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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
Commonwealth Fusion Systems partners with Google DeepMind
Google DeepMind—Google’s artificial intelligence development subsidiary—recently announced a new partnership with fusion start-up Commonwealth Fusion Systems. The goal of this collaboration is to leverage AI to both advance plasma simulation and discover novel control strategies, ultimately accelerating CFS’s timeline to deliver commercial fusion to the grid.
Richard Sanchez, Simone Santandrea
Nuclear Science and Engineering | Volume 183 | Number 2 | June 2016 | Pages 196-213
Technical Paper | doi.org/10.13182/NSE15-78
Articles are hosted by Taylor and Francis Online.
A conservative linear surface approximation (CLS) has been recently introduced to speed up the method of characteristics in unstructured meshes. In this work, we present an analysis of the convergence of the CLS in unstructured geometries, which shows that, under optimal conditions, the method converges quadratically with the size of the regions, while the classical step characteristics approximation converges linearly. The predicted convergence rates apply only to a homogeneous convex domain with a regular boundary and regular sources and can be viewed as upper bounds for realistic heterogeneous cases. We also analyze the errors induced by the numerical implementation of the step and CLS approximations and show their impact in the final error. Numerical calculations illustrate the convergence rates.