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At least 217 records · Page 12

On Xenon Fission Product Poisoning

We all appreciate the special role Xenon-135 plays in reactor transients. Unless there is sufficient reactivity override, on shutdown a conventional reactor cannot immediately restart because of the buildup of strongly absorbing Xenon from Iodine decay and the absence of neutron flux to continue its elimination. We are also aware of how the flux imbalance in a large reactor core gives rise to Xenon induced power precession around the core in unpredictable ways. In addition, with regard to computational methods, we lack readily accessible numerical algorithms enabling reliable characterization of Xenon oscillations with simple models to explain this fundamentally important phenomenon. Nowhere is this more apparent than in the classroom. In this presentation, we first consider a new 12-element comprehensive decay to model Xenon and its corresponding numerical implementation and verification to establish a predictive model of Xenon buildup in a constant flux. We then follow with a reduced self-consistent flux model in an infinite reactor- a model not found in textbooks. This presentation should appeal to those interested in developing high order numerical methods for reactor transients.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fast Reactor Core Analysis Using AZNHEX Neutron Diffusion Code

The AZTLAN platform project emerged as an initiative to rank Mexico at a competitive level in software aspects for the analysis of nuclear reactors, in an effort to achieve autonomy in this area. The AZTLAN platform is conformed by a thermo-hydraulic code (AZTHECA), a neutron transport code (AZTRAN) and two neutron diffusion codes (AZKIND, AZNHEX). AZNHEX is a 3D diffusion code that solves numerically the time dependent neutron diffusion equations in hexagonal z-geometry using the RTN0 nodal finite element method. With this code, it is possible to simulate and analyze light water reactors, such as the Russian VVER, and variety of fast reactors. In this work, a sodium-cooled fast reactor core in steady state, with control rods fully withdrawn, is simulated. The comparison and validation of the values obtained with AZNHEX was done with the results obtained with MCNP6 Monte Carlo code.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The development of 3D physical program with integrated control rod calculation for HTR - 18525

The accurate calculation of the control rod worth in pebble bed high temperature gas cooled reactor(HTR) requires special treatment, because the control rod system of HTR is located outside the active zone. The current version VSOP did not calculate the control rod value directly, but use a compromise method called the Equivalent Boron Concentration (EBC). To obtain the value of the control rod with higher precision directly, this paper embedded the discontinuity factor (DF) corrected diffusion calculation into the original procedure of the VSOP. The computational procedure to obtain the DF on the side of the absorber region was optimized. While an appropriate coupling method has been developed to take into account the neutron leakage feedback, data transform and so on. The new program can achieve accurate control rod calculation and more realistic 3D power distribution during the physical calculation. The numerical results demonstrated the correctness of the new program preliminarily. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

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↗

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↗

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↗

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)

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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↗

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↗

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↗

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↗

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.↗

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↗

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↗

Coupling TRACE with nodal neutronics code Ants using the Exterior Communications Interface and VTT's multi-physics driver Cerberus

In this paper a recently developed coupling between system code TRACE and nodal neutronics code Ants is presented. The TRAC/RELAP Advanced Computational Engine (TRACE) is a reactor system code developed by U.S. Nuclear Regulatory Commission (NRC). The code has been designed to analyse loss-of-coolant accidents (LOCAs), operational transients and other accident scenarios in light water reactors. Ants is the reduced order nodal neutronics code of the Kraken framework. The diffusion solution method in Ants is based on the Analytic Function Expansion Nodal method (AFEN) and Flux Expansion Nodal Method (FENM). Rectangular, hexagonal and triangular geometries are supported. Both steady state and burnup problems including micro-depletion can be simulated. The coupling is implemented using VTT's multi-physics driver Cerberus and the Exterior Communications Interface (ECI) which is supplied with TRACE and enables the coupling of TRACE without source code modifications. The main focus in the paper is on describing the TRACE-Ants coupling in detail in order to share to other code developers what we have learned from the ECI based coupling process. The coupled code system is briefly tested by simulating a simple transient in a SMR core initiated by control rod movement. The results of the test calculation look reasonable and more complicated test cases will be modelled in the near future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Computation of Air Discharge into a Water Pool by Using Volume-of-Fluid Method

Suppression tanks, in-containment refueling water storage tanks (IRWSTs) and filtered containment venting systems (FCVSs) of nuclear power plants use water pools to accommodate high-pressure and high-temperature discharge of non-condensable gases and/or steam. Dynamic behavior of gas bubbles inside a water pool determines pressure and temperature loading to the system and thus we need validated method for applications. The underlying physics relevant to these problems is still a difficult issue due to the complicated nature of gas- liquid interfacial transfers of mass, momentum, and energy in a two-phase flow. Therefore, notwithstanding many studies performed over the past two or three decades, two-fluid theory is still a formidable task and direct numerical simulation (DNS) needs huge computing cost. Pellegrini et al. analyzed steam condensation and chugging in the water pool of the PPOOLEX STB-24 test by using STAR-CCM+ code implemented with two-phase interface model based on the Rayleigh-Taylor instability theory (RTI) which triggers steam depressurization. For the solution of the fine interface, they used Eulerian-Eulerian model for the fluid domain since the volume-of-fluid (VOF) model requires larger mesh points. The RTI resulted in complete steam condensation consistent with the experiment. The fluid tank was open to the atmosphere. They reported the volume fraction distributions in the pool, not the pool temperature or pressure history. For non-condensing gas discharges, however, the VOF is still a good alternative to the Eulerian two-fluid or the DNS approaches. The spatial distribution of each phase is defined in terms of volume fractions and the cell physical properties are obtained from linear combinations of those of constituent phases weighted by each volume fraction. Therefore, conditions where thermal and phase change effects become important are less likely to be simulated realistically. The VOF model is suited for the simulation of flows where each phase constitutes a large structure with a relatively small total contact area between phases. Present work is also interested in this VOF method for application to air discharge into a water pool which occurs in the early operating stages of the said facilities. Our purpose is to validate the VOF method against an existing air discharge experiment of PPOOLEX by using a commercial CFD code, STAR-CCM+ version 10.04, in terms of macroscopic flow properties. Effect of turbulence is also discussed.

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