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DOE OSTI2024

High-purity germanium semiconductor modeling in the detector response function toolkit

In this study, we have extended the detector response function toolkit (DRiFT) to provide modeling capabilities of semiconductor sensors. DRiFT provides realistic nuclear instrumentation response by post-processing Monte-Carlo N-particle (MCNP®) radiation transport outputs. MCNP® is capable of modeling radiation transport in complex environments, but has limited detector physics and readout electronics modeling capabilities. Semiconductor detector response can be calculated with a high-fidelity for a flexible range of environments by utilizing MCNP® to simulate radiation interactions inside of detector volumes, and then using DRiFT to model charge transport and signal formation in the semiconductor, as well as the readout electronics. DRiFT models charge transport in the semiconductor, the preamplifier, shaping amplifier, pulse pile-up, and electronic noise to generate detector response. The semiconductor application in DRiFT can model a range of semiconductor materials, shapes, and sizes; and is demonstrated here for a large volume coaxial high-purity germanium (HPGe) detector. Here, we compare detector response functions of a coaxial HPGe detector with measurement of 60 Co, 133 Ba, and 137 Cs at varying count rates, and we conduct a parameter study to demonstrate the effect of changing parameters in the DRiFT simulation. The HPGe detector response function shows excellent agreement with measurements of difference sources with varying dead times and count rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Radiation Source Localization Using Surrogate Models Constructed from 3-D Monte Carlo Transport Physics Simulations

Recent research has focused on the development of surrogate models for radiation source localization in a simulated urban domain. We employ the Monte Carlo N-Particle (MCNP) code to provide high- delity simulations of radiation transport within an urban domain. The model is constructed to employ a source location (x, y, z) as input and return the estimated count rate for a set of speci ed detector locations. Because MCNP simulations are computationally expensive, we develop e cient and accurate surrogate models of the detector responses. We construct surrogate models using Gaussian processes (GP) and neural networks (NN) that we train and verify using the MCNP simulations. The trained surrogate models provide an e cient framework for Bayesian inference and experimental design. We employ Delayed Rejection Adaptive Metropolis (DRAM), a Markov Chain Monte Carlo (MCMC) algorithm, to infer the location and intensity of an unknown source. The DRAM results yield a posterior probability distribution for the source's location conditioned on the observed detector count rates. The posterior distribution exhibits regions of high and low probability within the simulated environment identifying potential source locations. In this manner, we can quantify the source location to within at least one of these regions of high probability in the considered cases. Employing these methods, we are able to reduce the space of potential source locations by at least 60%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

CADIS and FW-CADIS Variance Reduction in Gamma Transport for Predicting Prompt Forensics Signatures

The goal of prompt nuclear forensics is to determine the characteristics of a nuclear detonation based on the signatures available almost immediately after the explosion. An important characteristic is the reaction time history (RTH), a measure of the device’s rate of neutron multiplication. The RTH can be estimated by observation of the gamma radiation emitted from the detonation, which can be detected directly or observed indirectly as Teller light. Gamma transport simulations used to predict these radiation fields are often modeled stochastically using the Monte Carlo N-Particle (MCNP) code, which can be a computationally demanding task due to the number of particle histories needed to achieve statistical convergence. In an attempt to improve the efficiency of these calculations, we evaluate two variance reduction techniques: Consistent Adjoint-Driven Importance Sampling (CADIS) and Forward-Weighted Consistent Adjoint-Driven Importance Sampling (FW-CADIS). These methods use a deterministically calculated adjoint flux to create weight windows and source biasing that guide MCNP sampling. We study the utility of CADIS and FW-CADIS for their use in MCNP gamma transport for nuclear forensics prediction simulations. Furthermore, the results demonstrate that both CADIS and FW-CADIS improve the accuracy for forensics-focused simulations, with CADIS being most beneficial in direct detection and FW-CADIS being ideal for computing a global Teller light source.

CADIS↗

DOE OSTI2022

Easy_PERT: a Python tool for writing PERT cards and parsing PERT card results [Slides]

This presentation begins by providing an overview of the PERT card. The PERT card uses differential operator method to compute first- and second-order tally variations due to density, composition, and reaction cross-sections. It is possible to have multiple PERT cards in one MCNP input deck to study tally variations for several sets of nuclides, reactions, and energy ranges. Furthermore, the METHOD option tells MCNP to calculate either the perturbed tally (METHOD=-1, -2, -3) or the change in the unperturbed tally (METHOD=1, 2, 3). In summation, a powerful use-case for the MCNP code PERT card is that it facilitates calculating tally sensitivities to nuclear data. Writing PERT card entries and parsing output MCTAL files is tedious and error prone. however, Easy_PERT makes use of existing tools (Faust and MCNPTools) to handle writing PERT card entries and parsing the output MCTAL files. The PERT card is early in the development process and planned upcoming capabilities include calculating sensitivities and combining MCTAL files from separate runs into one JSON file.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Carrier gas attenuation in gamma assay of radioactive xenon samples

Gamma attenuation attributable to xenon and carbon dioxide carrier gas in radioactive xenon assay samples has been calculated using Monte Carlo n-Particle (MCNP) transport code for the 0.65 mL flame sealed ampoule (bean), and 15 mL and 50 mL Schlenk tube geometries. The attenuation was correlated as a % loss per standard mL of carrier gas. In this work, high Purity Ge gamma spectroscopy experiments were performed to measure against the MCNP results. The experimental results from the 133 Xe in xenon carrier gas in a bean geometry showed 0.97 ± 0.4% loss per standard mL xenon, which was in agreement with the MCNP predictions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2021

Benchmarking GEANT4 and PHITS for 14.8-MeV neutron transport in polyethylene and graphite materials

The feasibility of GEANT4 and PHITS with ENDF/B-VIII.0, JEFF-3.3 and JENDL-4.0 evaluated nuclear data libraries in 14.8-MeV neutron transport simulation are verified by comparing with the MCNP calculations and the experimental data. Here the measured data are from neutron integral experiments including graphite and polyethylene samples. For 6 cm-thick polyethylene and 20 cm-thick graphite samples, the results from GEANT4 and PHITS with three evaluated nuclear data libraries agree well with the MCNP calculations. For a 2 cm-thick graphite sample, the simulated results from GEANT4 and PHITS agree with the MCNP calculations, and they all underestimate the experiment data in below 3 MeV and overestimate them in the energy range of 5–7 MeV. The difference between the simulation results and the experimental data depends on the evaluated nuclear data libraries. In overall, GEANT4 and PHITS are performing reasonable jobs for 14.8-MeV neutron transport simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

PyTrac

SAND2025-00635O PyTrac is a software tool that analyzes and visualizes PTRAC event files generated by MCNP 6.3. It converts these files into a graph network that makes it easier to interpret individual histories. The software includes command line tools for viewing the graph data structure in both 2D and 3D formats. PyTrac also integrates with MCNP to run simulations and manage data files. This provides a streamlined approach to analyzing and understanding the complex data generated by MCNP simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nowack, Aaron [Sandia National Lab. (SNL-CA), Live↗

DOE OSTI2024

RadSim: Particle Transport Wrapper

RadSim is being developed to provide the capability to simulate radiation source emissions, interpolate results from radiation transport tools into a common format to prepare incident flux, and model radiation detector response. This software package includes wrapper API code which is utilized in the development of the second (transport) task of the RadSim project. This software package only contains tools to interface RadSim with radiation transport tools (GEANT4 and MCNP) and does not include any part of the transport source code itself. The users will need prior access to the transport tools (GEANT4 and MCNP), and can use this software package to interface with the transport tool of their choice. This software package takes the geometry file for a radiation transport problem and converts it into an input deck for the transport tools (GEANT4 and MCNP). Additionally, it also contains filters that convert the output of the transport tools to a common flux format.

Cheung, Hoi Sing↗

DOE OSTI2020

Demonstration of NEAMS Multiphysics Tools for Fast Reactor Applications

The SHARP toolkit is a high-fidelity reactor simulation tool developed under the U.S. Department of Energy, Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. SHARP toolkit is comprised of the neutronics module PROTEUS thermal hydraulics module Nek5000, and structural mechanics module Diablo. During FY17 and FY18, the PROTEUS and Nek5000 components of SHARP were applied to solve challenging sodium-cooled fast reactor (SFR) problems. In particular, selected hot channel factors (HCF) for a prototype metal-fueled SFR design (the AFR-100) were analyzed in high fidelity, and the “SHARP zooming capability” for SFRs was developed and demonstrated to reduce computational expense for full core problems in cases where detailed data is needed in selected fuel assemblies. After the previous success applying SHARP to challenging SFR problems, the focus in FY19 and FY20 expanded to additional fast reactor applications including lead cooled fast reactors (LFR) and sodium cooled fast reactors (SFR). The specific technical tasks were (1) assessment of hot channel factors for LFR, for which no data currently exists, and (2) demonstration of zooming capability in assemblies of the Versatile Test Reactor (VTR). First-of-a-kind hot channel factor (HCF) estimation for LFR with high fidelity codes (PROTEUS/Nek5000) was successfully demonstrated in this study which began in FY19 and continued in FY20. Selected HCF were computed and compared with SFR data (AFR-100, EBR-II). The findings confirm that different reactor types, design parameters and uncertainties lead to different HCFs. Careful estimation of HCF for a specific design is necessary to obtain appropriate HCFs. In addition to improvement in HCF accuracy, high fidelity tools generate data to help the designer better understand the mechanism of the impact from these uncertainties. For example, the impact of cladding thickness manufacturing tolerance resulted in non-intuitive effects in the corner pins of the LFR assembly. This procedure of computing HCF using high fidelity models shows promise and flexibility for being repeated for any arbitrary reactor of choice. Along with the application on SFR and LFR, the capability of the tools has also been matured to deal with different reactor types and designs. Progress was made towards extending the previously demonstrated SHARP zooming capability to non-fueled SFR assemblies. In particular, in FY19 a gamma transport capability was implemented in both high fidelity PROTEUS solvers in order to accurately account for heat deposition caused by gamma particles, which accounts for ~10% of total core power. Neutronics verification cases were carried out for a candidate Versatile Test Reactor (VTR) design using the new gamma transport capability in PROTEUS. Comparisons were made with continuous energy MCNP calculations and shown to agree well. The models for the full core design with heterogeneous control and fuel assemblies is in progress for PROTEUS-SN and completed with MCNP. The MCNP power distributions were transferred to Nek5000 to perform thermal hydraulic calculations of the control and fuel assembly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Analysis of Approximations in Modeling of BWR Bundle Void Distributions

In boiling water reactors, complex heterogeneous bundle designs, control blades adjacent to the corner of bundles, and the presence of boiling can lead to complex internal void distributions. A few approximations exist to model these void distributions. They could be modeled using a 1D axial solver in which each axial node is assumed to be at an average void, or each pin cell could be modeled with its own void concentration. In the latter case, the void could be discretized in pin-centered or coolant-centered channels. The goal of this project was to quantify the effect of using the different approximations for modeling internal void distributions on neutronics calculations. Using 3D void distributions calculated with CTF, Monte Carlo Neutral Particle (MCNP) transport code models were created for GE-9 and GE-14 lattices. For each model, the internal void distribution from CTF at a given axial node was selected, and a lattice calculation was carried out with MCNP. Comparisons between models using a lattice-averaged void, or using a void distribution in coolant-centered channels, showed large differences in reactivity which in some cases were well above 1,000 pcm, and it also showed differences in normalized fission rates greater than 20%. It was also found that using a lattice average void can lead to a significant difference in the estimation of the worth of a control blade. The differences found when comparing results from models using pin-centered and coolant-centered channels were up to 200 pcm in reactivity and up to 1.4% in the normalized fission rates. In addition to these two sets of comparisons, MCNP models were set up so that each subchannel had a saturated liquid component around the fuel pins and a saturated vapor component in the center to approximate annular flow. In comparison to the models using coolant-centered subchannels, up to 1–3% differences in normalized fission rates could be found.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Initial Investigation of Coupled Electron-Photon Transport with SCEPTRE and RAPTURE (Rev.1.1)

The SCEPTRE1 code models coupled photon and electron transport in material media using discrete ordinates methods. The code can use different solvers in 1D and 3D in parallel, promising users the ability to run problems that are significant both in physics and computational scale. One capability that is perhaps unique at this time in the NNSA complex is SCEPTRE’s coupled photon– electron transport physics in a discrete ordinates approach. For example, incident x–rays can generate a significant electron population, whose transport can be simulated within the same code. In this context, fully–coupled means that photons can produce electrons and electrons can produce photons; uncoupled or no–coupling means photons do not produce electrons. Partial–coupling, an intermediate option in which photons can produce electrons but electrons do not produce photons, is not considered in the present work. The MCNP code can treat this physics with a Monte Carlo approach. MCNP should be viewed as complementary to SCEPTRE in both computational method (Monte Carlo versus discrete ordinates) as well as data libraries. SCEPTRE and MCNP should provide important checks on each other, especially from complementary modeling frameworks of a S n (discrete ordinates) mesh based method versus Monte Carlo particle based method. In order to learn more about SCEPTRE, and how it might inform engineering work at the Laboratory, we used it to carry out a set of initial studies. This was a series of 1D simulations of photon beams hitting Aluminum slabs. Our studies mainly used SCEPTRE directly, and made little use of the closely associated RAPTURE code (more on this below). The goals of these studies were first, to familiarize ourselves with operating the code, and second, to begin to assess the importance of coupled electron–photon transport. To support these studies, we began to develop a set of scripts to initialize inputs, run tools, process outputs, and plot results. An initial version of these scripts has been committed to the Lightning workflow repository. This memo relates the results of those studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Monte Carlo Analyses of the FOEHN Experiment

The FOEHN critical experiment, which has been carried out at Cadarache (France) in the reactor EOLE in the early 70s, was designed to verify RHF design analyses. This study focuses on the impact of the FOEHN experiment uncertainties on the calculation of the energy deposition. The latter has been obtained by the Monte Carlo codes Serpent and MCNP. In the calculation of the energy deposition, the first code relies on KERMA factors whereas the latter code relies on Q-values. The two Monte Carlo codes share the same geometry and material specifications. In addition to the design and experiment parameters uncertainties, nuclear data also impacts the calculation of the energy deposition. In this study, the MCNP simulations use three different nuclear data library sets: ENDF/B versions VII.0, VII.1, and VIII.0. Finally, the ksens card of MCNP, using perturbation theory, has been used to identify the cross sections and isotopes with largest impact on the effective multiplication factor. By showing that the use of different software and computational methodologies and design parameters uncertainties do not significantly impact the core power distribution, this work demonstrate the appropriateness of the tools and methods employed for the conversion of involute-plate reactors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Methodology to Generate the Decay Gamma Source for a Second Target Station Target Wedge

This report details the specifics of applying the Position-Averaged Method methodology for the calculation of the rotating lasagna-style target wedge activation and the resulting decay gamma source terms. The methodology uses MCNP® Code Version 6.2.0 with the RNUCS patch coupled with CINDER2008 from the AARE V1.0 package. The process begins with model preparations that include ensuring impurities are included in the materials in the regions of interest along with segmentation of the geometry in order to capture the decay gamma source gradients. This report also details the physics models and other MCNP®, CINDER2008, and ADVANTG 3.2.0 related options used to calculate the decay gamma source terms. ADVANTG 3.2.0 is used to generate a weight window set to aid in convergence of the neutron fluxes in the initial MCNP® protons-on-target particle transport calculation to calculate the neutron fluxes and spallation products in the regions of interest. The neutron fluxes and spallation products are then used in the CINDER2008 transmutation calculation, and the decay gamma sources are generated by the AARE_GAMMA_SOURCE_SCRIPT as a part of the AARE V1.0 package. These decay gamma sources include the energy distributions as well as the necessary distributions to sample the location of the source using the cell rejection method. The gamma sources that are produced using the methodology may be used for a wide variety of analysis involving the target wedge. This report includes the material specifications, physics options, proton source term description, geometrical configuration, and post-processing details.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Parallel Programming in MCNP6

Monte Carlo N-Particle (MCNP)1 is a general-purpose Monte Carlo particle transport code developed by Los Alamos National Laboratory (LANL). To efficiently handle long simulations, MCNP version 6 (MCNP6) supports parallel execution using two primary programming models: • Shared-memory task-based threading using OpenMP (Open Multi-Processing), and • Distributed-memory calculations using MPI (Message Passing Interface). The OpenMP and MPI programming models enable MCNP6 to scale from desktop systems to high-performance computing (HPC) clusters, allowing users to run MCNP in one of three parallel modes: • OpenMP-only, • MPI-only, and • Hybrid (MPI + OpenMP). The choice of parallelization mode depends on the underlying computer architecture and the characteristics of the simulation problem.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1996

Investigation of Natural and Man-Made Radiation Effects on Crews on Long Duration Space Missions

Over the past several years, NASA has studied a variety of mission scenarios designed to establish a permanent human presence on the surface of Mars. Nuclear electric propulsion (NEP) is one of the possible elements in this program. During the initial stages of vehicle design work, careful consideration must be given to not only the shielding requirements of natural space radiation, but to the shielding and configuration requirements of the on-board reactors. In this work, the radiation transport code MCNP has been used to make initial estimates of crew exposures to reactor radiation fields for a specific manned NEP vehicle design. In this design, three 25 MW(sub th), scaled SP-100-class reactors are shielded by three identical shields. Each shield has layers of beryllium, tungsten, and lithium hydride between the reactor and the crew compartment. Separate calculations are made of both the exiting neutron and gamma fluxes from the reactors during beginning-of-life, full-power operation. This data is then used as the source terms for particle transport in MCNP. The total gamma and neutron fluxes exiting the reactor shields are recorded and separate transport calculations are then performed for a 10 g/sq cm crew compartment aluminum thickness. Estimates of crew exposures have been assessed for various thicknesses of the shield tungsten and lithium hydride layers. A minimal tungsten thickness of 20 cm is required to shield the reactor photons below the 0.05 Sv/y man-made radiation limit. In addition to a 20-cm thick tungsten layer, a 40-cm thick lithium hydride layer is required to shield the reactor neutrons below the annual limit. If the tungsten layer is 30-cm thick, the lithium hydride layer should be at least 30-cm thick. These estimates do not take into account the photons generated by neutron interactions inside the shield because the MCNP neutron cross sections did not allow reliable estimates of photon production in these materials. These results, along with natural space radiation shielding estimates calculated by NASA Langley Research Center, have been used to provide preliminary input data into a new Macintosh-based software tool. A skeletal version of this tool being developed will allow rapid radiation exposure and risk analyses to be performed on a variety of Lunar and Mars missions utilizing nuclear-powered vehicles.

Bolch, Wesley E.↗

NASA NTRS2014

Path Toward a Unifid Geometry for Radiation Transport

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Lee, Kerry↗

DOE OSTI2020

JMOCUP Physics Depletion Calculations for the As-Run AGR-5/6/7 TRISO Particle Experiment in ATR Northeast Flux Trap

This ECAR documents the as-run Jim Sterbentz’s MCNP ORIGEN Coupled Utility Program (JMOCUP) physics depletion calculation and the calculated results for the AGR-5/6/7 irradiation experiment in the Advanced Test Reactor (ATR). AGR 5/6/7 was irradiated for nine power cycles in the northeast flux trap. The depletion calculations were performed to provide input data for a variety of other engineering analyses supporting the AGR-5/6/7 experiment along with post-irradiation characterization of the tri-structural isotropic (TRISO) particle fuel compacts. Detailed full-core MCNP models and Oak Ridge Isotope Generation (ORIGEN2) radionuclide generation models were specifically developed as part of the JMOCUP Monte Carlo depletion calculations. The MCNP ORIGEN2 computer codes were coupled using the well-established JMOCUP utility modules to couple the two codes and run the depletion calculations. The physics calculations were performed in support of the Advanced Gas Reactor (AGR) program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗