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At least 19 records

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗

Development of the first relativistic electron loss probe with pitch and energy resolution in the DIII-D tokamak

A relativistic electron probe has been developed in the DIII-D tokamak, capable of simultaneously resolving pitch angles and energies of runaway electrons (REs) for the first time. Due to the relativistic speeds of REs, their gyro-orbit size becomes comparable to those of fast deuterium with energies in the tens of keV range. This allows for the measurement of RE strike images on a phosphor plane, with their orbits being deflected by the Lorentz force as they pass through a pinhole aperture. The strike positions correspond to the energies and pitch of the incident REs. Monte Carlo N-Particle Transport Code has shown that an ultra-thin phosphor coating significantly reduces the energy deposition from γ-rays, while allowing a much greater deposition from REs, minimizing the background noise. Finally, the novel system, developed for the DIII-D tokamak, is expected to provide unprecedented insights into the phase-space dynamics of REs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rates for neutron-capture reactions on tungsten isotopes in iron meteorites

High-precision W isotopic analyses by Harper and Jacobsen indicate the W-182/W-183 ratio in the Toluca iron meteorite is shifted by -(3.0 +/- 0.9) x 10(exp -4) relative to a terrestrial standard. Possible causes of this shift are neutron-capture reactions on W during Toluca's approximately 600-Ma exposure to cosmic ray particles or radiogenic growth of W-182 from 9-Ma Hf-182 in the silicate portion of the Earth after removal of W to the Earth's core. Calculations for the rates of neutron-capture reactions on W isotopes were done to study the first possibility. The LAHET Code System (LCS) which consists of the Los Alamos High Energy Transport (LAHET) code and the Monte Carlo N-Particle(MCNP) transport code was used to numerically simulate the irradiation of the Toluca iron meteorite by galactic-cosmic-ray (GCR) particles and to calculate the rates of W(n, gamma) reactions. Toluca was modeled as a 3.9-m-radius sphere with the composition of a typical IA iron meteorite. The incident GCR protons and their interactions were modeled with LAHET, which also handled the interactions of neutrons with energies above 20 MeV. The rates for the capture of neutrons by W-182, W-183, and W-186 were calculated using the detailed library of (n, gamma) cross sections in MCNP. For this study of the possible effect of W(n, gamma) reactions on W isotope systematics, we consider the peak rates. The calculated maximum change in the normalized W-182/W-183 ratio due to neutron-capture reactions cannot account for more than 25% of the mass 182 deficit observed in Toluca W.

Masarik, J.↗

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↗

Radiation Transport Tools for Space Applications: A Review

This slide presentation contains a brief discussion of nuclear transport codes widely used in the space radiation community for shielding and scientific analyses. Seven radiation transport codes that are addressed. The two general methods (i.e., Monte Carlo Method, and the Deterministic Method) are briefly reviewed.

Cosmic Ray Effects on Micro-Electronics (CREME96)↗

Quantifying uncertainty in uranium concentration measurements via K-edge densitometry

This study quantifies the uncertainty in uranium concentration predictions of fluoride and chloride-based salts within a steel pipe using K-edge densitometry. Modeling and simulation was conducted with the Monte Carlo N-Particle Transport (MCNP) code. The quality of of this technique’s prediction in a pipe requires proper characterization of the pipe’s thickness, which is dependent on the source size and axial offset from the pipe centerline. The thickness was determined as either the center-line thickness seen by the X-ray source or an average value determined through random sampling. Generally, the predicted concentrations were slightly better at lower offset with the random sampling thickness and using the center-line thickness for the highest offsets. For a line-beam source and varying axial offsets, the relative error of concentration was within 1% of the true value but uncertainty increased by 2 orders of magnitude. Similarly, for no axial offset, the relative error was significantly less than 1% while no trend for uncertainty was found. However, at the largest possible offset for a given source size, the concentrations become erroneous and greater than the allowable 1% relative error. Furthermore, high offsets tended to increase the variance of the transmission spectra by 3 orders of magnitude.

Characterization and Analytical Technique↗

Materials for Low-Energy Neutron Radiation Shielding

Various candidate aircraft and spacecraft materials were analyzed and compared in a low-energy neutron environment using the Monte Carlo N-Particle (MCNP) transport code with an energy range up to 20 MeV. Some candidate materials have been tested in particle beams, and others seemed reasonable to analyze in this manner before deciding to test them. The two metal alloys analyzed are actual materials being designed into or used in aircraft and spacecraft today. This analysis shows that hydrogen-bearing materials have the best shielding characteristics over the metal alloys. It also shows that neutrons above 1 MeV are reflected out of the face of the slab better by larger quantities of carbon in the material. If a low-energy absorber is added to the material, fewer neutrons are transmitted through the material. Future analyses should focus on combinations of scatterers and absorbers to optimize these reaction channels and on the higher energy neutron component (above 50 MeV).

Singleterry, Robert C., Jr.↗

Modeling Radiation Sources for Experimental Validation

To build on previously completed experimental work, I have been working to implement a model of our lab’s Americium-Beryllium neutron source and Ludlum detection instruments computationally to provide secondary verification of our experimental results. This has been done using the radiation transport code MCNP6 (Monte Carlo N-Particle). I have developed files to calculate the mass ratio of various composite materials that we have exposed to the radiation source, as well as the components of the detection instruments and converted all of these into geometric coordinates that define the experimental setup. Identifying the proper energy distribution and detector efficiencies as well as the correct interpretation of the detector physics have proven to be the most difficult and time-consuming challenges of the work. It is currently too early for results based on the most updated and accurate models. With this experience, the next step is to develop another source model of a proton beam to simulate exposures on other composite targets. This will be developed based on existing experimental datasets, but not used to validate them. Each of these projects will further define the radiation shielding needs for humans in space radiation environments that astronauts will someday be exposed to beyond Low Earth Orbit.

Juliana Simon↗

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING↗

MCNP® Code Version 6.3.2 Theory & User Manual (Rev. 1)

This document acts as a repository of knowledge for the Monte Carlo N-Particle (MCNP) transport computer code. It is maintained alongside the source code and attempts to introduce new users and re-familiarize experienced users with the theory and practices of using the MCNP code for the wide range of particle transport analyses that it is appropriate for. The latest version of the MCNP code, version 6.3.2, provides the Monte Carlo particle transport community with the latest feature developments and bug fixes in the MCNP code. The MCNP code version 6.0 and later is also known as the MCNP6 code.

42 ENGINEERING↗

Impact of Time Dependent Reactor and Sensor Physics on Core Power Synthesis

Online synthesis of the power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins, and to provide essential knowledge associated with the burnup of the fuel. In light water reactors (LWRs), power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report aims to study the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a LWR. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative pressurized water reactor low-enriched uranium (LEU) core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used, as well, to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative (PBI) method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly under- or over-approximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumption leads to severe levels of error, approaching 25% at maximum. The authors also discovered that V SPNDs are extraordinarily robust in the low-enriched uranium fuel cycle considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Impact of Time-Dependent Reactor and Sensor Physics on Core Power Synthesis (Rev.1)

Online synthesis of power distribution is critical in the operation and control of nuclear power reactors to ensure that the core is operating within safety margins and to provide essential knowledge associated with the burnup of the fuel. In light-water reactors, power synthesis is achieved by using some a priori knowledge of the state of the reactor core and updating based on the signals coming from in-core sensors—namely, self-powered neutron detectors (SPNDs). This report examines the effects of fuel burnup and sensor degradation on the ability to accurately synthesize the power distribution in a pressurized water reactor (PWR), considering the typical low-enriched uranium (LEU, 3%-5% enrichment) fuel cycle as well as the higher enrichment LEU+ (5%-8% enrichment) fuel cycle. Several modeling tools were used to simulate power synthesis based on the responses of SPNDs, with emitters made out of Rh or V. A representative PWR LEU core was modeled using the Polaris/Purdue Advanced Reactor Core Simulator (PARCS) approach. The Monte Carlo N-Particle Transport 6 (MCNP6) code was used as well to calculate response functions between different segments of fuel to individual SPNDs; this is a crucial parameter for power synthesis. The Oak Ridge Isotope GENeration (ORIGEN) package in the Standardized Computer Analyses for Licensing Evaluation (SCALE) code was used to model the time-dependent isotopic transmutation in the SPND emitters. All these data were fed into a custom code that enacted the point-based iterative method to simulate power synthesis. Developmental work was also performed on high-fidelity SPND models in the GEometry ANd Tracking 4 (Geant4) code, which enables higher-accuracy modeling of the current responses from SPNDs. In this work, five sets of time-dependent power synthesis test cases were conducted. In these test cases, systematic changes in the input conditions enabled an analysis of the effect of (1) slightly inaccurate a priori power distribution assumptions with respect to fuel burnup, (2) highly inaccurate a priori power distribution assumptions with respect to fuel burnup (such that burnup is not included in the a priori assumed distribution), and (3) differences between Rh and V SPNDs in terms of downstream consequences of the transmutation in the emitters and the extended nature of the LEU+ fuel cycle in comparison with LEU. The authors discovered that one may permissibly have slightly inaccurate a priori assumptions of the fuel burnup (such that the level of burnup may be slightly underapproximated or overapproximated by the accumulated burnup in approximately 9.3 full power days), but to not account for burnup at all in the a priori assumptions leads to severe levels of error, approaching 25% at maximum (for LEU). The authors also discovered that V SPNDs are extraordinarily robust in both the LEU and LEU+ fuel cycles considered in this modeling work, whereas Rh SPNDs undergo significant transmutation that can result in large errors in the synthesized power distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Monte Carlo Analysis of Pion Contribution to Absorbed Dose from Galactic Cosmic Rays

Accurate knowledge of the physics of interaction, particle production and transport is necessary to estimate the radiation damage to equipment used on spacecraft and the biological effects of space radiation. For long duration astronaut missions, both on the International Space Station and the planned manned missions to Moon and Mars, the shielding strategy must include a comprehensive knowledge of the secondary radiation environment. The distribution of absorbed dose and dose equivalent is a function of the type, energy and population of these secondary products. Galactic cosmic rays (GCR) comprised of protons and heavier nuclei have energies from a few MeV per nucleon to the ZeV region, with the spectra reaching flux maxima in the hundreds of MeV range. Therefore, the MeV - GeV region is most important for space radiation. Coincidentally, the pion production energy threshold is about 280 MeV. The question naturally arises as to how important these particles are with respect to space radiation problems. The space radiation transport code, HZETRN (High charge (Z) and Energy TRaNsport), currently used by NASA, performs neutron, proton and heavy ion transport explicitly, but it does not take into account the production and transport of mesons, photons and leptons. In this paper, we present results from the Monte Carlo code MCNPX (Monte Carlo N-Particle eXtended), showing the effect of leptons and mesons when they are produced and transported in a GCR environment.

Aghara, S.K.↗

Lunar Surface Reactor Shielding Study

Nuclear reactor system could provide power to support a long term human exploration to the moon. Such a system would require shielding to protect astronauts from its emitted radiations. Shielding studies have been performed for a Gas Cooled Reactor (GCR) system because it is considered to be the most suitable nuclear reactor system available for lunar exploration, based on its tolerance of oxidizing lunar regolith and its good conversion efficiency (Wright, 2003). The goals of the shielding studies were to provide optimal material shielding configuration that reduces the dose (rem) to the required level in order to protect astronauts, and to estimate the mass of regolith that would provide an equivalent protective effect if it were used as the shielding material. All calculations were performed using MCNPX code, a Monte Carlo transport code.

Monte Carlo N-Particle eXtended (MCNPX)↗

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↗

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↗

Earth and Planetary Science Letters

Systematic measurements of the concentrations of cosmogen Ca-41 (half-life = 1.04 x 10(exp 5) yr) in the Apollo 15 long core 15001-15006 were performed by accelerator mass spectroscopy. Earlier measurements of cosmogenic Be-10, C-14, Al-26, Cl-36, and Mn-53 in the same core have provided confirmation and improvement of theoretical models for predicting production profiles of nuclides by cosmic ray induced spallation in the Moon and large meteorites. Unlike these nuclides, Ca-40 in the lunar surface is produced mainly by thermal neutron capture reactions on Ca-40. The maximum production of Ca-41, about 1 dpm/g Ca, was observed at a depth in the Moon of about 150 g/sq cm. For depths below about 300 g/sq cm, Ca-41 production falls off exponentially with an e-folding length of 175 g/sq cm. Neutron production in the Moon was modeled with the Los Alamos High Energy Transport Code System, and yields of nuclei produced by low-energy thermal and epithermal neutrons were calculated with the Monte Carlo N-Particle code. The new theoretical calculations using these codes are in good agreement with our measured Ca-41 concentrations as well as with Co-60 and direct neutron fluence measurements in the Moon.

K. Nishiizumi↗

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↗