1. NAME AND TITLE
SWORD 7.0: Software for Optimization of Radiation Detectors, SWORD Version 7.0 Beta.
AUXILLARY LIBRARIES INCLUDED:
LLNL/RAPISCAN FISSION
GEANT4 10.1
XERCES
AUXILLARY PROGRAMS INCLUDED:
RADSRC
2. CONTRIBUTORS
Naval Research Laboratory, Washington, DC. This package contains Geant4 V10.1, which was developed at CERN, the European Organization for Nuclear Research, Genève, Switzerland.
3. CODING LANGUAGE AND COMPUTER
C++, Java, Python; Linux (C00767MNYCP07).
4. NATURE OF PROBLEM SOLVED
Software for Optimization of Radiation Detectors (SWORD) is a framework to allow easy simulation and evaluation of radiation detection systems. It is targeted at system designers who want the ability to evaluate and optimize system parameters without building hardware first; sponsors who must evaluate proposed or actual system designs independent of the supplier, without having access to actual hardware; and operators who aim to use simulation to evaluate observed phenomena.
SWORD is vertically integrated and modular. It allows users to define their own radiation detection instruments by building them from basic geometric “objects” and assigning those objects materials, detection, and/or radioactive emission properties. This process is accomplished by a computer-aided design (CAD)-like graphical user interface, in which objects may be defined, translated, rotated, grouped, arrayed, and/or nested to produce compound objects. In addition to providing the ability to build a detection system model from scratch, SWORD provides a library of “standard” detector design objects that can be used as-is or modified by the user.
5. METHOD OF SOLUTION
Using existing radiation transport codes, SWORD supplies a vertically integrated framework for creating models, assigning emission spectra, running the transport code, and analyzing the results. The user interface is independent of the chosen transport code.
SWORD gives the user the option of running their simulation using one of two well-known known Monte Carlo simulation engines: Geant4 from CERN (Version 10.1 included in package distribution) and Monte Carlo N-Particle Transport (MCNP). In addition, SWORD supports the Denovo discrete ordinates solver. In general, the SWORD workflow consists of four steps:
· Design the scenario. In this step, all the geometric elements of the simulation are defined, together with material properties, radioactive emission, and detector properties. The tool used here is the SWORD geometry builder, a CAD-like graphical tool.
· Configure the run. Here, all the simulation run parameters are defined. This includes simulated duration, which analysis processes will be run, and what outputs will be produced.
· Run the simulation. Normally this is done from within the SWORD interface. However, SWORD can also be run in batch mode without graphical interfaces. The latter is useful for running high compute time runs on high-performance machines. SWORD as supplied includes Geant4. SWORD can also run MCNP 6.1.1 or newer or the Denovo discrete ordinates solver.
· Examine the results. Spectrum histograms can be created in the SWORD Analyzer Python app. Various histogram binning can be created. Spectra can be output as N42.42 XML files or as SWORD emission spectrum files to be used for further simulation. The Analyzer app also serves as a spectrum viewer and allows fitting model lines and continua to the data. Alternatively, the output files can be read and analyzed using a variety of software tools such as spreadsheet programs.
· Improvements in SWORD7 over SWORD6
Simulation Engine Support:
Geant4 support added for LLNL/Rapiscan improved fission modeling
Geant4 support added for polarization physics
MCNP output rewritten to work with much more complicated models
Denovo interface changed from ADVANTG to OMNIBUS package; the latter is part of the SCALE package
Geometry Builder:
Global/Parent frame options
Expanded standard library
Analysis:
Spectrum creation moved to Analyzer app
Spectra can be created from coordsAndEnergy.dat, N42.42 files, SWORD emission spectra files, and MCNP outputs for various tallies
Spectra creation from flux.dat and SILO files in a future release
Spectrum plot/fitting moved to Analyzer app
Performance:
Faster program launch
Geometry viewer use of hardware acceleration improved, especially with high‑end GPUs
Geant4 run speed performance improved, especially with complex models
MCNP model performance improved
6. RESTRICTIONS OR LIMITATIONS
This is beta code. It has been tested and has no known issues, but users should keep in mind that it is beta code.
7. TYPICAL RUNNING TIME
Run time varies depending on complexity of models and statistics of simulation run.
8. COMPUTER HARDWARE REQUIREMENTS
Any Intel-based Windows, Linux, or Mac OSX platform with at least 4 GB of RAM and 30 GB of free disk space (see software requirements).
9. COMPUTER SOFTWARE REQUIREMENTS
Current distribution is available as a virtual appliance in the Open Virtual Appliance (OVA) format. The file can be opened in Virtualbox or imported into VMware. The guest operating system is Ubuntu 20.04 Linux. Binary installers for Ubuntu and Centos will be distributed at a later date.
Installation instructions are included in the provided documentation. Note that MCNP and Denovo are not distributed with SWORD and must be obtained by the user. They are available as the MCNP package and the SCALE package respectively from RSICC.
10. REFERENCES
a. Included in package:
“SWORD Installation Guide (SWORD Version 7.0 Beta, 7 October 2021).”
“SWORD Release notes (SWORD Version 7.0 Beta, 7 October 2021).
“SWORD Training Problem Set (SWORD Version 7.0 Beta, 7 October 2021).
“SWORD Reference Guide (SWORD Version 7.0 Beta, TO BE RELEASED AT A LATER DATE).”
b. Background references:
W. Duvall, B. Phlips, A. Hutcheson, R. Cordes, J. Hartsell and M. Strickman, "Improving Radiation Transport Simulation Capabilities for Nuclear Threat Detection Using SWORD," 2019 IEEE International Symposium on Technologies for Homeland Security (HST), 2019, pp. 1–6, doi: 10.1109/HST47167.2019.9032903.
11. CONTENTS OF CODE PACKAGE
The package is distributed containing the virtual appliance for 64-bit architectures, installation, and tutorial guides.
12. DATE OF ABSTRACT
May 2010, July 2010, January 2012, October 2013, May 2016, October 2021, December 2021
KEYWORDS: RADIATION DETECTION; SIMULATION; WEAPONS RADIATION; MONTE CARLO