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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structure and Process of Managing the UO2 Dry In-Pile Fracture Test Irradiation Experiment

The management and structure of a novel research and development (R&D) project can be hard to navigate. This is especially true when it involves nuclear fuel. Familiarity with institutional safety and procedural requirements, a well defined scope, and accurate cost estimates can all help ensure successful project management from start to finish. The Dry In-Pile Fracture Test (DRIFT) experiments performed at the Transient Test Reactor Facility are an excellent example of managing an R&D project within its scope and budget constraints. The objective of the DRIFT test was to develop fracture propagation data in a manner consistent with light-water reactors to validate and improve the fracture propagation models of uranium oxide fuels in the MOOSE (Multiphysics Object-Oriented Simulation Environment)-BISON-Marmot code framework [1].

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Multi-scale modeling of the evolution of structure and properties in materials for nuclear energy applications

Nuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities, particularly in the area of materials for nuclear applications, where experimental data can be very challenging and expensive to acquire, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic, mesoscale, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. These modeling efforts make extensive of MOOSE (Multiphysics Object-Oriented Simulation Environment), a general-purpose open source finite element framework developed at INL. In this talk, I will give an overview of the approach and tools used, and several examples of application, including performance of nuclear fuels, understanding radiation-driven formation of nanoscale void and gas bubble superlattices, and powder densification through electric field assisted sintering.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Computational fluid dynamics modeling of high level waste plug formation - 15228

At Hanford, an extensive network of pipelines traversing several miles is used to transfer the high level radioactive nuclear waste from tanks to the treatment facilities. During transfer operations, however, there is a potential risk for the transport lines to plug, causing significant delays, increasing operation costs and creating hazardous conditions for personnel and the environment. In this study we investigate the phenomena of plug formation in the pipelines due to solids depositing during the waste transfer process. A three-dimensional (3-D) Computational Fluid Dynamics (CFD) model has been developed using Comsol Multiphysics 4.3b by Florida International University (FIU) to evaluate the factors that can contribute to pipeline plug formation. Several virtual scenarios are developed simulating the settling mechanics as a function of particle size, solids volume fraction and solids density. The numerical results are validated with the available experimental results and the established critical velocity correlations. The 3-D numerical results were also compared with the previous 2-D numerical studies to understand the trade-off between the two studies in terms of computing speed and numerical accuracy. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Artificial Neural Network Representation of Dynamic Criticality Excursion Experiment Data

This paper outlines time dependent considerations in applying the artificial neural network (ANN) paradigm to dynamic nuclear criticality excursion experiment data. The ANN amongst a variety of uses, can apply to function fitting of multiple input-multiple output data sets, pattern recognition, cluster analysis, and time series prediction. The ANN is a component of Machine Learning (ML) data analysis. The practical application of ML to criticality safety has been funded through the Y-12 Plant Directed Research and Demonstration (PDRD) program to support criticality safety and emergency planning efforts. The initial effort considered function fitting of criticality excursion data. Recent efforts successfully extended the ANN to criticality safety code validation. The initial ANN work applied to criticality excursions centered around multivariate function fitting of static (tabular) data taken from the French Consequences Radiologiques d'un Accident de Criticite (CRAC) and SILENE reactor campaigns. The former report (LeCorche) summarized important tabular data for the first 44 CRAC experiments. The initial ANN was trained to specific time-independent inputs, then applied to predict peak fission rate and total fissions for a wide variety of fissile solutions process conditions. This work extends that effort to apply the ANN paradigm to dynamic prediction of time-dependent criticality excursion experiment data. A dynamic criticality excursion in fissile solution represents a complex multiphysics phenomenon. Factors include among other things, coupled neutronic, multiphase fluid flow, temperature, pressure, acoustic shock, boiling heat transfer, reactivity feedback, and radiolytic gas considerations. There have been many efforts to model (over time) as coupled ordinary and (space) as partial differential equations (ODE, PDE). The ANN representation noted here does not rely on solving explicit ODE or PDEs. Rather the intent is to demonstrate that as a time series, the criticality excursion can be predicted by training specific ANN architectures to experimental input and output time series exclusively. The rationale for extending this work to the time-dependent regime is important in developing a 'criticality excursion emulator' solely on the basis of learning characteristics from experiment dynamic data. An emulator is different than a computer code simulator driven by the solution of ODEs and PDEs given select 'tuning parameters' that match outputs to experiments. A criticality excursion emulator, derived exclusively from an ANN or ML, could predict most likely excursion characteristics, trained from historic dynamic experiment data, presented with input values within the range of those experiments. The work noted shows that generic time-series ANN architectures can be satisfactorily applied to the prediction of dynamic, extremely chaotic criticality excursion power given an initial time dependent input series. In reality, an excursion emulator could be driven by user-supplied initial (t=0), time independent or constant values to generate time dependent outputs. Thus ongoing work includes developing a custom ANN such that initial dynamic conditions would be predicted. Those results then serve as inputs to a customized ANN architecture currently in development. (author)

42 ENGINEERING↗
DOE OSTI2016

Multi-Physics Surrogate Modeling with Dimensionality Reduction

This summary provides a new algorithm to construct surrogate models for multi-physics, nonlinear, high dimensional models which typically suffer from the curse of dimensionality. To deal with the high computational cost and difficult error estimation, we employ recent advances in reduced order modeling (ROM) techniques to do an error-preserving reduction for the number of influential model parameters, followed by a conventional surrogate construction process. To implement ROM for a multiphysics model, a range finding algorithm (RFA) is used to identify a linear transformation in which the number of influential parameters can be minimized and the errors resulting from the non-influential parameters can be upper-bounded. The proposed algorithm is applied to the MAMMOTH coupled code system developed at the Idaho National Laboratory. In particular, we investigate the reducibility of Rattlesnake and BISON codes and their multi-physics coupling. The most important result of this work is that the reduction obtained with coupled physics is more significant than that with individual physics models. This summary explores the application of ROM techniques on multi-physics coupling codes system. Concise methodology is provided and selected numerical results are provided to show that coupling system provides additional reduction at interfaces. Future work could be invested to determine the optimum surrogate model format. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Modeling the Effect of Evaporative Flux and Colloidal Aggregation on Crud Deposition

During the last few years lot of research has been conducted to investigate and predict the Crud deposition in PWRs. One of the common findings of various experimental and computational studies is that thickness or amount of crud deposits is directly related to evaporative flux maps. Evaporation driven deposition profile on the surfaces takes different forms, i.e. from ring to disk shapes during initial stages and in the form of porous to impervious continuous layers covering the hot fuel surface at the later stages. The amount and thickness of these deposits although are directly related to evaporative flux, the relationship is much complex and can be dependent upon several other factors. A popular problem relating evaporative flux to particulate deposition has been well studied in the form of drying of sessile colloidal drops. It was proposed that, this phenomenon is due to a geometrical constraint: the free surface, constrained by a pinned contact line squeezes the fluid outwards to compensate for evaporative losses and thereby transporting particles to the contact line. Later on a quantitative relationship between evaporative flux and deposition rate was proposed and validated by the same group, which showed power-law relationship. Deposition studies conducted with controlled concentration of particles with subcooled nucleate boiling also showed a power-law relationship rather than a simpler linear relationship whereas physics of evaporation would tend to concentrate particles at linear rate. In a typical subcooled nucleate boiling system, bubble growth and departure time is of the order 1-2 ms, measured experimentally. Diffusion time constant for dilute spherical metallic colloids such as crud particulates, generally present as particulate in process piping, range from 0.0025-2.5 sec in water for a size range 0.1-1.0 μm. Colloidal behavioral characteristics during the growth of bubbles can be computed with escape time constant at collision, which is dependent on effective Hamaker constant. For minimum effective Hamaker constant of Hematite is -2.5 kT and diffusion time constant τ = 0.0025 sec, escape time constant is computed as Kramer rule, τexp[A/kT] magnitude is 0.03 sec or 30 ms. This clearly indicates that evaporation will cause particles to come together and they cannot escape at a fast enough rate which would lead them to form agglomerates. Therefore both effects of evaporative flux in conjunction with the agglomeration kinetics must be considered for modeling the crud deposition if the evaporative flux is known. In this paper, we propose a phenomenological model of colloidal transport and aggregation with evaporative flux. The dynamic of particles interactions while drying of sessile colloidal drops is developed by coupling general transport equation with Smoluchowshki Coagulation equation. Crud deposition on the nuclear fuel has been a serious problem with severe consequences in nuclear power plants. In several studies it has been consistently reported that crud deposition is directly related to evaporative flux on the nuclear fuel surfaces. However, it has not been established how to quantify the deposition rates of crud type particulates if the evaporative flux is known. This complex multiphysics problem is similar to coffee-ring effect, where the governing physics is understood more clearly. In this work, a simplified geometry is used to model the effects of evaporative flux acting at a boundary on the colloidal concentration. The effect of this condition on change in concentration is shown numerically. Further, agglomeration is suspected to play a significant role in high evaporative flux such as bubble nucleation. The coagulation kinetics is modeled using uniform particle distribution and the effective total concentration of colloids including original particles and agglomerates is studied. Once this model is validated with a simple separate effect experiments, it can be integrated to large scale PWR models of evaluating evaporative flux and chemistry models developed by Electrical Power Research Institute (EPRI). (authors)

42 ENGINEERING↗
DOE OSTI2016

An Overview of Material Models in the BISON Fuel Performance Code

BISON is a modern finite element-based nuclear fuel performance code that has been under development at Idaho National Laboratory (INL) since 2009. The code is applicable to both steady and transient fuel behavior and supports the use of one-, two-, and three-dimensional meshes. BISON is designed to be a multi-fuels code. Although primarily applied to Light Water Reactor (LWR) fuel to date, the code has been used to analyze TRISO-coated particle fuel and metal fuel in rod and plate form, design and interpret fuel irradiation experiments and investigate novel fuel concepts. Nuclear fuel operates in an extreme environment that induces complex multiphysics phenomena occurring over distances ranging from inter-atomic spacing to meters, and times scales ranging from microseconds to years. To simulate this behavior requires a wide variety of material models which are often complex and nonlinear. Nearly all of the material models currently available in BISON are empirical, using correlations from existing fuel performance codes or material property libraries. Although these models perform adequately under many conditions, they have well-understood limitations. One obvious weakness is that the models are only valid in the domain of the associated experimental data, and extrapolating beyond this domain can result in substantial errors. A further weakness is that these models are often correlated in terms of imprecise quantities, such as burnup. Materials can, for example, reach a given burnup under very different circumstances, leading to very different material behavior. To overcome these weaknesses, efforts are underway with BISON to develop models based on a multi-scale approach, where material behavior is described with a series of interdependent microstructure based models. This paper provides an overview of the material models available in BISON. To keep the scope manageable, only LWR fuel will be considered. The first section focuses on UO{sub 2} fuel, identifying the models generally required and briefly describing those that have been implemented in the code. The second section repeats this approach for Zircaloy cladding. A final section provides examples of areas where multi-scale material modeling has been applied to BISON. BISON is a modern 2D and 3D nuclear fuel performance code that is applicable to multiple fuel forms. A wide variety of complex and nonlinear material models are required to simulate fuel behavior. Focusing on UO{sub 2} fuel and Zircaloy cladding (LWR fuel), the set of empirical models currently implemented in BISON have been reviewed. To overcome some of the deficiencies associated with empirical models, multi-scale material models are being developed. Two multi-scale models that have been used in BISON were reviewed. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2016

Meso-Scale Fuel Performance Modeling using the MARMOT Code

The in-pile behavior of light-water-reactor (LWR) fuels is governed by the physics from various time and spatial scales. Accordingly, multi-scale modeling and simulation are needed to accurately predict the fuel performance at the engineering scale. To improve the traditional fuel performance modeling, the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program targets at developing multi-scale, multiphysics modeling tools for in-pile fuel behavior prediction under various operating or accident scenarios. In traditional fuel performance modeling, the history of fuel is represented by a single parameter, fuel burn-up. Burn-up measures the energy that has been extracted from fuels. However, it is not an adequate measure of fuel history as it ignores the flux effect, which is critical for the irradiation-induced microstructural evolution in fuels. Moreover, the traditional fuel performance models are usually fitted to experimental data. Their capabilities of being extrapolated to new operating conditions and being extended to new types of fuels are strongly limited by the empirical or semi-empirical nature. To improve the burn-up based models, a microstructure based fuel approach, the MOOSE-BISON-MARMOT (MBM) tool-kit, is being developed under the fuel product line (FPL) of the NEAMS program for predictive fuel performance modeling. In the MBM approach, the evolution of fuel microstructure and changes in fuel properties are described by the MARMOT code. The transient fuel properties obtained from MARMOT are then fed into the BISON code for engineering scale fuel performance modeling. Both BISON and MARMOT are developed within the MOOSE framework, which was developed at Idaho National Laboratory. In this summary, the development and the capabilities of the MARMOT code will be introduced. In the past few years, several materials models have been developed including: (1) a grain growth model that describes the grain size evolution as a function of time, temperature and fuel porosity, considering the effects of impurity and porosity dragging and anisotropic grain boundary energy, (2) a fission gas release model that describes the fission gas diffusion in grain interior, fission gas bubble formation in grain interior and at grain boundaries, and fission gas release to the fuel-cladding gap, (3) a fracture model that describes the fracture initiation and propagation in grain interior and along grain boundaries, and (4) a thermal conductivity model that describes the change in thermal conductivity due to grain growth, gas bubble formation, fracture and radiation damage. Several other models are also being developed in MARMOT for hydride formation in Zr-based cladding, radiation damage and grain size subdivision. In most cases, these materials models are coupled with each other. For instance, to accurate predict the transient thermal conductivity, information on grain size, fission gas density, porosity and fracture is required. Further development is on going to improve all these models. These models are developed primarily for UO{sub 2} fuels used in LWRs. They can be extended to other fuels with possibly new development. All models in MARMOT will be rigorously verified and validated before being applied for fuel performance modeling. A version of MARMOT was recently released in September 2015 with an assessment report. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of the Intelligent, Preventive Infrared (IR) Inspection System Housed in Hybrid Robotic Platforms

Robots and robotic systems that are designed for inspection, environmental study, and health and safety aid are becoming an increasing necessity. However, there is a number of challenges that accompany robots that are designed for these specific applications. These challenges include: navigating compact, enclosed spaces, travelling over multiple terrains and large obstacles, using the proper sensing and detection methods to assess an environment, and the use of lightweight and durable materials. The robotic platforms currently in development look at all of these challenges and attempt to overcome them. These designs specific use of hybrid robotic platforms, or platform that utilizes soft and rigid materials, allows for a more flexible platform and makes environments more navigable. To further improve the navigation of the platforms and environmental assessment, a novel infrared detection system is housed in the platforms to create a robot that can be used for the applications listed above and more. Objectives: Further develop two types of robotic platforms that utilize additive manufacturing, soft materials, and rigid materials. Continue the development of an intelligent and inhibitory infrared detection system based on an artificial intelligence (AI) algorithm. Continued study and fabrication of active soft materials designed for both sensing and actuation in hybrid robotic systems. Improve additive manufacturing fabrication to design rigid and semi-rigid components for hybrid robotic platforms. Transformable Wheel Robotic Platform: The chassis, wheels, tires and inspection system housing use different additive manufacturing techniques for fabrication. Continued work with additive manufacturing has lead to studies in metal-based printing and modular design and manufacturing. The new platform design with integrated electrical component printed. This will allow integration of the sensor housing onto the platform. Electrical components are being tested for battery life and performance. To improve this performance, such as integration of Lithium Polymer (LiPo) batteries. Snake Robotic Platform: The main focus of the development has centered around liquid-based soft actuators. That act on the principles of electrostatic and hydraulic actuation. A liquid dielectric sits between two compliant electrodes, contained by a flexible polymer shell. The electrodes and film gradually collapse toward each other from one corner of the electrode to the other. When the electrodes and film close together, a majority of the fluid is pushed into the area not covered by an electrode. A thin layer of the liquid dielectric remains between the electrode. The actuators will be stacked to cause large displacement, and move the linkages. The chassis of this platform uses purely additively manufactured linkages. Intelligent, Preventive IR Inspection System: Development of the AI for the system has lead to using a Scikit-Learn which assists in creating predictive models based on Regression, clustering, classification etc. To improve the infrared thermometry for low emissivity sources, work on the fabrication of a tandem photoconductive infrared thermometer was a main focus. Distance-Voltage-Temperature response data has been collected in the range of 7 cm - 100 cm and 200-400 deg. C. Modifications were made to the existing test bench to have a better control over the data. Automated data collection was realized using a Python code and an Arduino controlled stepper motor to increase the sample rate. A protective enclosure has been built around the setup to minimize the effect of the environment on the measurements. To better predict temperature, different AI models are being optimized. The regression model, LARS showed a high accuracy but had convergence issues and only works for the current test set-up. Results: The Transformable Wheel Robot has developed into a more flexible and modular platform. With the improvements to the current work, effort on the tire or soft gripper design been a large focus. The soft grippers will be interchange able to allow for increased performance in identified terrain types. The development of the liquid-based actuators allows the snake robotic platform to achieve the goals of being flexible and able to navigate confined spaces. However, there is room for improvement. Optimization work is currently being done in COMSOL Multiphysics. With the current IR system set-up the LARS model perfectly predicts the data; however, considering the mobility aspect of the project other models will allow for an optimized system. Testing of other model types is currently being done.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Neutronic-Thermal Hydraulic Benchmark using the SKINATH Point Kinetics Model

The SKINATH point kinetics program, whose name comes from: A Computer Program for Solving the Reactor Point Kinetics Equations with Simple Thermal Hydraulic-Feedback, had its origins at ORNL. The authors were interested in investigating low-level criticality events such as might occur in a waste repository of 55 gallon drums. We assume a relatively realistic thermal feedback for fissionable material in a container (called a reactor here), either critical or subcritical, with the potential to undergo a further excursion. The system is a homogeneous fissile fluid (mostly water), increasing in temperature as it absorbs all heat from the excursion. An ideal gas eternally cools the reactor at constant temperature T{sub c}. The SKINATH numerical concept in 1984 was to use an off-the-shelf Livermore ODE solver LSODE to solve the kinetic equations, much as one does today with MATLAB{sup TM}. Here, we develop a novel solver that uses the simplest of numerical methods including convergence acceleration. This work represents the initiation of a Multiphysics benchmark effort at INL. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Preliminary Development of a Drift-Flux Model Based Pin-Resolved Core Thermal-Hydraulic Code for Dedicated Use in Efficient High-Fidelity Neutronics Coupled Calculations

As the high-fidelity multiphysics coupled core calculation becomes more practical with the advent of high-performance computing technology, efficient coupling of a neutronics code with a thermal-hydraulic (T/H) code at the pin level poses a new challenge. The COBRA-TF (CTF) code which is one of the well-known subchannel analysis codes based on the two-fluid, three-field model was coupled with many neutron transport codes such as MPACT, TORTTD, and nTRACER due to the easiness of coupling by its well-established coupling interface. Nevertheless, the calculation efficiency of such coupled codes is not satisfactory because of the heavy computational burden of CTF. The MATRA subchannel analysis code of KAERI which is based on the homogeneous equilibrium model (HEM) was coupled with neutronics codes as well. The choice of the HEM and the marching scheme in MATRA reduces the computational burden significantly. However, the applicability of the HEM for the two-phase flow conditions is limited to normal operating conditions of pressurized water reactors (PWRs) and therefore a better model which would allow wider applicability than HEM is necessary in order to deal with the core states involving nontrivial voiding. The drift-flux model (DFM) which uses 5 equations for two-fluid analyses by adopting the mixture velocity instead of two phasic velocities can be a good compromise between the two-fluid model and the HEM. With the DFM, the computational cost can be reduced and moreover the modeling of the interfacial area constitutive relations can be avoided. The phase separation for the mixture velocity can be incorporated by using the drift-flux parameters, C0 and Vgj, which can be obtained by using empirical formulas. Several subchannel codes such as WOSUB and ASSERT were developed based on the DFM. It was also adopted in some system analysis codes such as RETRAN3D. In the work here, the development of a DFM based pin-resolved T/H analysis code, ESCOT (Efficient Simulator of Core Thermal-hydraulics), is introduced for the use in efficient coupled calculations with a high-fidelity neutronics code. The field equations and the numerical methods are briefly described. Then the efficiency tests of various linear system solvers including the Krylov subspace methods (KSMs) are presented. A test problem is solved by ESCOT, MATRA and CTF for performance comparison and validation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Comparison of subchannel and averaged channel thermal-hydraulic descriptions on coupled pin-by-pin neutronic calculations

Best-estimate transient analysis of Light Water Reactors (LWRs) requires high accuracy code systems solving neutronics (NK), thermal-hydraulics (TH) and thermal-mechanics to model the core behavior. For long time, nodal diffusion methods for solution of the transport equation using assembly size computational meshes have been applied neglecting the details within the fuel assembly, or using 'pin power reconstruction' techniques to predict those details. Moreover, the multiphysics analysis has been commonly performed coupling those neutronic diffusion methods to thermal-hydraulic system codes using a nodalization of several fuel assemblies per computational node without taking into account the effects that this type of averaging can have on the results obtained. This paper presents the work accomplished with the coupled system COBAYA4/CTF for a preliminary analysis of the effect of the different accuracy levels in the NK and TH domain. COBAYA4 is a neutronic code able to solve the diffusion equation at two resolution levels, nodal and pin by pin (PbP). CTF is a thermo-hydraulic code able to solve the coolant conservation equations also at two levels, channel (fuel assembly averaged solution) and sub-channel (real cooling channel) level. The coupled system COBAYA4/CTF is used through SALOME platform, i.e. SALOME is the software able to map conveniently the NK and TH meshes. This coupling allows combining different resolution levels for NK and TH problems. Therefore, the study of the effect of using different resolutions for the NK and TH nodalizations has been performed applying the system to a fuel assembly with selected boundary conditions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Overview of the Salt at Wall Thermal Exchanges (SWATH) Experiment

Molten Salt Reactors have attracted increased attention in recent years because of the design and safety possibilities offered by the use of a liquid fuel. The European project SAMOFAR1 (2015-2019) is currently coordinating the research efforts on the Molten Fast Salt Reactor (MSFR) concept in Europe. The MSFR is a fast-spectrum breeder reactor with a large negative power coefficient that can be operated in a Thorium fuel cycle. The fast spectrum allows the reduction of the reprocessing requirements and a better reactor breeding ratio. Other advantages of the MSFR design are the possibility for actinide burning and extending fuel resources, on-line fuel loading and reprocessing and the use of novel passive safety systems such as the fuel salt draining system. The reference MSFR concept is a 3000 MW(th) reactor with three different circuits: the fuel circuit, the intermediate circuit and the power conversion system. The main components of the fuel circuit are the fuel salt which serves as fuel and coolant, the core cavity, the inlet and outlet pipes, the gas injection system (not shown in the figure), the salt-bubble separators, the fuel heat exchangers and the pumps. A lithium fluoride salt has been selected as the fuel matrix. The initial composition (non-irradiated) of the MSFR fuel salt is a mixture of a lithium fluoride, thorium fluoride salts and actinides fluoride (LiF-ThF{sub 4}-{sup 233}UF{sub 4} or LiF-ThF{sub 4}- {sup enr}UF{sub 4}-(Pu-MA)F{sub 3}), with the proportion of LiF fixed at about Development of accurate numerical models for the MSFR can only be accomplished by the use of a multiphysics approach which allows taking into account the coupling between relevant neutronics, thermal hydraulics and thermomechanics phenomena. As it is discussed in the next section, such a reactor model requires further progress on the knowledge of molten salt thermal hydraulics, in particular regarding the accuracy of the fuel salt Computational Fluid Dynamics (CFD) models. The Salt at Wall: Thermal Exchanges (SWATH) experiment is being designed to contribute to this particular point. SWATH is one of the experimental activities of the European H2020 SAMOFAR project and includes both experimental and numerical developments. The main objectives of SWATH are to: (i) Improve molten salt numerical models used for design and safety studies and (ii) Demonstrate the working principles of the cold plug device. The cold plug device is a key safety component of the salt draining system of the MSFR. The cold plug is intended to passively melt during accidental conditions thus allowing the flow of the nuclear fuel from the core cavity to the fuel salt draining tanks by gravity forces. The fuel salt draining tanks are designed to ensure that adequate margins are obtained regarding the fuel cooling capabilities and the reactivity control. The next sections provide an overview of the current challenges in molten salt thermal hydraulics modeling and the SWATH experiment design. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Advancement of Functional Expansion Tallies Capabilities in Serpent 2

The need for accident tolerant fuels (ATFs) became self-evident after the series of unfortunate nuclear events at Fukushima Daiichi in 2011. Restarting the Transient Reactor Test Facility (TREAT) at INL is one component in this concerted effort to establish the ATF development and testing program under the United States Department of Energy. Prior to the closure of TREAT in 1994, each experiment required multiple low-power calibration tests before and after each run. Since then, computing advancements have set computer-based modeling and simulation (M and S) as the preferred calibration method. The anticipated savings are both temporal and monetary. MAMMOTH, a collection of M and S tools built from the finite element-based MOOSE Framework, has been established to support the designed experiments intended for TREAT. This collection of tools includes: 1) Rattlesnake, a striking diffusion-based neutronics code, 2) BISON, an advanced materials and fuels performance code, and 3) RELAP-7, a powerful thermal-hydraulics solver. Each is capable of independently performing its function accurately and effectively; unified, they create a powerful multiphysics reactor core M and S application. One unfortunate weakness in this configuration lies in the unique geometry and design of TREAT's core. Although simple to model, this poses a challenge to the diffusion solver in Rattlesnake. One alternative is to replace Rattlesnake with Serpent, a fully-fledged Monte Carlo (MC) neutronics code. Coincidentally, Rattlesnake calculations are frequently validated against Serpent simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

VUSAT - A VERA-CS Uncertainty and Sensitivity Analysis Toolkit

VERA-CS (the Virtual Environment for Reactor Applications, Core Simulator) is a high-fidelity multiphysics core simulator under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). VERA-CS includes three main components: MPACT for reactor physics and neutron transport, COBRA-TF for thermal-hydraulics, and ORIGEN for isotopic depletion. VERA-CS has been applied to an array of problems including core physics analysis, and the modeling for all of the fuel cycles of Watts Bar Nuclear Unit 1 (WBN1). MPACT is a 3D pin-resolved reactor transport code developed by Oak Ridge National Laboratory (ORNL) and the University of Michigan. COBRA-TF (CTF) is a three-field two-phase flow subchannel analysis code developed by ORNL and North Carolina State University. CTF solves the mass, momentum, and energy equations for the liquid, vapor, and droplet phases for each subchannel in the core and captures the axial flow within each channel as well as cross-flow between channels. Direct coupling between neutronics (MPACT) and thermal-hydraulics (CTF) in VERA-CS provides temperature and density feedback. CTF includes a number of models important for LWR safety and design analysis including flow regime dependent two-phase wall heat transfer, inter-phase heat transfer and drag, droplet breakup, and quench-front tracking. ORIGEN is developed by ORNL and released through the SCALE package. ORIGEN is directly integrated in MPACT through its API to calculate the changes in nuclides for every depletable cross-section region. Uncertainties exist in safety calculations with computer codes for nuclear reactor modeling and simulation, and they come from code limitations, scaling inaccuracies embedded in the experimental data, and uncertainties associated with the state of the reactor at the initiation of the transient. Consequently, for applications of high fidelity calculations using VERA-CS, proper uncertainty quantification (UQ) and sensitivity analysis (SA) of the computing models of reactor neutronics and thermal-hydraulics are important to comprehensively understand the results. New methods in UQ and SA have to be developed in multi-physics calculations using VERA-CS. Toward this end, a software package called VUSAT which stands for VERA-CS Uncertainty and Sensitivity Analysis Toolkit has been developed to facilitate the applications of VERA-CS within the context of best estimate plus uncertainty (BEPU) analysis framework. In this work, the VUSAT application to analyze departure from nucleate boiling (DNB) is presented.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Uncertainty Quantification and Sensitivity Analysis for Coupled VERA-CS and FRAPCON

The current nuclear power plant fleet in the U.S. is facing numerous challenges economically ranging from low natural gas price to the rapidly growing renewable energy sources such as wind and solar power. In order for the nuclear industry to keep the viability of its operating fleet, new innovations have to be introduced to lower the costs to operate the fleet. One area that could contribute to the cost reduction is to lower the fuel cycle cost and improve the plant safety through initiatives such as higher burnup fuel and accident tolerant fuel. At the same time, the nuclear industry has to address future challenges on the horizon such as load following and other flexible operating strategies as well as those associated with new regulations such as 10 CFR 50.69 and 10 CFR50.46c etc. All these require coupled analysis of core neutronics, thermal hydraulics and fuel performance, which necessitates the development of a multi-physics toolkit. Since different models, assumptions, and fidelities have gone into various computer codes, how to consistently propagate uncertainties in a multi-physics environment warrants careful evaluation. The U.S. DOE's Light Water Reactor Sustainability (LWRS) Program initiated a project to develop analytical capabilities to support the industry to address these challenges. The general idea behind the initiative was the development of an integrated multiphysics evaluation model. This integrated evaluation model is called LOTUS which stands for LOCA Toolkit for the U.S. Light Water Reactors. The focus of LOTUS is to establish the automation of the interface between the five disciplines. LOTUS framework ensures that uncertainties can be easily propagated to solve the problems forward and backward (inverse) with large numbers of simulations. The objective of this work is to perform uncertainty quantification (UQ) and sensitivity analysis (SA) on a coupling of CASL's Virtual Environment for Reactor Applications-Core Simulator (VERA-CS) and NRC's fuel performance code FRAPCON. The work presented herein is a subset of the overall LOTUS framework. The figures of merit (FOM) selected for analysis are minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and the gap conductance at peak power (GCPP). All FOM are obtained at the end of the of a depletion case for a half cycle lasting 263 days. The minimum is taken over all spatial location for each pin at the end of the half cycle. This value is calculated in VERACS alone and has been analyzed in previous work by Brown and Zhang. The MFCT is available in both VERA-CS and FRAPCON, but is calculated via different methods (see Model Inconsistencies section for more details). For this work, only the FRAPCON values are reported due to the code's maturity from extensive validation in fuel performance. Previous work includes SA on a standalone nuclear fuel performance code VTT-modified FRAPCON- 3.4 by Ikonen. The GCPP is the gap conductance at the location corresponding to maximum power in the fuel rod. This value is available in FRAPCON alone and highlights the capability of LOTUS to obtain unique fuel performance metrics for each pin in a core simulation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Diffusion Synthetic Acceleration for High Order S{sub N} Transport on Meshes with Curved Surfaces

Thermal radiation transport is integral to multiphysics applications such as inertial confinement fusion and astrophysics. Materials in these problems can be exceptionally optically thick and diffusive. A transport solver must be capable of accurate and efficient solutions to such problems. Previously, Woods et al. established a proof-of-concept for high order (HO) discontinuous Galerkin finite element (DGFEM) transport on meshes with curved surfaces. They numerically demonstrated the spatial convergence is order p + 1. Remarkably, these convergence rates are relatively invariant to the amount of curvature of the spatial mesh. We present here an extension of this work that demonstrates a rapidly-convergent iterative solver for the FEM transport equations on meshes with curved sides. We use the modified interior penalty (MIP) diffusion synthetic acceleration (DSA) established by Wang and Ragusa. The partially consistent MIP equations stem from the symmetric interior penalty (IP) derivation of the diffusion equation. The IP method is not stable for optically thick cells so it was combined with the diffusion conforming form (DCF), a discretized diffusion equation derived from the discretized S N equations that is not stable for intermediate optical thicknesses. The MIP equations adapt a 'switch' to the IP method in optically thinner regions and the DCF method in optically thicker regions. The literature does not reveal any Fourier analyses performed for iterative transport on meshes with curved surfaces. Wang and Ragusa performed a Fourier analysis for orthogonal meshes and our results appear to be as expected. Previous literature has reported on some of the sensitivities that affect the spectral radius of DSA schemes: polynomial order, and scattering ratios. Presently, we focus on the sensitivity of the spectral radius to polynomial order, scattering ratio, the constant C, and mesh curvature for varying cell thicknesses. We also numerically study the behavior of the spectral radius to verify our DSA implementation. A sequence of problems is designed to exercise the acceleration. As the problems become more optically thick and diffusive, the accelerated solution continues to converge toward the analytic solution. We employ the Modular Finite Element Methods (MFEM) package, developed at Lawrence Livermore National Laboratory, to generate the linear algebraic system of equations for each angle in the discrete ordinates quadrature set, and use UMFPack to solve this system of equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Flexible Spatial Partitions in MPACT Through Module-Based Data Passing

As part of the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Virtual Environment for Reactor Applications (VERA) is being developed to provide high-fidelity multiphysics simulations of nuclear reactor cores. The MPACT code being developed collaboratively by Oak Ridge National Laboratory and the University of Michigan is the primary deterministic neutron transport solver available within VERA. MPACT employs the 2D/1D method to solve 3D problems using 2D method of characteristics (MOC) radial transport solvers with 1D nodal expansion method-based P3 (NEM-P3) axial transport solvers, which are coupled using axial and radial transverse leakages. A 3D coarse mesh finite difference (CMFD) solver is used to provide accelerated convergence and stability. Quarter-core problems in MPACT are typically run on moderately sized clusters ({approx}500-10,000 cores). As such, it relies heavily on spatial decomposition, both radially and axially, using MPI data communication along spatial domain boundaries to pass angular flux boundary condition and neighboring data. The initial spatial decomposition strategy implemented into MPACT overlaid a Cartesian grid over the core to form the domain boundaries. With this approach, a single buffer spanning across the entire boundary between two spatial domains is passed to a domain's neighbor. Additionally, only one neighboring domain index was allowed in each direction. For example, the entire eastern boundary of a domain must be the entire western boundary of the corresponding neighbour's domain. This implementation helped to execute cases on several thousand cores, where substantial radial decomposition was used. The default for several years was to use assembly decomposition, which yielded 73 radial partitions in the Watts Bar Unit 1 (WBN1) models being analyzed. However, as CASL formed stronger connections with industry partners, there was a strong push to allow MPACT to run on fewer cores, preferably in the 500-1,000 core range. Such cases require much less radial decomposition, typically with 8-16 radial domains on each plane. Unfortunately, the previous decomposition strategy is very limited in its ability to yield well-balanced domains, and it does not permit partitions with an arbitrary number of domains, particularly with small numbers of radial domains (3, 5, 7, 11, 13, etc.). With these limitations, a more flexible approach that provided more even-load balancing was needed. The details of this new strategy are outlined here, along with insights to its advantages. The examples provided are for the WBN1 core, which has been the focus of several initial CASL analyses. It is worth noting that spatial decomposition strategies have been employed in many codes with focus on a number of different transport methodologies. The references cited are not exhaustive as this has been very important research topic across many areas.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗