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At least 793 records · Page 44

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↗

An Experimental and Modeling Study of NO x -CO Formation in High Hydrogen Content (HHC) Fuels Combustion in Gas Turbine Applications

Species concentration measurements specifically those associated with NO x can act as important validation targets for developing kinetic models to predict NO x emissions under syngas as well as natural gas combustion accurately. In this collaborative research effort that included both experimental measurements, model development and simulations a comprehensive kinetic model and a multiphysics computational fluid dynamics platform has been developed and validated against the experimental data available in the literature as well as those acquired under this project. The experimental data provide the necessary NO x and speciation data for conditions relevant to gas turbine operations but are not readily available in the literature. The comprehensive chemical kinetic model consists of CO/H 2 /NO x oxidation with the full implementation of NO x evolution pathways, including thermal, prompt, N 2 O and NNH paths. The experiments conducted included NO x perturbed oxidation of natural gas at elevated pressure in laminar flow reactor and syngas/air combustion in a McKenna Burner – Flow Tube setup. A wide range of equivalence ratio, operating pressure as well as H 2 /CO ratio (for syngas only) was investigated. Temperature and NO x concentrations were measured in the flame and post-combustion zone. Experiments were also conducted for seeded syngas where trace hydrocarbon was introduced. The proposed model has been extensively tested. Predictions from the model are compared against multiple experimental datasets over a wide range of venues and operating conditions. The experimental venues include shock tube, plug flow reactor, and stirred reactor experiments that cover pressures from 1 to 100 bar and equivalence ratios from 0.5 to 1.5. In general, the overall model predictions are in good agreement with global combustion targets, such as ignition delay time, as well as with more detailed measurements from flow reactors and stirred reactors. Simulations are conducted for a wide range of reacting mixtures (H 2 /O 2 /N 2 , CO/H 2 /O 2 and CO/H 2 O/O 2 /N 2 ) with initial NO and NO 2 perturbations to consider exhaust gas recirculation (EGR) conditions.

08 HYDROGEN↗

Low-order multiphysics coupling techniques for nuclear reactor applications

The accurate modeling and simulation of nuclear reactor designs depends greatly on the ability to couple differing sets of physics together. Current coupling techniques most often use a fixed-point, or Picard, iteration scheme in which each set of physics is solved separately, and the resulting solutions are passed between each solver. In the work presented here, two different coupling techniques are investigated: a Jacobian-Free Newton-Krylov (JFNK) approach and a new methodology called Coarse Mesh Finite Difference Coupling (CMFD-Coupling). In this work, both techniques were applied to the low-order CMFD system of equations. This allows for the multiphysics feedback effects to be captured on the low-order system without having to perform a neutron transport solve. The JFNK and CMFD-Coupling approaches were implemented in the MPACT neutron transport code, which is being developed for the Consortium for Advanced Simulation of Light Water Reactors (CASL). These methods were tested on a wide range of practical reactor physics problems, from a single 3D fuel pin to a massively parallel 3D full core problem. When coupled neutronics-thermal hydraulics problems were investigated with both JFNK and CMFD-Coupling, it was concluded that CMFD-Coupling outperformed JFNK in terms of both accuracy and runtime for every problem. When applied to large full core problems with multiple sources of strong feedback enabled, CMFD-Coupling reduced the overall number of transport sweeps required for convergence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimental studies of Micro- and Nano-grained UO 2 : Grain Growth Behavior, Sufrace Morphology, and Fracture Toughness

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 the experimental efforts in FY16 including the following important experiments: (1) in-situ grain growth measurement of nano-grained UO 2 ; (2) investigation of surface morphology in micrograined UO 2 ; (3) Nano-indentation experiments on nano- and micro-grained UO 2 . The highlight of this year is: we have successfully demonstrated our capability to in-situ measure grain size development while maintaining the stoichiometry of nano-grained UO 2 materials; the experiment is, for the first time, using synchrotron X-ray diffraction to in-situ measure grain growth behavior of UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Bridging scales in multiphysics VCSEL modeling

On our way to develop a comprehensive simulator of vertical-cavity surface-emitting lasers including carrier transport, optical modes, light-matter interaction and heat conduction, we address some critical multiscale aspects of the adopted coupling strategy. The quantum corrections to the semiclassical carrier transport framework are the bridge from nanometer to micrometer scales. In this paper, such corrections are shown to be fundamental in view of predicting the mode competition ruling VCSEL operation. Nevertheless, they can generate unforeseen features such as swirling electron flows in the active region, which are discussed here in detail. The simulation approach has been finally tested through a successful comparison with a large set of experimental results.

42 ENGINEERING↗

High frequency beam oscillation keyhole dynamics in laser melting revealed by in-situ x-ray imaging

The metal additive manufacturing industry is actively developing instruments and strategies to enable higher productivity, optimal build quality, and controllable as-built microstructure. A beam controlling technique, laser oscillation has shown potential in all these aspects in laser welding; however, few attempts have been made to understand the underlying physics of the oscillating keyholes/melt pools which are the prerequisites for these strategies to become a useful tool for laser-based additive manufacturing processes. Here, to address this gap, we utilized a synchrotron-based X-ray operando technique to image the dynamic keyhole oscillation in Ti-6Al-4V using a miniature powder bed fusion setup. We found good agreement between the experimental observations and simulations performed with a validated Lattice Boltzmann multiphysics model. The study revealed the continuous and periodic fluctuations in the characteristic keyhole parameters that are unique to the oscillating laser beam processing and responsible for the chevron pattern formation at solidification. In particular, despite the intrinsic longer-range fluctuation, the oscillating technique displayed potential for reducing keyhole instability, mitigating porosity formation, and altering surface topology. These insights on the oscillating keyhole dynamics can be useful for the future development and application of this technique.

36 MATERIALS SCIENCE↗

Modeling physical vapor deposition of energetic materials

Morphology and microstructure of organic explosive films formed using physical vapor deposition (PVD) processes strongly depends on local surface temperature during deposition. Currently, there is no accurate means of quantifying the local surface temperature during PVD processes in the deposition chambers. This study focuses on using a multiphysics computational fluid dynamics tool, STARCCM+, to simulate pentaerythritol tetranitrate (PETN) deposition. The PETN vapor and solid phase were simulated using the volume of fluid method and its deposition in the vacuum chamber on spinning silicon wafers was modeled. The model also included the spinning copper cooling block where the wafers are placed along with the chiller operating with forced convection refrigerant. Implicit time-dependent simulations in two- and three-dimensional were performed to derive insights in the governing physics for PETN thin film formation. PETN is deposited at the rate of 14 nm/s at 142.9 °C on a wafer with an initial temperature of 22 °C. The deposition of PETN on the wafers was calculated at an assumed heat transfer coefficient (HTC) of 400 W/m 2 K. This HTC proved to be the most sensitive parameter in determining the local surface temperature during deposition. Previous experimental work found noticeable microstructural changes with 0.5 mm fused silica wafers in place of silicon during the PETN deposition. This work showed that fused silica slows initial wafer cool down and results in ~10 °C difference for the surface temperature at 500 μm PETN film thickness. It was also found that the deposition surface temperature is insensitive to the cooling power of the copper block due to the copper block's very large heat capacity and thermal conductivity relative to the heat input from the PVD process. Future work should incorporate the addition of local stress during PETN deposition. Lastly, based on simulation results, it is also recommended to investigate the impact of wafer surface energy on the PETN microstructure and morphology formation.

36 MATERIALS SCIENCE↗

A Scalable Multigrid Reduction Framework for Multiphase Poromechanics of Heterogeneous Media

Simulation of multiphase poromechanics involves solving a multiphysics problem in which multiphase flow and transport are tightly coupled with the porous medium deformation. To capture this dynamic interplay, fully implicit methods, also known as monolithic approaches, are usually preferred. The main bottleneck of a monolithic approach is that it requires solution of large linear systems that result from the discretization and linearization of the governing balance equations. Because such systems are nonsymmetric, indefinite, and highly ill-conditioned, preconditioning is critical for fast convergence. Recently, most efforts in designing efficient preconditioners for multiphase poromechanics have been dominated by physics-based strategies. Current state-of-the-art “black-box” solvers such as algebraic multigrid (AMG) are ineffective because they cannot effectively capture the strong coupling between the mechanics and the flow subproblems, as well as the coupling inherent in the multiphase flow and transport process. In this work, we develop an algebraic framework based on multigrid reduction (MGR) that is suited for tightly coupled systems of PDEs. Using this framework, the decoupling between the equations is done algebraically through defining appropriate interpolation and restriction operators. One can then employ existing solvers for each of the decoupled blocks or design a new solver based on knowledge of the physics. We demonstrate the applicability of our framework when used as a “black-box” solver for multiphase poromechanics. Here, we show that the framework is flexible to accommodate a wide range of scenarios, as well as efficient and scalable for large problems.

97 MATHEMATICS AND COMPUTING↗

Workshop on Software Productivity for Extreme-scale Science, January 13-14, 2014, Hilton Hotel, Rockville, MD

While emerging extreme-scale computing systems provide unprecedented resources for scientific discovery, DOE’s scientific communities now face a crisis in extreme-scale scientific software productivity due to a powerful confluence of factors: ongoing disruptive changes in computer architectures and new frontiers in modeling, simulation, and analysis of complex multiscale and multiphysics phenomena. Research in mission-critical science and energy problems has become increasingly dependent on high-performance computing, but productivity in extreme-scale scientific application development has not kept pace. The principal issues are (1) a significant lag between extreme-scale hardware and algorithmic innovations and their effective use in applications, leading to poorly scaling codes; (2) obstacles in the combined use of independently developed software components; (3) lack of agile yet rigorous software engineering practices for high-performance computing; and (4) failure to consider the entire lifecycle of large scientific software efforts, leading to fragile, complicated application codes that are increasingly difficult to enhance.

97 MATHEMATICS AND COMPUTING↗

CTF: A modernized, production-level, thermal hydraulic solver for the solution of industry-relevant challenge problems in pressurized water reactors

CTF is a thermal hydraulic (T/H) subchannel tool that has been extensively developed over the past ten years as part of the Consortium for Advanced Simulation of Light Water Reactors (CASL) program. The code was selected early in the CASL program for support of high-impact challenge problems that were found to be relevant to the nuclear industry and its currently operating fleet of pressurized water reactors (PWRs), including issues such as departure from nucleate boiling (DNB), crud-induced power shifts (CIPSs), and reactivity-insertion accidents (RIAs). By incorporating CTF into the multiphysics Virtual Environment for Reactor Application (VERA) core simulator software developed by CASL, CTF has become the primary means of providing fluid and fuel thermal feedback, as well as T/H figure-of-merits (FOMs) in large-scale reactor simulations. With the goal of solving industry challenge problems, CASL placed great emphasis on developing high-quality, high-performance, validated software tools that offer higher fidelity than what is currently possible with current industry methods. In support of this effort, CTF was developed from a research tool into an nuclear quality assurance (NQA-1)–compliant, production-level software tool that is capable of addressing the stated challenge problems and goals of CASL. This work presents a review of the major technological achievements that were realized in developing CTF over the past decade of the CASL program and presents an overview of the code solution approach and closure models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

ORNL Design Engineering Library: Validated Thermoelectric Digital Twins

Radioisotope thermoelectric generators (RTGs) serve a crucial role in supplying thermal and electrical energy for reliable and long-duration power in remote and extreme environments. The thermal energy is provided by the decay of radioisotopes and is converted into electrical energy using the steady-state thermoelectric process by exploiting the Seebeck effect. Maintaining a thermal gradient through the material is necessary to drive current production. Modern predictive multi-physics tools are able to effectively describe the complex and strongly coupled phenomena needed for accurate model-based system engineering efforts needed to develop higher performing RTGs. Experimental validation of model simulations is essential to confirm the accuracy, reliability, and applicability of predictive multiphysics tools. Validation fosters confidence among users, helps meet regulatory requirements, and contributes to the ongoing improvement of simulation techniques, ultimately leading to better, safer, and more efficient designs and processes. Validated models can then be used as digital twins and can be interrogated to understand and quantify the performance gaps between theoretical and physical systems. These insights can be used to build higher performing systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SimELIT: A Novel GUI-Based Comprehensive Ion Trajectory Simulation Software for Mass Spectrometry

Ion trajectory simulation in mass spectrometry systems from injection to detection is technically challenging but very important for better understanding the ion dynamics in instrument development. Here, in this work, we present SimELIT (Simulator of Eulerian and Lagrangian Ion Trajectories), a novel ion trajectory simulation platform. SimELIT is built upon a suite of multiphysics solvers compiled into OpenFOAM (an open-source numerical solver library particularly used for computational mechanics), with a simple web-based graphical user interface (GUI) allowing users to define the details of OpenFOAM cases and run simulations. SimELIT is a modular program and can provide extensions of physics (e.g., gas flows, electrodynamic fields) and thus enable ion trajectory simulations from the ion source to detector. The current version (SimELIT) provides two numerical solvers for ion trajectory simulations–(1) a Lagrangian particle tracker in vacuum and (2) a Eulerian ion density solver in background gas in the presence of electric fields. Here, we describe the architecture of SimELIT, including its use of Docker and the React Framework, and demonstrate the computation of ion trajectories of multiple m/z values in a static/linear voltage drop in vacuum (across a 1 m long flight tube). Further, the drift motion of ions under 1 Torr pressure conditions in a static background (N 2 ) gas through a 20 V/cm static electric field is shown. The results produced from SimELIT were compared with SIMION and theoretical estimates. In addition, we report the computation of ion trajectories in electrodynamic fields within a planar FAIMS device operating at atmospheric pressure.

97 MATHEMATICS AND COMPUTING↗

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Modeling of Vertical Motor-driven Pump for Simulation of a Fault Signature \\ for Condition Monitoring

As part of the ongoing effort to transition from preventive maintenance strategies to condition-based maintenance strategies in nuclear power plants, there is significant reliance on using machine learning techniques. To develop a robust machine learning model that can diagnose all the fault modes of a vertical motor-driven pump, data capturing the unique signature of each fault mode is required. In practice, it is difficult to collect or capture data that captures all the fault modes from a single plant site. So to address this situation, a computational model of a vertical motor-driven pump is developed using the multipurpose finite element software COMSOL Multiphysics. The developed model is used to generate simulated data under normal operation and is compared with the vibration data collected using vibration sensors. Once the simulation model is verified under normal operating condition, simulated data for the fault mode for which minimal or no evidence is available in historical plant process data is developed. This simulated data is used to develop fault signatures to achieve robust predictive models. This paper presents modeling details and verification of the model that can used to generate data for fault modes that are not available at a plant site for condition monitoring purpose.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

COUPLED GRIFFIN AND PRONGHORN SIMULATION OF THE MOLTEN SALT FAST REACTOR (MSFR) FOR THE VIRTUAL TEST BED

The Virtual Test Bed (VTB) repository hosts a wide range of challenge problems to showcase modeling and simulation capabilities to support advanced reactor demonstration. An overview of a coupled multiphysics model for Molten Salt Reactors (MSR) is presented here. The analysis leverages MOOSE-based tools (notably Griffin and Pronghorn) for neutronic and thermal hydraulic simulation. Neutron precursor drifting capability is showcased, along with some initial turbulence models. Both steady-state and transient coupled multiphysics results for an MSR concept are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Statistical Distributions for Mesh Independent Solutions in ALEGRA

The representation of material heterogeneity (also referred to as "spatial variation") plays a key role in the material failure simulation method used in ALEGRA. ALEGRA is an arbitrary Lagrangian-Eulerian shock and multiphysics code developed at Sandia National Laboratories and contains several methods for incorporating spatial variation into simulations. A desirable property of a spatial variation method is that it should produce consistent stochastic behavior regardless of the mesh used (a property referred to as "mesh independence"). However, mesh dependence has been reported using the Weibull distribution with ALEGRA's spatial variation method. This report describes efforts towards providing additional insight into both the theory and numerical experiments investigating such mesh dependence. In particular, we have implemented a discrete minimum order statistic model with properties that are theoretically mesh independent.

36 MATERIALS SCIENCE↗

Interpretation of energy deposition data from historical operation of the transient test facility (TREAT)

The Transient Test Reactor (TREAT) at Idaho National Laboratory will resume operations in late 2017 after a 23 year hiatus while maintained in a cold standby state. Over that time period, computational power and simulation capabilities have increased substantially and now allow for new multiphysics modeling possibilities that were not practical or feasible for most of TREAT's operational history. Hence the return of TREAT to operational service provides a unique opportunity to apply state-of-the-art software and associated methods in the modeling and simulation of general three-dimensional steady state and kinetic behavior for reactor operation, and for coupling of the core power transient model to experiment simulations. However, measurements taken in previous operations were intended to predict power deposition in experimental samples, with little consideration of three-dimensional core power distributions. Hence, interpretation of data for the purpose of validation of modern methods can be challenging. For the research discussed herein, efforts are described for the process of proper interpretation of data from the most recent calibration experiments performed in the core, the M8 calibration series (M8-CAL). These measurements were taken between 1990 and 1993 using a set of fission wires and test fuel pins to estimate the power deposition that would be produced in fast reactor test fuel pins during the M8 experiment series. Because of the decision to place TREAT into a standby state in 1994, the M8 series of transients were never performed. However, potentially valuable information relevant for validation is available in the M8-CAL measurement data, if properly interpreted. This article describes the current state of the process of recovery of useful data from M8-CAL measurements and quantification of biases and uncertainties to potentially apply to the validation of multiphysics methods.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Experimentally validated multiphysics modeling of fracture induced by thermal shocks in sintered UO 2 pellets

Uranium Dioxide (UO 2 ) fuel powers almost all commercial Nuclear Power Plants (NPPs) worldwide, generating carbon-free energy and contributing to the fight against climate change. UO 2 fuel incurs damage and fractures due to large thermal gradients that develop across the fuel pellet during normal and transient operating conditions. A comprehensive understanding of the underlying mechanisms by which these processes take place is still lacking. A combined experimental and computational approach is utilized here to quantify the behavior of UO 2 fuel fracture induced by thermal shock. Here, this work introduces both (1) an experimental study to understand the fuel fracturing behavior of sintered UO 2 pellets when exposed to thermal shock, and (2) a Multiphysics phase-field fracture model capable of simulating this process. Parametric studies were conducted to evaluate the effects of uncertainties in fracture properties on the fracture behavior of UO 2 due to thermal shocking. A set of energy release rate (or equivalently fracture toughness) and contract area (the part of the fuel pellet in direct contact with the cold bath) were able to capture the overall fracture trends of the corresponding experimental data. Our combined approach presents a new method for accounting for the effects of microstructure and sample size on the energy release rate/fracture toughness. The experimental data were collected from multiple experiments that exposed UO 2 pellets to high-temperature conditions (589–676 °C) followed by a quench in sub-zero water. This work demonstrates that joint experimental and computational efforts are able to advance the understanding of thermal fracture in the primary fuel source for existing and future NPPs.

36 MATERIALS SCIENCE↗