Multifractal Analysis of Turbulent Flows Using Empirical Mode Decomposition: Combined Wind Tunnel Experiments and Field Measurements

POSTER

Abstract

Atmospheric turbulence represents a quintessential spatial-temporal chaotic system whose fractal properties serve as fundamental characteristics that effectively capture the essential features of chaotic dynamics. This study investigates the multifractal characteristics of atmospheric turbulence and the intermittent properties of coherent structures. Wind tunnel experiments are conducted to examine the aerodynamic resistance and the transport processes in response to different configurations of idealized roughness elements. For experimental validation, field measurements using an eddy covariance system are conducted over a two-month observation period in Yuen Long, Hong Kong. In order to analyze multifractal properties of all sizes, a combination of empirical mode decomposition (EMD) and multifractal detrended fluctuation analysis (MFDFA) is adopted. The analysis reveals consistent multifractal behavior in both streamwise and vertical directions, with good agreement between wind tunnel experiments and field measurements. Surface roughness plays a critical role, enhancing multifractal behavior due to intensified turbulent mixing and complex energy cascades. Multi-scale MFDFA results demonstrate that the multifractal index follows a characteristic growth pattern, peaking at intermediate scales before stabilizing at larger scales. Both experimental and field results confirm that turbulence exhibits the most significant multifractal behavior at intermediate scales. Asymmetry analysis reveals a consistent transition from negative to positive values across different rough surfaces, indicating increasing flow organization with scale processes. These findings advance the understanding of turbulent intermittency and energy transfer dynamics in urban areas in response to a range of surface roughness and real urban areas, with implications on the fundamental mechanism of urban airflows and pollutant dispersion.

Presenters

  • Ruiqi Wang

    The University of Hong Kong

Authors

  • Ruiqi Wang

    The University of Hong Kong

  • Chun-ho Liu

    The University of Hong Kong, The unversity of Hongkong