Improved cache performance in Monte Carlo transport calculations using energy banding

We present an energy banding algorithm for Monte Carlo (MC) neutral particle transport simulations which depend on large cross section lookup tables. In MC codes, read-only cross section data tables are accessed frequently, exhibit poor locality, and are typically too much large to fit in fast memory. Thus, performance is often limited by long latencies to RAM, or by off-node communication latencies when the data footprint is very large and must be decomposed on a distributed memory machine. The proposed energy banding algorithm allows maximal temporal reuse of data in band sizes that can flexibly accommodate different architectural features. The energy banding algorithm is general and has a number of benefits compared to the traditional approach. In the present analysis we explore its potential to achieve improvements in time-to-solution on modern cache-based architectures.United States. Department of Energy. Office of Science (Contract DE-AC02-06CH11357

Thermal Neutron Point Source Imaging using a Rotating Modulation Collimator (RMC)

This thesis demonstrates a previously untested capability of the Rotating Modulation Collimator (RMC) to image a point-like neutron source. The encouraging results, achieved using low-energy neutrons, provide motivation for further refinement and continued research with higher-energy neutrons. The detector and the masks on an existing RMC imaging system were exchanged to function with neutrons. The source in this research produced a poly-energetic spectrum of neutrons through the reaction. The source of alpha particles was a 72.7 mCi 239Pu source. The RMC detector was located 250 cm from the bare source and operated for three hours to generate a modulation profile: The number of particles detected at each rotation angle of the masks – it is unique for each source location. The measured modulation profiles were used in a Maximum-Likelihood-Expectation-Maximization algorithm to reconstruct the images, and a Bootstrap resampling technique was used to determine uncertainty. The reconstructed images exhibited high contrast but low precision. The resampled image locations were widely distributed, but the most frequent value was very accurate. The uncertainty originated from an expectation model that did not account for fast neutron downscatter into the thermal neutron region as well as the fast neutrons streaming through the masks and being detected

Monte Carlo and Depletion Reactor Analysis for High-Performance Computing Applications

This dissertation discusses the research and development for a coupled neutron trans- port/isotopic depletion capability for use in high-preformance computing applications. Accurate neutronics modeling and simulation for \real reactor problems has been a long sought after goal in the computational community. A complementary \stretch goal to this is the ability to perform full-core depletion analysis and spent fuel isotopic characterization. This dissertation thus presents the research and development of a coupled Monte Carlo transport/isotopic depletion implementation with the Exnihilo framework geared for high-performance computing architectures to enable neutronics analysis for full-core reactor problems. An in-depth case study of the current state of Monte Carlo neutron transport with respect to source sampling, source convergence, uncertainty underprediction and biases associated with localized tallies in Monte Carlo eigenvalue calculations was performed using MCNPand KENO. This analysis is utilized in the design and development of the statistical algorithms for Exnihilo\u27s Monte Carlo framework, Shift. To this end, a methodology has been developed in order to perform tally statistics in domain decomposed environments. This methodology has been shown to produce accurate tally uncertainty estimates in domain-decomposed environments without a significant increase in the memory requirements, processor-to-processor communications, or computational biases. With the addition of parallel, domain-decomposed tally uncertainty estimation processes, a depletion package was developed for the Exnihilo code suite to utilize the depletion capabilities of the Oak Ridge Isotope GENeration code. This interface was designed to be transport agnostic, meaning that it can be used by any of the reactor analysis packages within Exnihilo such as Denovo or Shift. Extensive validation and testing of the ORIGEN interface and coupling with the Shift Monte Carlo transport code is performed within this dissertation, and results are presented for the calculated eigenvalues, material powers, and nuclide concentrations for the depleted materials. These results are then compared to ORIGEN and TRITON depletion calculations, and analysis shows that the Exnihilo transport-depletion capability is in good agreement with these codes

Modeling noise experiments performed at AKR-2 and CROCUS zero-power reactors

CORTEX is a EU H2020 project (2017-2021) devoted to the analysis of ’reactor neutron noise’ in nuclear reactors, i.e. the small fluctuations occurring around the stationary state due to external or internal disturbances in the core. One important aspect of CORTEX is the development of neutron noise simulation codes capable of modeling the spatial variations of the noise distribution in a reactor. In this paper we illustrate the validation activities concerning the comparison of the simulation results obtained by several noise simulation codes with respect to experimental data produced at the zero-power reactors AKR-2 (operated at TUD, Germany) and CROCUS (operated at EPFL, Switzerland). Both research reactors are modeled in the time and frequency domains, using transport or diffusion theory. Overall, the noise simulators managed to capture the main features of the neutron noise behavior observed in the experimental campaigns carried out in CROCUS and AKR-2, even though computational biases exist close to the region where the noise-inducing mechanical vibration was located (the so-called ”noise source”). In some of the experiments, it was possible to observe the spatial variation of the relative neutron noise, even relatively far from the noise source. This was achieved through reduced uncertainties using long measurements, the installation of numerous, robust and efficient detectors at a variety of positions in the near vicinity or inside the core, as well as new post-processing methods. For the numerical simulation tools, modeling the spatial variations of the neutron noise behavior in zero-power research reactors is an extremely challenging problem, because of the small magnitude of the noise field; and because deviations from a point-kinetics behavior are most visible in portions of the core that are especially difficult to be precisely represented by simulation codes, such as experimental channels. Nonetheless the limitations of the simulation tools reported in the paper were not an issue for the CORTEX project, as most of the computational biases are found close to the noise source

Applications of Monte Carlo Methods in Biology, Medicine and Other Fields of Science

This volume is an eclectic mix of applications of Monte Carlo methods in many fields of research should not be surprising, because of the ubiquitous use of these methods in many fields of human endeavor. In an attempt to focus attention on a manageable set of applications, the main thrust of this book is to emphasize applications of Monte Carlo simulation methods in biology and medicine

Molecular dynamics as a tool to study heterogeneity in zeolites - Effect of Na cations on diffusion of CO and N in Na-ZSM-5

Zeolites typically contain extra-framework cations to charge-compensate for trivalent Al atom substitutions in the SiO framework. These cations, such as Na, directly interact with quadrupolar guest molecules, such as CO and N, which move through their micropores, causing energetic heterogeneity. To assess the effects of heterogeneity in Na-ZSM-5 on diffusion of CO and N, molecular dynamics (MD) simulations are carried out. In silicalite-1, the pure-silicon form of ZSM-5, the self-diffusivity exhibits a monotonic decrease with molecular loading, while the corrected diffusivity shows a relatively constant value. In contrast, the Na cations cause a maximum or a flat profile over molecular loading for the self- and corrected diffusivities of CO at T=200 and 300K, while the cations only have minimal impact on the diffusivity of N. The MD simulations allow us to identify energy basins or sites at which guest molecules spend a relatively long time, and construct a coarse-grained lattice representation for the pore network. Average residence times at these sites are calculated for both species. The trends observed in the residence times correlate to the trends observed in the diffusivity. The residence times for CO at T=200K are long at low loading, but decrease with loading as additional CO molecules compete to stay close to a cation. In contrast, the residence times for N are relatively insensitive to the cations, only mildly increasing near a cation. This difference in behavior can be associated to the quadrupole moments of these molecules

Numerical modeling study of a neutron depth profiling (NDP) system for the Missouri S&T reactor

”For decades, Neutron Depth Profiling has been used for the non-destructive analysis and quantification of boron in electronic materials and lithium in lithium ion batteries. NDP is one of the few non-destructive analytical techniques capable of measuring the depth profiles of light elements to depths of several microns with nanometer spatial resolution. The technique, however, is applicable only to a handful of light elements with large neutron absorption cross sections. This work discusses the possibility of coupling Particle Induced X-ray Emission spectroscopy with Neutron Depth Profiling to yield additional information about the depth profiles of other elements within a material. The technical feasibility of developing such a system at the Missouri University of Science and Technology Reactor (MSTR) beam port is discussed. This work uses a combination of experimental neutron flux measurements with Monte Carlo radiation transport calculations to simulate a proposed NDP-PIXE apparatus at MSTR. In addition, the possibility of implementing an Artificial Neural Network to perform automated data analysis of NDP is presented. It was found that the performance of the Artificial Neural Network is at least as accurate as traditional processing approaches using stopping tables but with the added advantage that the Artificial Neural Network method requires fewer geometric approximations and accounts for all charged particle transport physics implicitly”--Abstract, page iii

Monte Carlo domain decomposition for robust nuclear reactor analysis

Monte Carlo (MC) neutral particle transport codes are considered the gold-standard for nuclear simulations, but they cannot be robustly applied to high-fidelity nuclear reactor analysis without accommodating several terabytes of materials and tally data. While this is not a large amount of aggregate data for a typical high performance computer, MC methods are only embarrassingly parallel when the key data structures are replicated for each processing element, an approach which is likely infeasible on future machines. The present work explores the use of spatial domain decomposition to make full-scale nuclear reactor simulations tractable with Monte Carlo methods, presenting a simple implementation in a production-scale code. Good performance is achieved for mesh-tallies of up to 2.39 TB distributed across 512 compute nodes while running a full-core reactor benchmark on the Mira Blue Gene/Q supercomputer at the Argonne National Laboratory. In addition, the effects of load imbalances are explored with an updated performance model that is empirically validated against observed timing results. Several load balancing techniques are also implemented to demonstrate that imbalances can be largely mitigated, including a new and efficient way to distribute extra compute resources across finer domain meshes.United States. Dept. of Energy. Center for Exascale Simulation of Advanced Reactor