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DOE OSTI2015

MOOSE IPL Extensions (Control Logic)

In FY-2015, the development of MOOSE was driven by the needs of the NEAMS MOOSE-based applications, BISON, MARMOT, and RELAP-7. An emphasis was placed on the continued upkeep and improvement MOOSE in support of the product line integration goals. New unified documentation tools have been developed, several improvements to regression testing have been enforced and overall better software quality practices have been implemented. In addition the Multiapps and Transfers systems have seen significant refactoring and robustness improvements, as has the “Restart and Recover” system in support of Multiapp simulations. Finally, a completely new “Control Logic” system has been engineered to replace the prototype system currently in use in the RELAP-7 code. The development of this system continues and is expected to handle existing needs as well as support future enhancements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Treatment of Nuclear Data Covariance Information in Sample Generation

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

UFD Proof-of-Concept Demonstration

The BISON Spent Nuclear Fuel modeling capability has been demonstrated through simulations of the complete nuclear fuel lifecycle including in-reactor irradiation, spent fuel pool cooling, vacuum drying and finally dry cask storage. The importance of hydrogen in the cladding and the formation of hydrides at various stages of the fuel lifecycle have been a focus of the initial development work. In addition, the integration in BISON of a hydride damage model has improved the prediction of the cladding mechanical behavior. The work described in this report was performed under funding from the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. This report is issued in satisfaction of the level 2 milestone M2MS-17IN0201012 on UFD Proof-of-Concept Demonstration for the INL Engineering-Scale Fuel Performance (BISON) Workpackage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Coupled Calculations in Helical Steam Generator: Validation on Legacy Data

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. Flow-induced vibration (FIV) is widespread problem in energy systems because they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occurs. Given the importance of reliable components in the nuclear industry, flow-induced vibration has long been a major concern in safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from flow-induced vibration and related failures. Advanced reactors, such as integral Pressurized Water Reactors (PWRs) considered for Small Modular Reactors (SMR), often rely on innovative component designs to meet cost and safety targets. One component that is the subject of advanced designs is the steam generator, some designs of which forego the usual shell-and-tube architecture in order to fit within the primary vessel. In addition to being more cost- and space-efficient, such steam generators need to be more reliable, since failure of the primary vessel represents a potential loss of coolant and a safety concern. A significant amount of data exists on flow-induced vibration in shell-and-tube heat exchangers, and heuristic methods are available to predict their occurrence based on a set of given assumptions. In contrast, advanced designs have far less data available. Advanced modeling and simulation based on coupled structural and fluid simulations have the potential to predict flow-induced vibration in a variety of designs, reducing the need for expensive experimental programs, especially at the design stage. Over the past five years, the Reactor Product Line has developed the integrated multi-physics code suite SHARP. The goal of developing such a tool is to perform multi-physics neutronics, thermal/fluid, and structural mechanics modeling of the components inside the full reactor core or portions of it with a user-specified fidelity. In particular SHARP contains high-fidelity single-physics codes Diablo for structural mechanics and Nek5000 for fluid mechanics calculations. Both codes are state-of-the-art, highly scalable tools that have been extensively validated. These tools form a strong basis on which to build a flow-induced vibration modeling capability. In this report we discuss one-way coupled calculations performed with Nek5000 and Diablo aimed at simulating available FIV experiments in helical steam generators in the turbulent buffeting regime. In this regime one-way coupling is judged sufficient because the pressure loads do not cause substantial displacements. It is also the most common source of vibration in helical steam generators at the low flows expected in integral PWRs. The legacy data is obtained from two datasets developed at Argonne and B&W.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

Integral Full Core Multi-Physics PWR Benchmark with Measured Data

In recent years, the importance of modeling and simulation has been highlighted extensively in the DOE research portfolio with concrete examples in nuclear engineering with the CASL and NEAMS programs. These research efforts and similar efforts worldwide aim at the development of high-fidelity multi-physics analysis tools for the simulation of current and next-generation nuclear power reactors. Like all analysis tools, verification and validation is essential to guarantee proper functioning of the software and methods employed. The current approach relies mainly on the validation of single physic phenomena (e.g. critical experiment, flow loops, etc.) and there is a lack of relevant multiphysics benchmark measurements that are necessary to validate high-fidelity methods being developed today. This work introduces a new multi-cycle full-core Pressurized Water Reactor (PWR) depletion benchmark based on two operational cycles of a commercial nuclear power plant that provides a detailed description of fuel assemblies, burnable absorbers, in-core fission detectors, core loading and re-loading patterns. This benchmark enables analysts to develop extremely detailed reactor core models that can be used for testing and validation of coupled neutron transport, thermal-hydraulics, and fuel isotopic depletion. The benchmark also provides measured reactor data for Hot Zero Power (HZP) physics tests, boron letdown curves, and three-dimensional in-core flux maps from 58 instrumented assemblies. The benchmark description is now available online and has been used by many groups. However, much work remains to be done on the quantification of uncertainties and modeling sensitivities. This work aims to address these deficiencies and make this benchmark a true non-proprietary international benchmark for the validation of high-fidelity tools. This report details the BEAVRS uncertainty quantification for the first two cycle of operations and serves as the final report of the project.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Nek5000 Simulations on Turbulent Coolant Flow in a Fuel Assembly Experiment - AREVA/ANL collaboration for advancing CFD tools

The NEAMS program aims to develop an integrated multi physics simulation capability “pellet to plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite’s multi resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Warthog Framework Update: Depletion Capabilities

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program the US Department of Energy (DOE) Office of Nuclear Energy supports two simulation frameworks to provide advanced simulation techniques for analyzing nuclear reactors. Primarily at Idaho National Laboratory (INL), the fuels product line (FPL) is developing the fuel performance code BISON from Hales et al. [2016], which depends on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework developed by Gaston et al. [2009]. Likewise, at Argonne National Laboratory (ANL), in the reactor product line (RPL), PROTEUS is being developed by Lee et al. [2013] and Nek5000 by Fischer et al. [2015] based on the Simulation-based High-efficiency Advanced Reactor Prototyping (SHARP) framework from Tautges et al. [2013]. MOOSE employs a bottom-up approach to multiphysics coupling, where component codes are built upon a common framework. SHARP employs a top-down approach in which legacy component codes are connected after being separately developed. Each approach has benefits and disadvantages, but this work focuses on having the two approaches work in harmony.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analy- sis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncer- tainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is in- terested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assess- ment capability to RELAP-7, currently under develop-ment at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explaination of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

MOOSE IPL Extensions (Documentation)

In FY-2015, The development of MOOSE was driven by the needs of the NEAMS MOOSE-based applications, BISON, MARMOT, and RELAP-7. An emphasis was placed on the continued upkeep and improvement MOOSE in support of the product line integration goals. New unified documentation tools have been developed, several improvements to regression testing have been enforced and overall better software quality practices have been implemented. In addition the Multiapps and Transfers systems have seen significant refactoring and robustness improvements, as has the “Restart and Recover” system in support of Multiapp simulations. Finally, a completely new “Control Logic” system has been engineered to replace the prototype system currently in use in the RELAP-7 code. The development of this system continues and is expected to handle existing needs as well as support future enhancements.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2017

Low length scale modeling of Cr precipitation in FeCrAl under thermal aging conditions

This report summarizes the progress on lower length scale modeling of Cr precipitation in FeCrAl alloys, which has been identified as a possible cladding material for accident tolerant fuels due to its excellent corrosion resistance via the formation of a protective, slow growing alumina surface layer. The precipitation of Cr-rich α' clusters in FeCrAl can lead to degraded mechanical properties such as the well-known “475oC embrittlement”, and should therefore be avoided to ensure cladding integrity. In FY16, a lattice kinetic Monte Carlo (LKMC) model was developed for FeCr binary alloys. Due to the assumption of constant bond energies, the previous model cannot correctly reproduce the low-temperature part of the Fe-Cr phase diagram. It is also not possible to model the anomalous ordering tendency and repulsive interactions between Cr atoms in α Fe at the dilute concentration regime using constant bond energies. To address these issues, a new local-environment-dependent bond energy formalism has been developed for Fe-Cr in FY17 that can simultaneously reproduce the negative mixing energy at low Cr concentrations and the positive mixing energy at high Cr concentrations, and the consequent large solubility of Cr in bcc Fe at low temperatures. Furthermore, the LKMC model has been extended to include Al to enable the assessment of Cr precipitation tendency in ternary FeCrAl alloys under thermal aging. Results from the present KMC simulations show good agreement with available experiments in the literature. This study is supported by the DOE NEAMS program Accident Tolerant Fuel project.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Progress update on lower length scale research and development on U3Si2 fuel and FeCrAl cladding

This report summarizes the lower length scale model development and studies in regards to two accident tolerant (ATF) concepts, U 3 Si 2 and FeCrAl. U 3 Si 2 is proposed to replace UO 2 fuel for its high thermal conductivity and higher uranium density. FeCrAl alloys are proposed to replace Zr based cladding for their high mechanical strength and good corrosion resistance. Before applying them in reactors, sufficient data are needed to establish their predictable in-pile performance, but largely missing, and they are costly and time consuming to obtain by experimental approaches. Under the NEAMS ATF high-impact-problem (HIP), multiscale modeling and simulations are used to develop atomistic and mesoscale tools, obtain fundamental material properties, and assess the behaviors of these two ATF concepts. The accomplishments in FY17 are briefly introduced in this report including the development of interatomic potentials, assessment of swelling in U 3 Si 2 , and Cr precipitation in FeCrAl alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Development of a fully validated quantitative model of hydride morphology in zirconium alloy nuclear fuel cladding

This is a NEAMS milestone report for the subcontract to PennState U on modeling hydride formation and evolution in Zr based cladding.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Development of a UO2 Densification Model in the MARMOT Tool

A phase-field model for irradiation-enhanced densification is currently under development in the NEAMS code MARMOT. To begin, a simplified model of sintering without irradiation effects is developed. This model requires a method to generate sintering initial conditions, and the accepted phase-field rigid-body motion sintering model must either be fully implemented in MARMOT or shown to be unnecessary. It is shown to be unnecessary. Sintering simulation results without rigid body motion are shown. Shortcomings in the results are discussed and plans on how to address them are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Sample Generation for Nuclear Data

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Warthog: Coupling Nek5000 Thermal Hydraulics to BISON Fuel Performance through the Giraffe Interface

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program under the US Department of Energy (DOE) consists of three product lines. The Fuels Product Line (FPL), hosted at Idaho National Laboratory (INL), has produced a multiphysics framework with the name Multiphysics Object Oriented Simulation Environment (MOOSE) (Gaston et al. 2015). The FPL has also produced several high-fidelity physics codes including the fuel performance code Bison (Hales et al. 2016). The Reactors Product Line (RPL), hosted at Argonne National Laboratory (Argonne), has developed the high-order spectral-element Computational Fluid Dynamics (CFD) code Nek5000 (Fischer et al. 2015). The Integration Product Line (IPL), hosted at Oak Ridge National Laboratory (ORNL), is tasked with ensuring tools from the other product lines can be coupled together so that users may perform high-fidelity multiphysics simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

RAVEN User Manual, Revision 4

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assess- ment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Preparation for a PROTEUS Software Quality Assurance Plan

PROTEUS is the neutron transport solver package developed at Argonne National Laboratory under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. For the purposes of this report, we consider the PROTEUS package to include the three solvers PROTEUS-NODAL, PROTEUS-MOC, and PROTEUS-SN, as well as the PROTEUS mesh tools and utilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

A Transient Reactor Physics Experiment with High-Fidelity, 3-D Flux Measurements for Validation and Verification

This project led to the design and construction of a system of novel micro-pocket fission detectors (MPFDs) and their deployment as part of a series of steady-state and transient experiments at the University of Wisconsin Nuclear Reactor (UWNR). The data acquired during these experiments is intended for use in validation of reactor-physics models, including those developed as part of the NEAMS Toolkit (e.g., PROTEUS) and others. Part of the work led to a completely new computational model of UWNR based on Python-automated input generation for both MCNP and Serpent, and preliminary efforts have been made to develop a mesh for models in PROTEUS and other deterministic tools.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗