Verification of the Re-Released ENDF/B VIII.0 Based Thermal Scattering Libraries
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Analytic Insights into the Neutronic Characteristics of Neutron Moderators from MCNP Calculations
In the course of re-processing the ENDF/B VIII.0 thermal scattering law data, formulas and data checking insights were developed from MCNP calculations into the neutronic characteristics of moderators. Infinite medium test calculations were carried out in MCNP as part of the verification effort for the ACE formatted thermal scattering files. Edit results from MCNP were combined with derived results to formulate several equations which give analytic insights into the neutronic behavior of moderators.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Development of SCALE Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) from SCALE 5 through SCALE 6.2
This review paper provides an abbreviated historical review of the development of the TSUNAMI capabilities in SCALE, beginning with the first initiatives, to provide new insights into validation, uncertainty quantification, and safety assessment. The tools of TSUNAMI have evolved substantially over two decades to meet the growing application analysis and experiment design needs. Even more advancements are emerging as the next generation of innovators continue to use and develop these tools.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Updated Primers Generated for SCALE 6.2 for KENO V.a and KENO-VI
Primers were developed and published for the use of the KENO V.a and KENO-VI codes in 2005 and 2008, respectively. These primers were both developed for SCALE 5 using the GeeWiz graphical user interface (GUI). Many new capabilities have been added to the transport codes since the release of these primers. The GUI was also changed to Fulcrum with the release of SCALE 6.2. For these reasons, updated versions of both primers were developed for a planned released in September 2020. The KENO V.a and KENO-VI codes are almost always run within the associated CSAS5 and CSAS6 sequences within SCALE, so the primers use the sequences and do not address running the codes in stand-alone mode.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Validation of MCNP Critical Benchmark Models of PU-MET-FAST-016
A new centralized repository of high-quality MCNP models of critical benchmark experiments is currently under development at Los Alamos National Laboratory (LANL). The repository is the combined effort of the Nuclear Criticality Safety, Nuclear Data, and Monte Carlo code development/application organizations at LANL. The initial set of benchmark models in the repository are derived from the Whisper Suite provided with MCNP6.2 and are evaluated against the benchmark experiments described in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The goal is to build a single LANL benchmark collection that is up to date with the latest ICSBEP revision, has a formal review and revision process, is contained in an open-source repository, and utilizes new Python tools for improved input and output file review. This paper describes the validation of the models associated with PU-MET-FAST-016, “Flooded 3X3X3 Arrays of 3-kg Plutonium (Pu) Metal Cylinders – Phase I”. In this critical experiment, twenty-seven 3-kg Pu metal cylinders with a height of 46.33 ± 0.15 mm and diameter of 65.25 ± 0.05 mm were arranged in a cubic array. The Pu cylinders were sealed in aluminum cans, and three cans were placed in each of nine perforated aluminum sleeves, as shown in Fig. 1. The nine sleeves were supported by an aluminum frame that allowed for control of the lateral spacing of the cylinders, both in the X and Y directions. The benchmark experiment measured thirteen configurations. Of these configurations, six were modeled using MCNP.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Cumulative $\chi^2$ Metric for VALID for ENDF/B-VII.1 and ENDF/B-VIII.0 in SCALE 6.3b9
Nuclear data testing is generally performed in a manner similar to validation: a series of critical benchmark experiments is modeled, and the differences between calculated and expected results are examined to understand the performance of a code and cross section set. This process is repeated for multiple sets of experiments with different transport codes and sometimes with different datasets. Occasionally, data processing differences are also important in understanding the differences in calculated results. Relevant experts then meet periodically to compare results and set priorities for improvement in the next round of data updates. This process has been largely effective, despite the confounding factors of different benchmark sets, application areas, sponsors, nationalities, and the resulting different priorities.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Validation of KENO Delayed Neutron Fraction Capabilities
The delayed neutron fraction, which is necessary for the safe operation of reactors, varies by fissionable material and neutron spectrum. A prompt fission neutron spectrum has been included in the SCALE 6.2 release to account for the removal of delayed neutrons from precursor materials from the neutron balance. This paper describes how experimental measurements from criticality safety benchmarks were used to validate the SCALE calculational procedure for the delayed neutron fraction. Additionally, the effect of nuclear data uncertainty on the KENO calculation of β eff was examined with the SAMPLER sequence.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Performance of the Initial Implementation of the Shift Monte Carlo Code in SCALE 6.3
The Shift Monte Carlo code will be introduced in SCALE 6.3 as an alternative to the KENO V.a, KENO-VI, and Monaco codes. Calculations were performed to establish the performance of Shift for criticality safety analyses within the criticality safety analyses sequence (CSAS) based on models in the Verified, Archived Library of Inputs and Data (VALID). This test suite contains over 600 critical experiment models covering a broad range of fissile materials and neutron energy spectra. The comparisons presented include calculated k eff values and runtime performance for serial calculations and a selection of parallel calculations. Comparisons are presented for multigroup (MG) and continuous-energy (CE) calculations for KENO V.a and KENO-VI models. Results generated with a beta version of SCALE 6.3 indicate excellent agreement in k eff values between KENO and Shift. The largest differences in the average k eff value calculated for the 15 categories of KENO V.a models are 0.00020 ± 0.00011 Δ k for MG calculations and 0.00011 ± 0.00005 Δ k for CE calculations. Similar comparisons in three categories using KENO-VI result in the largest differences for MG calculations: as 0.00004 ± 0.00003 Δ k , and -0.00002 ± 0.00003 Δ k for CE. The preliminary results also indicate that Shift is faster than KENO on a per particle basis, especially for fast spectrum systems. The uncertainty per history is also higher, however, so the Monte Carlo figure of merit is higher for KENO for thermal and intermediate spectrum systems. As expected, Shift generally has better speedup than KENO for parallel calculations, regardless of neutron energy spectrum.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Multigroup Examination of Nickel-Reflected HEU System
Critical configurations of HEU-MET-FAST-003 (HMF-003) from the International Criticality Safety Benchmark Evaluation Project Handbook were modeled for addition into the Verified, Archived Library of Inputs and Data maintained at Oak Ridge National Laboratory. HMF-003 contains models of a highly enriched uranium sphere with a spherical metal reflector of natural uranium, tungsten carbide, or nickel. For these simple models, good agreement is expected between the k eff calculated with continuous-energy (CE) and multigroup (MG) transport. However, using the CSAS5 sequence of the SCALE 6.2.4 package, the 8 in. thick nickel reflector model resulted in a difference of around 1.2 % Δ k . Results presented a clear indication of poor performance for the SCALE 252-group based on ENDF/B-VII.1 cross section library for this model. The bias was investigated over a range of nickel thickness and then compared with other MG libraries available in SCALE 6.2.4. As the nickel thickness increases, the MG k eff deviates from the CE result, confirming a performance issue with the MG calculation. Additionally, the reactions were compared between the two libraries to help determine the cause of k eff bias. Finally, additional MG libraries within SCALE 6.3 and based on ENDF/B-VII.1 and ENDF/B-VIII were reviewed. The 302-group and 1597-group result in significant improvements compared with the 252-group library. Nickel cross sections were modified from ENDF/B-VII.1 to ENDF/B-VIII. For the ENDF/B-VIII library, the deviation between the CE libraries and MG libraries is less pronounced than for ENDF/VII.1, except for the 1597-group. This examination clearly indicates the importance of validating calculations with applicable benchmark experiments and caution when using MG libraries.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Recent SCALE Activities Within the Nuclear Criticality Safety Program
The role of SCALE in the Department of Energy’s Nuclear Criticality Safety Program (NCSP) is defined according to the Five-Year Plan, and summarized as follows. 1. Sustain/improve SCALE NCS features through user driven enhancements, software quality assurance (SQA) and validation and verification (V&V). 2. Assure adaptability to various computing platforms and compilers. 3. Improve user interfaces/documentation consistent with modern engineering software. 4. Support responsive communication to SCALE criticality safety users through SCALE Newsletters, email notices, and updates on the SCALE website. 5. Modernize software infrastructure and capabilities to improve quality and reliability and to ensure long term sustainability of the NCS capabilities. This paper describes the specific activities which have been performed within each area above for the NCSP in the fiscal year (FY) 2018, from October 1, 2017, to September 30, 2018.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Bias Between ENDF/B-VIII and ENDF/B-VII.1 for LEU Pin Array Systems
Extensive testing of new cross section data is performed in SCALE prior to its release. The release of ENDF/B-VIII.0 requires the generation and testing of new data libraries which are planned to be included in the release of SCALE 6.3 in 2019 or 2020. KENO benchmark results have been published previously for beta and final releases of ENDF/B-VIII.0 using the entire Verified, Archived Library of Inputs and Data (VALID). This work presents an energy-dependent change in the results for low-enriched uranium (LEU) pin array systems. The process of identifying the difference is highlighted as a case study to determine how data testing and benchmarking can be performed to provide more detailed feedback to the data community on potential data deficiencies.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases
A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.
97 MATHEMATICS AND COMPUTING↗
Crystal Plasticity Model of Reactor Pressure Vessel Embrittlement in GRIZZLY
The integrity of reactor pressure vessels (RPVs) is of utmost importance to ensure safe operation of nuclear reactors under extended lifetime. Microstructure-scale models at various length and time scales, coupled concurrently or through homogenization methods, can play a crucial role in understanding and quantifying irradiation-induced defect production, growth and their influence on mechanical behavior of RPV steels. A multi-scale approach, involving atomistic, meso- and engineering-scale models, is currently being pursued within the GRIZZLY project to understand and quantify irradiation-induced embrittlement of RPV steels. Within this framework, a dislocation-density based crystal plasticity model has been developed in GRIZZLY that captures the effect of irradiation-induced defects on the flow stress behavior and is presented in this report. The present formulation accounts for the interaction between self-interstitial loops and matrix dislocations. The model predictions have been validated with experiments and dislocation dynamics simulation.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Examining Computational Assumptions For Godiva IV
Over the course of summer 2016, the effects of several computational modeling assumptions with respect to the Godiva IV reactor were examined. The majority of these assumptions pertained to modeling errors existing in the control rods and burst rod. The Monte Carlo neutron transport code, MCNP, was used to investigate these modeling changes, primarily by comparing them to that of the original input deck specifications.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
A Well-Posed Two Phase Flow Model and its Numerical Solutions for Reactor Thermal-Fluids Analysis
A 7-equation two-phase flow model and its numerical implementation is presented for reactor thermal-fluids applications. The equation system is well-posed and treats both phases as compressible flows. The numerical discretization of the equation system is based on the finite element formalism. The numerical algorithm is implemented in the next generation RELAP-7 code (Idaho National Laboratory (INL)’s thermal-fluids code) built on top of an other INL’s product, the massively parallel multi-implicit multi-physics object oriented code environment (MOOSE). Some preliminary thermal-fluids computations are presented.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Sensitivity Data File Formats
The format of the TSUNAMI-A sensitivity data file produced by SAMS for cases with deterministic transport solutions is given in Table 6.3.A.1. The occurrence of each entry in the data file is followed by an identification of the data contained on each line of the file and the FORTRAN edit descriptor denoting the format of each line. A brief description of each line is also presented. A sample of the TSUNAMI-A data file for the Flattop-25 sample problem is provided in Figure 6.3.A.1. Here, only two profiles out of the 130 computed are shown.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
SCALE Code System 6.2.1
The SCALE Code System is a widely-used modeling and simulation suite for nuclear safety analysis and design that is developed, maintained, tested, and managed by the Reactor and Nuclear Systems Division (RNSD) of Oak Ridge National Laboratory (ORNL). SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor and lattice physics, radiation shielding, spent fuel and radioactive source term characterization, and sensitivity and uncertainty analysis. Since 1980, regulators, licensees, and research institutions around the world have used SCALE for safety analysis and design. SCALE provides an integrated framework with dozens of computational modules including three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution strategy. SCALE includes current nuclear data libraries and problem-dependent processing tools for continuous-energy (CE) and multigroup (MG) neutronics and coupled neutron-gamma calculations, as well as activation, depletion, and decay calculations. SCALE includes unique capabilities for automated variance reduction for shielding calculations, as well as sensitivity and uncertainty analysis. SCALE’s graphical user interfaces assist with accurate system modeling, visualization of nuclear data, and convenient access to desired results.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Bayesian Hypothesis Testing
These are a set of slides about Bayesian hypothesis testing, where many hypotheses are tested. The conclusions are the following: The value of the Bayes factor obtained when using the median of the posterior marginal is almost the minimum value of the Bayes factor. The value of τ 2 which minimizes the Bayes factor is a reasonable choice for this parameter. This allows a likelihood ratio to be computed with is the least favorable to H 0 .
97 MATHEMATICS AND COMPUTING↗