Thea Energy, Inc., NVIDIA Corporation, Synopsys, Inc., Argonne National Laboratory, And Princeton Plasma Physics Laboratory Collaborate To Accelerate Fusion Energy With Helios Power Plant Digital Twin And AI Surrogate Models
Thea Energy, Inc. announced collaborations to develop a digital twin model for its ?Helios? fusion power plant. Thea Energy, Inc. will work with NVIDIA Corporation and Synopsys, Inc., as well as the U.S. Department of Energy?s Argonne National Laboratory and Princeton Plasma Physics Laboratory to analyze and scale vast datasets, rapidly evolve Thea Energy, Inc.?s plant designs, and stress-test system operation in a workflow that outpaces traditional tools.
This collaboration aligns with the U.S. Department of Energy?s Genesis Mission which is focused on leveraging AI to fast-track scientific advancement. Thea Energy, Inc. is using AI to bridge simulation and real-world system operational data, closing critical gaps to build the Helios digital twin faster and with orders of magnitude less capital compared to traditional models. NVIDIA Corporation will accelerate and integrate Thea Energy, Inc.?s models, codes, and real-world data into a digital twin platform using NVIDIA Omniverse libraries.
Powered by NVIDIA Corporation AI infrastructure, this platform will allow Thea Energy, Inc. to analyze power plant performance in real-time at an unprecedented rate and scale. Synopsys, Inc. will deliver leading simulation software expertise to integrate data into a unified multiphysics framework. This Ansys simulation-driven, AI-accelerated approach allows for the rapid evaluation of Thea Energy, Inc.?s breeding blanket system, where the blanket converts energy from fusion and protects the magnet systems. Argonne National Laboratory will contribute expertise in neutronics analysis and blanket design as well as data that will be integrated into the Helios digital twin to bridge the knowledge gap in commercial blanket systems and ensure high efficiency energy conversion.
Princeton Plasma Physics Laboratory will supply key knowledge spanning plasma modeling and computational tools, specifically, high-fidelity codes required to simulate complex plasma behaviors under power-plant-relevant conditions. Thea Energy, Inc. is on track to operate Helios in the 2030s following ?Eos?, its large-scale demonstration system which will create power-plant-relevant, steady-state fusion. Eos will directly benefit from the breakthroughs highlighted in the Company?s Helios design, including its digital twin.
NVIDIA Corporation is the world leader in the design, development, and marketing of programmable graphics processors. The group also develops associated software. Net sales break down by family of products as follows:
- computing and networking solutions (89%): data center platforms and infrastructure, Ethernet interconnect solutions, high-performance computing solutions, platforms and solutions for autonomous and intelligent vehicles, solutions for enterprise artificial intelligence infrastructure, crypto-currency mining processors, embedded computer boards for robotics, teaching, learning and artificial intelligence development, etc.;
- graphics processors (11%): for PCs, game consoles, video game streaming platforms, workstations, etc. (GeForce, NVIDIA RTX, Quadro brands, etc.). The group also offers laptops, desktops, gaming computers, computer peripherals (monitors, mice, joysticks, remote controls, etc.), software for visual and virtual computing, platforms for automotive infotainment systems and cloud collaboration platforms.
Net sales break down by industry between data storage (88.3%), gaming (8.7%), professional visualization (1.4%), automotive (1.3%) and other (0.3%).
Net sales are distributed geographically as follows: the United States (46.9%), Singapore (18.2%), Taiwan (15.8%), China and Hong Kong (13.1%) and other (6%).
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Thea Energy, Inc., NVIDIA Corporation, Synopsys, Inc., Argonne National Laboratory, And Princeton Plasma Physics Laboratory Collaborate To Accelerate Fusion Energy With Helios Power Plant Digital Twin And AI Surrogate Models
