Cheap2Rich: A Multi-Fidelity Framework for Data Assimilation and System Identification of Multiscale Physics -- Rotating Detonation Engines

• URL: http://arxiv.org/abs/2601.20295v1
• Date: Wed, 28 Jan 2026 06:35:22 GMT
• Title: Cheap2Rich: A Multi-Fidelity Framework for Data Assimilation and System Identification of Multiscale Physics -- Rotating Detonation Engines
• Authors: Yuxuan Bao, Jan Zajac, Megan Powers, Venkat Raman, J. Nathan Kutz,
• Abstract summary: Cheap2Rich is a multi-scale data assimilation framework that reconstructs high-fidelity state spaces from sparse sensor histories.<n>We demonstrate the performance on rotating detonation engines (RDEs)<n>Results highlight a general multi-fidelity framework for data assimilation and system identification in complex multi-scale systems.
• Score: 1.8796659304823702
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Bridging the sim2real gap between computationally inexpensive models and complex physical systems remains a central challenge in machine learning applications to engineering problems, particularly in multi-scale settings where reduced-order models typically capture only dominant dynamics. In this work, we present Cheap2Rich, a multi-scale data assimilation framework that reconstructs high-fidelity state spaces from sparse sensor histories by combining a fast low-fidelity prior with learned, interpretable discrepancy corrections. We demonstrate the performance on rotating detonation engines (RDEs), a challenging class of systems that couple detonation-front propagation with injector-driven unsteadiness, mixing, and stiff chemistry across disparate scales. Our approach successfully reconstructs high-fidelity RDE states from sparse measurements while isolating physically meaningful discrepancy dynamics associated with injector-driven effects. The results highlight a general multi-fidelity framework for data assimilation and system identification in complex multi-scale systems, enabling rapid design exploration and real-time monitoring and control while providing interpretable discrepancy dynamics. Code for this project is is available at: github.com/kro0l1k/Cheap2Rich.

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