Reverse-mode automatic differentiation through a closed-Brayton reactor DAE twin makes gradient-based parameter inversion match or beat Kalman filters on transient and partial-observation benchmarks, with 0.43% mean error on the reflector coefficient.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
An Adjoint-Based Differentiable Physics Framework for Online Parameter Inversion in Closed-Brayton Gas-Cooled Reactor Digital Twins
Reverse-mode automatic differentiation through a closed-Brayton reactor DAE twin makes gradient-based parameter inversion match or beat Kalman filters on transient and partial-observation benchmarks, with 0.43% mean error on the reflector coefficient.