Saint-Paul-lès-Durance, France – In the heart of southeastern France, a monumental endeavor to replicate the power of the sun is underway: the International Thermonuclear Experimental Reactor (ITER) project. This ambitious undertaking, uniting approximately 2,000 leading physicists, scientists, and engineers from across the globe, aims to construct the world’s largest nuclear fusion device, slated for operation in 2033. Faced with unprecedented scale and exacting precision requirements, a suite of cutting-edge Artificial Intelligence (AI) tools is being deployed to provide critical support to this complex engineering feat.
The ultimate goal of nuclear fusion energy is to mimic the processes occurring within the sun, fusing isotopes of hydrogen – deuterium and tritium – under extreme heat and pressure to create helium and release immense energy. The primary method for achieving this is within a Tokamak, a toroidal (doughnut-shaped) reactor. Inside the Tokamak, fusion fuel is heated to hundreds of millions of degrees Celsius, forming a superheated plasma – temperatures exceeding those at the sun’s core by a factor of ten – creating the necessary conditions for nuclear fusion.
ITER’s core mission is to build the world’s largest Tokamak device to further explore and understand the complexities of nuclear fusion. However, the sheer scale of construction and the vast number of components involved make this project a daunting challenge. This is where the power of AI comes into play.
AI Enables High-Precision Construction
ITER’s Tokamak device will be assembled from nine massive sectors. Five of these sectors are being manufactured in Europe, while four are being produced in South Korea. Russia and India are also contributing crucial components. These components, crafted from specialized stainless steel, require meticulous machining and welding. To ensure flawless welds, advanced ultrasonic scanning technology is employed for inspection. This process generates vast amounts of data that require efficient and accurate analysis.
To address this, the research team utilized Microsoft’s Visual Studio Code development environment to build an AI model supporting multiple programming languages. This model can deeply analyze the data, significantly reducing the time required for manual inspection of weld quality and precision, thereby dramatically increasing work efficiency.
Furthermore, the AI model has been successfully applied in determining the selection of materials for the reactor vessel’s internal lining.
Intelligent Chatbots Optimize Information Management
As an international collaborative project involving over 30 countries and regions, ITER boasts a standardized document management system that has been running for over two decades and contains over 1.5 million documents. Finding specific information within this vast sea of data is akin to searching for a needle in a haystack.
To overcome this challenge, ITER’s IT Project Tools department constructed a Proof of Concept (PoC) AI chatbot model in the first quarter of 2024 and has been continuously iterating and improving it since. Earlier this year, the team upgraded the architecture from a standalone mode to a multi-agent mode. In this new mode, the AI tool first intelligently summarizes the documents and indexes key information into a large vector database. The advantage is that users can use natural language to query the database and quickly obtain the information they need, greatly improving the efficiency of information retrieval.
This AI-powered chatbot significantly streamlines information access, saving valuable time and resources for researchers and engineers working on the project.
Looking Ahead
The integration of AI into the ITER project demonstrates the transformative potential of this technology in tackling complex scientific and engineering challenges. By automating data analysis, optimizing information management, and enhancing precision in construction, AI is playing a crucial role in accelerating the progress of ITER and bringing the promise of clean, sustainable fusion energy closer to reality. As the project progresses towards its 2033 operational target, the continued development and deployment of AI tools will be essential for ensuring its success and paving the way for a future powered by the sun.
References:
- IT Home. (2024, March 27). 人工智能赋能 ITER 项目：加速全球最大核聚变装置建设进程 [AI Powers Up ITER: Accelerating Construction of the World’s Largest Nuclear Fusion Reactor]. Retrieved from [Insert original article URL here if available]
- ITER Organization. (n.d.). About ITER. Retrieved from https://www.iter.org/proj/ (Example URL)
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