scholarly journals Analysis of DD, TT and DT Neutron Streaming Experiments with the ADVANTG Code

2020 ◽  
Vol 225 ◽  
pp. 02003
Author(s):  
Bor Kos ◽  
Theodora Vasilopoulou ◽  
Scott W. Mosher ◽  
Ivan A. Kodeli ◽  
Robert E. Grove ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Importance Sampling ◽  
Variance Reduction ◽  
Neutron Transport ◽  
Plasma Source ◽  
Sampling Methodology ◽  
Transport Code ◽  
Weight Window ◽  
Monte Carlo Transport ◽  
Hybrid Methodology

The paper presents an analysis of DD, TT and DT neutron streaming benchmark experiments with the recently released hybrid transport code ADVANTG (AutomateD VAriaNce reducTion Generator). ADVANTG combines the deterministic neutron transport solver Denovo with the Monte Carlo transport code MCNP via the principle of variance reduction. It automatically produces weight-window and source biasing variance reduction parameters based on the CADIS (Consistent Adjoint Driven Importance Sampling) methodology. Using this novel hybrid methodology Monte Carlo simulations of realistic complex fusion streaming geometries have become possible. In this paper the experimental results from the 2016 DD campaign using measurements with TLDs and activation foils up to 40 m from the plasma source are analyzed. New detailed models of the detector assemblies were incorporated into the JET 360° MCNP model for this analysis. In preparation of the TT and DTE2 campaigns at JET a pre-analysis for these campaigns is also presented.

A Method to Alleviate the Long History Problem Encountered in Monte Carlo Simulations via Weight Window Variance Reduction

2017 ◽  
Vol 36 (6) ◽  
pp. 204-212 ◽  
Author(s):  
Xingchen Nie ◽  
Jia Li ◽  
Yuxiao Wu ◽  
Hengquan Zhang ◽  
Songlin Liu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Variance Reduction ◽  
Weight Window

scholarly journals Quicksilver: A Proxy App for the Monte Carlo Transport Code Mercury

2017 ◽  
Author(s):  
David F. Richards ◽  
Ryan C. Bleile ◽  
Patrick S. Brantley ◽  
Shawn A. Dawson ◽  
Michael Scott McKinley ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Transport Code ◽  
Monte Carlo Transport

Monte Carlo Neutron Transport on GPUs

2014 ◽  
Author(s):  
Ryan M. Bergmann ◽  
Jasmina L. Vujić
Keyword(s):  
Monte Carlo ◽  
Lower Energy ◽  
Neutron Transport ◽  
Memory Bandwidth ◽  
Performance Gain ◽  
Computational Power ◽  
Sorting Algorithms ◽  
Main Factors ◽  
Gpu Architectures ◽  
Monte Carlo Transport

GPUs have gradually increased in computational power from the small, job-specific boards of the early 90s to the programmable powerhouses of today. Compared to CPUs, they have a higher aggregate memory bandwidth, much higher floating-point operations per second (FLOPS), and lower energy consumption per FLOP. Because one of the main obstacles in exascale computing is power consumption, many new supercomputing platforms are gaining much of their computational capacity by incorporating GPUs into their compute nodes. Since CPU optimized parallel algorithms are not directly portable to GPU architectures (or at least without losing substantial performance gain), transport codes need to be rewritten in order to execute efficiently on GPUs. Unless this is done, we cannot take full advantage of these new supercomputers for reactor simulations. In this work, we attempt to efficiently map the Monte Carlo transport algorithm on the GPU while preserving its benefits, namely, very few physical and geometrical simplifications. Regularizing memory access and introducing parallel-efficient search and sorting algorithms are the main factors in completing the task.

Performance, Accuracy and Efficiency Evaluation of a Three-Dimensional Whole-Core Neutron Transport Code AGENT

2006 ◽  
Author(s):  
Tatjana Jevremovic ◽  
Mathieu Hursin ◽  
Nader Satvat ◽  
John Hopkins ◽  
Shanjie Xiao ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Neutron Transport ◽  
Three Dimensional ◽  
Open Architecture ◽  
Coarse Mesh ◽  
Research Reactors ◽  
Acceleration Techniques ◽  
Performance Accuracy ◽  
Transport Code ◽  
Neutron Propagation

The AGENT (Arbitrary GEometry Neutron Transport) an open-architecture reactor modeling tool is deterministic neutron transport code for two or three-dimensional heterogeneous neutronic design and analysis of the whole reactor cores regardless of geometry types and material configurations. The AGENT neutron transport methodology is applicable to all generations of nuclear power and research reactors. It combines three theories: (1) the theory of R-functions used to generate real three-dimensional whole-cores of square, hexagonal or triangular cross sections, (2) the planar method of characteristics used to solve isotropic neutron transport in non-homogenized 2D) reactor slices, and (3) the one-dimensional diffusion theory used to couple the planar and axial neutron tracks through the transverse leakage and angular mesh-wise flux values. The R-function-geometrical module allows a sequential building of the layers of geometry and automatic submeshing based on the network of domain functions. The simplicity of geometry description and selection of parameters for accurate treatment of neutron propagation is achieved through the Boolean algebraic hierarchically organized simple primitives into complex domains (both being represented with corresponding domain functions). The accuracy is comparable to Monte Carlo codes and is obtained by following neutron propagation through real geometrical domains that does not require homogenization or simplifications. The efficiency is maintained through a set of acceleration techniques introduced at all important calculation levels. The flux solution incorporates power iteration with two different acceleration techniques: Coarse Mesh Rebalancing (CMR) and Coarse Mesh Finite Difference (CMFD). The stand-alone originally developed graphical user interface of the AGENT code design environment allows the user to view and verify input data by displaying the geometry and material distribution. The user can also view the output data such as three-dimensional maps of the energy-dependent mesh-wise scalar flux, reaction rate and power peaking factor. The AGENT code is in a process of an extensive and rigorous testing for various reactor types through the evaluation of its performance (ability to model any reactor geometry type), accuracy (in comparison with Monte Carlo results and other deterministic solutions or experimental data) and efficiency (computational speed that is directly determined by the mathematical and numerical solution to the iterative approach of the flux convergence). This paper outlines main aspects of the theories unified into the AGENT code formalism and demonstrates the code performance, accuracy and efficiency using few representative examples. The AGENT code is a main part of the so called virtual reactor system developed for numerical simulations of research reactors. Few illustrative examples of the web interface are briefly outlined.

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