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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 559 records · Page 31
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DOE OSTI2023

Hydrogen Production, Grid Integration, and Scaling for the Future

The Hydrogen Production, Grid Integration, and Scaling for the Future project will inform clean hydrogen production deployment across the planning, procurement, and operation stages of hydrogen production on the grid. Hydrogen production from renewables is a clean source of fuel which is near zero for greenhouse gas emissions and criteria pollutants. The results from this project will inform entities looking to build clean energy projects that produce good paying jobs in manufacturing, installation, maintenance and operation of these facilities. This project provides system characterization examples, multiple configurations, optimizations, and suggested metering and custody transfer points through multiple scenarios and hardware testing of NREL's state-of-the-art 1.25 MW polymer electrolyte membrane (PEM) electrolyzer system to characterize system performance in relevant scenarios. This work also creates a digital twin for emulation in the Advanced Research on Integrated Systems (ARIES) virtual environment and performs hardware-in-the-loop (HIL) testing of pilot-scale, decentralized, and centralized hydrogen systems.

centralized hydrogen production↗
DOE OSTI2023

Digital Twin for Optimizing Real-time Economy of the Integrated Energy Systems

Economic and safe operation of integrated energy systems (IES) requires real-time optimization (RTO) of the control and actions conducted on each system component. In this regard, digital twins (DTs), which consist of a physical system, a virtual system, and the data communication that occurs between the two, are essential for effective RTO. Through the data warehouse, the virtual system is constantly updated with real-time data from the physical system, and functions as the model in the optimization framework. The reduced-order model of the dynamic process model in the virtual system is used in the optimization framework. The optimization results are then returned, via the data warehouse, as control actions to the physical system. This work demonstrates the software capabilities of DT assets for an IES in the context of preparing a DT for an experimental system comprised of Idaho National Laboratory (INL)’s Thermal Energy Delivery System and battery system. For the virtual demonstration, the DTs encompass (1) a physical system, including the Modelica models of the Thermal Energy Delivery System and the battery system; (2) virtual optimization via the Optimization of Real-Time Capacity Allocation (ORCA) platform; and (3) the open-source data warehouse software DeepLynx. This work assesses the performance of ORCA, which utilizes a reduced-order model built using the Risk Analysis Virtual Environment (RAVEN) and trained on the Modelica models and real-time data pipeline through the graph database hosted in DeepLynx. The proposed optimization workflow will be an RTO model based on DTs and the data they generate.

25 ENERGY STORAGE↗
DOE OSTI2022

CTF Improved Drag Model and Flow Regime Transition Criteria

The demand for accurate prediction of two-phase flow behavior in a boiling water reactor (BWR) requires a comprehensive understanding of flow regime, void fraction, heat transfer, and pressure drop. The CTF subchannel code, which is used for the Thermal/Hydraulic (T/H) solution in the Consortium for Advanced Simulation of Light Water Reactors (CASL)-developed Virtual Environment for Reactor Application (VERA) core simulator, is being further developed for BWR applications. In support of this goal, the present work highlights some of the two-phase closure model developments towards improving the CTF void fraction prediction, especially for subcooled boiling. The drift-flux approach has been well-developed for upward dispersed two-phase flows and proven to be accurate in predicting void fraction in bubbly and slug flow regimes. In this work, these kinematic constitutive relations for the drift-flux velocity have been implemented into CTF to describe the interfacial drag of bubbly flow as an alternative to the existing model for better void fraction prediction. The success of these constitutive relations also relies on a good flow regime map that accounts for flow conditions and channel geometry. A more reliable flow regime transition criteria that account for the flow condition has also been implemented in this study for modeling the flow regime transition criteria. The newly implemented models are shown to give improved void fraction predictions in comparison to experimental data.

Hizoum, Belgacem↗
DOE OSTI2013

Overview of development and design of MPACT: Michigan parallel characteristics transport code

MPACT (Michigan Parallel Characteristics Transport Code) is a new reactor analysis tool. It is being developed by students and research staff at the University of Michigan to be used for an advanced pin-resolved transport capability within VERA (Virtual Environment for Reactor Analysis). VERA is the end-user reactor simulation tool being produced by the Consortium for the Advanced Simulation of Light Water Reactors (CASL). The MPACT development project is itself unique for the way it is changing how students do research to achieve the instructional and research goals of an academic institution, while providing immediate value to industry. The MPACT code makes use of modern lean/agile software processes and extensive testing to maintain a level of productivity and quality required by CASL. MPACT's design relies heavily on object-oriented programming concepts and design patterns and is programmed in Fortran 2003. These designs are explained and illustrated as to how they can be readily extended to incorporate new capabilities and research ideas in support of academic research objectives. The transport methods currently implemented in MPACT include the 2-D and 3-D method of characteristics (MOC) and 2-D and 3-D method of collision direction probabilities (CDP). For the cross section resonance treatment, presently the subgroup method and the new embedded self-shielding method (ESSM) are implemented within MPACT. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Assessment of the 2D MOC solver in MPACT: Michigan parallel characteristics transport code

MPACT (Michigan Parallel Characteristics Transport Code) is a new reactor analysis tool being developed by researchers at the University of Michigan as an advanced pin-resolved transport capability within VERA (Virtual Environment for Reactor Analysis). VERA is the end-user reactor simulation tool being developed by the Consortium for the Advanced Simulation of Light Water Reactors (CASL). The MPACT development project is itself unique for the way it is changing how students perform research to achieve the instructional and research goals of an academic institution, while providing immediate value to the industry. One of the major computational pieces in MPACT is the 2D MOC solver. It is critical that the 2D MOC solver provide an efficient, accurate, and robust solution over a broad range of reactor operating conditions. The C5G7 benchmark is first used to test the accuracy of the method with a fixed set of cross-sections. The VERA Core Physics Progression Problems are then used to compare the accuracy of both the 2D transport solver and also the cross-section treatments. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Assessing pellet-clad interaction with VERA: WBN1, cycles 6-7

The Consortium for Advanced Simulation of Light Water Reactors (CASL) aims to provide high fidelity simulations of nuclear reactors through the development of the Virtual Environment for Reactor Applications (VERA). One of the primary goals of CASL is to estimate local cladding failure through pellet-clad interaction (PCI). While this capability is being pursued through several different approaches, the procedure presented here focuses on running independent fuel performance calculations with the BISON fuel performance code being developed by Idaho National Laboratory using the multicycle output data from coupled neutron transport/thermal-hydraulics simulations generated by MPACT, CTF, and MAMBA. This type of approach is consistent with traditional fuel performance analysis methods, where the fuel performance analyses are typically separate from core simulation analyses. Recent work simulating 12 cycles of Watts Bar Unit 1 (WBN1) with VERA are capitalized upon, and stand-alone quarter-core BISON results can be obtained for several cycles, assessing parameters of interest to PCI (e.g., maximum centerline fuel temperature, maximum clad hoop stress, minimum gap thickness, and cumulative damage index). This is accomplished by using the coupled neutronics/thermal-hydraulics output power and temperature distributions as inputs for each BISON fuel rod case. Building on previous work which demonstrated this capability for Cycles 1 through 3, this paper presents the results for Cycles 6 and 7. Cycle 7 is of particular interest because significant CRUD-induced power shift was observed. While the current results do not immediately indicate that any rods are at an extreme risk of failure, further analysis on rods highlighted by this work may shed additional light on the likelihood of failure. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Performance Improvements to the Cross Section Calculation in MPACT

The MPACT code is the primary deterministic neutron transport solver available in the Virtual Environment for Reactor Applications (VERA) as part of the Consortium for Advanced Simulation of Light Water Reactors (CASL). In contrast to the conventional two-step method using homogenization techniques, MPACT employs a direct transport methodology, where the transport calculation is performed with the explicit reactor core geometry, material compositions, and temperature distribution. As the direct whole-core transport calculation requires significant computational resources, performance improvements have been recently conducted in various components of MPACT. The initial MPACT profiling was performed on the EOS cluster at the Oak Ridge Leadership Computing Facility. Table I shows that the cross section processing accounted for 74% and 33% of the total runtime for VERA Progression Problems 5 and 7. Starting with a problem-independent multigroup (MG) library, two primary functionalities are performed in MPACT to obtain the problem-dependent MG cross sections: (1) the resonance self-shielding calculation, which currently MPACT is approaching with the subgroup method; (2) use of equivalence cross section from resonance calculation to compute the microscopic cross sections, and thus, the macroscopic cross sections of material regions. As shown in Table I, the time distribution in cross section processing varies from case to case. For Problem 5, a 2-D quarter core depletion case, the macroscopic XS dominates due to the increased number of isotopes in the depleted fuel. For Problem 7, a 3-D quarter core PWR at HFP and BOL, more subgroup calculations are performed to obtain updated self-shielded cross sections during the iteration. In this summary, the approaches to reduce the computing time in cross section processing are presented. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Comparison of Surrogate Models with Physical Models for Dynamic Probabilistic Risk Analysis Using the RAVEN Code

Dynamic probabilistic risk analysis (DPRA) has emerged in the nuclear industry as an effective tool to identify points of weakness in nuclear reactors and create a comprehensive approach to quantifying risk. While DPRA allows for detailed analysis, it usually requires thousands of runs due to the necessity of exploring low probability, high consequence events, which can be computationally prohibitively difficult to assess. Risk Analysis Virtual Environment (RAVEN) is a software package being developed under the Nuclear Energy Advanced Modeling and Simulation program at the Idaho National Laboratory. It is able to manage complex control logic to drive a RELAP-7 simulation and to handle sampling strategies including Monte Carlo, Latin Hypercube, Grid and Adaptive samplers. By performing a thorough investigation of the possibility space of an accident scenario with RELAP-7, RAVEN is able to identify consequences of accident scenarios that have not been encountered. The most computational resource intensive step of a RAVEN analysis is running the RELAP-7 code modeling the physical system behavior. Using surrogate models to represent the outcomes of more complex simulations rather than the full model can greatly reduce the computation effort required. In situations where the uncertainty distributions of a model are unknown, or when there are multiple sets of uncertainty distributions, DPRA generally requires rerunning the physical model for each set of uncertainty distributions used. By taking an unbiased sample of the physical model and creating a surrogate model from the results, the surrogate model can be sampled under a different set of uncertainty distributions to provide equivalent results. This paper presents an example of this approach. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Implementation of a Red-Black SOR CMFD Solver in MPACT

As part of the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Virtual Environment for Reactor Applications (VERA) is being developed to provide high-fidelity multi-physics simulations of nuclear reactor cores. The MPACT code being developed collaboratively by Oak Ridge National Laboratory and the University of Michigan includes the primary deterministic neutron transport solver available within VERA. MPACT employs the 2D/1D method to solve three-dimensional problems, using 2D method of characteristics (MOC) radial transport solvers with 1D NEM-SP3 axial transport solvers, which are coupled using axial and radial transverse leakages. A 3D coarse mesh finite difference (CMFD) solver is used to provide accelerated convergence that is more stable. The Portable, Extensible Tool kit for Scientific Computation (PETSc) generalized minimal residual (GMRES) iterative solver with a block Jacobi preconditioner has been used to solve the CMFD linear systems. This work focused on the addition of a red-black successive over-relaxation (RBSOR) solver to reduce overall runtime by reducing time spent solving the CMFD linear systems. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

CTF Parallel Performance Improvements

CTF is a modernized version of COBRA-TF (Coolant Boiling in Rod Arrays-Two Fluid), which is a thermal hydraulic (T/H) sub-channel code based on a two-phase, two-fluid model that formulates the conservation equations of mass, energy, and momentum for three fields of vapor, continuous liquid, and entrained liquid droplets. Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program sponsored by the U.S. Department of Energy, CTF is being further developed and improved for modeling and simulation of light water reactors. The code improvements for predicting T/H responses of pressurized water reactor (PWR) cores are focused on its applications to specific challenge problems deemed significant to the industry, such as departure from nucleate boiling (DNB) and crud-induced power shift. The code is also being used for T/H feedback in normal operating condition depletions in PWR and boiling water reactor designs in the reactor core simulator, Virtual Environment for Reactor Applications Core Simulator (VERA-CS), being developed by CASL. CTF modifications under the CASL program include software optimization, new closure models, and parallelization for modeling full reactor core T/H responses. The purpose of this work was to improve the parallel performance of CTF. CTF was originally parallelized via a domain-decomposition strategy using the Message Passing Interface (MPI), in which the basis of a solution domain was a physical assembly in the model. In other words, a user who wanted to perform a parallel solution with CTF had to provide the code one processor per assembly in the model (e.g., 56 cores for a 56 assembly quarter-core model, or 193 cores for a 193 assembly full-core model). This design was rigid, demanding a very specific number of processors for a model; furthermore, when CTF was run in VERA-CS-which typically uses thousands of processors- many processors sat idle during the CTF solve because CTF was unable to use any more processors than there are physical assemblies. This was not necessarily a problem if the CTF execution speed was very fast, but the average time spent in a CTF solve for prototypical PWR operating conditions was significant (i.e., over 20 % of the simulation wall time was being spent in CTF for a standard core depletion simulation). Larger, more computationally intensive simulations performed in support of the CASL DNB challenge problem demonstrated a need for improvements in this original parallelization approach. The specific goal of this work was to allow CTF to use more processors than there are physical assemblies in the model, which would not only speed up CTF and improve the overall efficiency of VERA-CS but also give users more-flexible options for executing their simulations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

VUSAT - A VERA-CS Uncertainty and Sensitivity Analysis Toolkit

VERA-CS (the Virtual Environment for Reactor Applications, Core Simulator) is a high-fidelity multiphysics core simulator under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). VERA-CS includes three main components: MPACT for reactor physics and neutron transport, COBRA-TF for thermal-hydraulics, and ORIGEN for isotopic depletion. VERA-CS has been applied to an array of problems including core physics analysis, and the modeling for all of the fuel cycles of Watts Bar Nuclear Unit 1 (WBN1). MPACT is a 3D pin-resolved reactor transport code developed by Oak Ridge National Laboratory (ORNL) and the University of Michigan. COBRA-TF (CTF) is a three-field two-phase flow subchannel analysis code developed by ORNL and North Carolina State University. CTF solves the mass, momentum, and energy equations for the liquid, vapor, and droplet phases for each subchannel in the core and captures the axial flow within each channel as well as cross-flow between channels. Direct coupling between neutronics (MPACT) and thermal-hydraulics (CTF) in VERA-CS provides temperature and density feedback. CTF includes a number of models important for LWR safety and design analysis including flow regime dependent two-phase wall heat transfer, inter-phase heat transfer and drag, droplet breakup, and quench-front tracking. ORIGEN is developed by ORNL and released through the SCALE package. ORIGEN is directly integrated in MPACT through its API to calculate the changes in nuclides for every depletable cross-section region. Uncertainties exist in safety calculations with computer codes for nuclear reactor modeling and simulation, and they come from code limitations, scaling inaccuracies embedded in the experimental data, and uncertainties associated with the state of the reactor at the initiation of the transient. Consequently, for applications of high fidelity calculations using VERA-CS, proper uncertainty quantification (UQ) and sensitivity analysis (SA) of the computing models of reactor neutronics and thermal-hydraulics are important to comprehensively understand the results. New methods in UQ and SA have to be developed in multi-physics calculations using VERA-CS. Toward this end, a software package called VUSAT which stands for VERA-CS Uncertainty and Sensitivity Analysis Toolkit has been developed to facilitate the applications of VERA-CS within the context of best estimate plus uncertainty (BEPU) analysis framework. In this work, the VUSAT application to analyze departure from nucleate boiling (DNB) is presented.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Flexible Spatial Partitions in MPACT Through Module-Based Data Passing

As part of the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Virtual Environment for Reactor Applications (VERA) is being developed to provide high-fidelity multiphysics simulations of nuclear reactor cores. The MPACT code being developed collaboratively by Oak Ridge National Laboratory and the University of Michigan is the primary deterministic neutron transport solver available within VERA. MPACT employs the 2D/1D method to solve 3D problems using 2D method of characteristics (MOC) radial transport solvers with 1D nodal expansion method-based P3 (NEM-P3) axial transport solvers, which are coupled using axial and radial transverse leakages. A 3D coarse mesh finite difference (CMFD) solver is used to provide accelerated convergence and stability. Quarter-core problems in MPACT are typically run on moderately sized clusters ({approx}500-10,000 cores). As such, it relies heavily on spatial decomposition, both radially and axially, using MPI data communication along spatial domain boundaries to pass angular flux boundary condition and neighboring data. The initial spatial decomposition strategy implemented into MPACT overlaid a Cartesian grid over the core to form the domain boundaries. With this approach, a single buffer spanning across the entire boundary between two spatial domains is passed to a domain's neighbor. Additionally, only one neighboring domain index was allowed in each direction. For example, the entire eastern boundary of a domain must be the entire western boundary of the corresponding neighbour's domain. This implementation helped to execute cases on several thousand cores, where substantial radial decomposition was used. The default for several years was to use assembly decomposition, which yielded 73 radial partitions in the Watts Bar Unit 1 (WBN1) models being analyzed. However, as CASL formed stronger connections with industry partners, there was a strong push to allow MPACT to run on fewer cores, preferably in the 500-1,000 core range. Such cases require much less radial decomposition, typically with 8-16 radial domains on each plane. Unfortunately, the previous decomposition strategy is very limited in its ability to yield well-balanced domains, and it does not permit partitions with an arbitrary number of domains, particularly with small numbers of radial domains (3, 5, 7, 11, 13, etc.). With these limitations, a more flexible approach that provided more even-load balancing was needed. The details of this new strategy are outlined here, along with insights to its advantages. The examples provided are for the WBN1 core, which has been the focus of several initial CASL analyses. It is worth noting that spatial decomposition strategies have been employed in many codes with focus on a number of different transport methodologies. The references cited are not exhaustive as this has been very important research topic across many areas.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Assembling Multiple Models Within the RAVEN Framework

RAVEN (Risk Analysis Virtual Environment) is an INL-developed software tool that can be used to identify and increase the safety margin in complex systems. As a generic software framework, RAVEN is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as 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. RAVEN is currently able to construct multi-targets Reduced Order Models (ROMs), which are aimed to represent the response of a system (in a fixed configuration) for multiple Figures of Merits (FOMs) and time-dependent ROMs. These capabilities represent the initial steps for a larger implementation about the interaction of multiple models. In fact, in several cases, multiple models need to interface with each other since the initial conditions of one are dependent on the outcomes of another. To better understand the problem that here is solved, it is useful to consider a simple example: The following problem is considered: a weather forecast simulation code 'a' is used to compute the external (i.e. ambient) temperature in a certain location. A second model 'b' is inquired to compute the average temperature in a room having as boundary condition, among several others, the external ambient temperature. The response of the model 'b' depends on the outcome of the model 'a'. The reported example is only aimed to illustrate the reason why the creation of a framework to make interact different models is a key development for the advancement of RAVEN as a comprehensive calculation flow driver. Before reporting how the ensemble-models have been implemented, it is necessary to briefly describe the representative Model 'entities' that are available in RAVEN.

42 ENGINEERING↗
DOE OSTI2017

Economic Assessment of Nuclear Hybrid Energy Systems: Optimization using RAVEN

The energy market supply is under pressure to achieve competing goals, such as minimizing the cost of electricity and greenhouse gas emissions while achieving grid resilience and reliability and meeting regulatory requirements. To study different scenarios for possible evolutions of the energy market that assume a certain renewable penetration and the possible introduction of hybrid nuclear reactors, the HYBRID modeling and simulation project has been initiated by INL. The term hybrid nuclear reactor here refers to nuclear power plants that not only produce electricity, but can also sell heat to an industrial process, like a hydrogen generation or water desalination plant. The RAVEN (Risk Analysis Virtual Environment) code developed at INL together with the modeling language Modelica (the Dymola compiler is used) have been selected as the main modeling tools for the HYBRID modeling and simulation project. This summary outlines the challenge, presents an overview of the developments in the RAVEN code needed to solve it and shows an illustrative example calculation. The HYBRID modeling and simulation project is a multi laboratory effort, involving research teams from three different U.S. national laboratories, led by the Idaho National Laboratory (INL) and supported by the Argonne National Laboratory (ANL) and the Oak Ridge National Laboratory (ORNL)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Two-Step Analysis of Watts Bar Nuclear 1 Cycle 1 with SCALE/PARCS

A two-step approach to reactor core analysis was performed using SCALE and PARCS. Polaris is a new lattice physics module in SCALE 6.2 that provides light water reactor (LWR) modelling capabilities. The VERA (Virtual Environment for Reactor Applications) benchmark problems have been established by the Consortium of Advanced Simulation of Light Water Reactors (CASL). These benchmark problems were chosen to assess the performance of Polaris and PARCS. Homogenized few-group assembly cross sections were generated using Polaris and used in the United States Nuclear Regulatory Commission (NRC) core simulator PARCS. This paper will provide descriptions of the benchmark problems modelled, discuss the impact of transport cross section approximations in SCALE 6.2.0 and 6.2.1, and present the results obtained from the SCALE/PARCS benchmark calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Demonstration of Load-Follow Operations with Standalone BISON through VERA

As part of the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Virtual Environment for Reactor Applications (VERA) is being developed to provide high-fidelity multiphysics simulations of nuclear reactor cores. VERA contains a number of single physics packages that are coupled together. MPACT is the primary deterministic neutron transport solver, CTF provides thermal hydraulics solutions, and BISON - which is built off of the MOOSE framework - is used for fuel performance simulations. Over the past year, a standalone BISON capability has been developed using a one-way coupling between MPACT/CTF coupling calculations and BISON. This has allowed CASL contributors to gain insight into the fuel performance characteristics while a more tightly coupled methodology between MPACT, CTF, and BISON has been under development. The standalone capability has been used to simulate Watts Bar Unit 1 (WBN1) Cycles 1-3 and to screen for quantities of interest to pellet-clad interaction in Cycles 6-7. The simulation and screening results are presented here. CASL recently partnered with Exelon and the University of Illinois at Urbana Champaign (UIUC) to begin simulating some of Exelon's plants, with particular focus on load-follow operations. In such operations, the power output from the plant will vary based on the demand or anticipated demand at the time. For example, demand is much lower late at night than during the day when people are awake, so it operating the plant at lower power in the evenings could be advantageous. Historically, nuclear power generation has been among the cheapest sources of energy, so most plants in the United States have been operated at full power except for outages and various small scale events. However, in the current economic climate, priorities have changed. A number of questions arise when load-follow operations are considered, particularly with respect to VERA's tools and capabilities. Can the coupled neutronics and thermal hydraulics simulations with MPACT and CTF perform well without substantial convergence issues? Can BISON handle the somewhat rapid power changes present with load-follow? Will clad hoop stresses be alarmingly high as a result of these power changes? This work addresses these questions and demonstrates operations to assess feasibility and robustness before Exelon and UIUC proceed with their simulations using VERA. To demonstrate load-follow capability, two test problems were developed. The first is a single rod that experiences nominal operations during Cycle 1, and then it simulates 18 months of representative load-follow operations in Cycle 2. This single-rod case was used to test the robustness of MPACT, CTF, and BISON on a typical rod. The second problem is a quarter-core model based on WBN1, Cycle 3, with a single month of load-follow operations inserted into the middle of the cycle. This provides better understanding of the stresses to the clad during the numerous power changes. Sections of this article are adapted from the original, full technical report on this capability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Watts Bar I ex-core analyses using VERA - 25430

The integration and direct coupling of the Oak Ridge National Laboratory (ORNL) Shift Monte Carlo code within the Consortium for Advanced Simulation of Light Water Reactors (CASL) Virtual Environment for Reactor Applications (VERA) offers unique capabilities that combine high-fidelity in-core and ex-core radiation transport. In this recent development activity, the deterministic neutronics code MPACT performs the in-core radiation transport with temperature feedback using COBRA-TF (CTF), and provides the fission source to Shift for a follow-on fixed source radiation transport calculation to determine ex-core quantities of interest. The coupling of MPACT to Shift allows the neutron source for the ex-core transport to be calculated from the time-dependent, fully coupled MPACT solution. This paper presents the first use of VERA to perform coupon irradiation for code-to-code comparison of its ex-core capabilities. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

An analysis of various solution strategies and perturbations on inputs of the reactor shielding problem - 25584

Previous work focused on the use of automated variance reduction parameters for use in a fixed source reactor shielding problem to solve for ex-core particle transport results. The current work assesses that strategy in light of a fully-coupled Monte Carlo problem run as a critical system with parallel processing and the use of moderate variance reduction parameters set manually. The results from the two strategies compare well. Also, results are compared between the MCNP, Virtual Environment for Reactor Applications (VERA) and Shift computer codes. Shift and VERA deliver similar results and compare well to MCNP. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗