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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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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Progress toward bridging from atomistic to continuum modeling to predict nuclear waste glass dissolution.

This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers, classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

Progress Report on Development of Intermediate Fidelity Full Assembly Analysis Methods

While high fidelity modeling capabilities for various physics phenomena are being pursued under advanced modeling and simulation initiatives under the DOE Office of Nuclear Energy, they generally rely on high-performance computation facilities and are too expensive to be used for parameter-space exploration or design analysis. One-dimensional system codes have been used for a long time and have reached a degree of maturity, but limit their validity to specific applications. Thus, an intermediate fidelity (IF) modeling method is being pursued in this work for a fast-running, modest-fidelity, whole-core transient analyses capability. The new approach is essential for design scoping and engineering analyses and could lead to improvements in the design of the new generations of reactors and to the reduction of uncertainties in safety analysis. This report summarizes the initial effort on the development of the intermediate-fidelity full assembly modeling method. The requirements and the desired merits of the IF approach have been defined. A three-dimensional momentum source model has been developed to model the anisotropic flow in the wire-wrapped rod bundle without the need to resolve the geometric details. It has been confirmed that the momentum source model works well if its affecting region is accurately imposed. The validity of the model is further verified by mesh and parameter sensitivity studies. The developed momentum source model, in principle, can be applied to any wire-wrapped bundle geometries and any flow regimes; while the modeling strategy can be applied to other conditions with complex or distorted geometry, such as flow in blocked channels.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Scoping analysis of the Advanced Test Reactor using SN2ND

A detailed set of calculations was carried out for the Advanced Test Reactor (ATR) using the SN2ND solver of the UNIC code which is part of the SHARP multi-physics code being developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in DOE-NE. The primary motivation of this work is to assess whether high fidelity deterministic transport codes can tackle coupled dynamics simulations of the ATR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

NEAMS VLTS project :

The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Very Long Term Storage (VLTS) Project is to develop a simple, benchmark model that describes the performance of Zry4 d-hydrides in cladding, under conditions of long-term storage of used fuel. This model will be used to further explore the requirements of hydride modeling for used fuel storage and transport. It is expected that this model will be further developed as its weaknesses are understood, and as a basis of comparison as the Used Fuel Disposition (UFD) Campaign explores more comprehensive, multiscale approaches. Cladding hydride processes, a thermal model, a hydride model API, and the initial implementation of the J2Fiber hydride model is documented in this report.

Hansen, Glen A.↗
DOE OSTI2013

Study of Air Ingress Across the Duct During the Accident Conditions

The goal of this project is to study the fundamental physical phenomena associated with air ingress in very high temperature reactors (VHTRs). Air ingress may occur due to a rupture of primary piping and a subsequent breach in the primary pressure boundary in helium-cooled and graphite-moderated VHTRs. Significant air ingress is a concern because it introduces potential to expose the fuel, graphite support rods, and core to a risk of severe graphite oxidation. Two of the most probable air ingress scenarios involve rupture of a control rod or fuel access standpipe, and rupture in the main coolant pipe on the lower part of the reactor pressure vessel. Therefore, establishing a fundamental understanding of air ingress phenomena is critical in order to rationally evaluate safety of existing VHTRs and develop new designs that minimize these risks. But despite this importance, progress toward development these predictive capabilities has been slowed by the complex nature of the underlying phenomena. The combination of inter-diffusion among multiple species, molecular diffusion, natural convection, and complex geometries, as well as the multiple chemical reactions involved, impose significant roadblocks to both modeling and experiment design. The project team will employ a coordinated experimental and computational effort that will help gain a deeper understanding of multiphased air ingress phenomena. This project will enhance advanced modeling and simulation methods, enabling calculation of nuclear power plant transients and accident scenarios with a high degree of confidence. The following are the project tasks: Perform particle image velocimetry measurement of multiphase air ingresses; and, Perform computational fluid dynamics analysis of air ingress phenomena.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Implementation of Stochastic Polynomials Approach in the RAVEN Code

RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, has been tasked to provide the necessary software and algorithms to enable the application of the conceptual framework developed by the Risk Informed Safety Margin Characterization (RISMC) [1] path. RISMC is one of the paths defined under the Light Water Reactor Sustainability (LWRS) DOE program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Continued Research for Improvement of PROTEUS-SN

Over the past several years, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program of U.S. DOE has focused on developing a neutronics component as part of a larger dynamics product meant to analyze both existing and proposed nuclear reactor systems. The goal is to reduce the uncertainties and biases in reactor design activities by providing enhanced prediction capabilities. As part of the SHARP program, we have invested considerable effort into creating the PROTEUS-SN code. The PROTEUS-SN solver was intended to treat conventional homogenized assembly to explicit geometry schemes for time dependent analysis with coupled thermal-hydraulics and structural mechanics.

Smith, M. A.↗
DOE OSTI2015

Assessment of MARMOT: A Mesoscale Fuel Performance Code

MARMOT is the mesoscale fuel performance code under development as part of the US DOE Nuclear Energy Advanced Modeling and Simulation Program. In this report, we provide a high level summary of MARMOT, its capabilities, and its current state of validation. The purpose of MARMOT is to predict the coevolution of microstructure and material properties of nuclear fuel and cladding. It accomplished this using the phase field method coupled to solid mechanics and heat conduction. MARMOT is based on the Multiphysics Object-Oriented Simulation Environment (MOOSE), and much of its basic capability in the areas of the phase field method, mechanics, and heat conduction come directly from MOOSE modules. However, additional capability specific to fuel and cladding is available in MARMOT. While some validation of MARMOT has been completed in the areas of fission gas behavior and grain growth, much more validation needs to be conducted. However, new mesoscale data needs to be obtained in order to complete this validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

An Update on NiCE Support for BISON

The Nuclear Energy Advanced Modeling and Simulation program (NEAMS) from the Department of Energy s Office of Nuclear Energy has funded the development of a modeling and simulation workflow environment to support the various codes in its nuclear energy scientific computing toolkit. This NEAMS Integrated Computational Environment (NiCE) provides extensible tools and services that enable efficient code execution, input generation, pre-processing visualizations, and post-simulation data analysis and visualization for a large portion of the NEAMS Toolkit. A strong focus for the NiCE development team throughout FY 2015 has been support for the Multiphysics Object Oriented Simulation Environment (MOOSE) and the NEAMS nuclear fuel performance modeling application built on that environment, BISON. There is a strong desire in the program to enable and facilitate the use of BISON throughout nuclear energy research and industry. A primary result of this desire is the need for strong support for BISON in NiCE. This report will detail improvements to NiCE support for BISON. We will present a new and improved interface for interacting with BISON simulations in a variety of ways: (1) improved input model generation, (2) embedded mesh and solution data visualizations, and (3) local and remote BISON simulation launch. We will also show how NiCE has been extended to provide support for BISON code development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Supplying materials needed for grain growth characterizations of nano-grained UO 2

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL) and aims at providing experimental data for the validation of the mesoscale simulation code MARMOT. MARMOT is a mesoscale multiphysics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. It is an important component of the Moose-Bison-Marmot (MBM) code suite that has been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. In order to ensure the accuracy of the microstructure based materials models being developed within the MARMOT code, extensive validation efforts must be carried out. In this report, we summarize our preliminary synchrotron radiation experiments at APS to determine the grain size of nanograin UO 2 . The methodology and experimental setup developed in this experiment can directly apply to the proposed in-situ grain growth measurements. The investigation of the grain growth kinetics was conducted based on isothermal annealing and grain growth characterization as functions of duration and temperature. The kinetic parameters such as activation energy for grain growth for UO 2 with different stoichiometry are obtained and compared with molecular dynamics (MD) simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Synchrotron characterization of nanograined UO 2 grain growth

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL) and aims at providing experimental data for the validation of the mesoscale simulation code MARMOT. MARMOT is a mesoscale multiphysics code that predicts the coevolution of microstructure and properties within reactor fuel during its lifetime in the reactor. It is an important component of the Moose-Bison-Marmot (MBM) code suite that has been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. In order to ensure the accuracy of the microstructure based materials models being developed within the MARMOT code, extensive validation efforts must be carried out. In this report, we summarize our preliminary synchrotron radiation experiments at APS to determine the grain size of nanograin UO 2 . The methodology and experimental setup developed in this experiment can directly apply to the proposed in-situ grain growth measurements. The investigation of the grain growth kinetics was conducted based on isothermal annealing and grain growth characterization as functions of duration and temperature. The kinetic parameters such as activation energy for grain growth for UO 2 with different stoichiometry are obtained and compared with molecular dynamics (MD) simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

FASTGRASS implementation in BISON and Fission gas behavior characterization in UO 2 and connection to validating MARMOT

This activity is supported by the US Nuclear Energy Advanced Modeling and Simulation (NEAMS) Fuels Product Line (FPL). Two major accomplishments in FY 15 are summarized in this report: (1) implementation of the FASTGRASS module in the BISON code; and (2) a Xe implantation experiment for large-grained UO 2 . Both BISON AND MARMOT codes have been developed by Idaho National Laboratory (INL) to enable next generation fuel performance modeling capability as part of the NEAMS Program FPL. To contribute to the development of the Moose-Bison-Marmot (MBM) code suite, we have implemented the FASTGRASS fission gas model as a module in the BISON code. Based on rate theory formulations, the coupled FASTGRASS module in BISON is capable of modeling LWR oxide fuel fission gas behavior and fission gas release. In addition, we conducted a Xe implantation experiment at the Argonne Tandem Linac Accelerator System (ATLAS) in order to produce the needed UO 2 samples with desired bubble morphology. With these samples, further experiments to study the fission gas diffusivity are planned to provide validation data for the Fission Gas Release Model in MARMOT codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Sensitivity Analysis of OECD Benchmark Tests in BISON

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on sensitivity analysis of a fuels performance benchmark problem. The benchmark problem was defined by the Uncertainty Analysis in Modeling working group of the Nuclear Science Committee, part of the Nuclear Energy Agency of the Organization for Economic Cooperation and Development (OECD ). The benchmark problem involv ed steady - state behavior of a fuel pin in a Pressurized Water Reactor (PWR). The problem was created in the BISON Fuels Performance code. Dakota was used to generate and analyze 300 samples of 17 input parameters defining core boundary conditions, manuf acturing tolerances , and fuel properties. There were 24 responses of interest, including fuel centerline temperatures at a variety of locations and burnup levels, fission gas released, axial elongation of the fuel pin, etc. Pearson and Spearman correlatio n coefficients and Sobol' variance - based indices were used to perform the sensitivity analysis. This report summarizes the process and presents results from this study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activaties are currently ongoing for coupling RAVEN with software such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Results and Analysis of the Research and Development Work Scope Request for Information (DE-SOL-0008246)

The Department of Energy (DOE) Office of Nuclear Energy (NE) released a request for information (RFI) (DE-SOL-0008246) for “University, National Laboratory, Industry and International Input to the Office of Nuclear Energy’s Competitive Research and Development Work Scope Development” on April 13, 2015. DOE-NE solicited information for work scopes for the four main program areas as well as any others suggested by the community. The RFI proposal period closed on June 19, 2015. From the 124 responses, 238 individual work scopes were extracted. Thirty-three were associated with a DOE national laboratory, including Argonne National Laboratory (ANL), Brookhaven National Laboratory (BNL), Idaho National Laboratory (INL), Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL). Thirty US universities submitted proposals as well as ten industrial/commercial institutions. Four major R&D areas emerged from the submissions, appearing in more than 15% of the proposed work scopes. These were: nuclear fuel studies, safety and risk analysis, nuclear systems analysis and design and advanced instrumentation and controls. Structural materials for nuclear power plants, used nuclear fuel disposition and various types of systems analysis were also popular, each appearing in more than 10% of the proposals. Nuclear Energy Enabling Technologies (NEET) was the most popular program area with 42% of the proposals referencing the NEET-CTD program. The order of the remaining programs was Fuel Cycle Technologies (FC) at 34%, Nuclear Energy Advanced Modeling and Simulation (NEAMS) at 29% and Reactor Concepts at 17%.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with software such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focusing on the input structure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Dakota Uncertainty Quantification Methods Applied to the CFD code Nek5000

This report presents the state of advancement of a Nuclear Energy Advanced Modeling and Simulation (NEAMS) project to characterize the uncertainty of the computational fluid dynamics (CFD) code Nek5000 using the Dakota package for flows encountered in the nuclear engineering industry. Nek5000 is a high-order spectral element CFD code developed at Argonne National Laboratory for high-resolution spectral-filtered large eddy simulations (LESs) and unsteady Reynolds-averaged Navier-Stokes (URANS) simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗