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At least 235 records · Page 13

Real Fuel Modeling for Gasoline Compression Ignition Engine

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode. A study detailing the development of the gasoline real fuel model was performed and various surrogates for gasoline fuel were investigated. The gasoline real fuel model will be used in subsequent CFD modelling activities for the development of an advanced mixed mode combustion system as part of the Department of Energy funded project DE-EE0008478.

Gasoline Compression Ignition, real fuel modeling,↗

Machine Learning Surrogates of a Fuel Matrix Degradation Process Model for Performance Assessment of a Nuclear Waste Repository

Spent nuclear fuel repository simulations are currently not able to incorporate detailed fuel matrix degradation (FMD) process models due to their computational cost, especially when large numbers of waste packages breach. The current paper uses machine learning to develop artificial neural network and k-nearest neighbor regression surrogate models that approximate the detailed FMD process model while being computationally much faster to evaluate. Further, using fuel cask temperature, dose rate, and the environmental concentrations of CO 3 2- , O 2 , Fe 2+ , and H 2 as inputs, these surrogates show good agreement with the FMD process model predictions of the UO 2 degradation rate for conditions within the range of the training data. A demonstration in a full-scale shale repository reference case simulation shows that the incorporation of the surrogate models captures local and temporal environmental effects on fuel degradation rates while retaining good computational efficiency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Overview of Base Model in Parametric Studies Specific to Performance of U-Mo Plates

This paper provides an overview of the base model specifically developed to perform parametric sensitivity studies on the U-10Mo monolithic fuel system. U-Mo monolithic fuels are being considered for the conversion of test reactors into high-performance research reactors that operate using proliferation-resistant, low-enriched uranium (LEU) fuels. These plate-type fuels contain a high-density, low-enrichment fuel sandwiched between zirconium diffusion barriers and encapsulated in aluminum claddings. All U.S. high-performance research reactors have released the designs of their LEU monolithic fuel reactor cores. These designs include nearly 50 distinct fuel plate geometries with different operational parameters. Consequently, a single generic plate geometry representing all the extreme points in this design matrix is unrealistic. To evaluate the performance for various parameters, a set of sensitivity studies was performed. These studies considered various input parameters (i.e., geometric, operational, and material property-related). The results revealed valuable information about plate performance and the sensitivity of this performance to various modeling inputs. To establish a reference state for comparing these result, base model featuring representative irradiation conditions was developed. To capture in-reactor behavior accurately, incorporation of representative constitutive models capable of evolving properties with respect to temperature, irradiation time, and burnup was needed. The behavioral models considered burnup-dependent properties, swelling, creep, and degradation. This paper introduces the base model created for the parametric sensitivity studies. The detailed description of the procedure includes the model geometry, model discretization, thermo-mechanical coupling, material properties and behavioral models. This paper also provides selected results and assesses the performance of the base model.

42 ENGINEERING↗

Parametric Thermal Models of the Transient Reactor Test Facility (TREAT)

This work supports the restart of transient testing in the United States using the Department of Energy’s Transient Reactor Test Facility at the Idaho National Laboratory. It also supports the Global Threat Reduction Initiative by reducing proliferation risk of high enriched uranium fuel. The work involves the creation of a nuclear fuel assembly model using the fuel performance code known as BISON. The model simulates the thermal behavior of a nuclear fuel assembly during steady state and transient operational modes. Additional models of the same geometry but differing material properties are created to perform parametric studies. The results show that fuel and cladding thermal conductivity have the greatest effect on fuel temperature under the steady state operational mode. Fuel density and fuel specific heat have the greatest effect for transient operational model. When considering a new fuel type it is recommended to use materials that decrease the specific heat of the fuel and the thermal conductivity of the fuel’s cladding in order to deal with higher density fuels that accompany the LEU conversion process. Data on the latest operating conditions of TREAT need to be attained in order to validate BISON’s results. BISON’s models for TREAT (material models, boundary convection models) are modest and need additional work to ensure accuracy and confidence in results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of an analytical model to assess fuel property effects on combustor performance

A generalized first-order computer model has been developed in order to analytically evaluate the potential effect of alternative fuels' effects on gas turbine combustors. The model assesses the size, configuration, combustion reliability, and durability of the combustors required to meet performance and emission standards while operating on a broad range of fuels. Predictions predicated on combustor flow-field determinations by the model indicate that fuel chemistry, as defined by hydrogen content, exerts a significant influence on flame retardation, liner wall temperature, and smoke emission.

Sutton, R. D.↗

Transition Core Modeling for Extended Enrichment & Accident-Tolerant Fuels Using Polaris/PARCS

Commercial light water reactor (LWR) operators and fuel vendors are currently interested in increasing the low-enriched uranium (LEU) fuel enrichments from the current limit of 5.0 $^w/_o$ $^{235}U$ up to 10 $^ w/_o$ $^{235}U$ (referred to as "LEU+") in their current fleets; they are also interested in using accident-tolerant fuel (ATF) with both LEU and LEU+ fuel. This report aims to identify modeling challenges and accuracy concerns in transition core analysis using the SCALE Polaris lattice physics code and U.S. Nuclear Regulatory Commission core simulator PARCS. At the time this study was started, no publicly available LEU+ core designs existed for boiling water reactor (BWR) or pressurized water reactor (PWR) systems. Therefore, fuel lattices were shuffled within a multi-assembly model to mimic neutronically challenging lattice combinations seen in transition cores, such as a fresh LEU+ lattice next to depleted LEU lattices. In addition to multi-assembly models, whole-core BWR transition core calculations were performed for ATF and LEU+ fuel using an existing Hatch-1 Cycle 3 core model. A whole-core BWR model was chosen due to the more heterogeneous core designs compared to those for a PWR core. Since the original core is an old checkerboard core design and no core or fuel design optimization was performed for the modeled fuel types, these core calculations were intended only to provide: (1) Comparisons of core characteristics of interest, such as the pin power distributions and peaking factors, Doppler temperature coefficients (DTCs), and control blade worths (CBWs) under challenging core designs, (2) Identification of reactor physics challenges in modeling LEU+ and ATF cores, and (3) A stress test for the Polaris/PARCS two-step modeling approach, including characterization of the relative accuracy for predicting characteristics of interest such as pin power distributions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Summary report on UO 2 thermal conductivity model refinement and assessment studies

Uranium dioxide (UO 2 ) is the most commonly used fuel in light water nuclear reactors and thermal conductivity controls the removal of heat produced by fission, therefore, governing fuel temperature during normal and accident conditions. The use of fuel performance codes by the industry to predict operational behavior is widespread. A primary source of uncertainty in these codes is thermal conductivity, and optimized fuel utilization may be possible if existing empirical models were replaced with models that incorporate explicit thermal conductivity degradation mechanisms during fuel burn-up. This approach is able to represent the degradation of thermal conductivity due to each individual defect type, rather than the overall burn-up measure typically used which is not an accurate representation of the chemical or microstructure state of the fuel that actually governs thermal conductivity and other properties. To generate a mechanistic thermal conductivity model, molecular dynamics (MD) simulations of UO 2 thermal conductivity including representative uranium and oxygen defects and fission products are carried out. These calculations employ a standard Buckingham type interatomic potential and a potential that combines the many-body embedded atom method potential with Morse-Buckingham pair potentials. Potential parameters for UO 2+x and ZrO 2 are developed for the latter potential. Physical insights from the resonant phonon-spin scattering mechanism due to spins on the magnetic uranium ions have been introduced into the treatment of the MD results, with the corresponding relaxation time derived from existing experimental data. High defect scattering is predicted for Xe atoms compared to that of La and Zr ions. Uranium defects reduce the thermal conductivity more than oxygen defects. For each defect and fission product, scattering parameters are derived for application in both a Callaway model and the corresponding high-temperature model typically used in fuel performance codes. The model is validated by comparison to low-temperature experimental measurements on single crystal hyper-stoichiometric UO 2+x samples and high-temperature literature data. Ongoing works include investigation of the effect of phase separation to UO 2 +U 4 O 9 on the low temperature thermal conductivity of UO 2+x , and modeling of thermal conductivity using the Green-Kubo method. Ultimately, this work will enable more accurate fuel performance simulations as well as extension to new fuel types and operating conditions, all of which improve the fuel economics of nuclear energy and maintain high fuel reliability and safety.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Understanding Impacts of Catalyst-Layer Thickness on Fuel-Cell Performance via Mathematical Modeling

In this article, a two-dimensional, multiphase, transient model is introduced and used to explore the impact of catalyst-layer thickness on performance. In particular, the tradeoffs between water production and removal through transport or evaporation are highlighted, with a focus on low-temperature performance. For the latter, a case study of an ultra-thin catalyst layer is undergone to explore how various material properties alter the steady-state and startup performance of a cell. The findings provide understanding and guidance to optimize fuel-cell performance with thin electrodes.

25 ENERGY STORAGE↗

Phase equilibria of advanced technology uranium silicide-based nuclear fuel

The phases in uranium-silicide binary system were evaluated in regards to their stabilities, phase boundaries, crystal structures, and phase transitions. The results from this study were used in combination with a well assessed literature to optimize the U-Si phase diagram using the CALPHAD method. A thermodynamic database was developed, which could be used to guide nuclear fuel fabrication, could be incorporated into other nuclear fuel thermodynamic databases, or could be used to generate data required by fuel performance codes to model fuel behavior in normal or off-normal reactor operations. The U 3 Si 2 and U 3 Si 5 phases were modeled using the Compound Energy Formalism model with 3 sublattices to account for the variation in composition. The crystal structure used for the USi phase was the tetragonal with an I4/mmm space. Above 450°C, the U 3 Si 5 phase was modeled. The composition of the USi 2 phase was adjusted to USi 1.84 . The calculated invariant reactions and the enthalpy of formation for the stoichiometric phases were in agreement with experimental data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evaluation of ceria as a surrogate material for UO 2 in experiments on fuel cracking driven by resistive heating

A variety of normal operation and accident scenarios can generate thermal stresses large enough to cause cracking in light-water reactor (LWR) fuel pellets. Cracking of fuel pellets can lead to reduced heat removal, larger centerline temperatures, and localized stress in cladding all of which impact fuel performance. Furthermore, pellet cracking also contributes to a temperature reduction in the pellet since the pellet fragments tend to move towards the heat sink (cladding), and the heat flow remains predominantly radial despite the presence of cracks. It is important to understand the temperature profile on the pellet before and after cracking to improve cracking models in fuel performance codes However, in-reactor observation and measurement of cracking is very challenging owing to the harsh environment and design of fuel rods. Recently, an experimental pellet cracking test stand was developed for separate effects testing of normal operations and accident temperature conditions, using thermal imaging to capture the pellet surface temperature for evaluation of thermal stresses and optical imaging to capture the evolution of cracking in real time. Cracking experiments were initially performed using ceria (CeO 2 ) as a surrogate fuel material, which is useful for developing and demonstrating the experimental approaches but is also valuable in its own right for cracking model development and validation. A combination of induction and resistance heating was used for volumetric heat generation in the pellet creating a thermal gradient. The material properties of CeO 2 and UO 2 are reviewed and compared for use in model development. Simulations of the experiment were performed to evaluate the behavior of the surrogate (CeO 2 ) fuel in BISON. The measured temperature profiles from BISON models match reasonably well with the observed experiments for the ceria pellets before cracking. The findings from this work will help improve confidence in fracture models used for fuel pellets under similar in-reactor conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Uncertainty Quantification of Calculated Temperatures for the AGR-1 Experiment

This report documents an effort to quantify the uncertainty of the calculated temperature data for the first Advanced Gas Reactor (AGR-1) fuel irradiation experiment conducted in the INL’s Advanced Test Reactor (ATR) in support of the Next Generation Nuclear Plant (NGNP) R&D program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR-1 test, the results of the numerical simulations can be used in combination with the statistical analysis methods to improve qualification of measured data. Additionally, the temperature simulation data for AGR tests can be used for validation of the fuel transport and fuel performance simulation models. The crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. The report is organized into three chapters. Chapter 1 introduces the AGR Fuel Development and Qualification program and provides overviews of AGR-1 measured data, AGR-1 test configuration and test procedure, and thermal simulation. Chapters 2 describes the uncertainty quantification procedure for temperature simulation data of the AGR-1 experiment, namely, (i) identify and quantify uncertainty sources; (ii) perform sensitivity analysis for several thermal test conditions; (iii) use uncertainty propagation to quantify overall response temperature uncertainty. A set of issues associated with modeling uncertainties resulting from the expert assessments are identified. This also includes the experimental design to estimate the main effects and interactions of the important thermal model parameters. Chapter 3 presents the overall uncertainty results for the six AGR-1 capsules. This includes uncertainties for the daily volume-average and peak fuel temperatures, daily average temperatures at TC locations, and time-average volume-average and time-average peak fuel temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Redwing: A MOOSE application for coupling MPACT and BISON

Fuel performance and whole core neutron transport programs are often used to analyze fuel behavior as it is depleted in a reactor. For fuel performance programs, internal models provide the local intra-pin power density, fast neutron flux, burnup, and fission rate density, which are needed for a fuel performance analysis. The fuel performance internal models have a number of limitations. These include effects on the intra-pin power distribution by nearby assembly elements, such as water channels and control rods, and the further limitation of applicability to a specified fuel type such as low enriched UO2. In addition, whole core neutron transport codes need an accurate intra-pin temperature distribution in order to calculate neutron cross sections. Fuel performance simulations are able to model the intra-pin fuel displacement as the fuel expands and densifies. These displacements must be accurately modeled in order to capture the eventual mechanical contact of the fuel and the clad; the correct radial gap width is needed for an accurate calculation of the temperature distribution of the fuel rod. Redwing is a MOOSE-based application that enables coupling between MPACT and BISON for transport and fuel performance coupling. MPACT is a 3D neutron transport and reactor core simulator based on the method of characteristics (MOC). The development of MPACT began at the University of Michigan (UM) and now is under the joint development of ORNL and UM as part of the DOE CASL Simulation Hub. MPACT is able to model the effects of local assembly elements and is able calculate intra-pin quantities such as the local power density on a volumetric mesh for any fuel type. BISON is a fuel performance application of Multi-physics Object Oriented Simulation Environment (MOOSE), which is under development at Idaho National Laboratory. BISON is able to solve the nonlinearly coupled mechanical deformation and heat transfer finite element equations that model a fuel element as it is depleted in a nuclear reactor. Redwing couples BISON and MPACT in a single application. Redwing maps and transfers the individual intra-pin quantities such as fission rate density, power density, and fast neutron flux from the MPACT volumetric mesh to the individual BISON finite element meshes. For a two-way coupling Redwing maps and transfers the individual pin temperature field and axially dependent coolant densities from the BISON mesh to the MPACT volumetric mesh. Details of the mapping are given. Redwing advances the simulation with the MPACT solution for each depletion time step and then advances the multiple BISON simulations for fuel performance calculations. Sub-cycle advancement can be applied to the individual BISON simulations and allows multiple time steps to be applied to the fuel performance simulations. Currently, only loose coupling where data from a previous time step is applied to the current time step is performed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improved Fracture Models for Relocation Modeling

The BISON fuel performance code is being developed to provide a modern tool that has the flexibility to analyze a wide variety of fuel forms and to model conditions and phenomena that could not be represented in legacy tools. There are a number of motivations for this, including providing support for development of advanced fuel with improved accident tolerance for existing light water (LWR) reactors, improved understanding of mechanisms in fuel designs in current use in a wider variety of conditions, and facilitating the development of fuel for advanced reactor designs. To accomplish these goals, it is clear that BISON must rely on models of fuel behavior that are based on fundamental physical behavior, rather than on empirical correlations that represent that behavior in a simplified fashion. BISON still does employ many empirical models that were originally developed for other fuel performance codes, but efforts are underway to replace these with models that are more physically based. Radial relocation in LWR fuel is an example of a phenomenon that is currently represented by an empirical model, but which is ripe for replacement by physically based models. During normal operation, ceramic LWR fuel experiences significant fracturing that is driven by spatially nonuniform volumetric expansion. This occurs due to the significant thermal gradients within the fuel that occur in fresh and irradiated fuel, as well as nonuniform swelling due to fission products that occurs over longer-term irradiation. Fracture and fragmentation of fuel allows the outer radius of the fuel pellet to expand due to the loss of mechanical constraint and outward radial migration of fragments. This radial expansion has a significant effect on the fuel system response because it decreases the size of the gap between the fuel and cladding. This decreases the thermal resistance across that gap, which leads to decreased fuel centerline temperatures. This report documents recent work to improve the ability of BISON to model radial relocation using the extended finite element method (XFEM). These enhancements include the ability to include cohesive zone models, improved code architecture for propagating cracks based on fracture integrals, and improved handling of fuel and cladding interfaces with XFEM. These capabilities are demonstrated on a simulation of radial relocation including a surface interaction model that enforces residual opening.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Simulation of a TRISO MiniFuel irradiation experiment with data-informed uncertainty quantification

An irradiation experiment using tristructural isotropic (TRISO) fuel particles and the miniature fuel (MiniFuel) irradiation vehicle was performed in Oak Ridge National Laboratory’s High Flux Isotope Reactor (HFIR) to support development of the Kairos Power fluoride salt–cooled, high-temperature reactor (KP-FHR). Here, this paper describes modeling predictions of temperatures and fuel burnup for the as-built experiment. An uncertainty quantification (UQ) analysis was performed to determine the effect of TRISO particle volume and position on the temperature predictions at various fuel heat generation rates (HGRs). This UQ study utilized fuel kernel position and volume measurements previously collected using X-ray computed tomography (XCT) techniques and Monte Carlo sampling methods to generate fuel compact cases that were then analyzed using a finite element thermal model. The UQ analysis indicated that uncertainty in calculated temperatures caused by varying TRISO particle arrangement is relatively small, even at high fuel HGR. Final predictions of particle temperatures throughout the irradiation are shown to be relevant to KP-FHR normal and off-normal operating conditions and to previous TRISO irradiation experiments. The combination of XCT with UQ analyses will inform post-irradiation examination (PIE) of the irradiated fuel compacts, and these analyses can be used to develop fuel performance models for coated particle fuel forms. Both PIE of separate-effects irradiation data and enhanced fuel performance modeling support accelerated qualification of TRISO fuels for a broad range of advanced reactor applications. The novel approach demonstrated here of measuring TRISO particle configurations with XCT methods and generating representative fuel compacts for finite element modeling and UQ analysis could be leveraged by the broader particle fuel community in the development of other TRISO fuel experiments in which these variables may have a significant impact on key outcomes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Asymptotic Expansion Homogenization for Multiscale Nuclear Fuel Analysis

Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed. This multiscale modeling approach is a central motivation in the development of the BISON-MARMOT fuel performance codes at Idaho National Laboratory. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale sim- ulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the microscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Uncertainty quantification of calculated temperatures for advanced gas reactor fuel irradiation experiments

This paper presents the quantification of uncertainty of the calculated temperature data for the Advanced Gas Reactor (AGR) fuel irradiation experiments conducted in the Advanced Test Reactor at Idaho National Laboratory in support of the Advanced Reactor Technology Research and Development program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR tests, the results of the numerical simulations are used in combination with statistical analysis methods to improve qualification of measured data. The temperature simulation data for AGR tests are also used for validation of the fission product transport and fuel performance simulation models. These crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. To quantify the uncertainty of AGR calculated temperatures, this study identifies and analyzes ABAQUS model parameters of potential importance to the AGR predicted fuel temperatures. The selection of input parameters for uncertainty quantification of the AGR calculated temperatures is based on the ranking of their influences on variation of temperature predictions. Thus, selected input parameters include those with high sensitivity and those with large uncertainty. Propagation of model parameter uncertainty and sensitivity is then used to quantify the overall uncertainty of AGR calculated temperatures. Expert judgment is used as the basis to specify the uncertainty range for selected input parameters. The input uncertainties are dynamic accounting for the effect of unplanned events and changes in thermal properties of capsule components over extended exposure to high temperature and fast neutron irradiation. The sensitivity analysis performed in this work went beyond the traditional local sensitivity. Using experimental design, analysis of pairwise interactions of model parameters was performed to establish sufficiency of the first-order (linear) expansion terms in constructing the response surface. To achieve completeness, uncertainty propagation made use of pairwise noise correlations of model parameters. Furthermore, time-dependent sensitivity over the test campaign duration was obtained using an interpolation scheme over the input parameter domain. This allows computation of uncertainty for the predicted peak fuel temperatures and the predicted graphite temperatures at TC locations over the whole AGR irradiation period.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗