Methods for deep-penetration radiation transport remain important for radiation shielding, nonproliferation, nuclear threat reduction, and medical applications. As these applications become more ...ubiquitous, the need for accurate and reliable transport methods appropriate for these systems persists. For such systems, hybrid methods often obtain reliable answers in the shortest time by leveraging the speed and uniform uncertainty distribution of a deterministic solution to bias Monte Carlo transport and reduce the variance in the solution. This work reviews the state of the art among such hybrid methods. First, we summarize variance reduction (VR) for Monte Carlo radiation transport and existing efforts to automate these techniques. Relations among VR, importance, and the adjoint solution of the neutron transport equation are then discussed. Based on this exposition, the work transitions from theory to a critical review of existing VR implementations in modern nuclear engineering software. At present, the Consistent Adjoint-Driven Importance Sampling (CADIS) and Forward-Weighted Consistent Adjoint-Driven Importance Sampling (FW-CADIS) hybrid methods are the gold standard by which to reduce the variance in problems that have deeply penetrating radiation. The CADIS and FW-CADIS methods use an adjoint scalar flux to generate VR parameters for Monte Carlo radiation transport. Additionally, efforts to incorporate angular information into VR methods for Monte Carlo are summarized. Finally, we assess various implementations of these methods and the degree to which they improve VR for their target applications.
To realize the practical application of the numerical reactor technology on the cutting-edge supercomputer with heterogeneous architecture, or the desktop workstation with consumer graphics cards, ...advanced lattice physics code based on heterogeneous architecture (ALPHA) was developed by the research center of nuclear power simulation at Harbin Engineering University as the highfidelity 3D neutron transport calculation code for reactor core based on heterogeneous architecture. Firstly, a massively parallel 2D method of characteristics (MOC) algorithm on GPU was proposed in ALPHA. Three parallel schemes were studied based on the ray parallelization in MOC solution method, and the performance optimization of MOCs GPU parallel computing kernel was performed. Numerical results demonstrate that the GPUbased 2D MOC parallel algorithm shows comparative accuracy compared with the other similar codes. The GPU shows powerful computing capacity especially with single precision operation, and the 1080Ti GPU achieves 100× speedup compared with the runtime on a single core of i9-7900 CPU. Secondly, the 2D MOC heterogeneous parallel algorithm which employs the MPI+CUDA programming model was proposed and implemented on CPUs/GPUs heterogeneous system. In this algorithm, the spatial domain decomposition technique provides the coarsegrained parallelism with the MPI protocol, while the finegrained parallelism was exploited through ray parallelization on GPU with CUDA environment. The strong scaling efficiency can be improved by overlapping the MPI communication with computation and applying the asynchronous datacopy between GPU and CPU. Thirdly, the resonance calculation model of ALPHA adopts the fine groupsubgroup secondary discrete strategy to treat the complex overlapping selfshielding effect and uses multigroup kernel to accelerate the performance of resonance treatment on GPU systems. Finally, 3D MOCEX heterogeneous parallel algorithm for neutron transport calculation on the CPUs/GPUs heterogeneous system was proposed, and the whole-core high-fidelity neutron transport calculation was performed high-efficiently and stably with the GPU-accelerated CMFD formulation. Numerical results show that the ALPHA has excellent parallel efficiency and scalable performance in the premise of ensuring the calculation accuracy, which is expected to achieve the lightweight and engineering application of neutronics calculation in numerical reactors.
A goal-based angular adaptivity has been described for solving the discrete ordinates transport equation. This method uses the linear discontinuous finite element quadrature sets, allowing for local ...angular refinement across space-energy dimensions. Anisotropy quantified factor derived by contributon theory is introduced in this adaptivity to locate spatial regions that require more angular unknowns in every energy group for a given goal region. The goal-based error metric is considered to trigger local refinement in angle, which requires the solutions of the contributon transport equation to determine the importance to a user-defined functional. Several problems that include both one-group and multi-group transport calculations are displayed to demonstrate the effectiveness of this method. Results indicate that our goal-based adaptivity can significantly reduce computational expenses in terms of angular unknowns and computational times for a similar accuracy, as compared to uniform quadrature sets. It is expected that this adaptivity has the potential to enhance the efficiency of an even wider range of transport problems.
•The goal-based angular adaptivity allows for different local angular refinement across space-energy dimensions.•Anisotropy quantified factor can locate spatial regions where require more angular resolutions in each energy group for a given goal region.•Contributon flux instead of adjoint flux is as a measure of importance to trigger local refinement in angle.•The goal-based adaptivity reduces computational expenses by 1–2 orders of magnitude for a similar accuracy compared to uniform discretization.
► An open source Monte Carlo particle transport code, OpenMC, has been developed. ► Solid geometry and continuous-energy physics allow high-fidelity simulations. ► Development has focused on high ...performance and modern I/O techniques. ► OpenMC is capable of scaling up to hundreds of thousands of processors. ► Results on a variety of benchmark problems agree with MCNP5.
A new Monte Carlo code called OpenMC is currently under development at the Massachusetts Institute of Technology as a tool for simulation on high-performance computing platforms. Given that many legacy codes do not scale well on existing and future parallel computer architectures, OpenMC has been developed from scratch with a focus on high performance scalable algorithms as well as modern software design practices. The present work describes the methods used in the OpenMC code and demonstrates the performance and accuracy of the code on a variety of problems.
•OpenMC is an open source Monte Carlo particle transport code.•Solid geometry and continuous-energy physics allow high-fidelity simulations.•Development has focused on high performance and modern I/O ...techniques.•OpenMC is capable of scaling up to hundreds of thousands of processors.•Other features include plotting, CMFD acceleration, and variance reduction.
This paper gives an overview of OpenMC, an open source Monte Carlo particle transport code recently developed at the Massachusetts Institute of Technology. OpenMC uses continuous-energy cross sections and a constructive solid geometry representation, enabling high-fidelity modeling of nuclear reactors and other systems. Modern, portable input/output file formats are used in OpenMC: XML for input, and HDF5 for output. High performance parallel algorithms in OpenMC have demonstrated near-linear scaling to over 100,000 processors on modern supercomputers. Other topics discussed in this paper include plotting, CMFD acceleration, variance reduction, eigenvalue calculations, and software development processes.
This paper presents the implementation of the discrete ordinates method (SN) in 2D cartesian geometry and the collision probability method (CP) in cylindrical and spherical 1D geometry in OpenNTP ...code (Open Neutron Transport Package). This code is a pedagogical tool for computer analysis of nuclear reactors. Its main features are as follows: a free software with an open source, it solves the neutron transport equation to a few steady-state groups on a grid structured in one or two spatial dimensions with an isotropic and anisotropic dispersion source, and any new calculation method and algorithm would be easy to implement in this proposed code. Also, the code offers the possibility to calculate the main parameters of nuclear reactors such as the multiplication factor and the distribution of the scalar and angular neutron fluxes. Additional parameters, like the reaction rates, the pin power distribution and the boundary currents are also calculated. Moreover, a graphical user interface written in Python 3 programming language has been developed to simplify the use of OpenNTP. Some applications of the OpenNTP code have been compared on the one hand with the Monte Carlo OpenMC and MCNP6.1 codes and the WIMSD-5B lattice transport code, on the other hand. Numerical results are given to illustrate the accuracy of the OpenNTP code.
Program Title: OpenNTP, version 1.2
CPC Library link to program files:https://doi.org/10.17632/gm2b6799j6.1
Developer’s repository link:https://github.com/mohamedlahdour/OpenNTP
Licensing provisions: GPLv2
Programming language: fortran90 and Python 3
External routines/libraries: NumPy, Matplotlib, PyQt5, f2py
Nature of problem: Solving the steady-state multigroup neutron transport equation by different methods in one, or two spatial dimensions.
Solution method: the characteristic method (MOC), the discrete ordinate (SN) method and the collision probability method (CP)
Fusion neutronics analysis before and after experiments at JET is traditionally performed using Monte Carlo particle transport code Monte Carlo N-Particle. For redundancy and diversity reasons there ...is a need of an additional Monte Carlo code, such as Serpent 2, capable of fusion neutronics analysis. In order to validate the Serpent code for fusion applications a detailed model of JET was used. Neutron fluxes and reaction rates were calculated and compared for positions outside the tokamak vacuum vessel, in the vacuum vessel above the plasma and next to a limiter inside the vacuum vessel. For all detector positions with DD and DT neutron sources the difference between neutron fluxes calculated with both Monte Carlo codes were within 2
σ
statistical uncertainty and for most positions (more than 90 % of all studied positions) even within 1
σ
uncertainty. Fusion neutronics analysis in the JET tokamak with Serpent took on average 10 % longer but this can be improved by changing the threshold value for determination of the transport method used. With the work presented in this paper the Serpent Monte Carlo code was validated to be a viable alternative to MCNP for fusion neutronics analysis for the JET tokamak.
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