Indian Institute of Technology Madras

Potsdam-institut Für Klimafolgenforschung E.v.

Vishnu Rajasekharan Unni

Sujith Raman Pillai Indusekharan Nair

Vineeth Nair Vinod

Induja Pavithran

Raman Pillai Indusekharan Nair Sujith

Manikandan Raghunathan

Abin Krishnan

Praveen Kasthuri

Nitin Babu George

Jürgen Kurths

Vineeth Nair

Meenatchidevi Murugesan

Norbert Marwan

Premchand Chandramouly Premakumari

Sujith Ramanpillai Indusekharan Nair

Achintya Mukhopadhyay

Alan John Varghese

Embodiments herein provide a system () to estimate the amplitude of oscillations in a turbulent flow system () that exhibits oscillatory instabilities. The system () comprises of a sensor (A) mounted on the turbulent flow system () to detect an oscillatory variable in the system obtaining a signal, a signal conditioner () that conditions the signal from the sensor, an amplitude estimator () that estimates the amplitude of the limit cycle oscillations, and also predict the proximity of the system to the oscillatory instability, a processor () connected to the amplitude estimator () to compare the predicted oscillation amplitude with a threshold value. The amplitude is estimated by estimating the spectral measure of the time series signal obtained from the system.

System and method for determining the amplitude of oscillatory instabilities in fluid mechanical devices

A system for early detection of onset of oscillatory instabilities in practical devices is described. The system consists of a measuring device (), an instability detection unit () and a control unit (). The measuring device () is configured to generate signals corresponding to the dynamics happening inside the practical device. The instability detection unit () along with an amplitude estimation unit () is configured to diagnose the stability of the practical device from the signals that are generated by the measuring device (). Further, the control unit () is configured to control various operating parameters in the practical device based on the information obtained from the instability detection unit ().

System and method for predetermining the onset of impending oscillatory instabilities in practical devices

A system and method for optimizing passive control strategies of oscillatory instabilities in turbulent systems using finite-time Lyapunov exponents are disclosed. The method includes receiving data from one or more measuring devices connected to the turbulent flow system incorporating a control strategy in the flow field. One or more flow characteristics are determined from the data obtained from the measuring devices. The method involves computing critical dynamics from backward time finite-time Lyapunov exponent (FTLE) field based on the one or more flow characteristics. Next, one or more regions of critical dynamics associated with impending oscillatory instabilities in the turbulent flow system are identified. The identified region of critical dynamics is disrupted the control the onset of oscillatory instabilities in the turbulent flow system.

System and method for optimizing passive control strategies of oscillatory instabilities in turbulent systems using finite-time Lyapunov exponents

The invention discloses a system for effecting a control strategy in a reactive flow field of a turbulent flow system. The system is configured to analyze flow field properties such as velocity, heat release rate, or mixture fraction of a device during the onset of the oscillatory instability using measures from complex network theory such as betweenness centrality, degree, or closeness. The system identifies critical regions in the flow field responsible for the oscillatory instability. Further, the system also identifies optimal control strategies to avoid the onset of oscillatory instabilities by analyzing the relative strength of various network parameters and thereby controlling oscillatory instabilities which are detrimental to the fluid dynamic system. The disclosed method and system provide for optimization of control of oscillatory instabilities in fluid dynamic systems.

System and method for optimizing passive control of oscillatory instabilities in turbulent flows

The invention includes a method for predicting the operational state of equipment with turbulent flow characterized by time series data relating to its operation. The invention further includes a system and method for predicting the onset of an impending oscillatory instability. Further, the invention includes a system and method for identifying an impending absorbing transition such as flame blowout in combustion systems. A variable representing the dynamics of operation is measured with the help of a sensor, to obtain time series data. A complex network is then derived from the measured time series data. Network properties are then calculated using the complex network to identify the state of stability relating to operation of the equipment. The stability information may include one of thermoacoustic instability, aero-elastic instability such as flutter, flow-induced vibration, magneto-hydrodynamic, aerodynamic, aeromechanical, aero-acoustic instability or onset of flame blowout of a combustor.

Devices and methods for early prediction of impending instabilities of a system

A method and system for determining one or more precursors to control blowout in a combustor is provided. The method includes obtaining a time series signal corresponding to a dynamic state variable of the combustor. The method includes detecting one or more precursor based on an analysis of the time series signal using one or more parameters to control blowout in the combustor. One or more parameters include a Hurst exponent estimation, a Burst count estimation, and a recurrence quantification based estimation.

System and method for detecting precursors to control blowout in combustion systems

A method for detecting onset of oscillatory instability in a device is described. The method includes obtaining a symbolic time series of a time series signal corresponding to a dynamic state variable of the device. The method further includes detecting the onset of oscillatory instability in the device based on the symbolic time series.

Growing community of inventors

Chennai, India

Vishnu Rajasekharan Unni