Network Structure of Transitions in Thermo fluid Systems in Nature and Engineering
Abstract
Critical phenomena in natural systems such as extreme rainfall, or in engineering systems such as the occurrence of thermoacoustic i,nstability occur due to the complex interaction between several variables. For example, the cloud cover and precipitation levels are, influenced by cyclonic systems, wind or topography in climate system. High-amplitude periodic oscillations are sustained due to the, interaction of hydrodynamic, acoustic and heat release rate fluctuations in a turbulent combustor. In order to understand, predict,or control such critical phenomena, it is essential to analyze the interaction between various subsystems influencing the dynamics o,f the system. The PI has been successful in using complex networks to study the onset of oscillatory instability in various engineer,ing systems such as thermoacoustic, aero-acoustic and aeroelastic systems. Also, we developed mitigation strategies to avoid thermoa,coustic instability by targeting critical regions identified using complex network analysis on spatio-temporal data obtained from tu,rbulent combustors. However, our studies were limited to single-layer complex networks constructed usinga single variable representi,ng the entire dynamics of the combustor. In order to understand the interaction between various subsystems, we will analyze multilay,er networks built from variables representing the dynamics of various subsystems. Using multilayer networks approach, we will attemp,t to highlight the influence of each subsystem on the other and on the dynamics of the entire system. Similarly, we will study the o,ccurrence of extreme events in climate systems using single and multilayer networks. We will use our understanding developed from th,ermoacoustic systems to study critical phenomena in climate systems. Further, by studying the network topology during extreme events,, we wish to draw similarity between the occurrence of critical phenomena in natural and engineering systems. We will also perform r,educed order modelling to understand the nonlinear interactions between components of the system that will help understand the compl,ex dynamics observed.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 08, 2022
- Source ID
- N629092212011
Entities
People
- Sujith Raman Pillai Indusekhara
Organizations
- Indian Institute of Technology Madras
- Office of Naval Research
- United States Navy