This project develops a Bayesian physics-informed polynomial chaos expansion (B-PC^2) framework for uncertainty quantification and reliability analysis in high-dimensional, computationally expensive simulation models. Present surrogate approaches either incorporate physics constraints or provide a Bayesian uncertainty treatment, but rarely both. The proposed B-PC^2 approach unifies these aspects to achieve effective uncertainty propagation in realistic engineering applications. The project will provide an open, theoretically consistent foundation for Bayesian, physics- informed polynomial chaos expansions. By combining Bayesian estimation, physics constraints, and active learning, it will advance the state of the art in reliability-oriented uncertainty quantification and provide validated methods applicable to complex, high-dimensional engineering models

Keywords
uncertainty quantification, surrogate modeling, structural reliability

26-24969L

English

Novák Lukáš, doc. Ing., Ph.D. - principal person responsible

Institute of Structural Mechanics
- responsible department (21.9.2025 - not assigned)
Institute of Structural Mechanics
- beneficiary (21.9.2025 - not assigned)

Responsibility: Novák Lukáš, doc. Ing., Ph.D.