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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

On MCNP Stochastic Volume Estimation Normalization

This paper resolves a perennial point of confusion regarding the source-weighting normalization factor recommended in the MCNP manual (𝜋⁢𝑟 2 ) to stochastically estimate the volume of a region within an enclosing inward-directed spherical surface source with radius 𝑟. The normalization factor arises from the relationship between a sphere’ s mean chord length, its volume, and the values estimated by MCNP track-length tallies. A brief derivation is given that relates these quantities and results in the stated normalization. The correctness of this factor is demonstrated by estimating the volume of a variety of convex and nonconvex volumes. A heuristic demonstration of how biasing the inward-directed source reduces the statistical uncertainty of the stochastic volume estimate is also given, but a rigorous analysis of this improvement is left as future work.

42 ENGINEERING↗
DOE OSTI2020

Validation of MCNP Critical Benchmark Models of Moderated Highly Enriched Uranium Slabs

A new centralized repository of high-quality MCNP models of critical benchmark experiments is currently under development at Los Alamos National Laboratory (LANL). The benchmark experiments are described in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook, and the initial set of benchmark models are derived from the Whisper Suite provided with MCNP6.2. This effort is a collaboration among the Nuclear Criticality Safety, Nuclear Data, and Monte Carlo code development/application organizations at LANL. The goal is to build a single LANL benchmark collection that is up to date with the latest ICSBEP revision, has a formal review and revision process, is contained in an open-source repository, and utilizes new Python tools for improved input and output file review. This paper describes the validation of the models associated with HEU-MET-FAST-007, “Uranium Metal Slabs Moderated with Polyethylene, Plexiglas, and Teflon”. The Monte Carlo n-Particle (MCNP) models were compared to the second revision of HEU-MET-FAST-007. The experiment considered critical configurations of highly enriched uranium (HEU) metal slabs and various moderators in 43 unique cases. The slabs of uranium were separated by layers of moderating material, forming an assembly. The assembly was separated in two halves with one half placed on a stationary table and the other attached to a moveable table that could be raised and lowered via pulleys connected to the ceiling of the shielded room. To reach criticality, the two halves were brought together with a negligible gap between the assemblies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Coupling of MCNP and ABAQUS for Reactor Multiphysics (MARM) [Slides]

Summer 2021 Internship Objectives: Learn MCNP (Monte Carlo N-Particle) transport code - Unstructured Mesh & Burnup Features, and Implement Python Code for MARM framework - MARM = MCNP and Abaqus based Reactor Multiphysics. Slides provide background and details for achieving learning objectives, as well as ideas for future work in the area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Going under the hood of MontePy: A python API for MCNP input files [Slides]

MontePy is an open-source python software library for reading, editing, and writing MCNP input files. This presentation was given to a university research group interested in it. MontePy provides an object-oriented interface for working with these MCNP input files. It uses a lexer and parser system in order to create a concrete syntax tree representing the input from the input file.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Verifying MCNP Models of the TEX High 240 Plutonium Benchmark

Computational modeling programs are invaluable tools that allow us to understand systems, safely develop new processes, and make reliable predictions about future designs. However, the effectiveness of these codes is limited by the degree to which their parameters match the real world. In the field of nuclear engineering, cross section data is one of these vital parameters. Accurate cross section data on important fissile and fissionable isotopes promotes the design of safer and more efficient fabrication, transportation, storage, and stockpiling of nuclear fuel. Unfortunately, there are knowledge gaps in data on key isotopes. In 2011, a multinational meeting hosted by the US Department of Energy Nuclear Criticality Safety Program ranked the priority of certain cross section data needs. In response, Lawrence Livermore National Lab (LLNL) designed the Thermal and Epithermal eXperiment (TEX) series of benchmark experiments. Benchmark experiments are used to validate current cross section data. They validate data by comparing the results of an actual experiment to the predicted results from a computational model. The data a benchmark applies to depends on the isotope and energy range the experiment’s neutron multiplication factor ( k eff ) is most sensitive to. The development and testing of the TEX High 240 Plutonium Benchmark will help validate 240 Pu cross section data. The configuration and materials of this benchmark are designed to be most sensitive to 240 Pu's intermediate energy range (from 0.625 ev to 100 keV ). MCNP® models of the assembly have been developed by LLNL and the results have been written in the final design report. In order for the discrepancies between benchmark models and experiments to be attributed to cross section inaccuracies, the accuracy of the models needs to be verified. The goal of this project is to verify of the results of LLNL's modeling by creating a new set of MCNP models and comparing the results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nuclear Quality Assurance Certification of the MCNP-ORIGEN Activation Automation tool

The MCNP-ORIGEN Activation Automation (MOAA) tool couples MCNP and ORIGEN-S, allowing to support ATR and TREAT experiments by predicting their composition and activity before their irradiation takes place. MOAA is developed and maintained by the Irradiation Experiment Neutronics Analysis group (C-150) at INL. This poster presents the motivation behind the development of MOAA, its main workflow, as well as the software quality assurance (SQA) efforts required by LWP-13620, "Managing Information Technology Assets."

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Preliminary verification of the MCNP perturbation and fixed-source tally sensitivity tools

Integral benchmark experiments are vital in the adjustment and validation of the nuclear data that govern predictive simulations across the nuclear community. The nuclear data sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®) transport code are currently limited; however, expanding sensitivity capabilities will allow benchmark experiments to be designed to resolve compensating errors and adjust nuclear data where previously prohibitively difficult. This paper provides details of a preliminary verification for the use of (i.) the recently revised perturbation and (ii.) developmental fixed-source sensitivity tools within MCNP to calculate sensitivities of tallied responses (such as current integrated over a surface, F1, and flux averaged over a cell, F4) to nuclear data in fixed-source simulations. Energy-binned and energy-integrated sensitivities calculated with these tools are compared against sensitivities calculated using a central-difference approximation. Here, the verification is completed for four configurations of a benchmarked system using a 4.5-kg plutonium sphere surrounded by varying amounts of copper and/or polyethylene. The results show that sensitivities calculated with the perturbation and fixed-source sensitivity tools agree with the central-difference-based approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Validation of MCNP Critical Benchmark Models of PU-MET-FAST-016

A new centralized repository of high-quality MCNP models of critical benchmark experiments is currently under development at Los Alamos National Laboratory (LANL). The repository is the combined effort of the Nuclear Criticality Safety, Nuclear Data, and Monte Carlo code development/application organizations at LANL. The initial set of benchmark models in the repository are derived from the Whisper Suite provided with MCNP6.2 and are evaluated against the benchmark experiments described in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The goal is to build a single LANL benchmark collection that is up to date with the latest ICSBEP revision, has a formal review and revision process, is contained in an open-source repository, and utilizes new Python tools for improved input and output file review. This paper describes the validation of the models associated with PU-MET-FAST-016, “Flooded 3X3X3 Arrays of 3-kg Plutonium (Pu) Metal Cylinders – Phase I”. In this critical experiment, twenty-seven 3-kg Pu metal cylinders with a height of 46.33 ± 0.15 mm and diameter of 65.25 ± 0.05 mm were arranged in a cubic array. The Pu cylinders were sealed in aluminum cans, and three cans were placed in each of nine perforated aluminum sleeves, as shown in Fig. 1. The nine sleeves were supported by an aluminum frame that allowed for control of the lateral spacing of the cylinders, both in the X and Y directions. The benchmark experiment measured thirteen configurations. Of these configurations, six were modeled using MCNP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A comprehensive final summary of the MCNP calculations performed concerning the UW 137 Cs release event

This document combines and supersedes earlier reports (e.g. LA-UR-19-32358 and LA-UR-20- 22216) that discussed MCNP-calculated conversion factors (count rate per unit activity per unit area) for collimated 2”x2” NaI detectors (Ludlum model 44-10 and Thermo model SPA3) in contact with various surfaces of interest to the University of Washington 137 Cs release event. These surfaces include: Exterior surface of round and rectangular ducts, Exterior surface of outdoor brick work, Exterior surface of cast iron pipes, Exterior surface of an O 2 filter assembly For each surface, the calculated conversion factors allowed inferences on 137 Cs activity on interior surfaces based on exterior contact measurements of the 662 keV photopeak count rate. The MCNP calculations included the effect of attached collimators (i.e. either a Pb/Sb-based Ludlum or a W-based “Rees” model) on detector response. As a consequence, the conversion factors only apply to the appropriate collimated 2”x2” NaI detector operated in pulse height analysis (PHA) mode. Other assumptions affecting the calculations and valid application of the conversion factors will be outlined below.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Guide for Using ENDF/B-VIII.0 Nuclear Data with MCNP

This report provides guidance for using the ENDF/B-VIII.0 nuclear data that were released in 2018 and 2020 with MCNP. Appendix A: Obtaining and installing the new ENDF/B-VIII.0 ACE nuclear data. Appendix B. Obtaining & using XSDIR files that include ENDF/B-VIII.0 data. Appendix C: ENDF/B-VIII.0-based ACE files for neutron cross-sections. A listing of the available temperatures and ZA numbers for neutron cross-sections (ACE files with suffix .nnC). Appendix D: ENDF/B-VIII.0-based ACE files for thermal scattering law (TSL) data, $S$(α,β). A listing of the available thermal scattering $S$(α,β) data (ACE files with suffix .nnT) The next section below provides guidance for modifying existing $\textit{mcnp}$ input files to use the ENDF/B-VIII.0 data. Detailed results from running several benchmark suites for nuclear criticality safety with both ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data are reported in. It is important to note that this report deals only with TSL data released in 2020. With the original release of ENDF/B-VIII.0 in 2018, the ACE files for neutron cross-sections were contained in a directory called Lib80X and the ACE files for TSL data were contained in a directory called ENDF80SaB. A few years later, it was determined that many of the TSL data files had been generated with faulty data or with incorrect processing, and a new set of ACE files for TSL data was created, with the corrected files contained in directory ENDF80SaB2.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Computational Modeling and Simulation for Nonproliferation: The History (and Present) of Monte Carlo and the MCNP(R) Code at Los Alamos [Slides]

The emergence of the Monte Carlo method as a research tool springs from work done at Los Alamos in the 1940s.Monte Carlo and the MCNP Code have been and continue to be developed at Los Alamos for many decades. From basic science in support of understanding nuclear interaction physics to global security applications, application uses of the code are extensive. Recent R&D projects and code modernization efforts make the MCNP code a great tool for nuclear nonproliferation applications. In collaboration with nuclear safeguards experts, new training has just recently been developed to help new practitioners learn how to use the code for nuclear safeguards applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

MCNP Intrinsic Source Constructor (MISC): A User’s Guide

The MCNP Intrinsic Source Constructor (MISC) facilitates the construction of MCNP source definition cards for radioactive materials. Given a material nuclide specification, either weight or atom fractions of those nuclides, and either a weight or atom density of the material, MISC will construct the source spectrum distribution of a specified particle type. MISC also calculates the absolute number of particles emitted per second per unit mass or volume. Furthermore, if decay chain information is available in the data sets selected by the user, the initial isotopes specified by the user can be approximately decayed to the resulting isotopes after a specified amount of time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Validation of Nuclear Data Sensitivity Calculations by the MCNP PERT Card [Poster]

This work validates a method of estimating sensitivities that utilized the MCNP PERT card and tallies. The agreement of the PERT card and Brute Force results proves the validity of calculating nuclear data sensitivities by use of the MCNP PERT card, especially at higher energies. The overall agreement will be easier to understand once an uncertainty analysis is completed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Reassessing the MCNP Random Number Generator

Random number generators are integral components to Monte Carlo codes. They provide the pseudorandom number sequence used to actually sample the distributions of interest. As a result, they are one of the most important components to the software. The current recommended MCNP random number generator is a 63-bit linear congruential generator (LCG). This generator is quite fast, but it has some drawbacks. First, it only has a period of 2 63 . Due to the necessarily non-optimal usage of random numbers to ensure parallel reproducibility, this amount is too few to guarantee random number sequences are not reused in all configurations the code runs under. As simulation size increases, users will need to be aware of the limitations of the generator and tune configuration variables to best suit their simulations, or they will need to assume that reuse is not negatively affecting their answers. Neither of these are optimal. Second, small LCGs are fairly weak in bit generation quality, and this can have an unknown impact on the quality of the simulation. This paper is an investigation into whether or not more modern random number generators can supersede the current ones. The goal is to find a generator that is similar or superior in speed to the LCGs, has a state space large enough to make strong guarantees about random number reuse, and passes all modern random number test suites. If such a generator is found, it would eliminate the need for the user to even be aware of the limitations of the random number generator and would simplify the use of the code. This paper will be broken into several parts. Sec. 2 will discuss the evolution of the random number generator within the MCNP code. Sec. 3 will go over what a Monte Carlo code needs from a generator to be reproducible and portable and how the current generator behaves in that light. Sec. 4 goes through how each generator was tested. Finally, Sec. 5 will discuss improvements that could be made to the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

GEOMWRITER - A Workflow for Automatically Generating MCNP Geometry for Neutron Guide Simulations

This report describes the functionality of the geomwriter.py script, which is a python script for producing complex MCNP CSG geometries from the IGES CAD format. It is specifically written to handle neutron supermirror guides, but can handle more complex objects through utilizing a convex hull algorithm. This work flow reduces the amount of time spent on generating the surface definitions for a complex neutron guide system with hundreds of segments such that changes to the neutron guide system design in McStas can be rapidly incorporated into an MCNP model and integrated with the shielding geometry present in that model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

ACRRF High-Bay Dose Calculations using MCNP (Part A)

Analytical tools and models have been developed as a starting point for directly assessing dose in the Annular Core Research Reactor Facility (ACRRF) due to reactor operation. Key results include peak dose along the Central Cavity (CC) centerline (beamline) at the cavity level, dose throughout the High-Bay (HB), and dose on the facility roof for partially-shielded reactor operation where the 4” insert is removed from the CC Shield Plug (SP). Model results in the beamline are benchmarked against measured doses from passive dosimetry evaluations. Personnel total (neutron and gamma) dose in the ACRRF HB is calculated using Monte Carlo N-Particle (MCNP). Various CC and SP configurations are analyzed, including unshielded (no SP) and partially shielded (SP installed but 4” insert removed). Novel application of Variance Reduction (VR) techniques, namely the Surface Source Write (SSW) and Surface Source Read (SSR) capabilities in MCNP, enable impressive resolution (in a Monte Carlo modeling sense) of dose throughout much the facility. The VR techniques reduce stochastic error for challenging tallies, with more advanced techniques explored in the companion to this report (Part B) [1]. Supplementary studies (including a verification analysis) and pedagogic evaluations in Part B involve neutron spectra, angular distributions, and the dose impact of facility characteristics. With the SP 4” insert removed and the Lead-Boron (44”) Bucket (LB–44) in the reactor cavity, Total Effective Dose (TED) within the CC beamline is ≈140 rem per 300 MJ of reactor yield (or 3900 rem per hour at 100% Steady-State (SS) power). With no SP (unshielded) and a Free-Field (FF) cavity, TED within the beamline is ≈610 rem per 300 MJ (or 17000 rem per hour at 100% SS power). Due to the predicted collimation of radiation by the reactor pool (and partial SP, if present), beamline dose is much greater than the scattered radiation field surrounding the cavity and reactor tank. Comparisons are made to beamline dosimetry measurements to validate the model. Model predictions agree reasonably well (⪅10%) with measured quantities of neutron fluence, gamma fluence, and spectral metrics. Away from the beamline, comparisons made to previous dose measurements in the HB agreement within an order of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Development of the MCNP-ORIGEN activation automation tool

This paper introduces the MCNP-ORIGEN activation automation tool for streamlining the calculation of experiment source terms. This tool couples the Monte-Carlo radiation-transport solver, MCNP to the depletion tool, ORIGEN-S. To showcase its current capabilities, this paper presents an activation analysis exercise, which is conducted with Serpent, and the results are com- pared. The experiment consists in a 90%-enriched uranium sphere surrounded by light water. A non-fissile cylinder is placed in the water, representing an irradiation experiment. We conducted simulations for 2 different cylinder materials: iron and cobalt at two different temperatures: 300 K and 900 K. The exercise consists of an irradiation of 50 days at a constant power of 5 MW, followed by a decay of 50 days. These studies highlight the discrepancies between how the different tools handle nuclear data. Finally, the results underscore multiple areas of possible improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗