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Emulator-accelerated Bayesian framework for nonlinear parameter estimation of entry capsule dynamic stability
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DOI：10.1016/j.ast.2026.112342.png)
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Abstract
En 中文
• Emulator-accelerated Bayesian inversion estimates nonlinear stability derivatives. • Physics-guided feature compression preserves damping-relevant dynamics. • Neural-network emulation reduces MCMC sampling time by about 60x. • Emulator-based posteriors closely match direct MCMC for the Genesis capsule. • The method enables efficient uncertainty-aware dynamic stability estimation.
Keywords:
Bayesian inversion
neural network emulator
uncertainty quantification
nonlinear stability
parameter estimation
Journal
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5.8
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1.0W
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3.0W