Understanding Nonlinear Coherent Structure Interactions in Boundary-Layer Transition using Adaptive Signal Analysis
Abstract
The proposed five-year research program will provide an improved understanding of the multi-scale nature of a turbulent boundary layer by studying the spatio-temporal evolution of unsteady modes and emergence of coherent structures during transition. Cutrent research in boundary-layer turbulence has identified the presence of several major classifications of coherent structures. Particularly large-scale stuctures, such as hairpin vortex packets and superstructures, have been found to provide a skeletal structure of wall turbulence. However, the fundamental mechanisms behind the emergence and self-sustaining behavior of these various flow structures are currently not well understood. The proposed research seeks to answer three major questions: (I) How is the turbulence spectrum produced by a collection of multi-scale coherent structures? (2) How do coherent structures emerge during transition? (3) How can the nonlinear dynamics of turbulence be expressed? The proposed study is motivated by the underlying scientific hypothesis, that the self-sustained structure of a turbulent boundary layer can be explained through a series of multi-scale dynamic contributions present in a turbulent flow, immediately following transition. The proposed research will develop and utilize an Empirical Mode Decomposition (EMD) technique, which is an adaptive signal analysis method capable of providing a set of amplitude- and frequency-modulated modes that effectively represent nonlinear processes. The modes are extracted and ranked based on spatial or temporal scale (i.e., wavelength or period), rather than amplitude or stability criterion. The decomposition technique wi11 be developed with both multivariate and multi-dimensional capabilities. It will be applied to a set of volumetric PIV measurements of boundary-layer velocity across a controlled K-type transition, which will be acquired during the proposed study. The decomposition will also be applied to a DNS dataset of K-type transition computed in the prior study by Sayadi et al.[60]. By allowing multivariate signals to be decomposed, the coherence in modes between u, v, and w will be maintained. Furthermore, by utilizing a multi-dimensional decomposition technique, the modes will be identified while retaining dependence on three dimensions of space as well us time. In order to provide an understanding of the evolutionary nature of the turbulent scales, a Hilbert-Huang transform will be used for space-wavenumber and time-frequency analysis. This study will allow the three-dimensional wave characteristics of primary and secondary instability waves to be identified, along with the excitation of harmonics during transition. The extracted modes will also be used to identify the emergence and development of coherent structures during transition by calculating and visualizing the Q-criterion and swirling strengths associated with the various scales of the flow. Preliminary results discussed in the project description are quite promising, as they clearly show a separation of flow scales, nonlinear developments in the space-wavenumber spectrogram, and organizational behaviors of large-scale motions. The proposed study will ultimately be used to investigate the multi-scale dynamics of the turbulent boundary layer immediately following transition. By focusing on the turbulent region after breakdown, the local interactions of structures provide a dominant contribution to the turbulence dynamics, with little influence of historical states of the turbulent boundary layer. A theoretical characterization of the hierarchy of scales will be conducted in order to ideutify self-similar behavior between scales. The use of wave packet analysis will also be explored to develop an analytic representation of the multi--scale influence of turbulent fluctuations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 07, 2018
- Source ID
- W911NF1810030
Entities
People
- Phillip J. Ansell
Organizations
- Army Contracting Command
- United States Army
- University of Illinois Urbana–Champaign