Uncertainty Quantification and Global Sensitivity Analysis Methods for Monte Carlo Radiation Transport Solvers
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Clements, Kayla [Oregon State University]↗
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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 ↗
Emulation of radiation transport in 3D stochastic media using 1D planar Monte Carlo stochastic media radiation transport algorithms
A subset of stochastic media radiation transport problems involves those in which radiation is incident on a thin slab of stochastic material. Particle tracking in 3D for such problems is expensive, and 1D planar models lack accuracy because they only allow the material to change in one dimension. Therefore, we propose dimensional emulation, which through a slight modification allows existing 1D planar geometry stochastic media radiation transport models to reproduce results from the equivalent 3D models by allowing the material to change in all three dimensions, reproducing the fidelity of the 3D model for the low computational cost of the 1D planar model. In this work, we apply dimensional emulation to three Monte Carlo stochastic media radiation transport models: Chord Length Sampling (CLS), the Local Realization Preserving method (LRP), and a variant of Conditional Point Sampling (CoPS). For a common Markovian benchmark set, the 3D emulation variants of these algorithms are numerically verified to reproduce the results of the 3D variants within statistics while running 1.3 to 2 times faster in the implementation within Sandia National Laboratories open-source research code PlaybookMC. The 3D emulation variants are also shown to yield a 72%–92% reduction in error for the thin slab problems in comparison to the 1D benchmark. As a result, the 3D emulation variant of CLS and CoPS-1 are shown to reproduce 3D CLS results that were used to approximate results for a 3D spherical inclusion geometry benchmark set.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Radiation Dose Modeling for Niowave’s Accelerator Driven Uranium Target Assembly 3
Molybdenum-99 is a high-value radionuclide commonly used for medical purposes within the United States. The National Nuclear Security Administration (NNSA) seeks to reliably produce the radioisotope 99 Mo without the use of highly enriched uranium. NNSA’s Office of Material Management and Minimization (M3) provides funding and government laboratory expertise to private companies to expedite the production process domestically and currently funds designs that use low-enriched uranium or other 99 Mo production pathways. Several production designs are being explored across the industry, including uranium fission and photonuclear conversion of 100 Mo targets. Niowave Inc. seeks to produce 99 Mo via a high-energy electron accelerator that strikes a lead-bismuth eutectic target that ultimately produces a consistent neutron flux. The neutron flux then interacts in a subcritical reactor core configuration to produce fission in low-enriched or natural uranium targets. These fissionable targets are then processed to extract 99 Mo. The purpose of this work is to estimate the neutron and photon dose response across Niowave’s proposed facility for worker safety during operation. Owing to the size of the proposed Niowave facility and necessary shielding, unbiased Monte Carlo radiation transport is impractical, and variance reduction methods are required. This work focuses on the weight window variance reduction method to produce high confidence dose response results within a Monte Carlo radiation transport code. Specifically, an adjoint-informed weight window methodology was created to improve the dose response estimates for accelerator-driven subcritical reactor designs. This adjoint-informed methodology was implemented for Niowave’s proposed design and improved dose results at far-field locations across the facility. Acceptable dose rate contours for the proposed facility were generated across the facility and are presented in this work.
07 ISOTOPE AND RADIATION SOURCES↗
Enhancing Monte Carlo Workflows for Nuclear Reactor Analysis with Metamodel-Driven Modeling
Monte Carlo codes are essential components of many reactor physics simulation workflows as high-fidelity continuous-energy neutron transport solvers. Among Monte Carlo radiation transport codes, MCNP is particularly notable due to its diverse simulation capabilities, large user base, and long validation history. Despite being a powerful simulation tool, MCNP provides limited capabilities to allow automated execution, model transformation, or support for user-defined logic and abstractions that limit its compatibility with modern workflows. Here, to better integrate MCNP into a modern scientific workflow, we have developed an intuitive yet full-featured MCNP Application Program Interface (API) in Python, named MCNPy, which provides a specialized set of classes for MCNP input development. Moreover, to guarantee that our reading, writing, and modeling capabilities remain self-consistent (and to render the huge scope of the MCNP API manageable), we have adopted a strategy of model-driven software development in which a generalized model of the MCNP input format has been created. From this generalized model, or “metamodel,” problem-specific implementations such as an engine for input validation or a codebase for programmatic operations may be automatically generated. Since MCNPy primarily acts as a Python front-end to the underlying Java API that directly interfaces with the metamodel, it is intrinsically linked to the metamodel and thus remains maintainable. With MCNPy, users can programmatically read, write, and modify any syntactically valid MCNP input file regardless of its origin. These capabilities allow users to automate complicated tasks like design optimization and model translation for nuclear systems. As examples, this work demonstrates the use of MCNPy to find the critical radius of a plutonium sphere and to translate a 9000+ line MCNP input file into a corresponding OpenMC model.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
A Computationally Efficient Algorithm for Sampling the Rudd Differential Cross Section
Monte Carlo radiation transport codes such as RITRACKS or Geant4 are used to simulate the interaction of ions with matter. These codes rely on sampling algorithms to determine interactions and various physical properties of particles involved in the simulations. It is crucial to develop efficient sampling algorithms since Monte Carlo radiation transport simulations can be time consuming. This work presents an efficient sampling algorithm to determine the energy of secondary electrons following ion-water interactions. The applicability and intended use of the algorithm are discussed in detail, and it is shown that the new algorithm is up to 6X10 4 times faster than the method currently used in Geant4-DNA.
Floriane Poignant↗
Variance Reduction within Implicit Monte Carlo Thermal Radiation Transport using the Local Importance Function Transform [Slides]
System of equations derived by Fleck and Cummings to model time-dependent thermal radiative transfer (TRT) problems: Solution of radiation specific intensity (I), non-linearly coupled to material internal energy (U); Absorption and re-emission approximated by effective scattering events. Useful for high-energy density physics simulations: i.e., astrophysics, inertial confinement fusion (ICF). Whereas deterministic methods are fully discretized and free of statistical noise, Monte Carlo methods allow for dynamic sampling of the phase space at the price of statistical noise; Monte Carlo methods are also characterized by a slow $\frac{1}{√Ν}$ convergence rate.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Accelerated radiation transport modeling techniques for pencil beam computed tomography using gamma rays
Monte Carlo radiation transport modeling studies were performed for a compact, and high-resolution gamma-ray computed tomography system designed for imaging irradiated nuclear fuel. The system comprises a 60 Co source – chosen for its highly penetrating 1173 keV and 1332 keV gamma rays – a pair of high-aspect-ratio pencil beam collimators, and an inorganic scintillator detector. Here two acceleration methods are proposed to rapidly model a transmission type gamma-ray tomography system. The first, a variance reduction technique, is based on performing Monte Carlo simulations with a monodirectionally-biased source, sampled from a characteristic sub-volume of the full source volume. The second acceleration method is based on the deterministic calculations using the Beer–Lambert law and detector response characteristics. Comparison of simulations using acceleration approaches with analog simulations of the fully isotropic, full-volume equivalent, show that the Monte Carlo variance reduction technique gives quantitatively accurate predictions for large collimator aspect ratios while the deterministic calculations are semi-quantitative but converge close to the correct result as the collimator aspect ratio increases. As such, these techniques can be used to reduce the computational cost in generating simulated radiographs and tomographs by several orders of magnitude. Experimental validation efforts are currently underway and will be demonstrated in future work.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Nuclear Astrophysics through simulations of neutron star mergers using Monte‐Carlo neutrino radiation transport (DE-SC0020435 Final Technical Report)
Neutron star mergers are an important source of information for nuclear physics. Except for black holes, neutron stars are the densest macroscopic objects known to exist in the Universe. They provide us with a remarkable laboratory to study the poorly understood high-density states of matter, complementing the study of heavy nuclei performed by nuclear physics experiments on Earth. Collisions of neutron stars are of particular interest. They are among the most energetic events observable in the Universe, powering a broad range of signals across the electromagnetic spectrum as well as gravitational wave signals. These signals contain important information about the properties of extremely dense matter. Colliding neutron stars additionally eject large amounts of neutron-rich material into the surrounding interstellar medium -- material that then undergoes rapid neutron-capture (r-process) nucleosynthesis, the mechanism thought to be responsible for the production of about half of the heavy nuclei. In order to understand current and future observations of neutron star mergers, we need reliable models for the signals that they power. An important component in the construction of such models are numerical simulations of colliding neutron stars. These simulations are costly, running for multiple months on supercomputers, and require the inclusion of complex physics (general relativity, magnetohydrodynamics, neutrino physics, nuclear reactions). In this document, we describe the development of new methods for the treatment of neutrinos in merger simulations, as well as the first simulations capable of evolving the equations of neutrino radiation transport directly and their impact on our understanding of neutron star mergers and more broadly in nuclear astrophysics. We also discuss additional work performed in the study of nucleosynthesis and neutrino physics in neutron star mergers as part of Early Career Award DE-SC0020435.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Monte Carlo Thermal Radiation Transport With Nonlinear Elimination
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Physics - Nuclear physics and radiation physics↗
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↗
Demonstration of the On-the-Fly Shielding Analysis Method: Spent Fuel and Waste Disposition
This report documents work performed supporting the US Department of Energy (DOE) Office of Nuclear Energy (NE) Spent Fuel and Waste Disposition (SFWD) Integrated Waste Management activities under work breakdown structure element 1.08.02.04.01, “Data and Tools Development, Validation, and Maintenance.” In particular, this report fulfills milestone M3SF-21OR020401016, “Implement on-the-fly dose analysis methodology in UNF-ST&DARDS” within work package SF-21OR02040101, “Commercial SNF Characterization - ORNL.” The Used Nuclear Fuel - Storage, Transportation & Disposal Analysis Resource and Data System (UNFST& DARDS) enables automated dose rate calculations for spent nuclear fuel (SNF) transportation packages and storage casks using a Monte Carlo radiation transport code. The explicit method uses a detailed model of the SNF system and its contents. Therefore, a dose rate calculation is required for each as-loaded transportation package or storage cask because the SNF assemblies within a canister typically have unique irradiation characteristics. An alternate method, referred to as the “on-the-fly” shielding analysis method, has been proposed that requires only a set of Monte Carlo dose rate calculations for each transportation packaging/storage cask design. The results of the Monte Carlo dose rate calculations are independent of the SNF assembly irradiation and decay characteristics. The dose rate values may then be combined with the radiation source strength of the SNF assemblies associated with a particular transportation packaging/storage cask design to determine actual dose rates. This report presents on-the-fly dose rate calculations for a representative SNF storage cask and verification of the on-the-fly dose rate calculation results by comparison with reference dose rate calculations using the explicit Monte Carlo dose rate calculation. The on-the-fly shielding analysis method was implemented in UNF-ST&DARDS. A Python program was developed to process the MAVRIC dose rate results obtained by source particle type, energy group, and fuel geometry region. A Python processor created binary files, which were saved as a special UNF-ST&DARDS library for on-the- fly shielding analyses. UNF-ST&DARDS uses the precalculated on-the-fly binary libraries generated by the Python data processor and directly executes the Python code for on-the-fly dose analysis. This Python code unzips the pre-generated binary files mentioned above, reads the data, and combines them with user-specified sources for dose and uncertainty calculations. The Python programs were verified using Excel calculations and by comparison with the values obtained with the MAVRIC post-processing utilities applied to the 3dmap files. This method can currently be used to determine dose rates for as-loaded HI-STORM FW storage casks. The UNF-ST&DARDS analysis wizard for on-the-fly shielding analysis is described in this report.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Directional dependence of equilibrated TLD-400 chips in multiple radiation fields
Fielding of thermoluminescent dosimeters (TLDs) for measurement of photon radiation dose in experiments is the standard practice for γ-irradiation facilities, pulsed power x-ray facilities, and reactor facilities at Sandia National Laboratories (SNL). Due to the high-dose experimental conditions and the mixed ( 1 n, γ) fields in these facilities, SNL radiation metrologists have historically used CaF 2 :Mn TLDs (also known as TLD-400). Recent inquiries to the radiation metrology staff have raised concerns that the aluminum-equilibrated TLD-400 chips may exhibit a directionally dependent response. The metrologists were asked whether the dose measured by the chip may be impacted by the angle of incidence on the equilibrated TLD. To provide a thorough answer to this query, a set of adjoint Monte Carlo radiation transport calculations was performed for three different equilibrated TLDs as well as bare TLD chips using the Integrated Tiger Series (ITS) code. The key feature of the adjoint calculations performed in this study is that each photon escaping the modeled geometry was tallied into angular bins to provide information on both the energy and angular dependence of the equilibrated chip. After the adjoint Monte Carlo calculations were completed, the resulting energy-dependent response function for each angular bin was convolved with multiple photon energy spectra representing various radiation facilities at SNL. The radiation facilities selected for analysis span a range of photon energies from approximately 1 keV up to approximately 20 MeV. Thus, the presented results are applicable to a wide variety of radiation facilities around the world. Although the bare TLD-400 chip was expected to display the largest variation due to the photon angle of impact on the dosimeter, the dosimeter with the thinnest aluminum equilibrator (SNL thin equilibrated TLD-400) was determined to have the biggest differential between the impact angle with the maximum dose ( D max ) and the impact angle with the minimum dose ( D min ). However, the SNL normal equilibrated TLD-400 chip demonstrated a dramatic reduction in that differential between maximum and minimum dose angles. The reduction in this differential is one of the dominant factors in experimenters’ choice to field these dosimeters at SNL radiation facilities. The results from the PNNL (Hanford) energy-flattening field capsule are consistent with the previous publications. The differential dose responses due to the photon impact angle indicate that experimenters should strive to field their TLD-400 dosimeters in a consistent manner to avoid additional uncertainty in the measurements based on dosimeter orientation.
Adjoint radiation transport↗
Total Dose Survivability of Hubble Electronic Components
A total dose analysis for exposure of electronic parts at the box level is presented for the Hubble Space Telescope. This was done using solid angle sectoring/3-dimensional ray trace and Monte Carlo radiation transport simulations. Results are discussed in terms of parts that are potential total dose concerns.
Monte Carlo radiation transport simulation↗
Preliminary Validation of the Shift Monte Carlo Code for Fixed-Source Radiation Transport Problems
Simulations of neutron and photon transport using the Shift Monte Carlo radiation transport code are compared with experimental measurements and their corresponding benchmark simulations from several sets of experiments. Overall, Shift results match the calculations made by the benchmark teams quite well and match the measured values, which typically have large uncertainties, fairly well. A variety of attenuation/scattering problems are examined, as well as a streaming problem and a skyshine problem.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Computation of Cosmic Ray Ionization and Dose at Mars: a Comparison of HZETRN and Planetocosmics for Proton and Alpha Particles
The ability to evaluate the cosmic ray environment at Mars is of interest for future manned exploration. To support exploration, tools must be developed to accurately access the radiation environment in both free space and on planetary surfaces. The primary tool NASA uses to quantify radiation exposure behind shielding materials is the space radiation transport code, HZETRN. In order to build confidence in HZETRN, code benchmarking against Monte Carlo radiation transport codes is often used. This work compares the dose calculations at Mars by HZETRN and the Geant4 application Planetocosmics. The dose at ground and the energy deposited in the atmosphere by galactic cosmic ray protons and alpha particles has been calculated for the Curiosity landing conditions. In addition, this work has considered Solar Energetic Particle events, allowing for the comparison of varying input radiation environments. The results for protons and alpha particles show very good agreement between HZETRN and Planetocosmics.
Gronoff, Guillaume↗
Radiation transport codes for potential applications related to radiobiology and radiotherapy using protons, neutrons, and negatively charged pions
Several Monte Carlo radiation transport computer codes are used to predict quantities of interest in the fields of radiotherapy and radiobiology. The calculational methods are described and comparisions of calculated and experimental results are presented for dose distributions produced by protons, neutrons, and negatively charged pions. Comparisons of calculated and experimental cell survival probabilities are also presented.
Armstrong, T. W.↗
Ex-Core Radiation Transport Modeling with VERA User Manual
It is important to be able to accurately predict the neutron flux outside the immediate reactor core for a variety of safety and material analyses. Monte Carlo radiation transport calculations are required to produce these high–fidelity ex-core responses. The Virtual Environment for Reactor Applications (VERA) provides the automated capability to launch independent Shift fixed-source and eigenvalue Monte Carlo (MC) calculations for user-specified state points during a standard Virtual Environment for Reactor Applications (VERA) calculation. VERA couples MPACT with COBRA-TF (CTF) to Shift to perform ex-core tallies for multiple state points concurrently, with each component capable of parallel execution on independent processor domains. In these ex-core calculations, MPACT is coupled to CTF and performs the in-core depletion and heat transfer calculation, followed by a fixed-source Shift transport calculation including ex-core regions to produce ex-core responses. The fission source, fuel pin temperatures, moderator temperature and density, boron concentration, and fuel pin depleted isotopic compositions can be transferred to Shift from the MPACT calculation. Specifically, VERA performs fluence calculations in the core barrel outward to the end of the pressure vessel and detector response calculations in ex-core detectors. It also performs the requested tallies in any user-defined ex-core regions. VERA takes advantage of the General Geometry (GG) package in Shift. This gives VERA the flexibility to explicitly model features outside the core barrel, including detailed vessel models, detectors, and power plant details. A very limited set of experimental and numerical benchmarks is available for ex-core simulation comparison. The Consortium for Advanced Simulation of Light Water Reactors has developed a set of ex-core benchmark problems to include as part of the VERA verification and validation set of problems. The ex-core capability in VERA has been tested on small representative assembly problems, multi-assembly problems, as well as quarter-core and full-core problems. VERA View has also been extended to visualize these vessel fluence results from VERA. This manual serves to present a guide to VERA users about the methodology behind ex-core calculations and the details of input, output, and analysis of results from these calculations. Details in this version of the manual are based on features in VERA 4.0.1.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗