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DOE OSTI2025

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR reactor safety analysis. It aims to provide fast-running, modest-fidelity, whole-plant transient analyses capabilities, which are essential for fast turnaround design scoping and engineering analyses of advanced reactor concepts. While SAM is being developed as a system-level modeling and simulation tool, advanced modeling techniques being implemented include a reduced-order three-dimensional module, pseudo 3-D conjugate heat transfer modeling in reactor core, flexible and multi-scale modeling of heat transfer between fluid and structures, in addition to the advances in software environments and design, and numerical methods. SAM aims to be a generic system-level safety analysis tool for advanced non-LWRs, including Liquid-Metal-cooled fast Reactors (LMR), Molten Salt Reactors (MSR), Fluoride-salt-cooled High-temperature Reactors (FHR), and High-Temperature Gas-cooled Reactors (HTGR). SAM takes advantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented computational framework (MOOSE), and its underlying meshing and finite-element library and linear and non-linear solvers, to leverage the modern advanced software environments and numerical methods. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As new code capabilities and features are added, the SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Modeling and Simulation of Xe-100-type Pebble Bed Gas-Cooled Reactor with SCALE

The US Department of Energy (DOE) announced the Advanced Reactor Demonstration Program (ARDP) to accelerate the deployment of advanced reactor concepts. Awardees of ARDP funds are expected to demonstrate the operation of an advanced reactor within 7 years of receiving the award. X-Energy’s advanced reactor concept, the Xe-100, was selected as one of two advanced reactor concepts to receive funding to demonstrate the operation of its high-temperature gas-cooled pebble-bed reactor before the end of this decade. As a result of this push to bring advanced reactors to maturation and commercialization, transition and deployment scenario studies are being performed under the Systems Analysis and Integration (SA&I) campaign within the DOE Office of Nuclear Energy (DOE-NE) to evaluate the transition of the current US commercial fleet of light-water reactors (LWRs) to a future fleet of advanced reactors consisting of a mix of ARDP type reactor concepts and advanced LWRs. To accurately evaluate the front- and back-end resource requirements, it is important to perform reactor physics calculations to determine the discharge burnup and isotopic content, fuel residence time, as well as other parameters. For this purpose, a summer project funded by the SA&I campaign allowed for the setup of SCALE models for full-core Xe-100 type high-temperature gas-cooled pebble-bed reactor and a Xe-100 type slice using publicly available information. The core-averaged equilibrium compositions and zone-wise equilibrium compositions for the slice and 3D models, respectively, were obtained following an iterative depletion method developed by Bostelmann et al. using SCALE’s reactor physics sequence TRITON. The slice model was used with TRITON to generate burnup-dependent cross section libraries at different temperatures which can be used with SCALE’s ORIGAMI code to rapidly determine fuel inventory and therefore to perform quick sensitivity studies on parameters such as the pebble location in the core. The SCALE/TRITON transport and depletion calculation for the Xe-100 type slice model indicates that the isotopic concentrations are in good agreement at 1,300 effective full power days (EFPD) for 235 U. An analysis of 236 U results match 239 Pu results would seem to indicate a typographical error in Mulder and Boyes wherein the reported results of 236 U and 239 Pu are reversed. In addition to SCALE/TRITON calculations, a new capability within SCALE/ORIGAMI for the simulation of pebble-bed reactors was used to study the burnup sensitivity with respect to the pebble pathway through the core. The SCALE/ORIGAMI results show that pebbles that travel closer to the reflector for the entire depletion history have a higher burnup than pebbles that travel through the middle of the core because of the higher thermal to fast flux ratio near the reflector. Consequently, a pebble’s burnup is strongly affected by the pebble’s pathway for each pass. Additional phenomena such as temperature distributions in the core and different travel times of the pebbles in the individual radial zones further affect the burnup distribution. The sensitivity of the discharge vector to the pebble pathways taken during each pass can be evaluated in the future using SCALE/ORIGAMI now that the SCALE inputs have been established.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR reactor safety analysis. It aims to provide fast-running, modest-fidelity, whole-plant transient analyses capabilities, which are essential for fast turnaround design scoping and engineering analyses of advanced reactor concepts. While SAM is being developed as a system-level modeling and simulation tool, advanced modeling techniques being implemented include a reduced-order three-dimensional module, pseudo 3-D conjugate heat transfer modeling in reactor core, flexible and multi-scale modeling of heat transfer between fluid and structures, in addition to the advances in software environments and design, and numerical methods. SAM aims to be a generic system-level safety analysis tool for advanced non-LWRs, including Liquid-Metal-cooled fast Reactors (LMR), Molten Salt Reactors (MSR), Fluoride-salt-cooled High- temperature Reactors (FHR), and High-Temperature Gas-cooled Reactors (HTGR). SAM takes ad- vantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented computational framework (MOOSE), and its underlying meshing and finite-element library and linear and non-linear solvers, to leverage the modern advanced software environments and numerical methods. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As new code capabilities and features are added, the SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Critical Experiments in Support of Current Reactors and Advanced Reactor Deployment [Slides]

Limited, specific needs exist to support current reactor fleet and fuel cycle. Primarily, MOX experiments representative of low burnup LWR fuel are needed. LEU+ power distribution measurements may also be useful. Advanced reactors present many challenges and opportunities. New fuel forms and associated processes lack validation. Initial core criticality calculations can be validated with appropriate, highly similar experiments. Transportation of LEU+/HALEU material will be essential, and will rely on new experiments to support validation

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Analysis of hafnium configuration of FLUOLE-2 program - 25409

The purpose of this paper is to present an analysis of the hafnium configuration of FLUOLE-2 program. FLUOLE-2 is a set of benchmark-type experiments dedicated to neutron attenuation analysis with the aim of improving the TRIPOLI-4{sup R} Monte Carlo code validation and industrial neutron physics scheme. The CEA developed this program, with the support of EDF, in order to be representative of 900 and 1450 MWe Pressurized Water Reactors operated in France. For that purpose, different stainless steel structures have been designed and appropriately positioned inside the EOLE facility located at Cadarache CEA center. EOLE is a pool type zero power reactor, composed of a cylindrical aluminum vessel with an over-structure of stainless steel, that is able to contain various types of core and related structures. The FLUOLE-2 core has been designed as a 29 x 29 pins square lattice of fuel rods. Different kind of dosimeters (cobalt, gold, tin, rhodium, indium, iron, nickel, titanium, aluminum, and vanadium) were irradiated inside and outside the core. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

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↗

DOE OSTI2022

Projecting the Thermal Response in a HTGR-Type System during Conduction Cooldown Using Graph-Laplacian Based Machine Learning

Accurate prediction of an off-normal event in a nuclear reactor is dependent upon the availability of sensory data, reactor core physical condition, and understanding of the underlying phenomenon. This work presents a method to project the data from some discrete sensory locations to the overall reactor domain during conduction cooldown scenarios similar to High Temperature Gas-cooled Reactors (HTGRs). The existing models for conductive cooldown in a heterogeneous multi-body system, such as an assembly of prismatic blocks or pebble beds relies on knowledge of the thermal contact conductance, requiring significant knowledge of local thermal contacts and heat transport possibilities across those contacts. With a priori knowledge of bulk geometry features and some discrete sensors, a machine learning approach was devised. The presented work uses an experimental facility to mimic conduction cooldown with an assembly of 68 cylindrical rods initially heated to 1200 K. High-fidelity temperature data were collected using an infrared (IR) camera to provide training data to the model and validate the predicted temperature data. The machine learning approach used here first converts the macroscopic bulk geometry information into Graph-Laplacian, and then uses the eigenvectors of the Graph-Laplacian to develop Kernel functions. Support vector regression (SVR) was implemented on the obtained Kernels and used to predict the thermal response in a packed rod assembly during a conduction cooldown experiment. The usage of SVR modeling differs from most models today because of its representation of thermal coupling between rods in the core. When trained with thermographic data, the average normalized error is less than 2% over 400 s, during which temperatures of the assembly have dropped by more than 500 K. The rod temperature prediction performance was significantly better for rods in the interior of the assembly compared to those near the exterior, likely due to the model simplification of the surroundings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Investigation of methods for targeted search of dominant higher modes in subcritical systems

The reactor physics modeling of subcritical systems requires a substantially different approach from that of a critical reactor due to the presence of the so-called higher modes. Earlier investigations showed that the dominant higher modes lie in the inner part of the eigenvalue spectrum, making the conventional eigenvalue searches unfeasible and calling for a targeted search. This paper investigates the possibility of targeted and multitudinous eigenvalue calculation by testing the Krylov-Schur and the Dynamic Modes Decomposition (DMD) method for simple, analytically tractable problems. While the DMD method clearly showed its efficiency in a one-group homogeneous problem, modal analysis of a three-dimensional reflected reactor in two-groups approximation demonstrated that the increasing complexity poses challenges for both methods. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2017

Sensitivity Analysis of Lbloca In Response To 10 Cfr50.46c New Rulemaking

The Nuclear Regulatory Commission (NRC) is proposing a new rulemaking on emergency core system/loss-of-coolant accident (LOCA) performance analysis. In the proposed rulemaking, designated as 10 CFR 50.46c, the US NRC puts forward an equivalent cladding oxidation criterion as a function of cladding pre-transient hydrogen content. The proposed rulemaking imposes more restrictive and burnupdependent cladding embrittlement criteria; consequently more fuel rods need to be analyzed under LOCA conditions to maintain the safety margin, in contrast to the current practice with which only one hot rod needs to be analyzed. New multi-physics analysis methods are required to provide a thorough characterization of the reactor core in order to identify the locations of the limiting rods and quantify safety margins under LOCA conditions. The U.S. DOE’s Light Water Reactor Sustainability (LWRS) Program has initiated a project to develop multi-physics analytical capabilities, called LOTUS, to support the industry in the transition to the proposed rule. An approach to uncertainty quantification and sensitivity analysis with LOTUS was developed. A typical four-loop PWR plant model was developed and simulated by RELAP5-3D with inputs generated from core design and fuel performance analyses, and uncertainty quantification and sensitivity analysis were performed with seventeen uncertain input parameters. The maximum equivalent cladding reacted ratio (ECRR) and peak clad temperature ratio (PCTR) were selected as the figures of merit (FOM). Pearson, Spearman, partial correlation coefficients, and Sobol indices were considered for all of the figures of merit in the sensitivity analysis.

10CFR50.46c↗

DOE OSTI2016

Criticality Calculations with MCNP6 - Practical Lectures

These slides are used to teach MCNP (Monte Carlo N-Particle) usage to nuclear criticality safety analysts. The following are the lecture topics: course information, introduction, MCNP basics, criticality calculations, advanced geometry, tallies, adjoint-weighted tallies and sensitivities, physics and nuclear data, parameter studies, NCS validation I, NCS validation II, NCS validation III, case study 1 - solution tanks, case study 2 - fuel vault, case study 3 - B&W core, case study 4 - simple TRIGA, case study 5 - fissile mat. vault, criticality accident alarm systems. After completion of this course, you should be able to: Develop an input model for MCNP; Describe how cross section data impact Monte Carlo and deterministic codes; Describe the importance of validation of computer codes and how it is accomplished; Describe the methodology supporting Monte Carlo codes and deterministic codes; Describe pitfalls of Monte Carlo calculations; Discuss the strengths and weaknesses of Monte Carlo and Discrete Ordinants codes; The diffusion theory model is not strictly valid for treating fissile systems in which neutron absorption, voids, and/or material boundaries are present. In the context of these limitations, identify a fissile system for which a diffusion theory solution would be adequate.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Hafnium Isotope Ratio Method for Enhanced Safeguards at Research Reactors

Pacific Northwest National Laboratory (PNNL) is developing a Hafnium (Hf)-based, enhanced safeguards measure for the verification of energy production in a research reactor. Historically, verification of nuclear reactor use has been based on extracting and measuring physical samples from non-fuel components of the reactor. The Hafnium Isotope Ratio Method for Enhanced Safeguards (HIRMES) provides a means of verifying reactor operation based upon measuring the changes in isotopic ratios in purpose-built coupons. The first activity is installing a purpose-built, integrated sample collection coupon containing hafnium which undergoes isotopic changes when irradiated in the reactor. The second activity is analysis of the isotopic changes of the irradiated coupon after removal of the coupon using the isotope ratio method (IRM). The energy, or plutonium production, in a fission reactor can be estimated using IRM by measuring and correlating stable isotope ratios in non-fuel reactor components using standard reactor modelling methods. This paper presents HIRMES, a technology intended to provide an inexpensive, accurate, and robust measurement capability for validating operator declarations at low-power research reactors. Deploying HIRMES in research reactors would provide the IAEA with an in-core reactor “odometer” on total energy production with higher accuracy than other methods. HIRMES could be integrated in new fuel or reactor core designs as part of a protocol that is simple to implement and minimizes effort required of the operator or inspector. This paper also discusses early demonstrations at U.S. research reactors to-date, which demonstrate HIRMES as a practical tool for independent verification of low-power research reactor utilization. Specifically, the measurement uncertainty during an irradiation campaign of 39766 MWh was 22 MWh, representing two hours at a 10 MW reactor for a total irradiation campaign over the course of approximately six months.

research reactor safeguards, isotope ratio method↗

DOE OSTI2018

The Application of MCNP6.2 Unstructured Mesh Geometry Capabilities to the Study of Heavy Ion Single Event Effect on Microelectronic Devices and the Reactor Physics Analysis - 25691

Unstructured meshes allow irregular or complex geometries to be modeled precisely in Monte Carlo radiation transport codes. Through this capability, it is possible to share an unstructured mesh model between multiple codes that use unstructured mesh geometry and thus improving coupled multi-physics simulations. In this work, unstructured meshes are used to model energy deposition from heavy ion strikes for single event effects on microelectronic devices as well as neutron flux mapping of nuclear reactor configurations. In each case, MCNP6.2's unstructured mesh functionality and applicability to the problem is demonstrated and analyzed. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Surrogate Models for TREAT Transient Calculations

The Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) is currently preparing for resumption of operation after more than 20 years in a long-term standby state. In parallel with preparation for operations and a new transient testing program, the DOENE Advanced Modeling and Simulation program (NEAMS) has been supporting the development of three-dimensional transient multi-physics modeling capabilities within the reactor physics application MAMMOTH. Recently, the MAMMOTH reactor physics team has begun development of uncertainty and sensitivity analysis for the TREAT core. This research will be used to support the analysis of reactor operation and experiment planning. Traditional approaches, i.e., Monte Carlo simulations, for such tasks require a large number of model evaluations under both steady state and transient conditions. However, exhaustive sets of sampling runs are simply not practical for TREAT since evaluations of each model can take a substantial amount of time. A solution to this problem is to build a surrogate model employing a smaller number of model evaluations. The surrogate model is designed to provide an accurate and fast approximation to the detailed TREAT model. In this manner, the surrogate model can be used in place of the TREAT transient model for uncertainty and sensitivity analysis at a fraction of the computational cost. The high dimensional model representation (HDMR) method is employed here for approximating the responses of interest in terms of functions of lower dimensions. This method has been implemented in RAVEN and all TREAT transient calculations are performed using the multiphysics code MAMMOTH. In addition, a code interface has also been developed in order to couple RAVEN with MAMMOTH. The surrogate model is then tested and compared for TREAT startup testing program Transient Test no. 15 core, and its accuracy is measured by its ability to estimate the mean, coefficient of variance, skewness, excess kurtosis and probability density function of the outputs of Transient Test no. 15 model, as well as root mean square error metric.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

SAM User’s Guide

The System Analysis Module (SAM) is a modern system analysis tool being developed at Argonne National Laboratory for advanced non-LWR safety analysis. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for Sodium-cooled Fast Reactors (SFR), Lead-cooled Fast Reactors (LFR), and Molten Salt Reactors (MSR) or Fluoride-cooled High-temperature Reactors (FHR). SAM takes advantage of advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability. It utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage the modern advanced software environments and numerical methods. This document provides a user’s guide, which will help users understand the input description and core capabilities of the SAM code. A brief overview of the code is presented, as well as how to obtain and run it. The input syntax for various parts of the code is provided. Additionally, a number of example problems, starting with simple unit component problems to problems with increasing complexity, are provided. Because the code is still under active development, this SAM User’s Guide will evolve with periodic updates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

SAM User's Guide

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Optimal Temperature Grid for Accurate Doppler Kernel Reconstruction

For computational efficiency, both Monte Carlo and deterministic neutron transport codes often rely on pre-tabulated cross section sets and simple interpolation schemes to represent the Doppler broadening of the cross sections at a needed temperature. Accurate accounting of Doppler effects is of paramount importance for reactor analysis since it impacts the power distribution and the reactor response during transients. Temperature interpolation methods for Doppler broadening have traditionally been physically motivated engineering curve-fits, selected upon best-performance criteria on important nuclides.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Development of a phonon-based sampling method for thermal neutron scattering data

Simulations of reactor systems require access to accurate nuclear data. For many systems, thermal neutron scattering data can have large effects on the eigenvalue and neutron flux distributions. Inelastic thermal neutron scattering can excite or de-excite vibrational, rotational, and translational modes in a material, so thermal scattering evaluations are often obtained by summing over the number of phonons created/destroyed by a scattering event. In recent years, the thermal scattering cross sections and angular distributions have greatly improved in accuracy, but the format in which this data is delivered to simulation codes has remained virtually unchanged. Thermal scattering data is typically either compiled into large tables and sorted by incoming neutron energy, outgoing neutron energy, scattering angle, and material temperature, or represented as cumulative distribution functions of momentum exchange or energy exchange. Either method can be quite memory intensive when fine bins are used. In an effort to decrease the amount of space that processed thermal scattering data requires, an alternate format is proposed. The phonon-based sampling method introduced here can sample the number of phonons excited for each collision, the change in neutron energy, and the scattering angle while avoiding pre-computed angular bins and limiting the amount of data that is dependent on incoming energy. Through this method, the generation and storage of large interpolation tables is avoided, which could have benefits in both memory storage and accuracy. While the initial implementation of this method is slower than current alternatives, it is significantly more resistant to grid coarseness errors and has good potential for improvement. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗