Stellarator Equilibrium Reconstruction Capabilities with DESC
POSTER
Abstract
We present newly-implemented capabilities in DESC [2,3,4,5] for solving the 3D stellarator equilibrium experimental reconstruction problem. The 3D equilibrium reconstruction problem conventionally requires many expensive 3D equilibrium solves in order to acquire the derivative information necessary for matching the synthetic diagnostic signals to the measured signals [1]. DESC’s use of automatic differentiation (AD) reveals the necessary derivative information with a single equilibrium solve, advantageous for more quickly solving the reconstruction problem. Functionality for calculating synthetic magnetic diagnostic signals, similar to the DIAGNO 2.0 code [6], has been implemented in DESC with AD-compatibility, and is verified against analytic test cases. Results will be shown using these capabilities to perform reconstruction and compare the DESC result to various examples from the literature.
[1] Hanson et. al., NF (2009).
[2] Dudt, D. & Kolemen, E. PoP (2020).
[3] Panici, D. et al. JPP (2023).
[4] Conlin, R. et al. JPP (2023).
[5] Dudt, D. et al. JPP (2023).
[6] Lazerson et al. PPCF (2013).
[1] Hanson et. al., NF (2009).
[2] Dudt, D. & Kolemen, E. PoP (2020).
[3] Panici, D. et al. JPP (2023).
[4] Conlin, R. et al. JPP (2023).
[5] Dudt, D. et al. JPP (2023).
[6] Lazerson et al. PPCF (2013).
Presenters
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Dario Panici
Princeton University
Authors
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Dario Panici
Princeton University
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Rory Conlin
Princeton University, University of Maryland
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Daniel William Dudt
Thea Energy
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Kian Orr
Princeton University
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Yigit Elmacioglu
Princeton University
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Rahul Gaur
Princeton Univeristy
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Egemen Kolemen
Princeton University