Implementation of Task Variance Model in Security Assessment Models
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98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
SEARCH · Engineering Papers
Results for “Advanced Modeling and Simulation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Refinements of a treat model for transient analysis
In order to prepare for the TREAT reactor being taken off standby, the Gateway for Advanced Modeling and Simulation Lab has used a set of KENO models to simulate certain TREAT temperature- limited transients using the Transient Reactor excursion simulator (T-ReX) code, a hybrid deterministic-stochastic code. These transients are from the M8CAL experiment series, a set of experiments done to calibrate the reactor for the planned M8 series of fuel tests. Recently, the model has been updated in media definitions and geometry. Models were examined and calculations were performed to low uncertainty values to find the k{sub eff} and reactivity insertions. Alterations to modeled values of shutdown and initial transient rod insertion depth were made to create models which had experimental values of reactivity insertion, pre-transient k{sub eff}, or both. It was found that two of the altered media inputs, fuel and Zircaloy-3 cladding, had significant effect on the k{sub eff}. Surprisingly, the Zircaloy-3 composition had a larger effect on k{sub eff}. The reactivity insertions in this model's 2855, 2856 and 2857 temperature-limited transients were found to be above experimental values by a factor of 5.5% to 7%, and that pre-transient k{sub eff} was too high, at 1.002. It was found that increasing shutdown rod insertion by 2 to 2.5 cm decreased pre-transient k{sub eff} to 1.0, and that increasing shutdown rod insertion by 3 to 5 cm and decreasing initial transient rod insertion by 1 to 2 cm gave perfect pre-transient k{sub eff} and total reactivity insertion. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Multiscale modeling for high burnup structure formation and associated pulverization
This report summarizes the lower length scale modeling work performed in the fiscal year 2023 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to capture the microstrutural evolution and associated pulverization criteria in the high burnup regions. This year, the resolution mechanisms within the cluster dynamics code has been updated and it influence on the bubble growth in HBS regions at the mesoscale is studied. To improve the accuracy of phase-field models of fission gas bubble growth, a new Helmholtz free energy for high-density Xe gas is derived from a virial equation of state. Two previously used strategies for representing net vacancy production in phase-field models of fission gas bubble growth are compared with each other and with analytical models of bubble growth. The vacancy source only model is found to be more convenient to parameterize realistically compared with the vacancy source+sink model. Furthermore, the phase-field-fracture simulation have been performed using MD- informed failure stress values and realistic HBS structure obtained from the phase-field simulations. We also present the uncertainty bands on prediction of the critical stress to account for the effect of the lower length scale variabilities on the failure criteria at the mesoscale. It is observed that pulverization may occur in partially restructured regions with restructuring fraction as low as 17%. In light of this, an update to the BISON’s pulverization criteria is recommended.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Orientation-Dependent Surface Faceting in UO{sub 2}
The surface behavior of UO{sub 2} plays an important role throughout the lifetime of this widely-used commercial nuclear fuel, from manufacturing to waste storage. UO{sub 2} surface properties affect fuel swelling behavior by determining the morphology, size and distribution of fission gas bubbles. Additionally, UO{sub 2} surface characteristics influence fracture behavior, which is controlled by the thermodynamics of fracture surfaces. Therefore, detailed understanding of the fundamental surface behavior will help advance prediction of the fuel performance of UO{sub 2}. Due to significant anisotropy in surface tension, faceting features form after annealing in both UO{sub 2} and many other crystalline materials. Knowledge of the correlation between crystallographic orientation and surface faceting features will expand the fundamental knowledge of UO{sub 2} surface characteristics, leading to a better understanding of fission gas swelling and fracture mechanisms. Inherent characterization technique limited previous studies on the crystallographic orientation of UO{sub 2} surface facets to low Miller index surfaces in single crystal specimens. In this study, synchrotron Laue microdiffraction was utilized to examine the crystallographic orientation of grains on the coarse surface of a polycrystalline UO{sub 2} specimen. The results were then compared with the surface morphology, obtained from scanning electron microscopy (SEM), so that a general correlation between the surface faceting features and crystallographic orientation in UO{sub 2} can be established. Both the fundamental surface characteristics and the crystallographic orientation measurements obtained in this study help advance the experiment validation of MARMOT, a mesoscale multi-physics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. The MARMOT code is an indispensable component of the MOOSE-BISON-MARMOT (MBM) code suite that has been developed by Idaho National Laboratory to enable next generation fuel performance modeling capability as a part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program Fuels Product Line (FPL). In this study, the surface-faceting features of UO{sub 2} were found to be dominated by the triple-plane structure and its variants. With this knowledge, by measuring the directions of the <110> edges, the crystallographic orientation of a surface UO{sub 2} grain can be precisely deduced in most regions of the standard stereogram triangle (SST) of the surface normal. (authors)
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Comparison of Surrogate Models with Physical Models for Dynamic Probabilistic Risk Analysis Using the RAVEN Code
Dynamic probabilistic risk analysis (DPRA) has emerged in the nuclear industry as an effective tool to identify points of weakness in nuclear reactors and create a comprehensive approach to quantifying risk. While DPRA allows for detailed analysis, it usually requires thousands of runs due to the necessity of exploring low probability, high consequence events, which can be computationally prohibitively difficult to assess. Risk Analysis Virtual Environment (RAVEN) is a software package being developed under the Nuclear Energy Advanced Modeling and Simulation program at the Idaho National Laboratory. It is able to manage complex control logic to drive a RELAP-7 simulation and to handle sampling strategies including Monte Carlo, Latin Hypercube, Grid and Adaptive samplers. By performing a thorough investigation of the possibility space of an accident scenario with RELAP-7, RAVEN is able to identify consequences of accident scenarios that have not been encountered. The most computational resource intensive step of a RAVEN analysis is running the RELAP-7 code modeling the physical system behavior. Using surrogate models to represent the outcomes of more complex simulations rather than the full model can greatly reduce the computation effort required. In situations where the uncertainty distributions of a model are unknown, or when there are multiple sets of uncertainty distributions, DPRA generally requires rerunning the physical model for each set of uncertainty distributions used. By taking an unbiased sample of the physical model and creating a surrogate model from the results, the surrogate model can be sampled under a different set of uncertainty distributions to provide equivalent results. This paper presents an example of this approach. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Verification of High-Fidelity Neutronics Code PROTEUS for C5G7 Benchmark Problems
Under the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the 3D whole core transport code PROTEUS has been developed at Argonne National Laboratory to perform the detailed 3D transport calculation for various reactor types including irregular or complex geometric reactors. PROTEUS includes two distinct transport solvers: SN and MOC. Among them, the MOC solver based on the extruded geometry, thus named MOCEX, can produce the faithful 3-D transport solutions by employing the rigorous and robust 2D/3D MOC formulation. This formulation overcomes the drawbacks of a full 3D MOC method requiring enormous memory and computational resources and resolves the instability issues of the 2D/1D method as well. The solution of MOCEX converges to that of a Monte Carlo code as the discretization of angle, space and energy is refined, unlike the 2D/1D method. As a verification and validation (V and V) effort of PROTEUS-MOCEX, this paper presents verification test results using the well-known 3D C5G7 benchmark problems by solving and comparing eigenvalues and pin powers with MCNP solutions.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Surrogate Models for TREAT Transient Calculations
The Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is currently preparing for resumption of operation after more than 20 years in a long-term standby state. In parallel with preparation for operations and a new transient testing program, the DOENE Advanced Modeling and Simulation program (NEAMS) has been supporting the development of three-dimensional transient multi-physics modeling capabilities within the reactor physics application MAMMOTH. Recently, the MAMMOTH reactor physics team has begun development of uncertainty and sensitivity analysis for the TREAT core. This research will be used to support the analysis of reactor operation and experiment planning. Traditional approaches, i.e., Monte Carlo simulations, for such tasks require a large number of model evaluations under both steady state and transient conditions. However, exhaustive sets of sampling runs are simply not practical for TREAT since evaluations of each model can take a substantial amount of time. A solution to this problem is to build a surrogate model employing a smaller number of model evaluations. The surrogate model is designed to provide an accurate and fast approximation to the detailed TREAT model. In this manner, the surrogate model can be used in place of the TREAT transient model for uncertainty and sensitivity analysis at a fraction of the computational cost. The high dimensional model representation (HDMR) method is employed here for approximating the responses of interest in terms of functions of lower dimensions. This method has been implemented in RAVEN and all TREAT transient calculations are performed using the multiphysics code MAMMOTH. In addition, a code interface has also been developed in order to couple RAVEN with MAMMOTH. The surrogate model is then tested and compared for TREAT startup testing program Transient Test no. 15 core, and its accuracy is measured by its ability to estimate the mean, coefficient of variance, skewness, excess kurtosis and probability density function of the outputs of Transient Test no. 15 model, as well as root mean square error metric.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Implementation of CMFD Acceleration Scheme in PROTEUS-MOC
The PROTEUS-MOC code is a three-dimensional (3D) transport code, which is being developed at Argonne National Laboratory under the DOE-NE's Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. It provides a fully consistent 3D discretization of the transport equation by combining the two-dimensional (2D) method of characteristics (MOC) for the planar direction with the discontinuous Galerkin method for the treatment of the axial variable. PROTEUS-MOC uses the unstructured finite element method (FEM) and thus allows the explicit representation of any extruded geometries. It also has a capability of massively parallel computation in energy group, angle, plane, and space using a top-level GMRES linear algebra solver. For parallel computation in space, it uses an unstructured domain decomposition by adapting METIS. The computational burden for direct heterogeneous core calculations based on unstructured geometries is excessive for practical reactor problems, and hence it is essential to implement an efficient acceleration scheme in PROTEUS-MOC. Recently, the coarse mesh finite difference (CMFD) method, which was originally applied to the nodal diffusion methods, has been successfully applied to the MOC transport solvers, resulting in a remarkable reduction in the number of fission source iterations. In addition, a modified CMFD method has been developed to overcome the limitation of the conventional CMFD that is applicable only to neutronics solvers with a conservative discretization. This CMFD method was derived to be consistent with the FEM, which is based on a nonconservative discretization. In this method, the neutron balance in each coarse mesh is enforced by introducing a pseudo absorption cross section (PAXS), and the well-established alternating solution process of CMFD and transport calculations is employed to accelerate source convergence. This modified CMFD acceleration scheme was adopted in PROTEUS-MOC to accelerate the fission source iteration. Pin-cell and assembly based CMFD schemes have been implemented by defining individual pin cells or assemblies as a coarse mesh. For this, an algorithm to map the finite elements to coarse meshes was developed, and the routines were developed to determine the coupling coefficients and PAXS of the CMFD equations from the transport solution. Preliminary performance tests were carried out using the C5G7 benchmark problem. This paper presents the main features of this CMFD acceleration scheme and the preliminary test results.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Ease of use and deployment for a fast, scalable data movement infrastructure
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42 ENGINEERING↗
Development of a Computational Framework for Multiphysics Multiphase Species Tracking using NEAMS Tools
This report implements a high-fidelity multiphysics modeling framework using the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program tools to track isotopic species in Molten Salt Reactors (MSRs), with a specific focus on the 91-depletion chain within the Molten Salt Reactor Experiment (MSRE). The model integrates neutronics, thermal-hydraulics, depletion, and thermochemistry to simulate the production, transport, and phase transitions of isotopes under steady-state and transient conditions. The main findings reveal that isotopes such as bromine-91 largely remain in the liquid phase, while others, including krypton-91and yttrium-91, transition to the gas phase, significantly influencing the reactor’s radiological source term. The study also shows that during transients, like a reactivity insertion transient, rapid void formation and the expansion of the liquid-gas interface led to substantial transfers of dissolved isotopes into the gas phase, altering isotope distribution and largely increasing the source term in the off-gas system. Additionally, the research highlights that short-lived isotopes dominate the initial off-gas response during transients, while longer-lived isotopes determine the equilibrium state, underscoring the necessity of dynamic simulations for accurate species tracking and reactor safety analysis. The developed methodology will be applied in the future to the tracking of a larger number of species and introduce other species tracking mechanisms, such as deposition and plating.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Generating An Advanced Cross-section Library For HTGR Pebble Bed Depletion Calculations Using Reduced-Order Model Generation Techniques
For code development, Advanced Reactor Technologies - Gas Cooled Reactors Program (ART-GCR) rely on a collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, but the cross sections generation and the methodology definition is part of this program area goals. Based on previous studies in FY23, the size of microscopic cross section libraries increases rapidly with the number of tabulations, requiring significant amount of memory and drastically slowing down the Griffin calculations when evaluating cross sections via the multivariate linear interpolation approach. Rising to these challenges, this work investigates constructing Reduced-order Models (ROMs) for the multi-group microscopic cross sections to accelerate the cross section evaluation in Griffin. A database of multigroup cross sections is first collected considering all possible parameters that a designer could change for optimization. Down-selection of the ROM techniques afterward shows Deep Neural Network (DNN) as the best candidate when jointly consider memory efficiency, predictive accuracy, computational cost, scalability, flexibility and ease of implementation of the algorithms in comparison to the multidimensional interpolation. This work develops a specific interface that enables the cross section predictions using pre-trained DNN models into Griffin leveraging the existing ROM capabilities. DNNs have been trained for all isotopes for use in Griffin. Preliminary Griffin testing shows that DNNs exhibit exceptional predictive accuracy and the use of DNNs provides orders of magnitude improvement in memory efficiency compared to conventional interpolation techniques. With such ROM techniques, it holds great promise to further increase the fidelity of the Pebble Bed Reactor (PBR) simulation by increasing the number of tabulations/state variables during cross section evaluation, while maintaining the computational cost affordable in Griffin.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Coupling coarse mesh CFD with fine mesh CFD for modeling for Molten Salt Reactors in the Virtual Test Bed VTB
The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims at developing a simulation tool kit to accelerate the development and deployment of nuclear power technologies. NEAMS multiphysics tools have been designed to provide numerical simulation support for the design and licensing of GEN IV reactors. Pronghorn is NEAMS’s coarse-mesh computational fluid dynamics (CFD) tool, which is designed to run 3D core transients in GEN IV reactors at a reduced computational cost. To increase their accuracy, coarse-mesh CFD simulations require calibrated closure coefficients. One way of computing these coefficients is via the Nek5000, NEAMS’s high-fidelity CFD tool. This article discusses our current research lines in informing Pronghorn closure coefficients via Nek5000 to enable multiphysics simulations of the core cavity of the molten-salt fast reactor. We present an application in which Pronghorn mixing length turbulent viscosity has been calibrated from Nek5000 simulations. The resulting Pronghorn thermal-hydraulics model is then coupled to Griffin, the NEAMS neutron transport solver, to solve for the steady-state configuration of the molten-salt fast reactor.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Results of an In-Field Validation Exercise in Support of Wide-Area Environmental Sampling
The National Nuclear Security Administration’s (NNSA) Office of Nonproliferation and Arms Control (NA-24) is evaluating Wide-Area Environmental Sampling (WAES) as an additional safeguards verification tool for the International Atomic Energy Agency to detect undeclared nuclear activities. The NNSA is evaluating strategies for conducting a generic WAES campaign, the cost of a WAES campaign, and the effect of technological advancements that have occurred since the last major WAES review in 1999. Until now, the NNSA effort has focused on tabletop exercises (TTXs) in which high-performance computing allows for advanced modeling and simulation efforts to be applied to the WAES question. Although the modeling and simulations used in the TTXs are extremely valuable, field campaigns are still needed to validate the assumptions that underpin the models and the modeling process itself. During a 7 week period beginning in May 2023 and ending in June 2023, which included 4 weeks of active field collections, a multilaboratory team conducted its first in-field validation exercise. Prior to the in-field exercise, abbreviated TTXs were conducted to estimate the performance of all collection systems to be used during the field test. These TTXs guided the selection of materials to be released and the placement of the collection system. Based on these determinations, materials were procured to use in the field test, and an injection/release system was designed, built, and installed at the test facility. Background samples were collected during weeks one and four, and environmental collections against active releases were conducted during weeks two and three. The goals of this validation exercise included a demonstration of (1) the ability to provide controlled releases of particulates of surrogate materials, (2) the fielding and operation of collection systems (including deposition and active air collectors), and (3) the flexibility to revise equipment and campaign plans in the field. This paper presents the results and preliminary conclusions for this initial validation test. Based on these results, subsequent field campaigns are anticipated and will include the addition of other released materials.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Heat Pipe Modeling Capabilities in Sockeye
Presentation to be given in a meeting with stakeholders of the Nuclear Energy Advanced Modeling and Simulation program for modeling related to microreactors. This presentation gives an overview of the capabilities and status of the heat pipe code Sockeye.
97 MATHEMATICS AND COMPUTING↗
Meso-scale modeling of UO2 nuclear fuel to high burnup
To improve the economics of light water reactors for commercial nuclear energy generation, utility operators are seeking to obtain regulatory approval to run UO2 fuel to higher levels of burnup. One potential impediment to obtaining this approval is the phenomenon of fuel fragmentation, relocation, and dispersal (FFRD). FFRD can result when fuel experiences a rapid temperature transient, such as that occurring during a Loss Of Coolant Accident (LOCA). FFRD has historically been most associated with the rim region in UO2 fuel pellets, where the phenomenon of fragmentation is also referred to as pulverization due to the small size of the fragments. More recent evidence suggests that the so-called “dark zone” (due to its appearance in micrographs) that can be observed in the mid-radial regions of high burnup fuel is also susceptible to FFRD. Although empirical fuel performance models have been developed that can adequately predict pulverization in the rim region under typical LWR conditions, a scientific understanding of what underlies fuel restructuring and subsequent FFRD is lacking even in the rim region, and no models are currently available for the behavior the dark zone. To address these challenges, the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has employed a multi-scale modeling approach to improve scientific understanding and develop new fuel performance models. In this talk, I will focus on meso-scale efforts, which form a crucial link between atomic-scale and engineering-scale models. Phase-field modeling combined with cluster dynamics is used to predict the restructuring process in the rim region. Phase-field fracture modeling, informed by atomistic simulations, is used to predict the onset of pulverization in the rim region. Combining these techniques together allows the extent of rim pulverization to be predicted. The formation and evolution of the dark zone has also been simulated with the phase-field method, using an improved approach to vacancy source term parameterization. The work shows the important impact of microstructure on fuel performance.
fracture↗
Development of mechanistic, microstructure-informed BISON models for fission product-induced failure mechanisms in advanced nuclear fuels
The US continues to prioritize commercial deployment of advanced reactors—particularly those utilizing U-Zr metallic and TRISO particle fuels. Fission product-induced failure mechanisms for these systems include fuel–cladding chemical interaction in metallic fuel rods, which threatens cladding integrity, and Pd penetration in TRISO particles, which degrades SiC layer properties. Empirical models can be applied within the bounds of existing irradiation databases, but their utility is limited when considering new designs or investigating fundamental material behaviors. The Nuclear Energy Advanced Modeling and Simulation Program is therefore developing mechanistic models for these behaviors, which are expected to aid in fuel design, assist in development of failure mitigation strategies, and provide support for qualification and licensing. These efforts leverage multiscale capabilities to capture the microstructural features and processes that govern these behaviors. This talk summarizes past and ongoing efforts to develop and validate these models for the BISON fuel performance code.
FCCI↗
Lattice Structured Lightweight Structural Materials
The development of lightweight structural materials is crucial for enhancing the performance and deployment feasibility of fission batteries. This study aims to produce lightweight structural materials whose strength-to-weight ratios exceed those of current widely used structural materials. To achieve this, advanced modeling and simulation tools were employed to design lattice structures with different lattice parameters and different lattice types. A process was successfully developed for transforming lattice-structured models into Multiphysics Object Oriented Simulation Environment (MOOSE) inputs. Finite element modeling (FEM) was used to simulate the uniaxial tensile testing of the lattice-structured parts to investigate the stress distribution at a given displacement. The modeling results showed that the lattice-structured sample displayed a lower Young’s modulus in comparison to the solid material; the increase in solid shell thickness and blend radius enhances the mechanical performance; and the effect of unit cell size on macro scale stress is minimal. Tensile testing was conducted on the solid and lattice-structured materials fabricated by laser powder bed fusion (LPBF) additive manufacturing. The experimental results agreed well with the model prediction. The approach of using modeling as a guiding tool for preliminary material design can significantly save time and cost for new material development.
lightweight material↗
Scientific/Technical Report for Framework for Modeling and Simulation of Security Systems in Nuclear Facilities
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Modeling, Simulation, Advanced and Small Reactor, ↗