Advanced Computational and Experimental Techniques for Characterizing Flow Regimes in Complex Fluid Systems Using Non-Intrusive Measurement Methods

This study presents a hybrid approach combining advanced Computational Fluid Dynamics (CFD) simulations with non-intrusive experimental techniques to characterize flow regimes in complex fluid systems. Targeting laminar, transitional, and turbulent flows, the research achieves real-time classification with high accuracy, critical for industrial applications where flow behavior impacts efficiency and safety. Using Reynolds number-based flow regime categorization and solving Navier-Stokes and continuity equations, the CFD models were validated with experimental data obtained via ultrasonic Doppler and eddy current flow meters. These non-intrusive methods provide real-time measurements without disturbing the flow, achieving an error margin below 5% across all flow types. The findings confirm the feasibility of this dual-method framework for dynamic flow regime identification and anomaly detection. This integrated approach enhances real-time monitoring, system performance optimization, and operational safety, setting a benchmark for accuracy and scalability in industrial fluid management.