RSICC Home Page ADVANTG 3.2.0

RSICC CODE PACKAGE CCC-854

1.         NAME AND TITLE

     ADVANTG 3.2.0: AutomateD VAriaNce reducTion Generator

 

AUXILIARY PROGRAMS

Denovo-6.2.3: 3-D parallel discrete ordinates solver


MSX/NAGSS-1.1.0: Utilities for deterministic, Monte Carlo, and hybrid activation analysis

ORNL-TN-1.0.0: ORNL transformative neutronics upgrade to MCNP5-1.60

Radiant-1.0.0: 3-D MCNP geometry visualization

DATA LIBRARIES

BUGLE-96 (DLC-185)

DABL69 (DLC-130)

FENDL-2.1 46n21g and FENDL-3.1 46n21g, 175n42g

HILO2K (DLC-220)

SCALE-6.1 27n19g and 200n47g ENDF/B-VII libraries (CCC-785)

2.         CONTRIBUTOR

Oak Ridge National Laboratory, Oak Ridge, Tennessee.

3.         CODING LANGUAGE AND COMPUTER

C, C++, Fortran 90, and Python for Linux Operating Systems. (C854PCX8600)

4.         NATURE OF PROBLEM SOLVED

ADVANTG is an automated tool for generating variance reduction parameters for fixed-source continuous-energy Monte Carlo simulations with MCNP5-1.60 (CCC-810, not included in this distribution) or ORNL-TN (included in this distribution) based on approximate 3-D multigroup discrete ordinates adjoint transport solutions generated by Denovo. The variance reduction parameters generated by ADVANTG consist of space and energy-dependent weight-window bounds and biased source distributions, which are output in formats that can be directly used with MCNP5 and ORNL-TN. ADVANTG has been applied to neutron, photon, and coupled neutron-photon simulations of real-world radiation shielding and detection scenarios. ADVANTG is compatible with all MCNP5 geometry features and can be used to accelerate cell tallies (F4, F6, F8), surface tallies (F1 and F2), point-detector tallies (F5), and mesh tallies (FMESH).

MSX is a suite of utilities that implement the Multi-Step CADIS (MS-CADIS) method for accelerating hybrid deterministic / Monte Carlo simulations of post-activation biological dose rate analysis. The suite was developed to work with the ADVANTG and MCNP codes. MSX uses the ORIGEN solver from the SCALE code system to perform activation calculations. The Neutron Activation Gamma Source Sampler (NAGSS) code reads a set of energy group-dependent, meshed inhomogeneous source files produced by the MSX code and writes a set of randomly sampled source particle launch data suitable for simulation using MCNP5-1.60 with a modified source subroutine.

ORNL-TN is a modified version of MCNP5-1.60 that was developed to improve the scalability and performance of the software. Geometry initialization algorithms that exhibit poor performance on very detailed models were replaced with highly scalable algorithms. In addition, a shared-memory mesh tally algorithm was developed, implemented, and tested that drastically reduces the memory required to generate high-resolution mesh tally results in multithreaded simulations. The implementation provides comparable run-time performance to unmodified MCNP5 by employing batch statistics instead of history-based statistics.

Radiant is a thread-parallel utility for rendering images of MCNP geometry models in a 3-D perspective. The code generates raster images using the ray tracing capabilities of the Lava library that was developed with the ADVANTG software. The ray tracer supports all MCNP5 geometry features, including universes, lattices, and transformations. Radiant makes no approximations when constructing the raster image. The color of each pixel is determined directly from the output of the ray tracer. Images are written in the space-efficient Portable Network Graphics (PNG) format. Radiant can render images at arbitrary resolutions. Anti-aliasing can be applied to produce very high-quality images. Options are provided to control the color and visibility of each material defined in the problem. The geometry can be clipped by one or more arbitrarily oriented planes to expose internal details. The direction of the planar light source can also be altered to affect the shading of surfaces displayed in the image.

5.         METHOD OF SOLUTION

ADVANTG implements the Consistent Adjoint Driven Importance Sampling (CADIS) method and the Forward-Weighted CADIS (FW-CADIS) method for generating variance reduction parameters. The CADIS and FW-CADIS methods provide a prescription for generating space- and energy-dependent weight-window targets and a consistent biased source distribution. The CADIS method was developed for accelerating individual tallies, whereas FW-CADIS can be applied to multiple tallies and mesh tallies. The CADIS method has been demonstrated to provide speed-ups in the tally FOM of O(10^1)-O(10^4) across a broad range of radiation detection and shielding problems. The FW-CADIS method has been shown to produce relatively uniform statistical uncertainties across multiple cell tallies and large space- and energy-dependent mesh tallies in real-world applications.

Denovo implements a structured, Cartesian-grid discrete ordinates solver based on the Koch-Baker-Alcouffe algorithm for parallel sweeps across x-y domain blocks. Multiple discretization schemes are available: step characteristics, linear-discontinuous, tri-linear discontinuous and diamond difference (optionally theta-weighted or with negative-flux fixup). Multiple quadrature sets are available: QR product, QR triangular, Gauss-Legendre product, linear-discontinuous finite element, level-symmetric, as well as user-defined quadratures. Denovo contains an embedded first-collision source treatments based on an analytic kernel. The Trilinos parallel solvers package is used to apply GMRES to accelerate the within-group iterations, resulting in a computationally efficient and robust transport solver.

MSX/NAGSS implements the Multi-Step CADIS (MS-CADIS) method for accelerating hybrid deterministic / Monte Carlo simulations of post-activation biological dose rate analysis. Given a gamma response of interest, MS-CADIS provides a prescription for calculating variance reduction parameters to optimize the initial neutron transport simulation. Parameters are calculated based on a neutron adjoint source that is developed by combining an approximate adjoint photon flux solution with linearized (approximate) activation kernels. The final neutron biased source and weight windows parameters ensure that regions of phase space where activated gamma sources contribute significantly to the response are well sampled in the neutron simulation. Having estimated space- and energy-dependent neutron fluences, parallel voxel-by-voxel activation and gamma source calculations can then be performed using the SCALE-6.2.3 ORIGEN C++ library through MSX. The final gamma transport calculation can then be performed using the ORNL-TN executable compiled with the NAGSS source subroutine included in this distribution.

The references provide a detailed description of the CADIS, FW-CADIS, and MS-CADIS methods, as well as the algorithms implemented in the ADVANTG, Denovo, and ORNL-TN packages..

 

6.         RESTRICTIONS OR LIMITATIONS

The implementations of the CADIS, FW-CADIS, and MS-CADIS methods in ADVANTG and MSX/NAGSS are based on the use of scalar flux estimates from Denovo calculations. As a result, no directional biasing, in either the weight-window parameters or the biased source distributions, is currently implemented.

The shared-memory mesh tally algorithm implemented in ORNL-TN is restricted to multithreaded simulations. The implementation does not support MPI-parallel or mixed MPI/multithreaded simulations. The merge-meshtal-hdf5 utility is provided for combining mesh tally results from multiple independent runs.

7.         TYPICAL RUNNING TIME

The run time consumed by ADVANTG is problem-dependent. The majority of computational time is consumed by the discrete ordinates solver, so the primary factors that affect the run time are: the size of the deterministic spatial grid, the physics of the problem (e.g., photon-only versus coupled neutron-photon, presence of upscatter, etc.), the number of quadrature directions, and the number of energy groups.

ADVANTG can drive either serial (i.e., single-processor) or parallel Denovo calculations. For serial calculations on modern desktops, typical run times vary from several minutes to several hours. The run time can be significantly reduced by executing the Denovo calculations in parallel.

8.         COMPUTER HARDWARE REQUIREMENTS

The included executables are operable on all modern x86-64 (64-bit) Linux platforms

9.         COMPUTER SOFTWARE REQUIREMENTS

The included Linux binary distribution package is essentially self-contained, lacking only continuous-energy cross section data for MCNP which can obtained, for example, from package CCC-740. The executables were created using the following compilers and open-source packages: GCC-7.3.0 with HDF5-1.8.20, LAPACK-3.5.0, libpng-1.6.32, OpenMPI-3.1.2, Python-2.7.15, Silo-4.10.2-BSD, SWIG-3.0.12, and Trilinos-12.12.1

ADVANTG and MSX output Silo-format files that can be read by the open-source VisIt 3-D, parallel visualization tool (https://wci.llnl.gov/simulation/computer-codes/visit/). Use of VisIt to inspect the quality of the deterministic solutions before starting Monte Carlo runs is highly recommended.

10.        REFERENCES

Documentation included in package:

S.M. Bowman, “SCALE 6: Comprehensive Nuclear Safety Analysis Code System,” Nuclear Technology, 174, 126 (2011).

T.M. Evans, A.S. Stafford, R.N. Slaybaugh, and K.T. Clarno, “Denovo: A New Three-Dimensional Parallel Discrete Ordinates Code in SCALE,” Nuclear Technology, 171, 171–200 (2010).

I.C. Gauld, G. Radulescu, G. Ilas, B.D. Murphy, M.L. Williams, and D. Wiarda, “Isotopic Depletion and Decay Methods and Analysis Capabilities in SCALE,” Nuclear Technology, 174, 169 (2011).

A.M. Ibrahim, D.E. Peplow, R.E. Grove, J.L. Peterson, and S.R. Johnson, “The Multi-Step CADIS Method for Shutdown Dose Rate Calculations and Uncertainty Propagation,” Nuclear Technology, 192, 286 (2015).

S.W. Mosher et al., “ADVANTG?An Automated Variance Reduction Parameter Generator,” ORNL/TM-2013/416 Rev. 1, Oak Ridge National Laboratory (2015).

S.W. Mosher and A.M. Bevill, “Estimating Biased Source Probabilities over Arbitrary Bins,” 20th Annual Topical Meeting of the American Nuclear Society Radiation Protection and Shielding Division, Santa FE, NM, August 26-31 (2018).

S.W. Mosher and S.C. Wilson, “Algorithmic Improvements to MCNP5 for High-Resolution Fusion Neutronics Analyses,” Fusion Science and Technology, 74, 263 (2018).

J.C. Wagner and A. Haghighat, “Automated Variance Reduction of Monte Carlo Shielding Calculations Using the Discrete Ordinates Adjoint Function,” Nuclear Science and Engineering, 128, 186 (1998).

J.C. Wagner, D.E. Peplow, and S.W. Mosher, “FW-CADIS Method for Global and Semi-Global Variance Reduction of Monte Carlo Radiation Transport Calculations,” Nuclear Science and Engineering, 176, 37–57 (2014).

S.C. Wilson, S.W. Mosher, K.E. Royston, C.R. Daily, and A.M. Ibrahim, “Validation of the MS-CADIS Method for Full-Scale Shutdown Dose Rate Analysis,” Fusion Science and Technology, 74, 288 (2018).

11.        CONTENTS OF CODE PACKAGE

The DVD contains executables and for 64-bit Linux, documentation, multigroup cross section libraries in ANISN format, and ORIGEN data

12.        DATE OF ABSTRACT

August 2019

KEYWORDS: VARIANCE REDUCTION; DISCRETE ORDINATES; HYBRID TRANSPORT; CADIS; FW-CADIS; MONTE CARLO; MCNP