The Tokamak Systems Monitor (TSM) is a software suite under development at ITER that provides operators with an integrated view of the tokamak’s engineering health based on operational instrumentation. A key functionality of TSM is anomaly detection, aimed at identifying unexpected behaviors across a wide range of systems. To this end, a dedicated anomaly detection module is being developed to...
The stability control of neoclassical tearing modes (NTMs) is critical for achieving high performance steady-state operation in future magnetic confinement fusion devices. Active suppression of seed magnetic island formation represents a key early intervention strategy to minimize the cost of NTM control. This study addresses the critical threshold problem of NTM seed magnetic island...
The Tokamak Systems Monitor (TSM) is a comprehensive monitoring and diagnostic framework developed in collaboration with Industry and supported by ITER, F4E, and U.S. partners. Designed to support tokamak operations from integrated commissioning onward, TSM integrates global machine models with real-time sensor data to assess system health, monitor component lifetimes, and detect...
MDSplus is a suite of tools for data acquisition and analysis; one of these tools is an interactive data visualization tool. The webScope project aims to modernize our visualizer’s capabilities using web-based technologies. Currently, MDSplus offers two visualization tools, which are showing limitations as they age and as computing expectations have evolved since they were first written. We...
HDF5 is an excellent storage system for collecting large amounts of scientific data but using it to collect real-time data from multiple sensors can be a challenge since the HDF5 library doesn't support multi-process writers. HSDS (HDF5 Scalable Data Service) enables the HDF5 data model to be accessed over the network using REST-based HTTP requests and enables simultaneous connections from...
In this talk, I will discuss how we are using advanced visualisation and immersive technologies to make fusion data more accessible, interactive, and meaningful. Fusion facilities, operations, and research generate vast, heterogeneous, and often multimodal data from different sources such as CAD models and diagnostics, multiphysics simulations, and AI predictions etc. These huge and complex...
Tokamak is a complex nuclear fusion reaction device composed of numerous systems. During physical experiments, different systems will obtain massive amounts of experimental data, which are highly specialized and require domain knowledge and specific tools to view and analyze. In addition, tokamak devices, as important nuclear fusion reaction devices, have strict management mechanisms and are...
One of the main obstacles to the propagation of ASCR-funded high-performance computing (HPC) libraries (e.g, MPICH, OpenMPI, Kokkos, Legion, RAJA) is the challenge posed by performance optimization of application codes that run on heterogeneous architectures at scale. A visual, interactive and intuitive tool to guide users through the execution of the application and highlight areas of...
This report focuses on technological innovations in visualization within magnetic confinement fusion research, systematically elaborating on the groundbreaking applications of cinematic dynamic simulation, extended reality (XR) interaction, and intelligent 3D reconstruction in device modeling, theoretical demonstration, and scientific communication.
Based on high spatiotemporal resolution...
Understanding plasma behavior throughout the entire duration of a pulse is critical for achieving the objectives of ITER and future fusion devices. Plasma parameters such as temperature, density, current profiles, and impurity content evolve dynamically during a discharge, influencing key aspects of performance including energy confinement, stability, and fusion power production. Analyzing...
Fusion devices such as ITER are expected to generate over one million sensor signals per discharge, each lasting 30 minutes or more. Identifying known patterns within these long time series is essential for understanding plasma behavior, but it poses significant computational challenges. In this work, we present a method for efficient pattern search in large-scale time series using FAISS, a...
EAST tokamak, one of the most important Magnetic Confinement Fusion (MCF) devices in China, provides an important experimental platform for the study of steady-state advanced plasma operation. Over sixty diagnostic systems on EAST tokamak provides huge amounts of multimodal diagnostic data about MCF plasma. Diagnostic data of EAST tokamak has the characteristics of volume, variety and...
Thermal Surrogate Modeling for the Monitoring of Actively Cooled First Wall Components in ITER
Nathaniel Saura1, Daniel Iglesias1
1ITER Organization, 13067 Saint Paul Lez Durance Cedex France
In the context of ITER operations, numerical simulation plays a critical role in predicting the thermal behavior of plasma-facing components subject to intense...
In modern fusion research, uninterrupted access to historical data is critical for thorough post-discharge analysis, precise experiment control, and robust machine health monitoring. The ability to efficiently retrieve, visualize, and analyze large volumes of time-series data plays a central role in improving operational reliability and supporting data-driven decision-making.
This work...
This work explores the application of Convolutional Neural Networks (CNNs) for tomographic reconstruction of visible plasma radiation distribution at the GOLEM tokamak. The training datasets are generated from emissivity phantoms of the poloidal cross-section together with synthetic measurements from two visible cameras. CNNs are employed for their capability to capture local image patterns in...
