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This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.
As part of the effort to modernize the ORIGEN depletion code [1], various “resources” have been created to store the fundamental nuclear data required for ORIGEN calculations, such as fission yields, decay data, and cross sections. The resources provide a convenient interface to load the same data from various file formats. Resources can be used directly in unit conversions (e.g., the decay resource can be used to convert atoms to activity) and are the fundamental input used to create an ORIGEN library, which is a fixed data collection of a specific set of nuclides and transitions. This report focuses on the extension of the yield resource and the decay resource, which allow ENDF-formatted nuclear data files [2] to be read directly.
Modern residential building energy codes provide a component tradeoff mechanism by which builders can trade reductions in the efficiency of some building components in trade for corresponding improvement in other components. One common tradeoff approach is based on maintaining a building "UA value," which represents the building envelope's overall thermal conductance. The building UA is the sum of individual component UA values, each of which is calculated as the product of the component's U-factor and area. Current codes, however, provide little guidance on including slab-on-grade components in the overall UA calculation. This brief provides information on calculating effective slab UA values and provides recommended text for building codes.
The objective of the Nuclear Criticality Safety Program (NCSP) Analytical Methods program element is to sustain state-of-the-art radiation transport modeling capabilities and the expertise necessary to develop, maintain, and disseminate the analytical tools and data libraries in a manner that is responsive to the needs of those responsible for developing, implementing, and maintaining criticality safety. To this end, the objective of the AMPX Development and Maintenance Subtask is to ensure that the AMPX cross-section processing system is available to prepare cross-section and covariance libraries that are needed by SCALE and other radiation transport packages to support criticality safety analyses of systems with fissionable material. Moreover, the task ensures that the cross-section processing software is current and up-to-date with the Evaluated Nuclear Data File (ENDF/B) formats and procedures for disseminating evaluated cross-section data provided through new measurement and evaluation work efforts. The AMPX subtask provides for the production of data libraries needed for criticality safety analyses. As such, the task provides the “bridge” between the nuclear data evaluations and the radiation transport software. In the absence of the AMPX cross-section processing task, the ability to maintain and update the SCALE nuclear data libraries (cross-section and covariance data) would be hindered. Therefore, the AMPX Development and Maintenance Subtask ensures that SCALE is up-to-date with the latest cross-section data for supporting criticality safety analyses. This letter report provides a summary of the FY 2015 AMPX development and maintenance activities that have been performed in support of the NCSP. Specifically, the report summarizes the AMPX code system updates and modernization accomplishments that have been made to the software package. Also, the report documents the cross-section library updates that have been made for the SCALE radiation transport package. In addition, the report documents testing activities that have been performed to process available cross-section and covariance data files to ensure the latest ENDF/B data files can be processed properly. This report satisfies the following reporting milestone in the NCSP FY16-20 Five Year Plan: Document AMPX modernization and technical support for SCALE continuous energy (CE), multigroup (MG), and covariance libraries and report status annually to the NCSP Manager (AM3: Q2)
The EFIT-AI project is creating a modern advanced equilibrium reconstruction code suitable for tokamak experiments of burning plasmas. EFIT [1,2] was the first and is the most extensively used equilibrium reconstruction code in the world. This project builds on the production-level experience and adds key elements as follows. 1. A Model Order Reduction (MOR) version of the two-dimensional (2D) Grad-Shafranov equation solver (EFIT-MORNN) using physics-informed neural networks. 2. Improved optimization and data analysis capabilities using a Bayesian framework enhanced with machine learning. 3. A MOR version of the three-dimensional (3D) perturbed equilibrium reconstruction tool.
MCFM is a dedicated Monte-Carlo simulation program for collider phenomenology at highest energies. Designed during the Tevatron era, it has successfully incorporated the latest developments needed for LHC precision calculations and remained on the forefront of collider phenomenology. The Fortran code includes interfaces to modern PDF and loop reduction libraries but has been unchanged structurally compared to the earlier versions. Parallel computing has been enabled using OpenMP and MPI. MCFM provides numerically highly stable one-loop amplitudes and superior phase-space efficiency, leading to excellent performance in NXLO calculations using jettiness or qT subtraction techniques for IR regularization.
AWE (UK), IRSN (France), LLNL (USA) and ORNL (USA) began a long term collaboration effort in 2015 to update the nuclear criticality Slide Rule for the emergency response to a nuclear criticality accident. This document, published almost 20 years ago, gives order of magnitude estimates of key parameters, such as number of fissions and doses (neutron/gamma), useful for emergency response teams and public authorities. This paper presents, firstly, the motivation and the long term objectives for this update, then it introduces the initial critical configuration, and finally it presents the preliminary results obtained with modern 3D radiation transport codes and nuclear data for new configurations including plutonium systems. (authors)
BISON is a modern nuclear fuel performance code that has been under development at Idaho National Laboratory (INL) since 2009. It is a finite element-based code capable of solving the energy, mechanics, and species diffusion equations in a fully-coupled sense. BISON also utilizes thermal and mechanical contact algorithms and variety of nonlinear material models. BISON is applicable to steady and transient fuel behavior and supports the use of one-, two-, and three-dimensional meshes. Although thus far used primarily to simulate light water reactor fuel, BISON is designed to be a multi-fuels code. As such, BISON has been used to analyze TRISO-coated particle fuel and metal fuel in rod and plate form, design and interpret fuel irradiation experiments and investigate novel fuel concepts. This publication provides a preliminary list of metal fuel-related material models recently implemented in BISON. Some preliminary results from a simulation of the EBR-II X447 experiment are shown, which begins to demonstrate how all these models work together. A follow-up publication will be presented with more detail at the ANS meeting in New Orleans during the embedded topical meeting titled 'Nuclear Fuels and Structural Materials for the Next Generation Nuclear Reactors'. (authors)
To meet regulatory needs for sodium fast reactors’ future development, including licensing requirements, Sandia National Laboratories is modernizing MELCOR, a severe accident analysis computer code developed for the U.S. Nuclear Regulatory Commission (NRC). Specifically, Sandia is modernizing MELCOR to include the capability to model sodium reactors. However, Sandia’s modernization effort primarily focuses on the containment response aspects of the sodium reactor accidents. Sandia began modernizing MELCOR in 2013 to allow a sodium coolant, rather than water, for conventional light water reactors. In the past three years, Sandia has been implementing the sodium chemistry containment models in CONTAIN-LMR, a legacy NRC code, into MELCOR. These chemistry models include spray fire, pool fire and atmosphere chemistry models. Only the first two chemistry models have been implemented though it is intended to implement all these models into MELCOR. A new package called “NAC” has been created to manage the sodium chemistry model more efficiently. In 2017 Sandia began validating the implemented models in MELCOR by simulating available experiments. The CONTAIN-LMR sodium models include sodium atmosphere chemistry and sodium-concrete interaction models. This paper presents sodium property models, the implemented models, implementation issues, and a path towards validation against existing experimental data.
This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0019441. The theme of this project was to develop and apply methods that allowed for the acceleration of atomistic calculations, particularly in challenging areas such as multiphase systems, electrified interfaces, uncertainty estimation, and applications requiring chemical accuracy, which tend to be applications where simulation time is severely bottlenecked by the computational time requirements. Much of the focus was on the application of emerging machine-learning methodologies, although a wide range of methodologies were employed. This report has two major sections. The first focuses on the methodological advances themselves. Within this part, we report a number of major advances, a few examples of which are described here. We report the first machine-learning scheme for the acceleration of electronically grand-canonical calculations (that is, those applicable to electrochemistry). We report new methods of performing transfer learning, in which physics-based priors can be used to provide predictions, often with uncertainty estimates, of images well outside of training sets; we also offer ways to fine-tune these transfer-learning models. We provide a new systematic means to generate and apply minimal training data sets to very large (10,000’s of atoms) systems, with only small training sets appropriate for electronic structure. We developed new methodologies to integrate surface vibrations into surface adsorption calculations. We made advances to the applicability of diffusion Monte Carlo methods to allow (learned) force prediction, finite-size error correction, and force-free means of searching for transition states. We integrated machine-learned atomistic predictions into mechanism generation codes. Additionally, we released new software including AmpTorch, a modernized version of our original atomistic machine-learning code Amp. The second part of this report focuses on the scientific applications that accompanied, and were often enabled by, the methodological advances described earlier. A few examples follow, but full details are in the individual chapters of the report. For example, we developed a general theory of phonon-induced friction on molecular adsorbates. We showed fundamentally how solvent influences the adsorption and desorption process and how it differs from the processes typically involved at the solid–gas interface, making aqueous-phase and electrocatalysis different from traditional thermocatalysis. We examined how metal–insulator and magnetic transitions can be probed, and accelerated exciton dynamics via Frenkel Hamiltonian parameters. We showed that the nearsighted force-training approach, developed within this project, can predict both the stability and reactivity of large nanoparticles, and can also lead to insights on catalyst coverage on binding energies and entropies. These applied studies, which generally integrated with our method development, allowed us to push forward the theoretical understanding of several reaction classes.
Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision from theoretical predictions of neutrino clustering. Numerical simulations of the non-linear evolution of cold dark matter and neutrinos play a pivotal role in this process. We incorporate neutrinos into the cosmological N-body code CUBEP3M and discuss the challenges associated with pushing to the extreme scales demanded by the neutrino problem. We highlight code optimizations made to exploit modern high performance computing architectures and present a novel method of data compression that reduces the phase-space particle footprint from 24 bytes in single precision to roughly 9 bytes. We scale the neutrino problem to the Tianhe-2 supercomputer and provide details of our production run, named TianNu, which uses 86% of the machine (13,824 compute nodes). With a total of 2.97 trillion particles, TianNu is currently the world’s largest cosmological N-body simulation and improves upon previous neutrino simulations by two orders of magnitude in scale. We finish with a discussion of the unanticipated computational challenges that were encountered during the TianNu runtime.
Neutrinos are particles that interact rarely, so identifying them re-quires large detectors which produce lots of data. Processing this data with thecomputing power available is becoming more dicult as the detectors increasein size to reach their physics goals. In liquid argon time projection chambers(TPCs) the charged particles from neutrino interactions produce ionization elec-trons which drift in an electric field towards a series of collection wires, and thesignal on the wires is used to reconstruct the interaction. The MicroBooNEdetector currently collecting data at Fermilab has 8000 wires, and planned fu-ture experiments like DUNE will have 100 times more, which means that thetime required to reconstruct an event will scale accordingly. Modernization ofliquid argon TPC reconstruction code, including vectorization, parallelizationand code portability to GPUs, will help to mitigate these challenges. The liquidargon TPC hit finding algorithm within theLArSoftframework used acrossmultiple experiments has been vectorized and parallelized. This increases thespeed of the algorithm on the order of ten times within a standalone version onIntel architectures. This new version has been incorporated back intoLArSoftso that it can be generally used. These methods will also be applied to otherlow-level reconstruction algorithms of the wire signals such as the deconvolu-tion. The applications and performance of this modernized liquid argon TPCwire reconstruction will be presented.
The Working Party on Nuclear Criticality Safety (WPNCS) under the guidance of the Organization for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) has over 20 years of experience addressing concerns related to static and transient configurations encountered within the nuclear fuel cycle: fuel fabrication, transportation, reprocessing, storage, and geological disposal. One of the cornerstone activities of the WPNCS is the International Criticality Safety Benchmark Evaluation Project (ICSBEP), which was established to identify a comprehensive set of criticality benchmark data, evaluate the data, including quantification of overall uncertainties; compile the data into a standardized format, perform sample calculations utilizing modern nuclear data sets and codes utilized in nuclear criticality safety, and formally document the work into a single source of verified benchmark data. Annually, members of the ICSBEP Technical Review Group (TRG) contribute evaluated benchmark data that undergoes comprehensive technical review prior to publication in the ICSBEP Handbook. In the years since the ICSBEP was established, there has been much work to prepare benchmark data to support validation activities in nuclear criticality safety. The 2020 edition of the ICSBEP Handbook contains acceptable benchmark specifications for 5,053 critical, subcritical, or near-critical configurations in 582 benchmark evaluations. Modern benchmark development benefits from decades of experienced international participants, a well-established handbook format, supplementary guides to deal with uncertainty quantification, and a comprehensive review process based upon independent reviews from international experts. The ICSBEP Handbook also contains 838 configurations deemed unacceptable to support criticality safety efforts. They are recorded, with the reasoning for their rejection, to preserve the experimental data, prevent reevaluation of data that are incomplete or contain known errors, and/or to potentially allow future reevaluation of the experiment pending the identification of sufficient data to resolve identified inconsistencies and errors. Users of the ICSBEP Handbook today might notice that the rigor and quality of modern criticality safety benchmarks is much greater than those prepared within the initial decade of the project. Benchmarks with 1s uncertainties in k eff greater than 1% were traditionally rejected unless they were identified as unique experiment types that encompassed materials, fuels, or designs not available from other benchmark experiments. However, benchmarks developed using modern experimental techniques and practices typically have uncertainties on the order of a few tenths of a percent. There have been ongoing efforts to improve the overall quality of previously published benchmark evaluations. Seventy-eight evaluations, containing approximately 600 configurations, have been revised just within the past decade. An additional eleven benchmarks are under revision for updated release in the 2020 edition of the ICSBEP Handbook. If some of the historic benchmarks were resubmitted in their current form to the TRG today, they would be rejected due to lack of data, missing components in the uncertainty analysis, or incomplete benchmark model development. The use of historic criticality safety benchmarks that underestimate the total uncertainty, lack properly quantified biases, or provide inadequate benchmark specifications do not sufficiently support modern criticality safety and nuclear data efforts. Although the ICSBEP Handbook is recognized by regulating bodies to support criticality safety, users are required to justify their reasons to ignore historic benchmark data and include additional safety margins within their designs. Discussions were held at the WPNCS 23rd Annual Meeting in September 2019 regarding the aforementioned issues. The resultant decision was to establish Subgroup 8 (SG-8): Preservation of Expert Knowledge and Judgement Applied to Criticality Benchmarks. The current activities of SG-8 are discussed herein.
The MPACT (Michigan PArallel Charactistics based Transport) code is designed to perform high-fidelity light water reactor (LWR) analysis using whole-core pin-resolved neutron transport calculations on modern parallel-computing hardware. The code consists of several libraries which provide the functionality necessary to solve steady-state eigenvalue problems. Several transport capabilities are available within MPACT including both 2-D and 3-D Method of Characteristics (MOC). A three-dimensional whole core solution based on the 2D-1D solution method provides the capability for full core depletion calculations.
The MPACT (Michigan PArallel Charactistics based Transport) code is designed to perform high-fidelity light water reactor (LWR) analysis using whole-core pin-resolved neutron transport calculations on modern parallel-computing hardware. The code consists of several libraries which provide the functionality necessary to solve steady-state eigenvalue problems. Several transport capabilities are available within MPACT including both 2-D and 3-D Method of Characteristics (MOC). A three-dimensional whole core solution based on the 2D-1D solution method provides the capability for full core depletion calculations.
The MPACT code is designed to perform high-fidelity light-water reactor (LWR) analysis using whole-core pin-resolved neutron transport calculations on modern parallel-computing hardware. The code consists of several libraries which provide the functionality necessary to solve steady-state eigenvalue problems. Several transport capabilities are available within MPACT including both 2-D and 3-D Method of Characteristics (MOC). A three-dimensional whole core solution based on the 2D-1D solution method provides the capability for full core depletion calculations.
Benchmarking has been recognized as an efficient tool for model validation as well as scientific collaboration. Several workshop series have been established to foster the benchmarking idea: setting up test cases with increasing complexity for method development and code comparison. In addition to representing model complexity, one of the key efforts is to develop codes that are suitable for modern HPC platforms such as PetaFlop supercomputers. It has been realized that those challenges are beyond single team capabilities. The Subsurface Environmental Simulation Benchmarking (SSBench) working group was initiated to develop, publish, and make publicly available well-described benchmark problems that could be used to demonstrate simulator conformance with norms established by the subsurface science and engineering community. SSBench supports the development of environmentally-relevant benchmark problem sets that provide rigorous tests for process model conceptualization, numerical implementation, process coupling, and accuracy. The initial SSBench focus on multicomponent reactive transport modeling reflects the expanding range of mechanisms and increasing complexity needed to address issues relevant to climate change, nuclear waste management, contaminant remediation, and pollution prevention.
The solution of large-scale combustion problems with codes such as Uintah on modern computer architectures requires the use of multithreading and GPUs to achieve performance. Uintah uses a low-Mach number approximation that requires iteratively solving a large system of linear equations. The Hypre iterative solver has solved such systems in a scalable way for Uintah, but the use of OpenMP with Hypre leads to at least slowdown due to OpenMP overheads. The proposed solution uses the MPI Endpoints within Hypre, where each team of threads acts as a different MPI rank. This approach minimizes OpenMP synchronization overhead and performs as fast or (up to 1.44) faster than Hypre's MPI-only version, and allows the rest of Uintah to be optimized using OpenMP. The profiling of the GPU version of Hypre shows the bottleneck to be the launch overhead of thousands of micro-kernels. The GPU performance was improved by fusing these micro-kernels and was further optimized by using Cuda-aware MPI, resulting in an overall speedup of 1.16—1.44 compared to the baseline GPU implementation. The above optimization strategies were published in the International Conference on Computational Science 2020 [1]. This work extends the previously published research by carrying out the second phase of communication-centered optimizations in Hypre to improve its scalability on large-scale supercomputers. Additionally, this includes an efficient non-blocking inter-thread communication scheme, communication-reducing patch assignment, and expression of logical communication parallelism to a new version of the MPICH library that utilizes the underlying network parallelism [2]. The above optimizations avoid communication bottlenecks previously observed during strong scaling and improve performance by up to 2 on 256 nodes of Intel Knight's Landing processor.