Experimental and numerical investigations of jet active ... - Cerfacs

Experimental and numerical investigations of jet active control for combustion applications Vincent Faivre and Thierry Poinsot §

Institut de Mécanique des Fluides de Toulouse, Allée du Pr. Camille Soula, 31400 Toulouse, FRANCE Abstract. Controlling the mixing of a gas (usually fuel) issuing from a tube into surrounding air is a basic problem in multiple combustion systems. The purpose of the present work is to develop an actuator device to control the mixing enhancement of an axisymmetric nonreactive jet. The actuators consist of four small jets feeding the primary jet flow. These four jets are oriented to add an azimutal component to the velocity field. The influence of jets deflection and position along the main jet duct is discussed. Schlieren photographs and Planar Laser Induced Fluorescence measurements are used to compare the efficiency of the three configurations of interest. The effect of ”control-to-main” mass flow rates ratio is quantified through hot wire anemometry results. Large Eddy Simulations (LES) of both forced and unforced configurations are also performed. The objectives of the numerical part of this work are to understand the actuator effect and to validate LES as a tool to study active control.

Submitted to: Journal of Turbulence

§ To whom correspondence should be adressed ([email protected])

Active jet control for combustion applications

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1. Introduction Combustion instabilities may occur in closed combustion chambers, resulting from the coupling between acoustics and combustion [1, 2, 3, 4, 5, 6, 7]. They can appear in many combustors such as gas turbines or industrial furnaces. Those instabilities are responsible for noise, vibrations and sometimes complete device failure [8]. Being able to control such phenomena is an important research path in the combustion community. There are two ways to control a flow. Passive control consists in modifying the geometry of the burner [9] and/or the combustion chamber ; on the other hand active control consists in injecting external energy through actuators [10, 11]. The quality of the control depends directly on the design of the actuators. Some of them are specific to combustion applications but most actuation techniques are encountered in both reactive and non reactive applications : loudspeakers [10, 12], synthetic jets [13], flaps [14]. The purpose of the present study is to quantify, experimentally and numerically, the effects of forcing on the aerodynamic field in a model configuration : a non-reactive jet of air. The actuators are designed to modify the flow in two ways (figure 1) : a radial fluid injection into the main jet enhances its mixing with the ambient air [15, 16],

a swirl addition drastically changes the aerodynamic pattern of the flow and can be used to stabilize the flame [17].

To obtain these effects simultaneously the actuators of the present work consist of four small jets feeding the primary jet flow. These four jets are oriented to add an azimutal component to the velocity field. To visualize the effect of the actuators on the main flow, hot-wire anemometry, Schlieren photographs and Planar Laser Induced Fluorescence (PLIF) measurements are used. Introducing swirl to increase mixing or to stabilize flames is not new [17, 18, 19, 20, 21, 22, 23]. The effect of swirl jets has been studied in details by many authors and the objective of the present work is not to repeat these analysis. Here, the objective is to design a control device (the four jets) which can be easily tuned to adjust swirl and turbulence levels without any geometry modification. Another objective is to minimize pressure losses which are often encountered in swirling devices using vanes for example. The interaction of the actuators jets with the main jet can also be simulated using Large Eddy Simulations. Such LES provide a detailed insight into the physical mechanisms which is difficult to obtain experimentally. At this stage, LES cannot be used for all regimes to investigate the most efficient actuation mode : for such a task, experiments are more efficient. However LES is more powerful to investigate one regime in details so that a combination of experiments and LES is used in this work where the strategy is the following : first, experiments are used to establish which actuator configuration is the most efficient in terms of mixing enhancement ; LES of this configuration only are then performed to understand how the actuator actually affects the main jet.


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Figure 1. Generic scheme of the SW90, A90 and A45 configurations.

Nozzle A90 A45 SW90

α( ) 90 45 90

h (mm) 30 30 8

Table 1. Control parameters for each configuration of actuator.

2. Experimental facility Figure 1 shows a generic scheme of the nozzle equipped with the actuator. The exit diameter of the main jet (D) is 10 mm while the exit diameter of each small secondary jet is 2mm. Previous investigations have shown that the exit diameter of the small jet (d) is one of the main parameters having an influence on the control efficiency [24]. Here, two other parameters are tested : the orientation of the four small jets relative to the main one (α) and the distance between the actuator and the main jet exit (h). To evaluate the importance of these parameters, three configurations of actuators have been tested (table 1). For all configurations, the control jets are tangential to the main one to add an azimutal component to the velocity field. The nozzle is connected to a cubic box so that the jet flow is confined. The characteristic length of the box is 10 diameters of the main jet. The outlet of the box ends directly into free atmosphere. The effects of the box size were investigated numerically : even though the uncontrolled flow was slightly affected by the box length, the effects of control on this flow were independent of it. The main air flow is delivered by an hot air generator. This device allows to reach mass flow rates up to 30 g/s at 400 C. Temperature regulation is performed using PID regulation. The control flow rate is measured by a DANTEC S2140 Mass Flow Transducer which has been specially modified for the present work to measure unsteady flow rates up to 1 g/s at a frequency up to 500Hz. The ratio between the mass flow rate of the control flow (m˙ act ) and


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the mass flow rate of the main jet (m˙ jet ) is : q

m˙ act m˙ jet

(1)

It is adjusted with a MOOG servovalve which works in both continuous and pulsated regime. The jet spreading is characterized by the mean and rms velocity fields measured with a single hot-wire probe. The flow is also visualized through Schlieren photographs to measure its spreading angle and through PLIF snapshots to characterize the flow structure. 2.1. Velocity measurements Velocity profiles are obtained using a DANTEC Streamline constant temperature anemometer coupled to a CHARLYROBOT displacement table which allows micrometric probe shifting. The single hot-wire calibration is performed on DANTEC 54H10 calibrator. Each part of the anemometry rig is linked to a computer equipped with a KEITHLEY DAS 1800ST/HR acquisition card. Velocity signals are recorded at a frequency of 25000 Hz during 1 second. 2.2. Optical diagnostics Two optical diagnostics have been used for the present study : Schlieren technique and Planar Laser Induced Fluorescence (PLIF). For the Schlieren visualization the main jet is preheated (70 C). Since the present experiments are carried out using non fluorescent gases, PLIF measurements require the flow to be seeded with acetone. Acetone fluorescence is induced by a laser sheet (Nd YAG l=266nm in UV, I0 =40mJ, sheet thickness=500nm). An intensified CCD camera sensitive to the acetone fluorescence wave length is used to collect PLIF images.

3. Numerical setup The principle of LES is to resolve the larger scales of turbulence while modelling the smaller ones [7]. LES is therefore a good tool to predict the effect of control on the flow because large structures are certainly essential in this mechanism. LES of the experimental configuration are performed using the parallel CFD code “AVBP” developed at CERFACS in Toulouse (www.cerfacs.fr) and at IFP in Paris, France. AVBP solves the full compressible Navier-Stokes equations on 2D or 3D meshes. Meshes can be structured, unstructured or hybrid. The numerical approach is based on finite-volume schemes using the cell-vertex method. The scheme provides third-order accuracy both in space and time. It has been tested on multiple simple (isotropic turbulence, vortices, acoustic waves, channel, etc...) and complex cases [25, 26, 27, 28, 29, 30]. The boundary conditions treatment is based on the NSCBC approach [31, 32] : acoustic waves are identified and treated independently on boundaries to satisfy the boundary conditions. At the inlet of the main jet and of the four actuator jets, velocity profiles are imposed. At the box outlet, a non reflecting condition is fixed [31, 7]. On all walls, no slip conditions are imposed (figure 2).


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Figure 2. Computational domain. 1 : actuators. 2 : main flow. 3 : jet blowing in the box.

The subgrid-scale model is the WALE (Wall Adapting Local Eddy viscosity) model [25, 33]. This model is based on the square of the velocity gradient tensor and degenerates correctly near the walls. All simulations are three-dimensional, the mesh is hybrid and contains 1 million cells for 600.000 points. Figure 2 shows the computational domain. Note that, even for the unforced case, the actuators are included in the mesh. 4. Experimental results : determination of the optimal configuration To quantify the actuators effect, a criterion based on the jet spreading angle measured on Schlieren views is used (figure 3). The estimated value of the jet spreading angle includes the large structures of the shear layer. This diagnostic is sufficient to compare solutions and identify the most efficient actuators.

Figure 3. Schlieren photographs of the unforced flow (a) and the forced one (b). Evaluation of the jet spreading angle.


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Different values of ”control-to-main” mass flow rate ratio (q) have been investigated and figure 4 shows the jet spreading angle evolution as a function of q. For every actuator the jet spreading angle increases with q but not in the same way. Note that the jet angle significantly varies with control ranging from 19 (unforced) to 70 (forced cases).

Figure 4. Jet spreading angle vs. ”control-to-main” mass flow rate ratio (q) for A45, A90 and SW90 configurations.

4.1. Effect of actuators deflection (α) The efficiencies of A90 (α=90 ) and A45 (α=45 ) actuators are compared to investigate the influence of α (see figure 1). The A90 configuration is the most efficient : except for very low values of q, the jet controlled by the A90 actuator spreads more than the one controlled by the A45 actuator at the same control mass flow rate. The orientation of the four small jets has therefore an effect on the control efficiency. One possible explanation is that, for equal control flow rates, the azimutal component added to the velocity field is larger for the A90 than for the A45 configuration. The A90 actuator only adds an azimutal component to the velocity field while the A45 actuator adds both azimutal and axial components. Therefore the main flow sweeps the actuator effect along the jet axis more easily.

4.2. Effect of the distance from actuators to main jet exit (h) The efficiencies of SW90 (h=8mm) and A90 (h=30mm) actuators are now compared to investigate the influence of h (see figure 1) on the jet angle. Figure 4 shows that the distance h between the actuator and main jet exit influences the control efficiency. For each value of q, the jet spreading is higher when the flow is controlled with the SW90 actuator which has the smallest h value. This result shows that the control effect vanishes along the nozzle presumably because of wall friction and confinement. As the SW90 configuration has been identified as the most efficient it was retained for all further studies.


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4.3. Effect of control flow rate on the velocity field Figure 5 shows the effect of increasing q on the radial profiles of mean axial and rms velocities at x/D=6 where D is the main jet exit diameter. Those profiles are obtained by using a single hot wire probe. Each profile is normalized by the mean centerline velocity at the jet nozzle exit of the free jet configuration (Uc0 ). Figure 5 shows that higher q values lead to larger mixing enhancement : the increase of q leads to a decrease of the mean centerline velocity and to an expansion of both mean and rms velocity profiles. Velocity profiles on figure 5 also show that the entrainment of the ambient air is favored when increasing the ”control-to-main” mass flow rate ratio.

Figure 5. Mean radial profiles of axial velocity (up) and rms axial velocity (down) at x/D=5 for different control flow rates.


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Figure 6. Mean radial profiles of axial velocity. Comparison between LES and experiments. Unforced case (q=0).

5. Numerical results In addition to experimental characterization, the actuators effect was also studied using simulations to : understand the phenomena induced by control and identify the mechanisms responsible for mixing enhancement,

validate LES as a tool to study active control by comparing LES and experimental results.

5.1. LES validation for the unforced case LES is validated first on the unforced case. Figure 6 shows radial profiles of mean and rms axial velocities at different distances from the jet nozzle exit (x/D=3 and 7) for both numerical and experimental tests. LES seems to be able to reproduce the experimental results : the mean profiles extracted from the simulations are in good agreement with the experimental ones. The amplitude of the velocity fluctuation is slightly overestimated at x/D=3, especially in the mixing zone. Nevertheless, figure 7 shows that LES predicts the entrainment rate, in agreement with experiments and literature on free round jets [9]. Both experimental and numerical streamwise mass fluxes are calculated by integrating the mean velocity profile, assuming that the flow is axisymmetric.


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Figure 7. Normalized streamwise mass flux. Comparison between LES, experiments and Gutmark and Grinstein data [9].

5.2. LES validation for the forced case Figure 8 shows radial profiles of mean and rms axial velocities at different distances from the jet nozzle exit (x/D=3 and 7) for both numerical and experimental tests. The configuration corresponds to a control mass flow rate of 15% of the main mass flow rate (q=0.15). As for the unforced case, figure 8 demonstrates that LES reproduces both mean and rms velocity when control is on. The agreement between numerical and experimental results is better for the forced than for the unforced case. It is probably due to the fact that the large structures involved by the control are correctly captured by LES. 5.3. Effects of control Figure 9 presents the mean axial velocity field in a transverse plane at a distance of 0.5 mm upstream from the nozzle exit. Two-dimensional vectors have been superimposed to the field : each of those is the projection of the local three-dimensional velocity vector on the plane. As expected, figure 9 shows a global rotation movement of the flow inside the nozzle. LES reveals that each of the four actuation jets induces a longitudinal vortex. This mechanism is also found for classical jets in cross flow (JICF) where the interaction between jet and cross flow leads to a contra-rotating vortex pair (CVP) [34]. In the present case, one vortex only is observed because the other one is constrained by the wall and has no place to develop. The jet spreading after the jet nozzle exit can also be visualized by computing the velocity in a cylindrical coordinate system. Figure 10 shows the orthoradial velocity (u θ ) field at a distance of x/D=1 from the jet nozzle exit for both forced and unforced configurations. The level of uθ reached in the forced configuration is very high compared the unforced case (scales are different in both cases). It shows that the control device has the expected effect : it adds swirl to the flow. This swirl is responsible for the mixing enhancement with the ambient air.


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Figure 8. Mean radial profiles of axial velocity. Comparison between LES and experiments. Forced case (q=0.15).

Figure 9. Actuator effect on the flow inside the nozzle : mean axial velocity field and 2D velocity vectors.


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Figure 10. Flow field of orthoradial velocity component at x/D=1 for both forced and unforced cases.

Figure 11. Effect of control on the flow. Vortex detection using Q criterion. Control is activated at t=T0 . Animation (1.57Mo).

Figure 11 illustrates the important topological differences between unforced and forced cases by displaying isosurfaces of Q criterion used for vortex detection [35]. Without control (at T0 ), the Q isosurfaces are organized in rings which destabilize at a distance of three to four nozzle diameters downstream. When control is activated these rings destabilize much faster and the jet becomes turbulent right after the nozzle (T0 5 10 4 s to T0 1 5 10 3 s).


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Figure 12. Jet spreading enhancement. PLIF visualizations. Influence of the control flow density.

6. Scaling parameters controlling actuation efficiency The previous results have shown that the ”control-to-main” mass flow rate ratio q controls the efficiency of the actuators. All those results were obtained by injecting the same gas (air) in the main jet and in the four actuators jets. Since it is well known for JICF that density ratio between jet and crossflow plays an important role, both experimental and numerical tests are repeated injecting a lighter (air-helium mix) or a heavier gas (CO2 ) in the actuators. Figure 12 presents different instantaneous concentration fields (obtained using PLIF) of the flow for different values of q and different species injected through the actuators. At a constant value of q, lighter gases produce a higher jet spreading angle : for each of the three values of q the jet spreading is higher when using the air-helium mix and lower when using CO2 than when using air. In those configurations, the value of q is not representative of the control efficiency. The same trend is observed for each value of q between 0 and 0.5, as shown on figure 13. On the other hand, when plotting the jet spreading angle vs. the impulsions ratio, defined by : J

2 ρact Uact 2 ρ jet U jet

(2)


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Figure 13. Jet spreading vs. q (left) and J (right). Effect of the control flow density.

the three curves corresponding to each species collapse and the jet spreading angle grows linearly with J. Simulations highlight the phenomena responsible for efficiency differences that occurs when the control gas density changes. Figure 14 shows concentration isocontours of the species injected through the actuators at various distances from the control flow injection. The three configurations use the same flow rate ratio (q=0.15) but different gases in the control device. Figure 14 confirms the experimental results : q is not representative of the control effect. LES reveal that the concentration fields exhibit two main modifications, concerning the global rotation movement and the interaction between the secondary jets and the main one. The global rotation movement can be visualized through the rotation of the vortical axial structures around the main jet : the injection of light gas enhances the swirl intensity ; the vortical structures turn faster around the main jet axis and so does the main flow. The flow topology is also affected by the control gas density through the interaction between the control jets and the main one. For heavy gas (J 1) the control jets are entrained by the main flow and do not penetrate it. On the other hand, for light gas (J 1) the penetration is higher.

7. Conclusion Experimental and numerical investigations of the control of a jet by four radial actuation jets have shown that swirl injection (obtained by shifting the axis of actuators jets) is an efficient way to control mixing and jet spreading over a very wide range. The effect of the deflection and the distance between the control jets and the main jet axis has been studied. The most efficient configuration in terms of mixing and jet spreading enhancement is the SW90 actuator device where actuation jets are located close to the nozzle and oriented to provide maximum swirl. Large Eddy Simulations have been validated on both unforced and forced cases. The simulations show which mechanisms are responsible for the control efficiency : the control jets add swirl (which was expected from the design of the actuators) that enhances the jet spreading. However, the LES reveals that the actuator choice (4 small jets) also induces


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Figure 14. Mean concentration isocontours of the species injected through the actuators. Effect of the control gas density. Controled flow with q=0.15

secondary vortices which may play a role for the reacting cases. Both experimental and numerical results performed with lighter or heavier actuator gases confirm that the control efficiency is governed by the impulsion ratio J (Eq. 2). 8. Acknowledgments We gratefully acknowledge the support provided by Air Liquide and ADEME.


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