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At least 1,153 records · Page 64

A Code-Agnostic Driver Application for Coupled Neutronics and Thermal-Hydraulic Simulations

While the literature has numerous examples of Monte Carlo and computational fluid dynamics (CFD) coupling, most are hard-wired codes intended primarily for research rather than as standalone, general-purpose applications. In this work, we describe an open source application, ENRICO, that enables coupled neutronic and thermal-hydraulic simulations between multiple codes that can be chosen at runtime (as opposed to a coupling between two specific codes). The application has been designed such that the control flow logic, domain mapping, nonlinear fixed-point iteration, solution transfers, and convergence checks are all agnostic to the underlying physics solvers used. Special emphasis has also been placed on enabling efficient execution on distributed-memory computing environments. The transfer of solution fields between solvers is performed in memory rather than through filesystem I/O. Additionally, solvers can be configured to run on overlapping or disjoint sets of processes. To date, coupling with the OpenMC and Shift Monte Carlo codes, the Nek5000 CFD code, and a simplified heat diffusion and subchannel solver has been implemented in ENRICO. We present results for coupled simulations of a single light-water reactor fuel assembly based on the NuScale reactor using various combinations of the physics solvers. For this problem, the coupled simulations are shown to converge in about four Picard iterations. A comparison of the heat source and temperature distributions computed by ENRICO using OpenMC coupled with Nek5000 and Shift coupled with Nek5000 illustrates remarkable agreement between the codes.

42 ENGINEERING↗

NEAMS Technical Area Support in MOOSE

The MOOSE framework is a foundational capability used by the NEAMS program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and other new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities outlined in this report include enabling selective polynomial basis refinement, implementing a custom convergence system, building a scalable preconditioner for saddle-point problems, and much more.

97 MATHEMATICS AND COMPUTING↗

Diagnosing Near-Surface Model Errors with Candidate Physics Parameterization Schemes for the Multiphysics Rapid Refresh Forecast System (RRFS) Ensemble during Winter over the Northeastern United States and Southern Great Plains

Abstract During the winter of 2020/21 an ensemble of FV3-LAM forecasts was produced over the contiguous United States for the Winter Weather Experiment using five physics suites. These forecasts are evaluated with the goal of optimizing physics parameterizations within the future operational Rapid Refresh Forecast System (RRFS) in the Unified Forecast System (UFS) realm and for selecting suitable physics suites for a multiphysics RRFS ensemble. The five physics suites have different combinations of land surface models (LSMs), planetary boundary layer (PBL) parameterizations, and surface layer schemes, chosen from those used in current and possible future operational systems and likely to be supported in the operational UFS. Full-season evaluation reveals a persistent near-surface cold bias in the U.S. Northeast from one suite and a nighttime warm bias in the southern Great Plains in another suite, while other suites have smaller biases. A representative case is chosen to diagnose the cause for each of these biases using sensitivity simulations with different physics combinations or modified parameters and verified with additional mesonet observations. The cold bias in the Northeast is attributed to aspects of the Noah-MP LSM over snow cover, where Noah-MP simulates lower soil water content, and thus lower thermal conductivity than other LSMs, leading to less upward ground heat flux during nighttime and consequently lower surface temperature. The nighttime warm bias found in the southern Great Plains is attributed to overestimation of vertical mixing in the K -profile-based eddy-diffusivity mass-flux (K-EDMF) PBL scheme and insufficient land–atmospheric coupling from the GFS surface layer scheme over short vegetation. A few key parameters driving these systematic biases are identified.

Meteorology & Atmospheric Sciences↗

Advanced Multiphysics Code Coupling for Cladding Surface Thermocouples During Two-Phase Heat Transfer from Nuclear Fuel

Transient testing of nuclear fuel involves the evaluation of fuel performance under off-normal and accident conditions and is essential for proving design performance. Instrumentation included in such experiments commonly includes thermocouples attached to the outer surface of the cladding to provide temperature measurements throughout the transient. However, the presence of thermocouples on the cladding surface can alter the local heat transfer characteristics with the surrounding coolant. These localized effects can influence the temperature of the nearby cladding surface and introduce uncertainties in interpreting the thermocouple data. Understanding the impact of thermocouples attached to the outer surface of the cladding is crucial for accurate data interpretation as well as its effect on the thermomechanical behavior of the cladding. This paper presents a novel methodology for simulating the impact of outer cladding thermocouples during transient testing of nuclear fuels. The simulation framework leverages the thermal-hydraulic capabilities of RELAP5-3D coupled to the BISON fuel performance code through the RELAPCouplingApp interface. The methodology is compared against Accident Tolerant Fuel Reactivity Initiated Accident-1-E experiment performed at Idaho National Laboratory. The results reveal approximately 100°C difference between thermocouple-altered temperature and virgin cladding surface. The model overpredicts surface rewet time due to conservative correlations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

MECHANISTIC MULTIPHYSICS MODELING OF CLADDING RUPTURE IN NUCLEAR FUEL RODS DURING LOSS-OF-COOLANT ACCIDENT CONDITIONS

The Loss of Coolant Accident (LOCA) is a design basis accident that is included as part of the safety analysis of nuclear power plants. As the nuclear industry desires to increase the cycle length and discharge burnup of existing nuclear power plants they must demonstrate safe operation during a LOCA on high burnup fuel. During a LOCA transient on high burnup fuel rods, the rods may undergo a process known as fuel fragmentation, relocation, and dispersal (FFRD). To permit dispersal, the cladding encapsulating the fuel must rupture with an opening size large enough to allow the fragmented fuel particles to release. Current licensing tools used by industry and the United States Nuclear Regulatory Commission are limited in geometric fidelity and materials that can be analyzed. These simulation tools generally employ a quasi-two-dimensional (1.5D or Layered1D) or 2D-RZ axisymmetric geometric representations exclusively. While a valid approach under some instances, there are times when important physics have an asymmetric behavior in the fuel rod. Examples include fuel fragmentation, thermal-hydraulic boundary conditions, and cladding rupture, all of which are important for LOCA analysis. As industry pursues burnup extensions it must be demonstrated that fuel dispersal can be mitigated or eliminated. To do this, an understanding of the rupture opening after cladding failure is required. This work presents the development of a model for predicting the size and location of the rupture opening in failed fuel rods during LOCA conditions using advanced modeling and simulation tools. In order to supply the rupture model with appropriate boundary conditions, improvements to fuel fragmentation, axial relocation and oxidation modeling were required. First, the eXtended Finite Element Method (XFEM) is used to mechanistically predict the number of fuel fragments that form due to material strength randomization, criteria for strength randomization, mesh density, power ramping rates and irradiation effects. These predictions with associated uncertainty were compared to empirical correlations developed for UO2 verifying that they can be used with increased confidence in subsequent axial relocation analyses. Secondly, a new first-of-its-kind Layered2D computational framework was developed that provides the ability to apply azimuthally varying boundary conditions while providing discrete layers to track fuel movement during the LOCA. An existing fuel axial relocation model developed for Layered1D was extended to work within the Layered2D framework. A large sensitivity study was performed on the initial version of the model to identify modeling parameters of particular importance, with the emissivity used for radiation after blowdown being the primary source of uncertainty. Then, a simplistic approach to incorporate mechanical degradation of the cladding due to oxidation was also developed to investigate the impact of reduced cladding thickness on predictions of the time to failure of cladding tubes. It was found that the cladding will typically rupture prior to a reduction in thickness that is sufficient to impact the rupture behavior. A model was then developed for predicting cladding rupture that transfers the cladding surface temperatures, rod internal and external pressures, fast neutron fluence, and fast neutron flux from a more detailed Layered1D, Layered2D, or 2D-RZ analysis to a 3D cladding only analysis. Comparisons of the rupture model to a few experiments indicate reasonable predictions. The rupture model was then applied to two accident tolerant fuel concepts (FeCrAl and Cr-coated Zircaloy) where it predicted that both ATF concepts would have smaller rupture openings and delayed rupture times than the standard Zircaloy-4 cladding material under identical loading conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A physics-informed deep learning model of the hot tail runaway electron seed

A challenging aspect of the description of a tokamak disruption is evaluating the hot tail runaway electron seed that emerges during the thermal quench. This problem is made challenging due to the requirement of describing a strongly non-thermal electron distribution, together with the need to incorporate a diverse range of multiphysics processes, including magnetohydrodynamic instabilities, impurity transport, and radiative losses. Here this work develops a physics-informed neural network (PINN) tailored to the solution of the hot tail seed during an axisymmetric thermal quench. Here, a PINN is developed to identify solutions to the adjoint relativistic Fokker–Planck equation in the presence of a rapid quench of the plasma's thermal energy. It is shown that the PINN is able to accurately predict the hot tail seed across a range of parameters, including the thermal quench timescale, initial plasma temperature, and local current density, in the absence of experimental or simulation data. The hot tail PINN is verified by comparison with direct Monte Carlo simulations, with excellent agreement found across a broad range of thermal quench conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Functor system: a new on-the-fly take on Material Properties based on C++ functions

In the context of solving multiphysics problems, the discretization of the partial differential equations (PDE) at hand often takes the spotlight. However, for most engineering users and even application developers, the discretization of the equations has already been performed. Instead, they are tasked with implementing specific closure relations and material properties. MOOSE has long enabled this using the Materials system. This system relied on the pre-computation of all properties before they are used in the PDE or in postprocessing. In this talk we will introduce the Functor system, which was deployed in MOOSE in 2021, then present a few applications of functors in flow modeling simulations by the NEAMS program. Functors first offer great flexibility in their evaluation. Rather than storing various arrays for material properties, they are evaluated on the fly at the location and state, e.g. current or old value, requested. Unlike regular material properties, several operations such as the time derivative, the divergence and the curl can be requested from a functor. Similar to material properties, functors can be made to depend on arbitrary combinations of variables, functions, postprocessors and other properties. However, unlike material properties, any of these can be substituted for a functor material property. Thanks to this, objects no longer need to be duplicated based on the types of their parameters.

97 - MATHEMATICS AND COMPUTING↗

Summary of BISON Development and Validation Activities - NEAMS FY15 Report

The objective of the NEAMS ToolKit is to develop a “pellet-to-plant” simulation capability useful for predicting performance and safety for a broad range of nuclear reactor power systems. The NEAMS ToolKit has been organized into a Fuels Product Line (FPL) and a Reactor Product Line (RPL) and is modular in design. Within the FPL, a multiscale approach has been adopted in which simulations of fuel performance at the engineering scale are informed by material property and irradiation performance models developed from mesoscale simulations of microstructural evolution. The focus in this report is on development and validation of the engineering-scale fuel performance analysis tool within the FPL, which is BISON. This summary report contains an overview of work performed under the work package enti- tled “FY2015 NEAMS INL-Engineering Scale Fuel Performance & Interface with RPL Tools.” A first chapter identifies the specific FY-15 milestones, providing a basic description of the asso- ciated work and references to related detailed documentation. Where applicable, a representative technical result is provided. A second chapter summarizes major additional accomplishments including 1) a BISON validation paper, 2) a multiphysics coupling paper, 3) application of BI- SON to Reactivity Insertion Accident analysis and 4) use of BISON for uncertainity analysis in fuel modeling. A final chapter outlines FY-16 future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Integrated Multiphysics Modeling of Environmentally Assisted Brittle Fracture

Brittle materials, such as cement, compose major portions of built infrastructure and are vulnerable to degradation and fracture from chemo-mechanical effects. Currently, methods of modeling infrastructure do not account for the presence of a reactive environment, such as water, on the acceleration of failure. Here, we have developed methodologies and models of concrete and cement fracture that account for varying material properties, such as strength, shrinkage, and fracture toughness due to degradation or hydration. The models have been incorporated into peridynamics, non-local continuum mechanics methodology, that can model intersecting and branching brittle fracture that occurs in multicomponent brittle materials, such as concrete. Through development of new peridynamic capabilities, decalcification of cement and differential shrinkage in clay-cement composites have been evaluated, along with exemplar problems in nuclear waste cannisters and wellbores. We have developed methods to simulate multiphase phenomena in cement and cement-composite materials for energy and infrastructure applications.

36 MATERIALS SCIENCE↗

Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Capturing the run-in of a pebble-bed reactor by using thermal feedback and high-fidelity neutronics simulations

Modeling the run-in of a pebble-bed reactor (PBR) can be challenging as a result of changes in the power, fuel type, and temperatures that occur throughout the run-in period. Previous work utilized high-fidelity neutronics simulations or lower-fidelity coupled neutronics/thermal-hydraulics models to capture the general characteristics of the run-in process. Here, the present work employs high-fidelity neutronics simulations (using Serpent) coupled with thermal-hydraulics simulations (using Griffin–Pronghorn) to capture the thermal feedback present during the run-in and approach to equilibrium for a PBR. Incorporating thermal feedback enables important distinctions to be made about conditions occurring inside the core, as the power distribution, discharge burnup, and isotopic compositions are all affected by the temperature distribution.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Implementation and testing of the on-the-fly thermal scattering Monte Carlo sampling method for graphite and light water in MCNP6

Here, a proper treatment of thermal neutron scattering requires accounting for chemical binding through a scattering law S(α,β,T). Monte Carlo codes sample the secondary neutron energy and angle after a thermal scattering event from probability tables generated from S(α,β,T) tables at discrete temperatures, requiring a large amount of data for multiscale and multiphysics problems with detailed temperature gradients. We have previously developed a method to handle this temperature dependence on-the-fly during the Monte Carlo random walk using polynomial expansions in 1/T to directly sample the secondary energy and angle. In this paper, the on-the-fly method is implemented into MCNP6 and tested in both graphite-moderated and light water-moderated systems. The on-the-fly method is compared with the thermal ACE libraries that come standard with MCNP6, yielding good agreement with integral reactor quantities like k-eigenvalue and differential quantities like single-scatter secondary energy and angle distributions. The simulation runtimes are comparable between the two methods (on the order of 5–15% difference for the problems tested) and the on-the-fly fit coefficients only require 5–15 MB of total data storage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Models and Measurements Quantify Photon Recycling, Charge-Carrier Diffusion and Photon Scattering Contributions to Photoluminescence in InP Nanowire Arrays

Nanowire arrays present many unique advantages for solar-to-chemical energy conversion. One possible advantage is that photon recycling between neighboring nanowires has the potential to increase solar energy conversion efficiencies. Here, in this work, we explore three underlying mechanisms of optical and electronic coupling between neighboring nanowires─incident photon scattering, photon recycling, and charge-carrier transport from the photoexcited nanowire to the neighboring nanowire via the underlying substrate─using single nanowire-level microscopy and spectroscopy measurements. We present a comprehensive analysis of light absorption and emission of a single nanowire at open circuit, and subsequent re-absorption and re-emission by a neighboring nanowire. We developed a novel correlated single nanowire microspectroscopy and widefield imaging methodology to spatially resolve photon communication pathways between neighboring nanowires and selectively image re-emitted and reflected photons. We developed unique multiphysics models to couple wave optics and semiconductor photophysics to especially isolate contributions from photon recycling and electronic transport to photon emission from neighboring nanowires. By systematically varying the morphologies of the nanowires modeled, we identified pathways to maximize photon recycling between neighboring nanowires. We concluded that the measured photoluminescence is more strongly influenced by the diffusion of charge carriers as compared to photon recycling in materials with moderate-to-large charge-carrier mobilities (>10 cm 2 V –1 s –1 ), and that photon recycling dictates photoluminescence intensity only when the charge-carrier mobility is low (<1 cm 2 V –1 s –1 ). The experimental and simulation platforms developed herein for photon management strategies can be leveraged by the semiconductor photocatalysis community to enhance solar-to-chemical conversion efficiencies in semiconductor nanowire arrays.

25 ENERGY STORAGE↗

Anatomy of a fumarolic system inferred from a multiphysics approach

Fumaroles are a common manifestation of volcanic activity that are associated with large emissions of gases into the atmosphere. These gases originate from the magma, and they can provide indirect and unique insights into magmatic processes. Therefore, they are extensively used to monitor and forecast eruptive activity. During their ascent, the magmatic gases interact with the rock and hydrothermal fluids, which modify their geochemical compositions. These interactions can complicate our understanding of the real volcanic dynamics and remain poorly considered. Here, we present the first complete imagery of a fumarolic plumbing system using three-dimensional electrical resistivity tomography and new acoustic noise localization. We delineate a gas reservoir that feeds the fumaroles through distinct channels. Based on this geometry, a thermodynamic model reveals that near-surface mixing between gas and condensed steam explains the distinct geochemical compositions of fumaroles that originate from the same source. Such modeling of fluid interactions will allow for the simulation of dynamic processes of magmatic degassing, which is crucial to the monitoring of volcanic unrest.

58 GEOSCIENCES↗

Computational Fluid Dynamics and Heat Transfer Modeling of a Dimpled Heat Exchanger

Multiphysics and analytical calculations were conducted for a heat exchanger with passive, natural circulation flow. A glycol/water working fluid convects the heat to a dimpled heat exchanger shell, which subsequently transfers the heat to the soil, which acts as the ultimate heat sink. Because the system is fully-passive, it is not subject to the expenses, maintenance, and mechanical breakdowns associated with moving parts. Density, heat capacity, and thermal conductivity material properties were measured for various soil samples, and subsequently included as input for the soil heat conduction model. The soil model was coupled to a computational fluid dynamics (CFD) heat exchanger model that included the dynamic Smagorinsky large eddy simulation and k- omega turbulence models. The analysis showed that the fluid dynamics and heat transfer models worked properly, albeit at a slow pace. Nevertheless, the coupled CFD/heat conduction simulation ran long enough to determine a key parameter—the amount of heat conducted from the heat exchanger to the ground. This unique performance value, along with experimental data, was used as input for stand-alone, fast-running CFD models, as well as boundaries to obtain solutions to partial differential equations for soil heat conduction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NEAMS Model Contributions in 2023 to the National Reactor Innovation Center Virtual Test Bed for Use by Industry and Other Stakeholders

The U.S. Department of Energy (DOE) Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program develops models of advanced reactor phenomena to demonstrate code applicability to challenging physics problems, drive code development through user assessment, and perform code verification and validation. Meanwhile, the U.S. DOE’s National Reactor Innovation Center (NRIC) hosts an open-source website and associated GitHub repository called the Virtual Test Bed (VTB) on which computational models for advanced reactors are documented and shared with the reactor community. This work documents NEAMS efforts to support industry adoption of advanced modeling tools through contribution of 10 NEAMS models to the NRIC Virtual Test Bed including models for the High Temperature Test Facility (HTTF), TRISO fuel failure in a microreactor, and multiphysics models of a molten chloride fast reactor, among others. The open sharing of these models benefits the reactor community by providing “best practice” examples using NEAMS tools for advanced reactor physics problems. In particular, the HTTF model is being used for code validation and benchmarking activities. The microreactor and molten chloride fast reactor models are representative of analysis that may be useful for current candidates of DOME and LOTUS, NRIC’s physical testbeds. This report summarizes and provides links to these new models, among others.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Neural network surrogate models for equations of state

Equation of state (EOS) data provide necessary information for accurate multiphysics modeling, which is necessary for fields such as inertial confinement fusion. Here, we suggest a neural network surrogate model of energy and entropy and use thermodynamic relationships to derive other necessary thermodynamic EOS quantities. We incorporate phase information into the model by training a phase classifier and using phase-specific regression models, which improves the modal prediction accuracy. Our model predicts energy values to 1% relative error and entropy to 3.5% relative error in a log-transformed space. Although sound speed predictions require further improvement, the derived pressure values are accurate within 10% relative error. Our results suggest that neural network models can effectively model EOS for inertial confinement fusion simulation applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiphysics modeling of accelerators through code integration

This work aims to improve the ability of particle accelerator researchers to develop high-performance accelerator cavity designs by creating an overall multiphysics framework that integrates and couples existing application codes. This framework will allow accelerator researchers to build multiphysics models that will optimize cavity design, improve understanding of whole-device performance, and reduce the development and fabrication costs of accelerator research. We utilize the open-source VizSchema data standard as an intermediate data structure interface layer to standardize interfaces between individual application codes. VizScema is extensively documented online, and plugins for VizSchema are available for popular visualization packages, including VisIt and ParaView. Currently, the work focuses on coupling the EM field solver COMSOL and the electron gun code MICHELLE to allow COMSOL field-solve results to be seamlessly used by MICHELLE for particle-solve. Later work will extend this integration to include other fields, particles, and thermodynamics simulation codes.

43 PARTICLE ACCELERATORS↗