Bulletin of the American Physical Society
75th Annual Meeting of the Division of Fluid Dynamics
Volume 67, Number 19
Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.
Session Z11: Acoustics: Thermo II |
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Chair: Daniel Rodriguez, Universidad Politecnica de Madrid Room: 138 |
Tuesday, November 22, 2022 12:50PM - 1:03PM |
Z11.00001: Physics-aware learning of thermoacoustic limit cycles Defne Ege Ozan, Luca Magri In thermoacoustic systems, if the heat release is sufficiently in phase with the pressure, self-excited oscillations with finite amplitudes can occur. A typical nonlinear regime of the dynamics is a limit cycle, which is a periodic orbit in the phase space. We develop physics-aware neural networks that learn these periodic solutions from data. Added to a data-driven loss, a physical residual penalises solutions that violate the conservation of momentum and energy. We impose periodicity by periodic activation functions and a trainable frequency. We employ acoustic eigenfunctions as spatial modes, while a jump discontinuity in velocity at the flame is captured by discontinuous modes. We test the algorithm on a time-delayed model of a Rijke tube and a higher-order model with a kinematic flame. We find that (i) physics constraints significantly improve the predictions from noisy or sparse data, (ii) periodic activations outperform conventional activations in terms of extrapolation capability, and (iii) boundary conditions and discontinuities can be hard-coded with a-priori selected spatial modes. This work opens up possibilities for the prediction of nonlinear thermoacoustics by combining physical knowledge and data. |
Tuesday, November 22, 2022 1:03PM - 1:16PM |
Z11.00002: Analysis of Acoustic Modes in Solid Fuel Ramjet Cavities Henry Pace Acoustic perturbation in ramjet cavities affect both the performance and the structural integrity of the combustion chamber. In the proposed research we investigate the role of near wall processes on the formation and sustainment of acoustic modes in the ramjet combustion and mixing chambers. We focus on the presence of melt layers over fuel walls and their effect on the diffusion flames and the acoustic field they support. We perform high-order computational simulations of the ramjet combustion with regressing fuel walls using a novel discontinuous Galerkin approach, which allows us to obtain a fully conjugate solution of thermal field. Preliminary results show a good agreement of cold flow simulations against measurements from an experimental campaign conducted at Virginia Tech. We investigate the acoustic energy distribution using spectral proper orthogonal decomposition of the pressure field. We will present results of fuel injection from walls with and without cavity regression and compare them against new experimental measurements. We will discuss the role of changes in cavity shape on the acoustic frequencies and energy distribution. |
Tuesday, November 22, 2022 1:16PM - 1:29PM |
Z11.00003: Azimuthally forced combustion instabilities in an annular combustor across different operating conditions and fuels Abhijat Verma, Håkon T Nygård, Nicholas A Worth Gas turbines running in low-emissions configurations (using alternative fuels in lean premixed mixtures) are known to exhibit self-excited azimuthal combustion instabilities. Previous work by Nygård et al. (2019 & 2021) has shown that these instabilities can be created and sustained in a lab-scale annular combustor by using a circular array of speakers. Furthermore, Nygård et al. developed the Azimuthal Flame Describing Function (AFDF) formalism to characterise azimuthal instability modes in a quantitative manner. Although their work covered a large range of instability mode types, it only focused on a single fuel mixture of ethylene operating at a single mean bulk velocity. |
Tuesday, November 22, 2022 1:29PM - 1:42PM |
Z11.00004: Modeling transition to thermoacoustic instability in a turbulent combustor: A synchronization-based approach Yue Weng, Vishnu R Unni, R. I. Sujith, Abhishek Saha Thermoacoustic instability, arising from interactions between the fluctuations in heat release and pressure, limits the stable operation of gas turbines in fuel-lean conditions. Modeling the dynamics of such instability in a modern gas turbine combustor, where combustion occurs in a turbulent environment, becomes key for safe and reliable operations. This work presents a phenomenological reduced-order model based on synchronization for the transition to thermoacoustic instability in such turbulent combustors. Here, the acoustic field and the unsteady heat release rate from the turbulent reactive flow are modeled as two non-linearly coupled sub-systems. By varying the coupling strength, the model can replicate the transition from low amplitude chaotic oscillation (i. e. combustion noise) to high amplitude periodic oscillation through intermittency, which is observed in previous experiments. The model shows that the pressure fluctuation in the regime of combustion noise is multifractal at one end of the transition. During the transition to the limit cycle oscillation, the pressure fluctuation loses its multifractality and poses a higher amplitude, which is the hallmark of the transition mechanism in turbulent thermoacoustic systems shown by previous experiments. |
Tuesday, November 22, 2022 1:42PM - 1:55PM |
Z11.00005: Bayesian Experimental Design for Data Assimilation in Thermoacoustics Matthew Yoko, Matthew P Juniper Bayesian data assimilation is a powerful tool for generating quantitatively-accurate physics-based models of thermoacoustic systems. Depending on the model, this method can require assimilation of thousands of experimental data points to achieve sufficient confidence. Conducting so many experiments on aircraft or rocket engines would be prohibitively expensive. To address this problem, we apply methods from information theory and Bayesian experimental design to identify the experimental configurations that provide the maximum information when assimilating into a given model. We demonstrate the power of this approach by applying an optimal experimental design strategy to select a subset of data points from a large experimental data set. The full data set contains 7000 experiments collected from 175 stable operating conditions of a hot wire Rijke tube. We show that by assimilating just 20% of the data points with the highest information content, we can achieve 90% of the confidence that is gained by assimilating the full data set. |
Tuesday, November 22, 2022 1:55PM - 2:08PM |
Z11.00006: Genetic programming control of quasiperiodic thermoacoustic oscillations Bo Yin, Yu Guan, Stephane Redonnet, Larry K.B. Li We use genetic programming (GP) to discover model-free control laws for the suppression of two-frequency quasiperiodic oscillations in a prototypical self-excited thermoacoustic system. Starting from an initial generation of control laws, we rank their performance based on a predefined cost function that quantifies the trade-off between pressure amplitude reduction and actuation cost. We then breed subsequent generations of control laws via a tournament algorithm in which direct forwarding of elitism individuals occurs alongside genetic operations such as mutation, replication and crossover. We implement this GP control strategy in both closed-loop and open-loop formats, and we benchmark these against conventional open-loop control involving harmonic forcing. We find that all three control strategies can deliver similar levels of amplitude reduction, but that GP closed-loop control requires the least actuation effort. We also find that GP closed-loop control can reveal novel actuation mechanisms, offering useful insight into the interactions between the pressure and heat-release-rate fields. |
Tuesday, November 22, 2022 2:08PM - 2:21PM |
Z11.00007: Nonlinear dynamics of thermoacoustic oscillations in syngas combustors Arvind Raj Sakthivel, Abhijit Kumar Kushwaha, Meenatchidevi Murugesan A combustion system can exhibit large-amplitude, self-excited limit cycle oscillations when the unsteady heat release rate from the flame oscillates in phase with the natural acoustic modes of the combustor. In this experimental study, we show that the dynamical features of these self-excited oscillations can vary as function of the fuel composition. For fuel-lean, methane-air combustion above a critical Reynolds number, the instability is observed at a frequency closer to the fundamental acoustic mode. As the percentage of hydrogen is increased with the concurrent reduction in the methane percentage, we observe that the instability transitions to higher harmonic modes. Further, we find that the presence of multiple frequencies when the fuel is comprised of mixture of methane, carbon monoxide and hydrogen. This study shows that the combustion of fuel having mixture fraction variation can involve multiple time lags in the unsteady heat release rate, causing the transition to multiple harmonic thermoacoustic oscillations. |
Tuesday, November 22, 2022 2:21PM - 2:34PM |
Z11.00008: Influence of Noise Characteristics on Thermoacoustic Instability Growth Rate Estimates Neha Vishnoi, Vikrant Gupta, Aditya Saurabh, Lipika Kabiraj Thermoacoustic oscillations in gas turbine combustors lead to sub-optimal performance and structural failures. Passive acoustic damping devices are employed to suppress these oscillations. Estimating system parameters that characterize the instability is required for designing these devices. Noise is an inherent feature of combustors and is beneficial in predicting instability via analysis of noise-induced dynamics. Previous reports on noise-induced dynamics model noise as an additive Gaussian white noise. However, experimental studies have indicated that noise, in particular from turbulent flame, is low-pass in character. In this work, we experimentally investigate the influence of Ornstein-Unhlenbeck colored noise on system identification using a prototypical thermoacoustic system exhibiting subcritical Hopf bifurcation. We investigate the effects of noise color and intensity on estimation of growth rates and show limitations of the white noise approximation in stable, bistable and linearly unstable regions. We find that estimated growth rates exhibit a deviation of 0–30% from true values with increasing noise color and intensity. We find that colored noise model, based on known statistics of combustion noise, predicts system growth rates significantly better than white noise model. |
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