Network-based modeling of energy transfer mechanisms of turbulent coherent structures

Abstract

Vortex-dominated turbulent flows are often characterized by dominant coherent structures and multi-scale physics. The common feature of these flows is the ability of shear to induce instabilities and compact vorticity that lead to observed coherence as well as vortex breakdown. Dominant coherent structures are organized features with characteristics scales, contain significant portion of the total turbulence kinetic energy, and are associated inter-scale transfers of energy throughout formation, evolution, and destruction processes. The multi-scale physics leads to inhomogeneity and nonlinear redistribution of energy that is strongly scale and position dependent. Energy transfer scenarios among scales create a large ÒwebÓ or network of connections in spectral space and adhere to the fundamental mechanism of triadic interactions, which stipulates that the energy cascade occurs through a triplet of scales. The transfer, transport, and dissipation of kinetic energy of individual coherent structure scales are quantified through a method employing the data-driven approximation of the Koopman operator, whereby a system of highly inter-connected equations of evolution of coherent kinetic energy is created that exhibits both spatial and spectral qualities. In this proposed work, network theoretic methodologies and models will be developed to elucidate key details of the inter-connectedness of energy transfer interactions by leveraging both spectral and spatio-temporal qualities. In particular, focus of the method develop will emphasis analysis of vortex-dominated flows over a wide range of Reynolds numbers including complex helical tip vortices produced by rotating blades. The objectives are to (1) Develop inter-scale connectivity relationships and network analyses that identify dominant pathways of energy transfer and organization through sparsity-promotion and graph searches; (2) Establish links between inter-scale networks and the kinetic energy budget by creating and investigating network models of energy transport, transfer, and dissipation to associated spectral quantities (i.e., triadic interactions) with spatial fluxes; (3) Identify spatio-temporal vorticity associations with inter-scale networks during vortex breakdown events. Expected outcomes include network theoretic operations for triadic interactions and energy transfer, identification of energy redistribution in vortical coherent structures, and vortex system modeling based on energy transfer mechanisms.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 08, 2023
Source ID
W911NF2310086

Entities

People

  • Daniel Foti

Organizations

  • Army Contracting Command
  • United States Army
  • University of Memphis

Tags

Fields of Study

  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Fluid Mechanics and Fluid Dynamics.
  • Neural Network Machine Learning.

Technology Areas

  • Space