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Two-timescale-based hybrid modeling framework for crystallization processes
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DOI：10.1016/j.cherd.2025.12.020.png)
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Abstract
En 中文
• A two-timescale hybrid framework integrates mechanistic and data-driven models. • Aggregation dynamics from Smoluchowski PBM are replaced with trained DNN. • Nucleation and growth are modeled via low-order method of moment (MoM) equations. • Data is generated using full-order Smoluchowski PBM coupled with MoM equations. • The hybrid model reduces stiffness and enables real-time MPC for CSD control.
Keywords:
First-principles models
Machine learning
Hybrid modeling
Crystallization
Two-timescale
Singular perturbation theory
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