A Multiscale Event-Centered Framework for Quantifying Dynamic Reorganization in Aerodynamic Systems

Aerodynamic performance is commonly evaluated using steady or time-averaged metrics such as lift, drag, or spectral energy content. While effective for characterizing mean behavior, these quantities often fail to capture changes in the temporal organization of the underlying dynamics induced by controlled modifications, particularly in unsteady and nonstationary flow regimes. Here we introduce a data-driven approach to diagnose dynamic reorganization in aerodynamic systems based on a multiscale, event-centered analysis of extreme fluctuations. Using a publicly available experimental dataset of unsteady aerodynamic load measurements obtained under multiple controlled forcing configurations, we define a scalar Aerodynamic Reorganization Index (IRA) that integrates complementary information from extreme-event statistics, critical activity density, and multichannel synchrony across measurement stations. The proposed index enables direct configuration-to-baseline comparison, providing a quantitative measure of how strongly a given modification alters the internal temporal organization of the system dynamics. Unlike classical amplitude- or energy-based indicators, the IRA is sensitive to collective, multichannel, and structural temporal changes, revealing dynamical reorganization even when conventional metrics remain largely unchanged. By focusing on temporal organization, intermittency, and collective dynamics, this approach complements conventional aerodynamic analysis and provides a physics-oriented diagnostic for comparing unsteady aerodynamic configurations prior to detailed modeling, simulation, or experimental refinement.