ANFM 2025 / Workshops -- ANS / Conferences / Advances in Nuclear Fuel Management (ANFM 2025)

1. Peacock Monte Carlo Code

Organizer: William Dawn (Studsvik)

Peacock is a three-dimensional, continuous-energy, Monte Carlo code developed by Studsvik Scandpower, Inc. (SSP). Peacock is intended to augment the current offerings from SSP to model advanced, next-generation nuclear reactors. The code allows modeling of general geometries and includes capabilities for depletion. Peacock is designed for efficient use on commonly available, consumer-grade computing architectures and includes shared-memory (OpenMP) parallelism.

In addition to a presentation on the theoretical foundations of the Peacock methodologies, attendees will be running Peacock cases. By running Peacock, attendees will be able to investigate reactor physics phenomena (e.g., temperature dependences, depletion, etc.). Participants will need to bring their own laptop with a ssh client to access the Peacock computing resources that will be furnished by SSP.

No licensing is required as no code or executables will be provided to attendees. Attendees will only be able to run Peacock on resources provided by SSP.

2. Virtual Environment for Reactor Applications (VERA)

Organizers: Nick Herring (ORNL), Matthew Jessee (ORNL), and Andrew Godfrey (Veracity Nuclear, LLC)

VERA—Virtual Environment for Reactor Applications—is a state-of-the-art Pressurized Water Reactor (PWR) core simulator using novel computational methods that integrate reactor physics, thermal hydraulics, and fuel performance into a single simulation platform. The goal of this workshop is to learn how to run the VERA core simulator for PWR analysis. The workshop will provide basic modeling demonstrations and exercises for pin, assembly, and full-core modeling.

The training will be conducted using computational resources at the Nuclear Computational Resource Center (NCRC) at Idaho National Laboratory (INL). Before the workshop, attendees are required to have an INL NRC account (https://inl.gov/ncrc/) and a license for VERA 4.3. Single-user licenses are available through the Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory (ORNL). Workshop attendees may also have a valid license through an active government use agreement or commercial license agreement for VERA through ORNL.

3. RAPID

Organizer: Alireza Haghighat

RAPID (Real-time Analysis for Particle-transport In-situ Detection) leverages the innovative Multi-stage Response-function particle Transport (MRT) methodology to deliver real-time simulation capabilities for complex nuclear systems. RAPID solves for pin-wise, axially-dependent fission neutron distribution, critical/subcritical multiplication, and detector response. Novel algorithms for 3-D fuel burnup (bRAPID) calculation and 3-D reactor

kinetics (tRAPID) have been developed and validated using the Jozef Stefan Institute (JSI)’s TRIGA research reactor. Additionally, RAPID use for generation of ‘training’ and ‘testing’ datasets for development of AI/ML models and algorithms will be discussed.

Further, a multi-user virtual reality system (VRS) has been developed that provides a web application for input preparation, real-time simulation, and output processing and visualization in a virtual environment. For an introduction, please view the following demo https://www.youtube.com/watch?v=1Q2ytjBrmXc

Schedule

RAPID’s MRT methodology and formulation (15 min)
RAPID code system, its algorithms and their benchmarking and validation (75 min)
Break (10 min)
Demonstration of RAPID-2 (20)
VRS-RAPID demonstration (20 min)
Hands-on use by participants (40 min)

Requirements

There will be access to wireless internet so that the participants can have remote access to VRS-RAPID. The current version of VRS-RAPID is optimized for a Personal Computer using the Google Chrome browser, but it can be accessed through iPad, Tablet, etc. using any other browser.

To facilitate establishing individual accounts, participants are encouraged to contact Prof. Haghighat (haghighat@vt.edu) prior to the workshop.

4. ACE and RAVEN: Emerging Technologies for Fuel Management Application: Optimization of Core Designs using Artificial Intelligence

Organizers: Westinghouse/INL

Time: 4 hrs total, 1 hr ACE and 2.5 hr RAVEN and 0.5 hr both presenters discuss comparison of surrogate modeling techniques and GA for this application.

This will be a highly interactive demonstration, but the participants will not be able to run the codes due to license complications. So, they are welcome to bring laptops if they want to download the open source Raven code as example, but they won’t have access to the nodal simulation codes to be able to actually generate any LPs.

Introduction to RAVEN: RAVEN is a multi-purpose stochastic platform that integrates uncertainty propagation, machine learning, optimization, and data analysis methods, and it provides a unique language to apply these methods to user-provided simulation models. With RAVEN, users can create customizable statistical analysis/optimization workflows where the response of simulation models is explored (e.g., for uncertainty propagation, model optimization, model calibration and model validation) for a variety of initial and operating conditions and the resulting data can be analyzed using machine learning, data mining and artificial intelligence algorithms. RAVEN orchestrates these machine learning/digital twinning pipelines on multiple operating systems and hardware configurations, ranging from laptops to high performance computing (HPC) environments. RAVEN also provides a plug-in interface that has already been leveraged by many system analysis and design tools, which enable simple multi-code integration across simulation tools.

An overview of the software is available at https://github.com/idaholab/raven/wiki

The software is open source and can be downloaded at: https://github.com/idaholab/raven

Training Objectives: The first objective is to provide a general understanding of the RAVEN package and its main capabilities. Second, a series of practical examples will be provided in ascending level of complexity, starting from the simplest statistical analysis to the generation of the complex machine learning models and their utilization in system analysis and uncertainty quantification. Third, the system optimization, especially, plant fuel reload optimization with genetic algorithms will be covered. This training section will include a theoretical/code usage overview of the subject capability and demonstrations. If the attendees would like to try some demonstrations, we recommend the attendees have their own laptop ready and follow the installation procedures provided in https://pypi.org/project/raven-framework/ before the workshop.

Detailed agenda will be provided as we come closer to the workshop date.

5. OpenMC

Organizer: Joffrey Dorville (ANL)

OpenMC is a general purpose Monte Carlo neutron and photon transport simulation code. It is capable of simulating 3D models based on constructive solid geometry with second-order surfaces as well as CAD-based geometries. It also has built-in capabilities for activation/depletion to track material evolution with time. This workshop will present a brief overview of the code and its growing list of features, and a walk-through on how to setup input files using the Python API using nuclear reactor examples. The workshop will also demonstrate how to leverage powerful Python packages for post-processing of results. Participants should bring their laptop to follow along and run OpenMC. A link will be provided to access the software on a cloud computing platform.

Attendees will indeed be running jobs interactively at the workshop. We find this to be a much more enjoyable experience than watching hours of powerpoint presentations!

OpenMC is open source so there are no licensing requirements. As the description above alludes to, participants will need to have a laptop with an internet connection and a web browser, but they don't need to have anything else preinstalled.