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At least 325 records · Page 18

Recent MCNP6 ® Code Developments and Improvements for Nuclear Engineering Applications [Slides]

The Los Alamos MCNP Monte Carlo radiation transport code has been the international gold standard for particle transport applications for over three decades. Many developments to the code have taken place with several significant new feature additions, major improvements, and enhancements to existing features. With significant institutional and programmatic investment in the code since the time of the last public release in 2018, important code development and infrastructure modernization has taken place and remains a high priority for all ongoing efforts across the code development team.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Random Ray Method Versus Multigroup Monte Carlo: The Method of Characteristics in OpenMC and SCONE

The Random Ray Method (TRRM) is a recently developed approach to solving neutral particle transport problems based on the Method of Characteristics. While the method previously has been implemented only in closed-source or limited-functionality codes, this work describes its implementation in two open-source Monte Carlo codes: OpenMC and SCONE. The random ray implementations required small modifications to the existing Multigroup Monte Carlo (MGMC) solvers, offering a rare venue for redundant, fine-grained, "apples-to-apples" speed and accuracy comparisons between transport methods. To this end, TRRM and MGMC solvers are evaluated against each other using each code's native capabilities on reactor eigenvalue problems with different degrees of energy discretization. On the C5G7 benchmark (featuring only seven energy groups), TRRM achieves a maximum pin power error comparable to or lower than that of MGMC for a given run time. On a problem with 69 energy groups, MGMC is found to scale more efficiently, obtaining a lower pin power error for a given run time. However, the defining difference between the two transport methods is found to be their vastly different uncertainty distributions. Specifically, TRRM is found to maintain similar levels of accuracy and uncertainty throughout the simulation domain whereas MGMC can exhibit orders-of-magnitude greater errors in areas of the problem that feature low neutron flux. For instance, TRRM provided an up to 373 times speed advantage compared with MGMC for computing the flux in low-flux regions in the moderator surrounding the C5G7 core.

42 ENGINEERING↗

Shielding Benchmark Comparison - MCNP6.2

This report documents the calculations performed for a shielding code comparison between various Department of Energy (DOE) sites. These shielding calculations were performed using an experiment drawn from the International Handbook of Evaluated Criticality Safety Benchmark Experiments, published by the Organisation for Economic Cooperation and Development/Nuclear Energy Agency (OECD/NEA). The benchmark selected for comparison is ALARM-CF-AIR-LAB-001 (“Neutron Fields in the Three-Section Concrete Labyrinth from Cf-252 Source, Benchmark ALARM CF AIR LAB-001”). The Y-12 submission for this code comparison was performed with Monte Carlo N Particle (MCNP) Transport Code System, Version 6.2 and Automated Variance Reduction Generator (ADVANTG).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Extension of OpenMC for Fixed Source Transmutation Calculations

This report documents work performed under a Strategic Partnership Project between Argonne National Laboratory (ANL) and the United Kingdom Atomic Energy Authority (UKAEA). The overall goal of this project is to extend OpenMC [1], a community-developed Monte Carlo particle transport code, to be able to perform fixed-source transmutation calculations. In fission and fusion reactors, the high flux of energetic neutrons causes materials within the reactor to “transmute,” or undergo a nuclear reaction that results in the addition/removal of neutrons and protons from the nucleus of an atom. If subjected to these reactions for long enough, the overall composition and physical properties of the material itself begin to change as a result of transmutation. Such a feature is vital for predicting the decrease in tritium production rate within a breeder blanket during the lifetime of a fusion reactor. OpenMC is capable of simulating neutron transport in fission/fusion systems, thereby allowing it to estimate the flux that causes transmutation. It is also capable of solving the transmutation equations, which determine how the composition of a material changes over time due to neutron irradiation and radioactive decay. However, solving the transmutation equations was previously only possible when the source of neutrons came from a fission system. In a fusion system, the source of neutrons is typically determined by a separate code and then given as an input to the particle transport simulation. This is known as a fixed source calculation. Through this project, we have extended OpenMC to solve the transmutation equations for a fixed source calculation. Evaluating the change in material compositions due to transmutation and its effect on physical properties is of key importance to a range of engineering analyses for fission and fusion systems. For example, in a fusion reactor, estimating the dose rate at different physical locations resulting from irradiated materials in the reactor allows designers to ensure that workers are not exposed to doses beyond applicable regulations. In order to properly dispose of irradiated materials, designers also need to estimate the radiotoxicity, which again relies on knowledge of the material composition at some future time. The specific tasks for this project that were agreed to between ANL and UKAEA were as follows: 1. Make changes and additions in the openmc.deplete and related modules in OpenMC to support transmutation calculations following a fixed source transport simulation. 2. Make necessary changes to OpenMC to model transmutation due to an arbitrary set of reactions needed for fusion applications. Use this new capability to generate a depletion chain file based on the TENDL nuclear data library. 3. Improve the openmc.deplete module in OpenMC to keep track of gases produced as a by-product of nuclear reactions during transmutation calculations. 4. Validate the new capabilities by carrying out fixed-source transmutation calculations on a suitable benchmark problem using OpenMC and a comparable Monte Carlo neutron transport code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Verification of Flux Sensitivity Estimates Using the MCNP Tally Perturbation Tool

Nuclear data is commonly used in applications such as nuclear nonproliferation, safeguards, and criticality safety. More specifically, nuclear data is used in predictive simulation codes like the Monte-Carlo N-Particle (MCNP ® ) transport code, Serpent, and similar radiation transport codes. The improvement of nuclear data enables more precise and accurate simulations, which result in higher fidelity designs and reduced operational/procedural costs. Therefore, the improvement of nuclear data is of paramount importance across the nuclear community. Nuclear data is improved and validated through integral benchmark experiments. The design of benchmark experiments is an extensive process; therefore, these experiments are often optimized on multiple characteristics, including sensitivity to the nuclear data, during the design process. Sensitivity is a measure of how much a quantity changes due to changes in independent variables such as experimental configuration. An experimental design that has a larger sensitivity to the nuclear data of interest will have a larger impact on the accuracy and precision of the validated data. Past integral benchmark experiments have primarily used the effective multiplication factor ($k_{eff}$) as the predominant measured quantity; however, experiments designed with other quantities in mind would be able to optimize on validating different areas of the nuclear data. A primary goal of the EUCLID project is to design, constrain, and reduce compensating errors in experiments focused on quantities other than $k_{eff}$ to better validate nuclear data across the board. Currently, there is a capability in MCNP to easily calculate the sensitivity of $k_{eff}$ to specific nuclear data of numerous reactions types and isotopes (KSEN card); however, the sensitivity of other quantities must be estimated in more strenuous manners. For example, the perturbation feature (PERT card) of MCNP can be used to estimate first-order sensitivities of some response in fixed source simulations. A recent announcement revealed that the first- and second-order perturbation features in previous releases of MCNP contained a bug. It was identified that particles were being scored into the wrong energy bin. The bug is in the most recent public release (MCNP6.2); however, a patch has been added to the most up to date version (MCNP6.2.2) that has not been released publicly. A direct comparison of the PERT card results for an F4 (neutron flux averaged over a cell) tally before and after the patch are shown in figure 1. All simulations used in the sensitivity estimates in this report were performed with MCNP6.2.2. This work verifies the patched MCNP perturbation tool by comparing first order sensitivities made using the PERT card to estimates made using manual perturbation of the compact ENDF (ACE) files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Monte Carlo Laplace Transform Estimator for Radiation Transport

This work formulates and implements a Laplace transform estimator in a simple Monte Carlo radiation transport code. The estimator maps flux-based quantities of interest, like reaction rates, from a desired phase-space dimension to the complex Laplace domain. This on-the-fly Monte Carlo integration technique enables the spectral analysis of arbitrary nuclear systems via the Laplace transform. A simple code tests the estimator in neutron slowing-down problems across various infinite media, and the results compare well with Ganapol’s uninverted analytical solution of the neutron slowing-down equation.

97 MATHEMATICS AND COMPUTING↗

Monte Carlo neutronics benchmarks on nuclear fuel depletion: A review

Monte Carlo (MC) neutronics codes are used widely for academic and industrial needs. Several schemes of coupling MC neutronics code with isotope generation and depletion code exist, which are used for performing nuclear fuel depletion simulations. These simulations can estimate the inventory of isotopes in neutron irradiated nuclear reactor fuel. However, the accuracy of these simulations shall be validated through experiments. MC codes are seldom validated by isotopic benchmarks compared to criticality benchmarks. This work compiles and analyzes the fuel depletion benchmarks and validations used to analyze the performance of MC-based fuel depletion neutronics codes. Analyses of these benchmarks and validations showed that the computed concentrations of 133 Cs, 135 Cs, 137 Cs, 148 Nd, 239 Pu, 240 Pu, and 241 Pu in the irradiated fuel by the depletion codes agreed with the measured values within 10% error. However, the computed concentrations of 125 Sb, 242 Cm, 243 Cm, 244 Cm, 245 Cm, and 246 Cm had errors more than 15% compared to the measured values. As a result, Ventina depletion code showed the most accurate predictions for the greatest number of isotope concentrations compared to ORIGEN2 and CINDER90.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Code-Agnostic Driver Application for Coupled Neutronics and Thermal-Hydraulic Simulations

While the literature has numerous examples of Monte Carlo and computational fluid dynamics (CFD) coupling, most are hard-wired codes intended primarily for research rather than as standalone, general-purpose applications. In this work, we describe an open source application, ENRICO, that enables coupled neutronic and thermal-hydraulic simulations between multiple codes that can be chosen at runtime (as opposed to a coupling between two specific codes). The application has been designed such that the control flow logic, domain mapping, nonlinear fixed-point iteration, solution transfers, and convergence checks are all agnostic to the underlying physics solvers used. Special emphasis has also been placed on enabling efficient execution on distributed-memory computing environments. The transfer of solution fields between solvers is performed in memory rather than through filesystem I/O. Additionally, solvers can be configured to run on overlapping or disjoint sets of processes. To date, coupling with the OpenMC and Shift Monte Carlo codes, the Nek5000 CFD code, and a simplified heat diffusion and subchannel solver has been implemented in ENRICO. We present results for coupled simulations of a single light-water reactor fuel assembly based on the NuScale reactor using various combinations of the physics solvers. For this problem, the coupled simulations are shown to converge in about four Picard iterations. A comparison of the heat source and temperature distributions computed by ENRICO using OpenMC coupled with Nek5000 and Shift coupled with Nek5000 illustrates remarkable agreement between the codes.

42 ENGINEERING↗

Implementation of Monte Carlo Transport in the General Relativistic SpEC Code

Neutrino transport and neutrino-matter interactions are known to play an important role in the evolution of neutron star mergers and of their post-merger remnants. Neutrinos cool remnants, drive post-merger winds, and deposit energy in the low-density polar regions where relativistic jets may eventually form. Neutrinos also modify the composition of the ejected material, impacting the outcome of nucleosynthesis in merger outflows and the properties of the optical/infrared transients that they power (kilonovae). So far, merger simulations have largely relied on approximate treatments of the neutrinos (leakage, moments) that simplify the equations of radiation transport in a way that makes simulations more affordable but also introduces unquantifiable errors in the results. To improve on these methods, we recently published a first simulation of neutron star mergers using a low-cost Monte Carlo algorithm for neutrino radiation transport. Our transport code limits costs in optically thick regions by placing a hard ceiling on the value of the absorption opacity of the fluid, yet all approximations made within the code are designed to vanish in the limit of infinite numerical resolution. We provide here an in-depth description of this algorithm, of its implementation in the SpEC merger code, and of the expected impact of our approximations in optically thick regions. We argue that the last is a subdominant source of error at the accuracy reached by current simulations and for the interactions currently included in our code. We also provide tests of the most important features of this code.

79 ASTRONOMY AND ASTROPHYSICS↗

MCNP® Code Version 6.3.1 Release Notes

The Monte Carlo N-Particle® (MCNP® ) code is a general-purpose, continuous-energy, generalized-geometry, time-dependent, radiation transport code developed by the MCNP development team. MCNP calculations provide predictive capabilities that can replace expensive or impossible-to-perform experiments. Specific application problems include simulations of experimental diagnostics, intrinsic radiation, radiation detection and measurement, criticality safety, nuclear threat reduction and response, radiation health protection, nuclear weapons effects, and nuclear forensics. This MCNP code, version 6.3.1, follows the MCNP6.3.0 version. Since the release of MCNP6.3.0, a variety of bug fixes and code enhancements have been completed for MCNP6.3.1. A few new features have also been added to this release to support both ongoing research and the release of the latest ENDF/B-VIII.1 nuclear data library. The MCNP code, version 6.3.1, theory and user input information is documented in MCNP® Code Version 6.3.1 Theory & User Manual, the build guidance for various platforms is documented in MCNP® Code Version 6.3.1 Build Guide, and the verification and validation testing for various application benchmark test suites is documented in MCNP® Code Version 6.3.1 Verification & Validation Testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

(U) A Code System for Cross-Section Uncertainty Propagation for PARTISN

A rudimentary code system has been developed for propagating neutron cross-section uncertainties to response uncertainties using the PARTISN multigroup discrete-ordinates neutron transport code. The code system uses the first-order sandwich rule with sensitivities computed using SENSMG and covariances computed using NJOY. Databases of reaction cross sections and covariances using ENDF/B-VIII.0 data in the LANL standard 30-group structure have been precalculated. The final uncertainty in a k eff example problem compares well with the result from TOFFEE, a similar code that propagates neutron cross-section uncertainties to response uncertainties using the MCNP6 Monte Carlo neutron transport code. Presently, neither code system propagates uncertainties in $\overline{v}$, $\overline{μ}$, or χ, and neither code system propagates nuclide-nuclide covariances

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

General Relativistic Implicit Monte Carlo Radiation-hydrodynamics

Abstract We report on a new capability added to our general relativistic radiation-magnetohydrodynamics code, Cosmos++ : an implicit Monte Carlo (IMC) treatment for radiation transport. The method is based on a Fleck-type implicit discretization of the radiation-hydrodynamics equations, but generalized for both Newtonian and relativistic regimes. A multiple reference frame approach is used to geodesically transport photon packets (and solve the hydrodynamics equations) in the coordinate frame, while radiation–matter interactions are handled either in the fluid or electron frames then communicated via Lorentz boosts and orthonormal tetrad bases attached to the fluid. We describe a method for constructing estimators of radiation moments using path-weighting that generalizes to arbitrary coordinate systems in flat or curved spacetime. Absorption, emission, scattering, and relativistic Comptonization are among the matter interactions considered in this report. We discuss our formulations and numerical methods, and validate our models against a suite of radiation and coupled radiation-hydrodynamics test problems in both flat and curved spacetimes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The FLUKA code: Overview and new developments

The FLUKA Monte Carlo Radiation Transport and Interaction code package is widely used to simulate the interaction of particles with matter in a variety of fields, including high energy physics, space radiation, medical applications, radiation protection and shielding assessments, accelerator studies, astrophysical studies and well logging. This paper gives a brief overview of the FLUKA program and describes recent developments, in particular, improvements in the modelling of particle interactions and transport are described in detail. In addition, an overview of selected applications is given.

Ballarini, Francesca↗

The MCNP ® 6 code: A decade of progress

After several years of effort involved in merging the Los Alamos National Laboratory MCNP5 and MCNPX codes, in 2013 the first production release of version 6 of the Monte Carlo N-Particle ® , or MCNP ® , code MCNP6.1 was distributed publicly. Since then, three significant releases have been issued: MCNP6.1.1beta in 2014, MCNP6.2 in 2018, and MCNP6.3 in 2023. While each release always contains new features, code enhancements, and bug fixes, each version has had a different primary focus, ranging from improved calculational efficiency to new powerful utilities and tools, to software modernization of the code base. With all that has been learned over the first decade of the MCNP6 code, continuous progress is being made toward a modernized, general-purpose Monte Carlo radiation transport code that remains a trusted resource for the global community of practitioners. This paper describes these first 10+ years of the MCNP6 code and its continually improving data libraries, and gives some insight into how the next decade is expected to unfold.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

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↗

Investigation of mode activity in NBI-heated experiments of Wendelstein 7-X

The 2018 operation phase (OP 1.2b) of the stellarator Wendelstein 7-X (W7-X) included, for the first time, neutral beam injection (NBI) to heat the plasma. Since the injection geometry at W7-X is not parallel, this generates both passing and trapped fast particles. During longer phases of NBI injection, with the primary purpose to study the heating efficiency of this system, Alfvén eigenmodes (AEs) were observed by a number of diagnostics, including the phase contrast imaging (PCI) system, the magnetic pick-up coils (Mirnov coils), and the soft x-ray multi-camera tomography system (XMCTS). Alfvén eigenmodes are of great interest for future fusion reactors as it has been shown that the resonant interaction of fast ions with self-excited AEs can lead to enhanced transport of fast ions and potentially to energy losses. This is especially true for so-called gap-modes, Alfvén eigenmodes with frequencies in gaps of the continuous spectrum, since they lack continuum damping. These modes are commonly known to be excited by fast ions, but other destabilizing mechanisms, e.g. the electron-pressure gradient are also possible. In this article we present a first analysis of the experimentally observed frequencies from the theoretical side. The calculation of shear Alfvén wave continua for selected cases and the assignment of observed frequencies to the gaps of the continuous spectra are presented. Using the ideal-MHD code CKA (Könies A. 2007 10th IAEA TM on Energetic Particles in Magnetic Confinement System), we find gap modes that match the experimental measurements in terms of the observed frequencies. We emphasize the crucial roles played by the coupling of sound and Alfvén waves as well as of the Doppler shift arising as a consequence of the radial electric field in W7-X. We employ the perturbative gyrokinetic code CKA-EUTERPE (Feh´er 2013 Simulation of the interaction between Alfv´en waves and fast particles), using a slowing-down distribution function for the fast ions as calculated by the Monte-Carlo particle following code ASCOT (Hirvijoki et al 2014 Comput. Phys. Commun. 185 1310–21) to assess the fast-ion drive. Here we find that the fast-ion drive is insufficient to overcome the background-plasma damping. The fact that unstable modes were observed experimentally may point to problems with the modelling or indicate the existence of other destabilizing mechanisms, e.g. associated with the electron-pressure gradient (Windisch et al 2017 Plasma Phys. Control. Fusion 59 105002) that sensitively depend on the profiles of the background plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Non-local slicing approaches for NNLO QCD in MCFM

We present the implementation of several processes at Next-to-Next-to Leading Order (NNLO) accuracy in QCD in the parton-level Monte Carlo program MCFM. The processes treated are pp → H, W ± , Z, W ± H, ZH, W ± γ, Zγ and γγ and, for the first time in the code, W + W - , W ± Z and ZZ. Decays of the unstable bosons are fully included, resulting in a flexible fully differential Monte Carlo code. The NNLO corrections have been calculated using two non-local slicing approaches, isolating the doubly unresolved region by cutting on the zero-jettiness, $\mathscr{T}_0$, or on q T , the transverse momentum of the colour singlet final-state particles. We find that for most, but not all processes the q T slicing method leads to smaller power corrections for equal computational burden.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗