FTLE-Based Flow Region Identification for Thermoacoustic Instability Suppression
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Solution Overview
Problem
Current methods fail to effectively identify the underlying dynamics responsible for oscillatory instabilities in turbulent flow systems and do not provide optimized passive control methods to suppress thermoacoustic instabilities.
Innovation Solution
A computer-implemented method and system that use backward time finite-time Lyapunov exponent (FTLE) fields to identify critical regions in turbulent flow systems, disrupting these regions through active or passive control strategies, such as secondary air injection or valve actuation, to prevent oscillatory instabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional precursor methods (0-1 test, recurrence tests, generalized Hurst exponent tests) are used to detect oscillatory instabilities, then instability detection capability is provided, but the underlying dynamics responsible for instabilities cannot be identified
Solution Approach 1:
The patent replaces conventional statistical precursor methods with a physics-based approach using finite-time Lyapunov exponent (FTLE) fields computed from velocity data. This substitution enables identification of critical regions and underlying dynamics by leveraging fluid mechanical principles rather than purely statistical analysis, thereby recovering lost information about the system's physical behavior.
2Measurement precision
If FTLE is used to find regions of distinct flows in wind turbine flows, then flow region identification is achieved, but optimized passive control methods to suppress thermoacoustic instabilities are not provided
Solution Approach 1:
The patent applies local quality by identifying specific critical regions within the flow field using backward-time FTLE analysis and applying control measures targeted at these localized areas. Instead of uniform control across the entire system, the approach focuses control resources on specific regions where they are most effective, thereby simplifying implementation while maintaining high suppression efficiency.
Solution Approach 2:
The patent changes the parameter perspective by using backward-time FTLE fields instead of conventional flow analysis parameters. This parameter transformation enables the identification of critical regions that are not apparent in standard flow visualizations, providing a new basis for implementing optimized passive control strategies.
3Measurement precision
If complex network and FTLE methods are used to identify critical regions, then region identification is achieved, but the dynamics responsible for instabilities are not identified and optimized passive control is not discussed
Solution Approach 1:
The patent implements feedback by using velocity data from the flow field to compute FTLE fields, identifying critical regions, and then applying control measures that disrupt the dynamics in these regions. The control effectiveness can be monitored through continued FTLE analysis, creating a closed-loop system that adapts to the actual system behavior and refines control strategies based on observed responses.
Data Source
AI summary
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.