Combustor thermoacoustics for multi-burner low emissions gas turbines (CHAMBER)
Combustor thermoacoustics for multi-burner low emissions gas turbines (CHAMBER)
批准号:
EP/P003036/1
负责人:
Aimee Morgans
金额:
$96.47万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
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英文摘要
Gas turbines generate electricity and power our aeroplanes. They will be a long term presence in the overall energy mix, complementing renewable but inconsistent sources of power, such as wind turbines. It is clearly important to make them as clean, quiet and efficient as possible. Unfortunately, the very conditions under which gas turbines produce ultra low NOx emissions (NOx cause air pollution and breathing problems) also make the combustor extremely prone to thermoacoustic instability. The associated high amplitude pressure and flame oscillations lead to damaging vibration, and make operation impractical. Thermoacoustic instability is caused by acoustic waves and unsteady heat release in the combustor mutually affecting one another, leading to positive feedback. There is an urgent need to be able to predict it as part of the gas turbine design process, so that it can be "designed out". This is currently not possible.Computationally simulating thermoacoustic instability requires many length scales to be resolved - from the tiny chemical reaction scales, to flame-front wrinkling, to the very long acoustic waves. Simulating compressible reacting flow over this range of scales is prohibitively expensive. Low order network models provide a computationally fast alternative. They approximate the combustor geometry as a network of simple connected modules, and exploit the fact that the acoustic wave behaviour is linear (even for large oscillations, nonlinearity comes only from the flame). Furthermore, at low frequencies the acoustic waves behave at most two-dimensionally. This means that simple analytical models for the acoustic waves can be coupled with more complex models, from computational flow simulations or experiments, for the flame.Recent work, in which the investigators have played a key role, has shown that (i) the flame nonlinearity can typically be captured via a weakly nonlinear modeling approach and (ii) that these weakly nonlinear flame models can be obtained by "incompressible" large eddy simulations (LES), which capture large turbulent flow features (although "incompressible", the density can change with flow temperature). The use of incompressible simulations saves roughly an order of magnitude in time compared to compressible simulations. For single turbulent flame combustors, major progress was recently achieved by coupling a low order thermoacoustic network model with incompressible LES of the flame, and accurately predicting not only the frequency of thermoacoustic instability, but also its limit cycle amplitude. It is now timely to attempt fast and accurate predictions for increasingly realistic combustor setups.The proposed work is two-fold. It will firstly seek to develop new methods for low order thermoacoustic network modeling and for incompressible LES of flames. These are needed to facilitate fast and accurate predictions for multi-burner annular combustors, more representative of real gas turbine set-ups. We will use data from a world-class experimental combustion facility at our collaborators, NTNU in Norway, for validation. We will consider flames which burn independently, and more complicated cases when they are close enough to interact with one another. We will investigate the flow physics at play - the combined effect of circumferential acoustic waves, flame nonlinearity and flame-flame interactions.At the same time, we will develop a UK-based configurable optical combustion rig to measure forced flame response using advanced laser imaging. This will have the option for multiple burners, and for the first time, multi-phase fuel, interchangeable combustor wall materials and variable exit conditions. It will provide insights into instability in practical combustors, and high-fidelity flame and flow data for modellers. We aim to predict thermoacoustic instability in the presence of these phenomena, moving predictive capability towards increasing industrially relevant combustors.
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