality safety applications - 14368

The first production version of MCNP6 was released in 2013, with an update in 2014. MCNP6 provides all of the standard methodology for criticality calculations available in previous versions and new capabilities for adjoint-based sensitivity profiles and perturbations. This paper reviews the current status of MCNP6, including new features, performance improvements, verification testing, and nuclear data libraries. For criticality safety support, a new statistical package called Whisper was developed and first applied in 2014 for validation and determining USLs. Whisper includes input files and sensitivity profiles for over 1000 ICSBEP benchmarks and will be distributed with MCNP6. For the long term, an initiative called MCNP 2020 is underway to improve performance, strengthen the code foundation, and prepare for future computer systems. (authors)

42 ENGINEERING↗
DOE OSTI2017

Evaluation of the Pool Critical Assembly Benchmark with Explicitly-Modeled Geometry using MCNP6

Despite being one of the most widely used benchmarks for qualifying light water reactor (LWR) radiation transport methods and data, no benchmark calculation of the Oak Ridge National Laboratory (ORNL) Pool Critical Assembly (PCA) pressure vessel wall benchmark facility (PVWBF) using MCNP6 with explicitly modeled core geometry exists. As such, this paper provides results for such an analysis. First, a criticality calculation is used to construct the fixed source term. Next, ADVANTG-generated variance reduction parameters are used within the final MCNP6 fixed source calculations. These calculations provide unadjusted dosimetry results using three sets of dosimetry reaction cross sections of varying ages (those packaged with MCNP6, from the IRDF-2002 multi-group library, and from the ACE-formatted IRDFF v1.05 library). These results are then compared to two different sets of measured reaction rates. The comparison agrees in an overall sense within 2% and on a specific reaction- and dosimetry location-basis within 5%. Except for the neptunium dosimetry, the individual foil raw calculation-to-experiment comparisons usually agree within 10% but is typically greater than unity. Finally, in the course of developing these calculations, geometry that has previously not been completely specified is provided herein for the convenience of future analysts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

A Python Tool for Aqueous Plutonium Nitrate Density Law Input Preprocessing in MCNP6

Here, this work develops a predictive density tool in Python, named Plutonium Nitrate Solutions (PuNS), to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer method and an empirical method were implemented into the PuNS tool to generate atom densities for use in MCNP6 material cards. These material cards are directly prepared into an MCNP6 input text file and are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, and plutonium isotope weight percentages. The PuNS tool is validated and verified against the International Criticality Safety Benchmark Evaluation Project Handbook experiments and is observed to predict densities within a root mean square error of 0.89% for the Pitzer method and 1.82% for the empirical method. These errors in density lead to up to 1569 pcm difference in MCNP6 calculated k eff for the Pitzer method and up to a 1751 pcm difference for the empirical method when compared to experimental benchmarks. Simultaneous work is also being performed at Los Alamos National Laboratory and the University of New Mexico to create a similar tool for plutonium chloride solutions, named Plutonium Chloride Solution, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also facilitate an improved understanding of solution systems and a potential relaxation in the conservatism of current aqueous plutonium processing criticality safety limits.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

SU-F-T-140: Assessment of the Proton Boron Fusion Reaction for Practical Radiation Therapy Applications Using MCNP6

Purpose: The proton boron fusion reaction is a reaction that describes the creation of three alpha particles as the result of the interaction of a proton incident upon a 11B target. Theoretically, the proton boron fusion reaction is a desirable reaction for radiation therapy applications in that, with the appropriate boron delivery agent, it could potentially combine the localized dose delivery protons exhibit (Bragg peak) and the local deposition of high LET alpha particles in cancerous sites. Previous efforts have shown significant dose enhancement using the proton boron fusion reaction; the overarching purpose of this work is an attempt to validate previous Monte Carlo results of the proton boron fusion reaction. Methods: The proton boron fusion reaction, 11B(p, 3α), is investigated using MCNP6 to assess the viability for potential use in radiation therapy. Simple simulations of a proton pencil beam incident upon both a water phantom and a water phantom with an axial region containing 100ppm boron were modeled using MCNP6 in order to determine the extent of the impact boron had upon the calculated energy deposition. Results: The maximum dose increase calculated was 0.026% for the incident 250 MeV proton beam scenario. The MCNP simulations performed demonstrated that the proton boron fusion reaction rate at clinically relevant boron concentrations was too small in order to have any measurable impact on the absorbed dose. Conclusion: For all MCNP6 simulations conducted, the increase of absorbed dose of a simple water phantom due to the 11B(p, 3α) reaction was found to be inconsequential. In addition, it was determined that there are no good evaluations of the 11B(p, 3α) reaction for use in MCNPX/6 and further work should be conducted in cross section evaluations in order to definitively evaluate the feasibility of the proton boron fusion reaction for use in radiation therapy applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Overview of the MCNP6® SQA Plan and Requirements [Memorandum]

For all X Computational Physics Division (XCP) software under the Associate Laboratory Directorate for Weapons Physics (ALDX), the Weapons Research Services Secure Networks and Assurance Group (WRS-SNA) manages the software quality assurance (SQA) plan, requirements and guidance with respect to development processes and tools to meet the broader LANL SQA requirements. Each XCP software product is categorized into one of three software types: Safety Software, Non-Safety Risk Significant Software, and Non-Safety Commercially Controlled Software. In 2018, using LANL Form 2033, the MCNP6 code was categorized by the XCP division as Non-Safety Commercially Controlled Software, provided in Appendix A. Using WRSFORM- 0001U, the MCNP6 code was graded as a Medium Impact software product, provided in Appendix B. Given these determinations, the WRS-AD-0010U SQA plan is followed for all MCNP6 developments, documentation and code releases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

(U) A General-Purpose Code for Correlated Sampling Using Batch Statistics with MCNP6 for Fixed-Source Problems

Correlated sampling can be used to reduce the uncertainty of a difference of tallies by taking advantage of the negative covariance term in the sandwich formula. Booth first showed how correlated sampling can be applied with batch statistics using MCNP’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies in fixed-source problems. Booth presented a problem in which a 1273% uncertainty in a difference was reduced to 8% by accounting for correlations. Researchers He and Su recently studied correlated sampling using the TFC in MCNP version 5. They determined that the code did not print enough digits in the TFC tally means for accurate batch statistics in some cases. After modifying the source code, they concluded that “correlated sampling can yield a standard deviation of about one magnitude smaller than that predicted by the direct, un-correlated simulation when the changes in system response are small (say about 1%), which is equivalent to saving in CPU time by a factor of 100. Such saving [sic] becomes less significant as the change in system response becomes larger.” He and Su provided the formulas needed to apply batch statistics to compute the correlated uncertainty of a difference of tallies. In this report, we follow up on their work by providing the formulas needed to apply batch statistics to compute the correlated uncertainty of a ratio of tallies and of a difference of two tallies divided by a third tally. We extend these formulas to differences and ratios of ratios. These formulas are applied to reduce the uncertainty associated with calculating a relative sensitivity. He and Su did not investigate the accuracy of their correlated sampling uncertainty estimates. We use their test problems and evaluate the accuracy of the uncertainty estimates by comparing with results obtained from random sampling, and, in simple cases, with theoretical values of the “exact” uncertainties. We find that the uncertainties obtained from batch statistics are accurate as long as at least 100 batches are used. We present a new computer code, COSUBS (COrrelated Sampling Using Batch Statistics), that reads MCNP6 TFCs and applies correlated sampling using batch statistics for the tally combinations that the user specifies. COSUBS is a very general tool that compares all TFCs for a base case and one or two perturbed cases. It computes uncertainties for ratios if given only a base case. This report is organized as follows. The equations to apply batch statistics to the difference of random tallies are reviewed in Sec. II. Section III presents the equations for applying batch statistics to a ratio of random tallies; this is useful for computing relative sensitivities using a one-sided finite difference and the relative sensitivity using the differential operator method. Section IV presents the equations for applying batch statistics to a difference of two random tallies divided by a third; this is useful for computing a relative sensitivities using a central difference. Section V presents the equations for applying batch statistics to a difference of two ratios with four random tallies. Section VI presents the equations for applying batch statistics to a one-sided finite difference estimate of the relative sensitivity of a ratio (this uses four random tallies). Section VII presents the equations for applying batch statistics to a central difference estimate of the relative sensitivity of a ratio (this uses six random tallies). Section VIII presents the equations for applying batch statistics to a sum of random tallies. Section IX discusses how to apply batch statistics using MCNP6. Section X presents COSUBS, describing its command-line options and logic. Sections XI through XVI present numerical results for various test problems. Section XVII is a summary and conclusions. Appendix A derives the theoretical Monte Carlo tally variance given certain assumptions; these variances are used to verify the batch statistics for some of the problems. Appendix B lists the MCNP6 input for the unperturbed example problem. Appendix C presents modifications made to MCNP6.3 to support this work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Python Tool for Reconstructing MCNP6 Particle Histories from an HDF5 PTRAC File [Slides]

A Python tool for converting the MCNP6 HDF5 PTRAC file to a list of Python trees is presented. The particle trees store MCNP6 simulated events for each history using parent-child relationships, which ensures that branching processes are accurately reproduced. A variety of post-processing scripts are presented and used in conjunction with the Python particle trees to make special tallies that are currently not available in the MCNP6 software and visualize the particle tracks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Testing the Delayed Gamma Capability in MCNP6 - Paper 86

The mission of the Domestic Nuclear Detection Office (DNDO) is to quickly and reliably detect unauthorized attempts to import or transport special nuclear material (SNM) for use against the United States. Developing detection equipment to meet this objective requires accurate simulation of both the detectable signature and detection mechanism. MCNP6 is capable of transporting the various types of radiation encountered in these scenarios; however, the accuracy of MCNP6 must be quantified such that we can be confident in the results of the simulations. Delayed gamma transport is one important component of these detection scenarios. Delayed gamma transport is defined as the combination of gamma emission from radioactive and subsequent transport through matter. MCNP always possessed the ability to emit delayed neutrons from fission; however, these delayed neutron spectra and intensity were functional fits and not directly sampled from the created fission products. Furthermore, there existed no method to emit the decay photons from radioactive fission products (or any radioactive nucleus) A delayed particle capability was initially added to MCNPX 2.6.A in 2005 to sample the radioactive fission product parents and emit decay particles resulting from the decay chain. At the point of capture, a residual nucleus is created and decayed using the CINDER90 depletion code. MCNP only sends CINDER90 a residual radioactive nucleus and not a flux (i.e. capture rate). As a result, the Bateman equations for the solution are coupled first order differential equations with constant coefficients. Theoretically, these equations could be solved analytically; however, CINDER90 employs a numerical Markov linear chain scheme to solve these equations. This paper addresses a more simplified approach to benchmarking in order to best assess: (1) whether or not deficiencies exist in the current methodology for certain types of decay chains; and (2) paths forward for improving the delayed particle emission capability. We utilize closed form analytic solutions to the granddaughter equations for particular sets of isotope systems to compare the accuracy of the delayed gamma capability in MCNP6. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Application of an Empirical Density Law via Python for Aqueous Plutonium Chloride Systems for MCNP6

Criticality safety models for aqueous plutonium chloride systems often contain a significant bias due to assumptions in material compositions. These systems are currently modeled as a fictitious metal-water mixture because little is known about the true solution density. Furthermore, no predictive density tools or capabilities for modeling aqueous plutonium chloride systems are approved for use at Los Alamos National Laboratory. Recent density measurements of this ternary system (PuCl 3 -HCl-H 2 O) have allowed for the development of a more realistic density law, which is applied in this work via an empirical method based in Python. This tool, entitled PuCS (Plutonium Chloride Solution tool) may be used to determine solution density and composition based on the plutonium content, acid content, and temperature for MCNP6 inputs. PuCS has been found to predict density within 2% of experimental data. In conclusion, MCNP6 calculations have found that crediting minimal amounts of free acid (0.5 M) may correspond to a ~12% decrease in peak reactivity in comparison to current modeling methods.

42 ENGINEERING↗
DOE OSTI2015

A Verification of MCNP6 FMESH Tally Capabilities

This work serves to verify the MCNP6 FMESH capability through comparison to two types of data. FMESH tallies, binned in time, were generated on an ideal detector face for neutrons undergoing a single scatter in a graphite target. For verification, FMESH results were compared to analytic calculations of the nonrelativistic TOF for elastic and inelastic single neutron scatters (TOF for the purposes of this paper is the time for a neutron to travel from its scatter location in the graphite target to the detector face). FMESH tally results were also compared to F4 tally results, an MNCP tally that calculates fluence in the same way as the FMESH tally. The FMESH tally results agree well with the analytic results and the F4 tally; hence, it is believed that, for simple geometries, MCNP6 FMESH tallies represent the physics of neutron scattering very well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Application of an Empirical Density Law via Python for Aqueous Plutonium Chloride Systems in MCNP6

Current aqueous plutonium processing models for criticality safety often contain significant bias due to material modeling assumptions. These solutions include plutonium chloride solutions, which are modeled as fictitious plutonium metal-water mixtures because little is known about the actual density of the solution. Furthermore, there is no current predictive capability for modeling plutonium metal-water mixtures that is approved for use at Los Alamos National Laboratory (LANL). Recent density measurements for aqueous plutonium chloride systems (PuCl 3 -HCl-H 2 O) now allow for the development and application of a more realistic density law. This work develops a Python-based density law for this ternary solution using an empirical method. This code can be used in conjunction with an MCNP6 input to determine the density and composition of a solution based upon user inputs of plutonium concentration, hydrochloric acid concentration, and temperature. The tool allows users to input plutonium and acid content of a solution in terms of molality, molarity, or concentration, and predicts density within the current data range within 1.4% of experimental data. Current preliminary MCNP6 calculations utilizing this tool have demonstrated a minimum decrease in system reactivity of 5% in comparison to the current modeling conventions. Thus, this tool enables more accurate criticality safety operational limits by better crediting chorine content while still maintaining necessary conservatism.

Density Law↗
DOE OSTI2016

Implementation and testing of the on-the-fly thermal scattering Monte Carlo sampling method for graphite and light water in MCNP6

Here, a proper treatment of thermal neutron scattering requires accounting for chemical binding through a scattering law S(α,β,T). Monte Carlo codes sample the secondary neutron energy and angle after a thermal scattering event from probability tables generated from S(α,β,T) tables at discrete temperatures, requiring a large amount of data for multiscale and multiphysics problems with detailed temperature gradients. We have previously developed a method to handle this temperature dependence on-the-fly during the Monte Carlo random walk using polynomial expansions in 1/T to directly sample the secondary energy and angle. In this paper, the on-the-fly method is implemented into MCNP6 and tested in both graphite-moderated and light water-moderated systems. The on-the-fly method is compared with the thermal ACE libraries that come standard with MCNP6, yielding good agreement with integral reactor quantities like k-eigenvalue and differential quantities like single-scatter secondary energy and angle distributions. The simulation runtimes are comparable between the two methods (on the order of 5–15% difference for the problems tested) and the on-the-fly fit coefficients only require 5–15 MB of total data storage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Total reaction cross sections in CEM and MCNP6 at intermediate energies

Accurate total reaction cross section models are important to achieving reliable predictions from spallation and transport codes. The latest version of the Cascade Exciton Model (CEM) as incorporated in the code CEM03.03, and the Monte Carlo N-Particle transport code (MCNP6), both developed at Los Alamos National Laboratory (LANL), each use such cross sections. Having accurate total reaction cross section models in the intermediate energy region (50 MeV to 5 GeV) is very important for different applications, including analysis of space environments, use in medical physics, and accelerator design, to name just a few. The current inverse cross sections used in the preequilibrium and evaporation stages of CEM are based on the Dostrovsky et al. model, published in 1959. Better cross section models are now available. Implementing better cross section models in CEM and MCNP6 should yield improved predictions for particle spectra and total production cross sections, among other results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Background-Source Cosmic-Photon Elevation Scaling and Cosmic-Neutron/Photon Date Scaling in MCNP6

Here, cosmic neutron and photon fluxes are known to scale exponentially with elevation. Consequently, cosmic neutron elevation scaling was implemented for use with the background-source option shortly after its introduction into MCNP6, whereby the neutron flux weight factor was adjusted by the elevation scaling factor when the user-specified elevation differed from the selected background.dat grid-point elevation. At the same time, an elevation scaling factor was suggested for the cosmic photon flux, however, cosmic photon elevation scaling is complicated by the fact that the photon background consists of two components: cosmic and terrestrial. Previous versions of the background.dat file did not provide any way to separate these components. With Rel. 4 of this file in 2015, two new columns were added that provide the energy grid and differential cosmic photon flux separately from the total photon flux. Here we show that the cosmic photon flux component can now be scaled independently and combined with the terrestrial component to form the total photon flux at a user-specified elevation in MCNP6.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

An Electron/Photon/Relaxation Data Library for MCNP6

The capabilities of the MCNP6 Monte Carlo code in simulation of electron transport, photon transport, and atomic relaxation have recently been significantly expanded. The enhancements include not only the extension of existing data and methods to lower energies, but also the introduction of new categories of data and methods. Support of these new capabilities has required major additions to and redesign of the associated data tables. In this paper we present the first complete documentation of the contents and format of the new electron-photon-relaxation data library now available with the initial production release of MCNP6.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Semi-Analytical Benchmarks for MCNP6

Code verification is an extremely important process that involves proving or disproving the validity of code algorithms by comparing them against analytical results of the underlying physics or mathematical theory on which the code is based. Monte Carlo codes such as MCNP6 must undergo verification and testing upon every release to ensure that the codes are properly simulating nature. Specifically, MCNP6 has multiple sets of problems with known analytic solutions that are used for code verification. Monte Carlo codes primarily specify either current boundary sources or a volumetric fixed source, either of which can be very complicated functions of space, energy, direction and time. Thus, most of the challenges with modeling analytic benchmark problems in Monte Carlo codes come from identifying the correct source definition to properly simulate the correct boundary conditions. The problems included in this suite all deal with mono-energetic neutron transport without energy loss, in a homogeneous material. The variables that differ between the problems are source type (isotropic/beam), medium dimensionality (infinite/semi-infinite), etc.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗