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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Spatially Continuous Depletion Algorithm for Monte Carlo Simulations

To correctly predict reactor behavior during cycle operations, the evolution of nuclide number densities throughout the core must be accurately modeled. The time-varying spatial distribution of nuclide number densities is typically resolved by discretizing the Monte Carlo geometry into smaller cells over which number densities are assumed to be spatially invariant. The nuclide number densities in these smaller cells are integrated through time using reaction rate tallies on the same discretized geometry. However, detailed distributions of nuclide number densities in a full three dimensional simulation can require a prohibitive amount of tallies, and the spatial discretization of the base geometry makes coupling to external multi-physics tools difficult. In this paper a method for solving for spatially continuous number density distributions during depletion calculations will be described. The spatially continuous number densities can be used in the transport method proposed by Brown and Martin which allows for transporting neutrons through a material with continuously varying properties such as temperature and nuclide number densities. Coupled with the ability of Functional Expansion Tallies (FETs) to represent tallied quantities as continuous functions, it is possible to both solve for and make use of spatially continuous nuclide number densities. The need for this capability was alluded to by Brown et. al., but no solution has yet been proposed. With a continuous depletion method, recent work which utilized FETs and continuous material tracking to incorporate multi-physics feedback in Monte Carlo simulations can be extended to simulations that include depletion analysis. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Dakota Uncertainty Quantification Methods Applied to the CFD code Nek5000

Predictive modeling and simulation of the performance of a nuclear reactor and its fuel is a challenging task because of the large number of coupled physical phenomena that must be addressed. In addition to this intrinsic complexity, model uncertainty must be accounted for in any analysis if the model will be used to facilitate design or operational decisions which may impact safety and performance. Rigorous, structured uncertainty analyses are performed by first characterizing the model's input uncertainties and, by propagating the uncertainty through the model in order to estimate the output's uncertainty. This paper presents the state of advancement of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) project to characterize the uncertainty of the CFD code Nek5000 using the Dakota package. Nek5000 is a high order spectral element computational fluid dynamics (CFD) code developed at Argonne National Laboratory for high resolution spectral-filtered large eddy simulations (LESs) and unsteady Reynolds averaged Navier-Stokes (RANS) simulations. The Dakota package developed at Sandia National Laboratory can be integrated with many scientific and engineering codes to facilitate efficient, effective uncertainty quantification (UQ) and sensitivity analyses. Dakota is designed to interface with external packages/codes such as Nek5000 through a script-driven interface called fork. Such interface provides maximum flexibility to the users for pre- and post-processing tasks preceding and following each function evaluation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Molten salt reactor core simulation with PROTEUS

The Nuclear Energy Advance Modeling and Simulation Program (NEAMS) of the US Department of Energy (DOE) aims to develop advanced simulation tools to aid the development of advanced nuclear technologies. The high-fidelity PROTEUS code was developed in the NEAMS program for reactor physics analysis. This paper tests the applicability of the PROTEUS code to simulate a Molten Salt Reactor (MSR). The OpenMC code based on the Monte Carlo Method was employed to generate the cross sections and to provide stochastic solutions for verification. The PROTEUS code was successfully employed to simulate the steady-state performance of an MSR represented by the ThorCon core design. The 2D lattice, 2D core, and 3D full core calculations performed by PROTEUS show good agreement with that predicted by OpenMC. Furthermore, for the nodal option within PROTEUS, the precursor drift model was also tested, and this effect resulted in a reduction of the k-eff by 300 pcm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Finite Element Based Full-Life Cyclic Stress Analysis of 316 Grade Nuclear Reactor Stainless Steel Under Constant, Variable, and Random Fatigue Loading

Although S~N curve-based approaches are widely followed for fatigue evaluation of nuclear reactor components and other safety critical structural systems, there is a chance of large uncertainty in estimated fatigue lives. This uncertainty may be reduced by using a more mechanistic approach such as physics based three-dimensional (3D) finite element (FE) methods. In a recent paper (Barua et al., 2018, ASME J. Pressure Vessel Technol., 140(1), p. 011403), a fully mechanistic fatigue modeling approach which is based on time-dependent stress–strain evolution of material over the entire fatigue life was presented. Based on this approach, FE-based cyclic stress analysis was performed on 316 nuclear grade reactor stainless steel (SS) fatigue specimens, subjected to constant, variable, and random amplitude loading, for their entire fatigue lives. The simulated results are found to be in good agreement with experimental observation. An elastic-plastic analysis of a pressurized water reactor (PWR) surge line (SL) pipe under idealistic fatigue loading condition was performed and compared with experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Using Whisper-1.1 to guide improvements to nuclear data evaluations

Along with the latest release of the general purpose Monte Carlo radiation transport code, MCNP6.2, came the first officially released version of Whisper, version 1.1, a statistical analysis code used for nuclear criticality safety (NCS) validation. The Whisper software package is primarily used to calculate the upper subcritical limit (USL) of a particular application case along with components of the margin of subcriticality (MOS). In the calculation of the MOS due to nuclear data uncertainties, Whisper uses the generalized linear-least-squares (GLLS) approach to obtain adjusted nuclear data uncertainties which are then propagated to estimate the nuclear data uncertainties in the k{sub eff} of the application. Due to the fact that Whisper contains the simulated and measured k{sub eff} values for over 1100 benchmarks, nuclear data sensitivity profiles for each benchmark along with the nuclear data covariance matrices, all of which are used in the GLLS method, it is possible to easily utilize these data available to help guide improvements to nuclear data evaluations. In the present work, the Whisper data and the GLLS method are used together to suggest an adjusted nuclear data cross section evaluation specifically for {sup 233}U such that the agreement between the calculated and experimental k{sub eff} measurements of the relevant benchmarks are improved. With this adjusted nuclear data available, feedback to the theoretical and experimental nuclear data community is provided. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Density functional theory calculations of defect and fission gas properties in U-Si fuels

Accident tolerant fuels (ATF) are being developed in response to the Fukushima Daiichi accident in Japan. One of the options being pursued is U-Si fuels, such as the U 3 Si 2 and U 3 Si 5 compounds, which benefit from high thermal conductivity (metallic) compared to the UO 2 fuel (insulator or semi-conductor) used in current Light Water Reactors (LWRs). The U-Si fuels also have higher fissile density. In order to perform meaningful engineering scale nuclear fuel performance simulations, the material properties of the fuel, including the response to irradiation environments, must be known. Unfortunately, the data available for U-Si fuels are rather limited, in particular for the temperature range where LWRs would operate. The ATF HIP is using multi-scale modeling and simulations to address this knowledge gap. The present study investigates point defect and fission gas properties in U 3 Si 2 , which is one of the main fuel candidates, using density functional theory (DFT) calculations. Based on a few assumption regarding entropy contributions, defect and fission diffusivities are predicted. Even though uranium silicides have been shown to amorphize easily at low temperature, we assume that U 3 Si 2 remains crystalline under the conditions expected in Light Water Reactors (LWRs). The temperature and dose where amorphization occurs has not yet been well established.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

A Variational Nodal Approach to 2D/1D Pin Resolved Neutron Transport: I Diffusion Theory

The variational nodal method (VNM) as implemented in the VARIANT code has been widely employed to fast reactor cores, but much less so for thermal reactors. In what follows we report the initial phase of development of the PANX code (Purdue - Argonne - Northwestern - Xi'an) for three-dimensional pin resolved PWR transport calculations. In two dimensions, prototype modifications of VARIANT using finite elements to obtain heterogeneous nodes and quasi-reflected interface conditions to reduce the high angular-order interface conditions, have been successfully employed to the 2D C5G7 benchmark. In three dimensions, however, the polynomial interface conditions employed in VARIANT smear fuel and coolant at each axial interface, leading to lack of convergence as the axial mesh is refined. This problem is also encountered in the 2D/1D approximations in MOC based methods. The intent of this work is to eliminate these interface homogenization effects from VNM calculations. For clarity, in this work we examine these phenomena in diffusion theory. The next stage of development will incorporate spherical harmonic trial functions to achieve more accurate transport solutions. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Comparisons between a priori Uncertainty Quantification and Calculation/Measurement Discrepancies Applied to the MERCI UO{sub 2} Fuel Rod Decay Heat Experiment

In 2008, an UO{sub 2} fuel rod was irradiated up to ∼ 3.5 GWd/tHL in the CEA/Saclay research reactor Osiris through the MERCI experiment. Some rod's pellets were analysed. Experimental results were obtained: - fuel rod decay heat measurement by calorimetry (cooling times from 27 minutes to 42 days), - evaluation of the amounts of some nuclei (U, Pu, Cs, Nd...) by isotopic dilution mass spectrometry, - nuclide activities. Comparison of type (C - M)/M where C is the calculated decay heat and M the experimentally measured decay heat was reported in reference. Neutronics flux was computed by CEA TRIPOLI-4 Monte-Carlo or APOLLO2 deterministic transport code system. Irradiation and cooling phases were simulated with CEA DARWIN/PEPIN2 code system. Good agreements were globally shown between numerical simulation results and experimental measurements on total decay heat. Uncertainty propagation in this previous work was established from Rebah's studies. These last years, within the framework of supports to its industrial partners EDF and Areva, the CEA/DEN has implemented two different approaches to propagate nuclear data uncertainties to depletion code outputs. A direct forward deterministic perturbation method using sensitivity profiles was implemented in the French industrial depletion code system DARWIN/PEPIN2. Meanwhile, a propagation based on Monte Carlo correlated sampling was achieved using the CEA uncertainty platform URANIE and the new generation depletion code MENDEL. Both methods will be described in this article. Uncertainties on nuclear data (independent fission yields, multigroup microscopic cross sections, radioactive decay constants, radioactive decay branching ratio and radioactive decay energies) are propagated to decay heat and isotopic concentrations. To match MERCI first study, flux computation is realized by APOLLO2. Furthermore, uncertainty quantification (UQ) is re-evaluated by both DARWIN/PEPIN2 and MENDEL codes. It is an important stage in the process of validating both depletion codes with their respective data library. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development of Predictive Models for Advanced Reactor Autonomous Control

Advanced reactor designs including microreactors and small modular reactors will contribute to the clean production of cheap energy, and autonomous control for advanced reactors is an appealing option for reducing cost. However, there is a lack of industry experience applying autonomous control for advanced nuclear reactors. To accelerate the development and industry acceptance of autonomous control software for nuclear reactors, we aim to demonstrate autonomous control of the Purdue University research reactor (PUR-1) using INL-developed model predictive control (MPC) methods. To prepare for this demonstration, data-driven predictive models based on process data collected from PUR-1 have been developed and integrated with MPC and used to control a physics-based model of PUR-1. A data-driven dynamics model and a gated recurrent unit (GRU) network were both trained on process data from PUR-1. The dynamics model was shown to effectively control the reactor model with MPC when provided reactivity as a control variable but failed to control the model through the control rod positions. The GRU network produced more accurate predictions than the dynamics model when evaluated on operational data, and future work will include the evaluation of the GRU network in the controller.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design

This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

MCNP6.3 Workshop [Slides]

This workshop presentation revisits several new features of MCNP6.2 and tools. Additionally, it offers a preview of the new features and improvements included in the upcoming MCNP6.3 code release that are most relevant to the nuclear radiation protection and shielding communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Applicable Experiment Selection [Slides]

This presentation discusses the UNF-ST&DARDS which performs many analyses for as-loaded SNF canisters, including criticality safety, shielding, thermal-hydraulic, and containment. It also discusses the experiment selection based on c k assessment of similarity and that the c k value of 0.8 or greater considered applicable for validation. 11 PWR SNF canisters (MPC-32) are used in this work. 1 model represents a failed fuel assembly as fresh, per the design basis and the remaining 10 models represent all 32 assemblies with depleted fuel. In conclusion, critical experiment selection can be performed with S/U techniques for as-loaded canisters in UNF-ST&DARDS. Sufficient benchmark experiments exist to support validation and additional MOX experiments that are a good match for commercial SNF would be a benefit to provide independent data. The presentations states that S/U techniques identify different pools of experiments for different systems and that the process is amenable to automation within UNF-ST&DARDS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Study of Whisper Statistics for Criticality Safety Code Validation

Whisper is computational software designed to assist with validation studies with the Monte Carlo particle transport package MCNP. Historical approaches rely on expert based judgment to select benchmarks while Whisper uses sensitivity/uncertainty (S/U) methods to select relevant benchmarks to a particular application model. Whisper will also derive a calculational margin and margin of subcriticality (MOS) that may be used to generate an upper subcritical limit (USL) for a particular application model. Whisper finds benchmark experiments whose isotope sensitivity profiles align best with the MCNP model in question, and assign a correlation coefficient ('ck' in Whisper parlance) to each selected benchmark as a measure of how closely those profiles agree. When ck values are high, there is less uncertainty between model and benchmarks and a higher USL is possible, relative to cases when ck values are low. The default Whisper settings recommends a 100,000 particles per cycle run for 500 active cycles, resulting in 50 M active neutron histories per application run. This is computationally intensive and may not be necessary to produce accurate results. A Whisper statistical study was done varying the neutron histories per cycle from 10,000 to the default 100,000. A lower number of neutron histories will allow Whisper to be used on low memory systems such as laptops. The intent of this paper is to present the changes in the Whisper results as the number of neutrons histories run is varied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

NEAMS TH CRAB

The MOOSE framework is a library designed to make it straightforward for physicists and engineers to model partial differential equations using finite element and finite volume methods. Finite elements have been a part of the framework library since MOOSE's inception over a decade ago. Initial finite volume capability, however, was added only as recently as May of 2020. Since that time, significant work has been conducted to develop fluid modeling capability based on the finite volume method. Much of this work has taken place in MOOSE's navier_stokes module and in the NEAMS program's coarse mesh CFD code Pronghorn. We report here on development in MOOSE and Pronghorn of incompressible, porous incompressible, and weakly compressible finite volume simulation capabilities and their application to modeling of MSR and FHR advanced reactor concepts.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

A time-dependent neutron transport method of characteristics formulation with time derivative propagation

A new time-dependent Method of Characteristics (MOC) formulation for nuclear reactor kinetics was developed utilizing angular flux time-derivative propagation. This method avoids the requirement of storing the angular flux at previous points in time to represent a discretized time derivative; instead, an equation for the angular flux time derivative along 1D spatial characteristics is derived and solved concurrently with the 1D transport characteristic equation. This approach allows the angular flux time derivative to be recast principally in terms of the neutron source time derivatives, which are approximated to high-order accuracy using the backward differentiation formula (BDF). This approach, called Source Derivative Propagation (SDP), drastically reduces the memory requirements of time-dependent MOC relative to methods that require storing the angular flux. An SDP method was developed for 2D and 3D applications and implemented in the computer code DeCART in 2D. DeCART was used to model two reactor transient benchmarks: a modified TWIGL problem and a C5G7 transient. The SDP method accurately and efficiently replicated the solution of the conventional time-dependent MOC method using two orders of magnitude less memory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Depletion-driven thermochemistry of molten salt reactors: review, method, and analysis

Molten salt reactors (MSRs) are innovative advanced nuclear reactors that utilize nuclear fuel by dissolving it in a high-temperature liquid salt. This unique feature differentiates MSRs from other types of reactors and allows for enhanced safety and economic performance. The liquid fuel also entails several multiphysics effects that can complicate reactor design and operation. One primary effect termed here as depletion-driven thermochemistry is a driving force in altering the multiphysics behavior of the reactor. Essentially, depletion-driven thermochemistry is the effect that fuel depletion has on changing the chemical redox potential of the fuel salt over time. As the fuel is consumed, the redox potential shifts toward a more oxidizing state. Without active control, the changing chemistry due to depletion increases corrosion thereby limiting reactor component lifetimes. Additionally, the changing redox potential of the fuel salt alters the vapor pressures of chemical species dissolved in the fuel salt. Changing vapor pressures of species in the fuel salt is an important parameter to understand when off-gassing volatile species during normal reactor operation, and for source term characterization during accident scenario transients. The present work represents a fundamental step toward modeling and coupling the driving physics (i.e., neutronics and chemistry) involved in altering the redox potential in an MSR. Here, the neutronic code Griffin models the depletion of the fuel-salt system, while the chemical equilibrium code Thermochimica calculates the thermochemical state of the isotopic inventory, using the Molten Salt Thermodynamic Database - Thermochemical (MSTDB-TC). These two codes are tightly coupled to predict the impact of fuel depletion in altering the chemistry in MSR systems. Redox potential control methods are discussed and can be modeled using this multiphysics approach. The vapor pressures of chemical species that could be extracted to an off-gas system, as determined by the reactor’s thermochemical state, are examined. The neutronics-chemistry coupling developed in this work is expected to have potential application for analyzing corrosion, source term evolution, and material safeguards in MSR systems. Lastly, suggestions for areas of further improvements of the models to expand these capabilities by incorporating other coupled physics effects is provided.

Walker, Samuel A.↗
DOE OSTI2022

Accomplishments of Thermal Neutron Scattering Research at North Carolina State University [Slides]

Thermal neutron scattering law (TSL) data evaluations have been completed and contributed to ENDF. New evaluations are underway. FLASSH is developing as a modern platform for thermal neutron data analysis featuring an enhanced user experience and low learning overhead. Advanced TSL techniques in combination with Doppler analysis have been developed, which were incorporated into FLASSH. ML/DL NeTS method development has been initiated. Experimental capabilities for validation have been developed at the PULSTAR reactor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Adjusted Graphite Thermal Scattering Data Applied to Fluoride-Salt-Cooled Reactors

Thermal scattering data is a key component of fission reactor simulation. While most materials can be reasonably modeled with a free gas approximation, the moderators in thermal systems require a more rigorous treatment to sufficiently capture their specific neutron interaction physics. Graphite does not typically feature as a principle moderator in power reactors in service today, but remains an attractive prospect for a number of new reactor concepts currently in development. In comparison to light water, a material nearly ubiquitous in thermal reactors, graphite offers a better neutron economy by way of a small absorption cross section, high thermodynamic stability and can be incorporated into the structure of the core itself. Graphite in its purest form is a crystalline material composed of stacked layers of graphene, a hexagonal planar lattice of carbon atoms. In-plane, each carbon atom is covalently bonded to 3 neighbouring carbon atoms, creating a strong bond, while between planes only a weak van der Waals force exists. Pure graphite has a density of 2.26 g/cm{sup 3}. However, reactor-grade contains a significant amount of carbon binder, leading to a porous bulk medium with randomly oriented micro crystals. Densities of 1.5 - 1.9 g/cm{sup 3} are typical for reactor-grade graphite, corresponding to porosities on the order of 10-30%. This deviation from pure crystalline graphite should be accounted for in the thermal scattering data. When an incident neutron is in or near the thermal region, its de Broglie wavelength is the same order as the molecular bond lengths, leading to elastic scattering. At similar energies, the dynamics of the moderator lattice (in the case of solid moderators) can cause inelastic scattering. For these moderators, special cross sections should be calculated and used in reactor simulations. To generate this thermal scattering data, parameters pertaining to the properties and structure of the material in question are fed into a nuclear data processing code, such as NJOY. Within NJOY is a module called LEAPR which is used to generate the thermal scattering law S(α,β), which is in turn is fed into another module THERMR which is used to generate thermal cross sections that factor in the molecular-scale scattering phenomena. The core of the thermal scattering law is the phonon spectrum ρ(β) which describes the modes of excitation of the material lattice. An investigation into the phonon frequency spectrum was conducted at North Carolina State University (NCSU) for reactor-grade graphite which accounts for porosity. This phonon spectrum was calculated using the ab initio density functional theory (DFT) code VASP. The inelastic cross section calculated using this spectrum was found to have good agreement with relevant experimental data. The resulting spectra differed from the benchmark spectrum produced by Young and Koppel, the same data used in current nuclear data evaluations. The latter uses the lattice dynamics of perfect crystalline graphite with four force constants fitted to the model from thermodynamics data from reactor-grade (porous) graphite, which yields a reasonable approximation to the phonon spectrum of reactor-grade graphite.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗