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CFD analysis/optimization of thermo-acoustic instabilities in liquid fuelled aero stationary gas turbine combustors

机译:液体燃料航空固定式燃气轮机燃烧室中热声不稳定性的CFD分析/优化

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摘要

It has been recognized that the evaporation process is one of the pivotal mechanisms driving thermo-acoustic instability in gas turbines and rockets in particular. In this regard, this study is principally focused on studying the evaporation process relevant to thermo-acoustic instability from three complementary viewpoints in an effort to contribute to an overall instability model driven primarily by evaporation in gas turbine combustors. Firstly, a state of the art LES algorithm is employed to validate an evaporation model to be employed in predictive modelling regarding combustion instabilities. Good agreement between the numerical predictions and experimental data is achieved. Additionally, transient sub-critical droplet evaporation is investigated numerically. In particular, a numerical method is proposed to capture the extremely important pressure-velocity-density coupling. Furthermore, the dynamic system nonlinear behaviour encountered in classical thermo-acoustic instability is investigated. The Poincaré map is adopted to analyse the stability of a simple non-autonomous system considering a harmonic oscillation behaviour for the combustion environment. The bifurcation diagram of a one-mode model is obtained where the analysis reveals a variety of chaotic behaviours for some select ranges of the bifurcation parameter. The bifurcation parameter and the corresponding period of a two-mode dynamic model are calculated using both analytical and numerical methods. The results computed by different methods are in good agreement. In addition, the dependence of the bifurcation parameter and the period on all the relevant coefficients in the model is investigated in depth. Moreover, a discrete dynamic model accounting for both combustion and vaporization processes is developed. In terms of different bifurcation parameters relevant to either combustion or evaporation, various bifurcation diagrams are presented. As part of the nonlinear characterization, the governing process Lyapunov exponent is calculated and employed to analyze the stability of the particular dynamic system. The study has shown conclusively that the evaporation process has a significant impact on the intensity and nonlinear behaviour of the system of interest, vis-à-vis a model accounting for only the gaseous combustion process. Furthermore, two particular nonlinear control methodologies are adopted to control the chaotic behaviour displayed by the particular aperiodic motions observed. These algorithms are intended to be implemented for control of combustion instability numerically and experimentally to provide a rational basis for some of the control methodologies employed in the literature. Finally, a state of the art neural network is employed to identify and predict the nonlinear behaviour inherent in combustion instability, and control the ensuing pressure oscillations. Essentially, the NARMAX model is implemented to capture nonlinear dynamics relating the input and output of the system of interest. The simulated results accord with the results reported. Moreover, a control system using the NARMA-L2 algorithm is developed. The simulation conclusively points to the fact that the amplitude of pressure oscillations can be attenuated to an acceptable level and the controller proposed may be implemented in a practical manner.
机译:已经认识到,蒸发过程是驱动尤其是燃气轮机和火箭中的热声不稳定性的关键机制之一。在这方面,本研究主要集中于从三个互补的观点研究与热声不稳定性有关的蒸发过程,以努力为主要由燃气轮机燃烧器中的蒸发驱动的整体不稳定性模型做出贡献。首先,采用最新的LES算法来验证要用于有关燃烧不稳定性的预测模型中的蒸发模型。在数值预测和实验数据之间达成了良好的一致性。另外,对瞬态亚临界液滴蒸发进行了数值研究。特别地,提出了一种数值方法来捕获极其重要的压力-速度-密度耦合。此外,研究了经典热声不稳定性中所遇到的动态系统非线性行为。庞加莱图被用来分析一个简单的非自治系统的稳定性,该系统考虑了燃烧环境的谐波振荡行为。获得单模模型的分叉图,其中分析揭示了对于分叉参数的某些选择范围的各种混沌行为。使用解析和数值方法都可以计算出分叉参数和双模式动态模型的相应周期。用不同方法计算的结果吻合良好。此外,深入研究了分叉参数和周期对模型中所有相关系数的依赖性。此外,建立了兼顾燃烧和汽化过程的离散动态模型。根据与燃烧或蒸发相关的不同分叉参数,给出了各种分叉图。作为非线性表征的一部分,计算了控制过程Lyapunov指数,并将其用于分析特定动态系统的稳定性。研究最终表明,相对于仅考虑气态燃烧过程的模型,蒸发过程对目标系统的强度和非线性行为具有重大影响。此外,采用了两种特定的非线性控制方法来控制由观察到的特定非周期性运动所显示的混沌行为。这些算法旨在实现数值和实验控制燃烧不稳定性,从而为文献中采用的某些控制方法提供合理的基础。最后,采用先进的神经网络来识别和预测燃烧不稳定性固有的非线性行为,并控制随之而来的压力振荡。本质上,NARMAX模型的实现是为了捕获与目标系统的输入和输出相关的非线性动力学。模拟结果与报告的结果一致。此外,开发了使用NARMA-L2算法的控制系统。该模拟最终指出了这样的事实,即压力振荡的幅度可以被衰减到可接受的水平,并且所提出的控制器可以以实用的方式来实现。

著录项

  • 作者

    Turan Ali; Lei Shenghui;

  • 作者单位
  • 年度 2010
  • 总页数
  • 原文格式 PDF
  • 正文语种 English
  • 中图分类

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