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Reality of the road ahead
Craig Piercycpiercy@ans.org
As 2025 winds down, it seems nuclear energy in the U.S. is now well on its way toward a renaissance, or resurgence, or whatever optimistic term you may use in your daily conversations.
New reactor designs, projects, and partnerships are being announced on a near-weekly basis; valuations of publicly traded nuclear companies are hovering near all-time highs; and AI’s thirst for reliable, clean electricity remains largely unquenched. The overall investment climate for nuclear energy has thawed dramatically. These days, it seems everyone from big Wall Street banks to individual investors is trying to get a piece of the nuclear action.
It’s the perfect time to talk about failure.
Yes, I know “nuclear failure” is not a topic on which we in the nuclear community like to dwell. For those of a certain age, it brings back bad memories of events beyond our control that shifted the trajectory of companies, careers, and lives for decades.
Blaise Faugeras
Fusion Science and Technology | Volume 69 | Number 2 | April 2016 | Pages 495-504
Technical Paper | doi.org/10.13182/FST15-171
Articles are hosted by Taylor and Francis Online.
This paper proposes a new fast and stable algorithm for the reconstruction of the plasma boundary from discrete magnetic measurements taken at several locations surrounding the vacuum vessel. The resolution of this inverse problem takes two steps. In the first one, we transform the set of measurements into Cauchy conditions on a fixed contour ΓO close to the measurement points. This is done by least-squares fitting a truncated series of toroidal harmonics functions to the measurements. The second step consists in solving a Cauchy problem for the elliptic equation satisfied by the flux in the vacuum and for the overdetermined boundary conditions on ΓO previously obtained with the help of toroidal harmonics. It is reformulated as an optimal control problem on a fixed annular domain of external boundary ΓO and fictitious inner boundary ΓI. A regularized Kohn-Vogelius cost function, which depends on the value of the flux on ΓI, measures the discrepancy between the solution to the equation satisfied by the flux obtained using Dirichlet conditions on ΓO and the one obtained using Neumann conditions. This function is minimized. The method presented here has led to the development of software, called VacTH-KV, which enables plasma boundary reconstruction in any tokamak.