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DOE OSTI2023

Simulation of the dynamics of gas mixtures during plasma processing in the C75 Cavity

Plasma processing using a mixture of noble gas and oxygen is a technique that is currently being used to reduce field emission and multipacting in accelerating cavities. Plasma is created inside the cavity when the gas mixture is exposed to an electromagnetic field that is generated by applying RF power through the fundamental power or higher-order mode couplers. Oxygen ions and atomic oxygen are created in the plasma which breaks down the hydrocarbons on the surface of the cavity and the residuals from this process are removed as part of the process gas flow. Removal of hydrocarbons from the surface increases the work function and reduces the secondary emission coefficient. This work describes the initial results of plasma simulation, which provides insight into the ignition process, distribution of different species, and interactions of free oxygen and oxygen ions with the cavity surfaces. The simulations have been done with an Ar/?2 plasma using COMSOL® multiphysics. These simulations help in understanding the dynamics and control of plasma inside the cavity and the exploration of different gas mixtures.

Dhakal, Pashupati↗

DOE OSTI2021

Coupling Finite Element and Finite Volume Simulation Within MOOSE

This work focuses on adding capability to couple finite element (FE) variables into finite volume (FV) physics within INL’s Multiphysics Object-Oriented Simulation Environment (MOOSE). This coupling can allow for improvement of multiphysics simulations where one set of physics is best suited for an FE discretization, while another set is best suited for an FV discretization. Electrohydrodynamics, which govern liquid metal reactor concepts and plasma dynamics, is a fitting example where the electromagnetic field equations are solved with FE and the fluid flow is solved with FV. The new FE to FV coupling method can be summarized as taking the element or face average of the FE variable value or gradient and applying that quantity directly in the FV equation objects.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Improvements to the Griffin Transport Solvers

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of steady-state solvers for fixed-source, k-eigenvalue, adjoint, and subcritical multiplication, as well as transient solvers for point-kinetics, improved quasi-static, and spatial dynamics. This document summarizes the transport solver development efforts pursued during Fiscal Year 2022. We added the multiphysics transient capability for the coarse-mesh finite difference accelerated Richardson iteration for discontinuous finite element method discrete ordinates (DFEM-SN) scheme to support high-order heterogeneous transport simulations. HFEM (hybrid finite element method) - PN (spherical harmonics expansion) was completed and red-black iteration was added for solving the HFEM-PN system with both preconditioned Jacobian-free Newton Krylov and Richardson iteration solvers. The HFEM-PN scheme, as one of the low-order transport schemes, is expected for supporting routine design simulations. Pin power reconstruction capability was also designed and implemented with the Griffin ISOXML module to enhance all the low-order transport solvers for more accurate multiphysics simulations. Numerical results are presented for demonstrating the capabilities and verifying their performance, and future works are discussed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Evaluating the Effects of Nitrogen Doping and Oxygen Doping on SRF Cavity Performance

Superconducting radiofrequency (SRF) cavities are resonators with extremely low surface resistance that enable accelerating cavities to have extremely high quality factors (Q₀). High Q₀ decreases the capital required to keep the accelerators cold by reducing power loss. The performance of SRF cavities is largely governed by the surface composition of the first §I{100}{nm} of the cavity surface. Impurities such as oxygen and nitrogen have been observed to yield high Q₀, but their precise roles are still being studied. Here, we compare the performance of cavities doped with nitrogen and oxygen in terms of surface composition and heating behavior with field. A simulation of the diffusion of oxygen into the bulk of the cavity was built using COMSOL Multiphysics software. Simulated results were compared to the actual surface composition of the cavities as determined from secondary ion mass spectrometry analysis. Understanding how these impurities affects performance allows us to have further insight into the underlying mechanisms that enable these surface treatments to yield high Q₀.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Coupled Monte Carlo and thermal-fluid modeling of high temperature gas reactors using Cardinal

Cardinal is an open-source application that couples OpenMC Monte Carlo transport and NekRS computa-tional fluid dynamics to the Multiphysics Object-Oriented Simulation Environment (MOOSE), closing neutronics and thermal-fluid gaps in conducting high-resolution multiscale and multiphysics analyses of nuclear systems. Here, we provide an introduction to Cardinal's software design, data mapping, and multi -physics coupling strategy to highlight our approach to overcoming common challenges in multiphysics simulation. We then describe an application of Cardinal to prismatic High Temperature Gas Reactors (HTGRs) with various combinations of NekRS, OpenMC, BISON, and THM. A high-resolution coupling of NekRS, OpenMC, and BISON provides a reference solution at the unit cell level and shows excellent agree-ment with a lower-resolution coupling of THM, OpenMC, and BISON. A full core coupling of THM, OpenMC, and BISON resolving the three-dimensional conjugate heat transfer and sub-pin power distri-bution then provides detailed predictions of HTGR temperatures and the fission distribution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Modeling a Sodium Heat Pipe Experiment at SPHERE Using Sockeye

The Single Primary Heat Extraction and Rejection Emulator (SPHERE) facility at Idaho Na- tional Laboratory was recently utilized to generate data for the startup and steady operation of a high-performance, sodium heat pipe over the course of 1000 hours, as a test of detrimental, long-term effects of heat pipe operation. The setup consists of a single, sodium heat pipe enclosed in a stainless-steel vacuum chamber, heated radiatively via a cylindrical ceramic fiber heater configuration and cooled via a water-cooled calorimeter. Measurements include temperatures at several axial locations along the outer surface of the heat pipe, the power provided to the heaters, and the heat removal rate of the calorimeter. In this work, this data is utilized to validate heat pipe models in the heat pipe application Sockeye, which is based upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Sockeye provides various heat pipe models at an engineering scale appropriate for the multiphysics simulation of microreactors, which may feature several hundred heat pipes. This work details models of this experiment in SPHERE using various heat pipe models with Sockeye, including heat conduction-based models and compressible flow models of the heat pipe interior. These models are compared to the experimental data to assess the accuracy of several aspects of heat pipe modeling, including frozen startup, the effect of non-condensable gases, and the coupling of the heat pipe to its environment.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Modeling a Sodium Heat Pipe Experiment at SPHERE Using Sockeye

The Single Primary Heat Extraction and Rejection Emulator (SPHERE) facility at Idaho National Laboratory was recently utilized to generate data for the startup and steady operation of a high-performance, sodium heat pipe over the course of 1,000 hours to test the detrimental, long-term effects of heat pipe operation. The setup consisted of a single, sodium heat pipe enclosed in a stainless-steel vacuum chamber, heated radiatively via a cylindrical ceramic-fiber heater configuration and cooled via a water-cooled calorimeter. Measurements included temperatures at several axial locations along the outer surface of the heat pipe, the power provided to the heaters, and the heat removal rate of the calorimeter. In this work, we use this data to validate heat pipe models in Sockeye, a heat pipe application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Sockeye provides various heat pipe models at an engineering scale appropriate for the multiphysics simulation of microreactors, which may feature several hundred heat pipes. This work details models of this experiment at SPHERE using various heat pipe models with Sockeye, including heat-conduction-based and compressible flow models of the heat pipe interior.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Monte Carlo/CFD Coupling for Accurate Modeling of the Delayed Neutron Precursors and Compressibility Effects in Molten Salt Reactors

Multiphysics reactor analysis has become one of the leading activities of most nuclear engineering research groups. Coupled neutronics and thermal/hydraulics (T/H) simulations have traditionally been performed by adopting deterministic transport tools and reactor system T/H codes. The main reason for avoiding higher fidelity numerical methods like continuous-energy Monte Carlo analysis has been the high computational cost of coupled, full-scale simulations. Nowadays, high fidelity multiphysics simulations represent a hot research topic, with several applications involving advanced nuclear systems. Liquid fuel Molten Salt Reactors (MSRs) feature peculiar physical phenomena that are not present in solid fuel reactors. Some of these phenomena are not correctly resolved by legacy reactor physics tools, and require specific treatments. This work focuses in particular on the analysis of the effect of the delayed neutron precursors drift and the impact of liquid fluid thermal expansion and compressibility in postulated criticality excursion transients in fast-spectrum MSRs. A new modeling tool based on a Monte Carlo approach for neutronics (Serpent code) coupled to a Computational Fluid Dynamic (CFD) analysis (OpenFOAM) was developed to obtain accurate modeling and simulation of these phenomena. The development of the Serpent Monte Carlo code [1] at VTT in the past few years has made this code particularly attractive for performing multiphysics studies. The availability of a flexible multiphysics interface, on-the-fly Doppler broadening and density-based collision rejection, and Delta-tracking, proved of paramount importance for the computationally efficient performance of coupled Monte Carlo/CFD calculations [2]. OpenFOAM is a C++ multiphysics toolkit featured by automatic matrix construction and solution capabilities for scalar and vector partial differential equations (PDEs), adopting several possible differencing and interpolation schemes, based on the Finite-Volume method. The ease of implementing the constitutive equations of different physical phenomena makes OpenFOAM particularly suitable for the modeling of complex coupled phenomena. In the past, several research activities proposed the adoption of both Serpent and OpenFOAM for the modeling and simulation of MSRs and the associated fuel cycles. In this work, these tools have been internally coupled for the steady-state and transient analysis of fast-spectrum systems, accounting for the effect of delayed neutron precursors transport and the salt thermal expansion and compressibility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Structural uncertainty assessment for fire-engulfed objects in crosswind: Establishing credibility for a multiphysics wall-modeled large-eddy simulation paradigm

A structural uncertainty validation study for a large-scale, fire-engulfed, elevated object subjected to crosswind is presented to establish the credibility of a high-fidelity, low-Mach, turbulent reacting flow wall-modeled large-eddy simulation (WMLES) approach that includes multiphysics coupling to participating media radiation and conjugate heat transfer. To establish that WMLES can accurately predict surface quantities including drag and pressure coefficient in the low-Mach crosswind regime, a foundational elevated isothermal cylinder validation case is presented at a similar gap-to-diameter ratio of 0.25, spanning the subcritical to supercritical drag regime (Re 𝐷 = 1.1 × 10 5 and 4.3 × 10 5 , respectively). Here, this study exercised both static and dynamic coefficient LES (Smagorinsky and 𝑘 sgs ) with both local and exchange-based velocity sampling. Results showcase that the drag crisis (or the sudden drop in drag coefficient at increased Re 𝐷 ) is well captured when using an exchange-based dynamic coefficient WMLES methodology, while noting lack of mesh convergence and overall drag and pressure coefficient predictively when using a static coefficient, local velocity sampling WMLES. For the 𝒪⁡(10) m JP-8 liquid pool fire crosswind validation study presented, two experimental crosswind configurations (2 m/s and 9.5 m/s) are showcased for a fire-engulfed mock fuselage roughly 4 m in diameter. Using the best model-form practices identified in the isothermal study, dynamic coefficient 𝑘 sgs exchange-based WMLES fire validation findings demonstrate accurate peak irradiation and skin temperature predictions as a function of crosswind magnitude. Excessive yaw in the low-crosswind fuselage configuration, consistent with experimental findings, captured a significant predicted asymmetry in flame attachment and heat flux toward the downwind cylindrical cap—indicative of axial vortex structures transporting the flame along the upper and lower fuselage leeward surface. All fire mesh resolution simulations captured the experimental finding that as crosswind increased, predicted flame shape and peak irradiation magnitude onto the fuselage transitioned from a windward to a leeward cylinder location due to the migration of the upper- to lower-shear fuel/air mixing layer thereby demonstrating the novelty, significance, and credibility of this high-fidelity WMLES reacting flow framework.

Domino, Stefan Paul [Sandia National Laboratories ↗

DOE OSTI2022

HI-STORM Overpack and MPC-32 Thermal-Hydraulic Model with MOOSE Framework

Nuclear power is a significant source of electricity in the United States, but the average age of nuclear power plants is around 40 years old. The safe management of the spent nuclear fuel (SNF) is a key aspect of the back-end of the nuclear fuel cycle. Spent fuel dry storage systems are becoming a popular and effective solution in this area, given the absence of a final disposal system. The spent fuel cask system (dry cask method) provides a feasible solution to maintain spent fuel for 60 years before final disposal. Dry cask storage has many characteristics that make it attractive. It fulfills the safety requirements of the Nuclear Regulatory Commission (NRC) while providing modularity and flexibility to contractors. The HI-STORM overpack and MPC-32 canister are the main parts of the HI-STORM 100 dry cask storage system. These components remove heat from the system using natural circulation, requiring no human intervention. This is the characteristic that provides passive heat removal and low maintenance features in dry cask storage systems. To develop a thermal model for a dry cask storage system, the physics behind the system should be defined clearly. There are two natural circulation loops in the system; circulation of helium cools down the nuclear assemblies in the MPC, while circulation of air cools down the walls of the MPC. This work aims to develop a thermal model of the MPC-32 canister and HI-STORM overpack using the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE is an open-source framework developed by Idaho National Laboratory (INL) for multiscale, multiphysics simulations. In this study, we will investigate and demonstrate the thermal-hydraulics modeling capabilities of the MOOSE framework, including natural circulation, heat transfer, and porous flow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Development of a MOOSE thermal model of the MPC-32 canister and HI-STORM overpack

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Development of a MOOSE thermal model of the MPC-32 canister and HI-STORM overpack

Nuclear power is a significant source of electricity in the United States, but the average age of nuclear power plants is around 40 years old. Safe management of spent nuclear fuel (SNF) is a key aspect of the back end of the nuclear fuel cycle, and SNF dry storage systems are becoming a popular, effective solution in this area, given the absence of a final disposal system. The spent fuel cask system (dry cask method) provides a feasible solution for maintaining SNF (~60 years) prior to final disposal. This project aims to develop a thermal model of the MPC-32 canister and HI-STORM overpack, using the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE is an open-source framework developed by Idaho National Laboratory (INL) for multiscale, multiphysics simulations. This study will investigate and demonstrate the thermal-hydraulics capabilities of the MOOSE framework, including natural circulation, heat transfer, porous flows, etc. The ultimate goal of the project is to verify whether MOOSE tools (including Pronghorn) can be used to study the thermal performance of the SNF dry cask storage system. This study provides reliable and inclusive solving strategy for dry cask problems. The detailed information about the solving scheme and the governing equations related to the physics of the system is provided in the report. The results for thermal-hydraulic analysis of the HI-STORM system is produced with using open source modules of the MOOSE framework. This results highlights the flexibility and modularity of the MOOSE which makes it a unique candidate for the frameworks and code packages. Therefore, integration of the MOOSE to UNF ST&DARDS will improve the thermal-hydraulic capability of the system while providing distinctive features to users.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

CG-Kit: Code Generation Toolkit for performant and maintainable variants of source code applied to Flash-X hydrodynamics simulations

CG-Kit is a new Code Generation tool-Kit that we have developed as a part of the solution for portability and maintainability for multiphysics computing applications. The development of CG-Kit is rooted in the urgent need created by the shifting landscape of high-performance computing platforms and the algorithmic complexities of a particular large-scale multiphysics application: Flash-X. To efficiently use computing resources on a heterogeneous node, an application must have a map of computation to resources and a mechanism to move the data and computation to the resources according to the map. Most existing performance portability solutions are focussed on abstracting the expression of computations so that a unified source code can be specialized to run on different resources. However, such an approach is insufficient for a code like Flash-X, which has a multitude of code components that can be assembled in various permutations and combinations to form different instances of applications. Similar challenges apply to any code that has composability, where a single specified way of apportioning work among devices may not be optimal. Additionally, use cases arise where the optimal control flow of computation may differ for different devices while the underlying numerics remain identical. This combination leads to unique challenges including handling an existing large code base in Fortran and/or C/C++, subdivision of code into a great variety of units supporting a wide range of physics and numerical methods, different parallelization techniques for distributed and shared memory systems and accelerator devices, and heterogeneity of computing platforms requiring coexisting variants of parallel algorithms. All of these challenges demand that scientific software developers apply existing knowledge about domain applications, algorithms, and computing platforms to determine custom abstractions and granularity for code generation. There is a critical lack of tools to tackle those problems. CG-Kit is designed to fill this gap by providing a user with the ability to express their desired control flow and computation-to-resource map in the form a pseudocode-like recipe. It consists of standalone tools that can be combined into highly specific and, we argue, highly effective portability and maintainability toolchains. Here we present the design of our new tools: parametrized source trees, control flow graphs, and recipes. The tools are implemented in Python. They are agnostic to the programming language of the source code targeted for code generation. In conclusion, we demonstrate the capabilities of the toolkit with two examples, first, multithreaded variants of the basic AXPY operation, and second, variants of parallel algorithms within a hydrodynamics solver, called Spark, from Flash-X that operates on block-structured adaptive meshes.

Algorithmic portability↗

DOE OSTI2024

Initial Demonstration of New Griffin Capability for Simulating the Running-In Phase of Pebble-Bed Reactors with Multiphysics

Griffin, a MOOSE (Multiphysics Object-Oriented Simulation Environment) based application targeting transient modelling of advanced reactors, has been used recently to model pebble-bed reactors (PBRs). The modelling effort has focused thus far on modelling the equilibrium core. A new capability to simulate the running-in phase of PBR operation has been added to Griffin. This work demonstrates the newcapability with a sample multiphysics running-in simulation. The basic features of the new running-in capability were documented previously; however, the sample simulation results presented there did not include multiphysics; the fuel temperatures were assumed to be constant. In this work, Griffin computes power densities in the core at each timestep of the running-in simulation and passes these to Pronghorn which models fluid flow and heat transfer to calculate temperatures that are passed back to Griffin and accounted for with temperature dependent cross-sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Community Geothermal: Borefield Design, Thermal Conductivity, and Subsurface Modeling Data - Chicago, IL

This dataset encompasses the development of a geothermal energy system for the West Woodlawn neighborhood in Chicago, Illinois. This project is part of a broader initiative to design and deploy geothermal heating and cooling systems at a community scale. The dataset includes thermal conductivity test results, calculations for borehole sizing based on the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) method, as well as simulated thermal loads based on actual energy usage from individual buildings. Also provided here are files used for numerical modeling via COMSOL Multiphysics to simulate borefield design and subsurface thermal behavior. Two manuscripts are attached, which outline the broad objectives of the project and a description of the numerical modeling methodology and results.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Streaming Data in HPC Workflows Using ADIOS

The “IO Wall” problem, in which the gap between computation rate and data access rate grows continuously, poses significant problems to scientific workflows which have traditionally relied upon using the filesystem for intermediate storage between workflow stages. One way to avoid this problem in scientific workflows is to stream data directly from producers to consumers and avoiding storage entirely. However, the manner in which this is accomplished is key to both performance and usability. This paper presents the Sustainable Staging Transport, an approach which allows direct streaming between traditional file writers and readers with few application changes. SST is an ADIOS “engine”, accessible via standard ADIOS APIs, and because ADIOS allows engines to be chosen at run-time, many existing file-oriented ADIOS workflows can utilize SST for direct application-to-application communication without any source code changes. This paper describes the design of SST and presents performance results from various applications that use SST, for feeding model training with simulation data with substantially higher bandwidth than the theoretical limits of Frontier’s file system, for strong coupling of separately developed applications for multiphysics multiscale simulation, or for in situ analysis and visualization of data to complete all data processing shortly after the simulation finishes.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗

DOE OSTI2025

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Griffin: A Moose-based Reactor Multiphysics Application For Radiation Transport And Depletion Simulations

Griffin is a MOOSE-based reactor multiphysics application that streamlines the analysis of a variety of nuclear multiphysics applications, including steady-state and transient radiation transport, core performance, fuel depletion, criticality and decay heat calculations, reprocessing and post-irradiation examination. This streamlining is accomplished via enhanced flexibility of the tools, uniform syntax in the MOOSE framework, dynamic linking of all relevant physics and a single point of execution. The design for flexible multi-physics, multi-radiation, multi-scheme tasks demands and ultimately makes Griffin a highly extendable code system. A software quality assurance (SQA) procedure is enforced during Griffin development.

DeHart, MarkD.↗