Abstract
The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols.
To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature.
Maintaining consistency with other simulation tools used within the nuclear energy
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- Developers:
-
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[1]
;
[1]
;
;
[1]
- Idaho National Laboratory (INL), Idaho Falls, ID (United States)
- Release Date:
- 2024-05-23
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Python
- Licenses:
-
GNU Lesser General Public License v2.1
- Sponsoring Org.:
-
USDOE Office of Nuclear Energy (NE)Primary Award/Contract Number:AC07-05ID14517
- Code ID:
- 155435
- Research Org.:
- Idaho National Laboratory (INL), Idaho Falls, ID (United States)
- Country of Origin:
- United States
- Keywords:
- simulation control machine learning digital twin command advanced reactors
Citation Formats
Faber, Jacob, Al Rashdan, Ahmad, Montezzo Coelho, Maria Eduarda, and Oncken, Joseph E.
Control And Optimization Modular Modeling Application For Nuclear Deployment.
Computer Software.
https://github.com/idaholab/command.
USDOE Office of Nuclear Energy (NE).
23 May. 2024.
Web.
doi:10.11578/dc.20250514.7.
Faber, Jacob, Al Rashdan, Ahmad, Montezzo Coelho, Maria Eduarda, & Oncken, Joseph E.
(2024, May 23).
Control And Optimization Modular Modeling Application For Nuclear Deployment.
[Computer software].
https://github.com/idaholab/command.
https://doi.org/10.11578/dc.20250514.7.
Faber, Jacob, Al Rashdan, Ahmad, Montezzo Coelho, Maria Eduarda, and Oncken, Joseph E.
"Control And Optimization Modular Modeling Application For Nuclear Deployment." Computer software.
May 23, 2024.
https://github.com/idaholab/command.
https://doi.org/10.11578/dc.20250514.7.
@misc{
doecode_155435,
title = {Control And Optimization Modular Modeling Application For Nuclear Deployment},
author = {Faber, Jacob and Al Rashdan, Ahmad and Montezzo Coelho, Maria Eduarda and Oncken, Joseph E.},
abstractNote = {The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols.
To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature.
Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.},
doi = {10.11578/dc.20250514.7},
url = {https://doi.org/10.11578/dc.20250514.7},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20250514.7}},
year = {2024},
month = {may}
}