Research: Active-Adaptive Noise Control in:
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Combustion Systems Our goal is develop a systems framework for analyzing and synthesizing an
actively controlled combustor with optimal behavior in which active control is
incorporated as an integral part of both the hardware and the software used to
manage the different functions of the combustor. Several factors contribute to
the functioning of a combustor, making its analysis and design a very complex
task. These include, in the case of liquid fueled combustor, the liquid fuel
injection, atomization, dispersion, evaporation, mixing and chemical
reactions, flame stabilization through recirculation, and acoustics-vortex
interactions. All of these processes are dynamically coupled, and together
they affect the flow dynamics. They also interact with the acoustic dynamics
of the system in ways which are determined by the flow conditions and
geometry. The introduction of active control is yet another complexity which
has to be designed so that it functions synergistically with the combustion
process since actuation, whether it is acoustically implemented, or via fuel
injection, imposes different conditions on the combustion process. Moreover,
since active control inputs affect the acoustic field, the flame stabilization
zone, and other flow dynamics mechanisms, a controlled combustor behaves
dynamically different from an uncontrolled one.
We have employed a systems framework for analyzing such an integrated
multi-component entity as well as for designing for optimal performance.
Several reasons can be cited for this: (a) Since the ultimate goal is to optimize multiple
global objectives from the combustor such as stability, low NOx, and high
efficiency, several input-output relations must be known a proiri or found
online. (b) The combustor can be viewed as a system made up of several
subsystems (see Fig. 1),
each of which can exhibit a strong temporal behavior that can be interrogated
individually. (c) Tightly knit coupling is present among these subsystems
(thermoacoustic resonance is one example of such a coupling; the creation of
secondary peaks while using active control is another) which warrants the
consideration of the combustor as a whole rather than a treatment of its
parts. A systems approach enables one to study how different subsystems
interact with each other and how they can be designed optimally for realizing
a high performance.
The results of this systems framework have yielded (i) reduced-order models of
combustion dynamics under weakly turbulent conditions and high Damkholer
numbers [C1,C2], (ii) reduced-order models under highly turbulent conditions
and low Damkholer numbers [C3], (iii) model-based control strategies that have
yielded optimal performance with an order of magnitude improvement in the
pressure suppression in laboratory-scale and mid-scale rigs [C4,C5], (iv)
adaptive and nonlinear control strategies that result in enhanced performance
in the presence of parametric uncertainties and time-delays [C6,C7,C8].
Our current projects in active combustion control are listed below:
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Reduced-order models of heat-release dynamics
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Models of vortex-heat release interactions
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Active-adaptive control of time-delays
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A systematic derivation of models for control using computational models
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Experimental design of a testbed for a parametric study of
active-adaptive time-delay control of combustion systems
A 75 kilowatt combustor has been designed and built to experimentally validate the combustion models and model-based control strategies developed in the AAC Lab. The experimental setup consists of a backward facing step-stabilized combustion tunnel, which can be operated as either premixed or nonpremixed, or with liquid fuel injection anywhere in the vicinity of the step, from a single hole, multiple holes or a slot. The combustion process is optically accessible through side windows and a variety of measurement and diagnostic techniques are available to interrogate the experiment. A Moog direct-drive valve is used as an actuator to pulse the secondary-fuel into the combustor. The facility is sufficiently flexible to allow for different test sections, different fuel injection locations and configuration.
A hallmark of unstable combustion is large pressure, heat release, velocity, and temperature oscillations. The backward step combustor is victim to the same phenomenon, as shown in the movie below where the light intensity of the flame is measured using a CCD camera operating at 1000 frames per second, indicating large temperature oscillations. The amplitude of the corresponding pressure oscillations is of the order of 5% of atmospheric pressure. Model-based feedback control strategies are being designed to reduce these oscillations.
The following movie shows active combustion control in a 85kW LPP(lean premixed prevapourized) combustor. Control was achieved by modulating the fuel flow rate using a Moog DDV valve in response to a measured pressure signal. The feedback control is an adaptive PosiCast controller which only requires the total time delay between actuation and response to achieve control. The algorithm achieves a reduction of up to 30 dB on the primary instability frequency. This performance was an improvement of 5-15 dB over an empirical control strategy (simple time-delay controller) specifically tuned to the same operating point. The experiments were performed at the University of Cambridge under the direction of Dr. Riley and Professor Dowling.
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Recent Publications:
[C2] M. Fleifil, A.M. Annaswamy, Z.A. Ghoneim, and A.F. Ghoniem, "Response of a Laminar Premixed Flame to Flow
Oscillations: A Kinematic Model and Thermoacoustic Instability Results," Combustion and Flame, vol. 106, pp.
487--510, 1996.
[C3] A.M.Annaswamy, M.Fleifil, J.P.Hathout, and A.F.Ghoniem, "Impact of Linear Coupling on the Design of Active
Controllers for Thermoacoustic Instability," Combustion Science and Technology, vol. 128, pp. 131-160, 1997.
[C6] S. Evesque, A.P. Dowling, and A.M. Annaswamy, “Self-tuning regulators for combustion oscillations,” Royal Society Journal Proceedings of the Mathematical, Physical and Engineering Sciences, Vol 459, Issue 2035, pp 1709-1749, 2003.
[C7] A.J. Riley, S. Park, A.P. Dowling, S. Evesque , and A.M. Annaswamy, "Adaptive Closed-Loop Control on an Atmospheric Gaseous Lean-Premixed Combustor," ASME Journal of Engineering for Gas Turbines and Power, vol. 126, October 2004.
[C8] S. Evesque, S. Park, A.J. Riley, A.M. Annaswamy, and A.P. Dowling, "Adaptive Combustion Instability Control with Saturation: Theory and Validation," AIAA J. Propulsion and Power, vol. 20, No. 6, pp. 1086-1095, 2004.
[C9] A.F. Ghoniem, A. Annaswamy, S. Park, and Z. Sobhani, “Stability and emissions control using air injection and H 2 addition in premixed combustion,”Proceedings of the Combustion Institute, vol. 30, pp. 1765-1773, 2005.
[C10] A.F. Ghoniem, S. Park, A. Wachsman, A. Annaswamy, D. Wee, and H.M. Altay, “Mechanism of combustion dynamics in a backward-facing step stabilized premixed flame,”Proceedings of the Combustion Institute, vol. 30, pp. 1783-1790, 2005.
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