Experimental Analysis of Wave Propagation in a Methane-Fueled Rotating Detonation Combustor

2018 ◽  
Author(s):  
C. Welch ◽  
D. Depperschmidt ◽  
R. Miller ◽  
J. Tobias ◽  
M. Uddi ◽  
...  
Keyword(s):  
Detonation Wave ◽  
Gas Turbines ◽  
High Speed ◽  
Wave Speed ◽  
Rotation Frequency ◽  
Oblique Shock ◽  
Oblique Shock Wave ◽  
Thermodynamic Efficiency ◽  
Analysis Techniques ◽  
Rotating Detonation

Recently, pressure gain combustion (PGC) has been a subject of intense study because of its potential to increase the thermodynamic efficiency of power generating gas turbines by several percentage points. The rotating detonation combustion/combustor (RDC) can provide large pressure gain within a small volume through rapid heat release by detonation wave(s) that propagate continuously in the circumferential direction. The RDC has been investigated mainly for propulsion applications using hydrogen fuel. In contrast, we present experimental results from an RDC operated on methane and oxygen-enriched air mixtures to represent the reactants in advanced power generating gas turbines. The propagation of detonation and oblique shock waves in the RDC is investigated through High Speed Video (HSV) imaging and Ion Probe (IP) data. HSV imaging requires optical access to the RDC, which can be difficult especially when the RDC is integrated with the gas turbine inlet hardware. Additionally, HSV systems are quite expensive. In contrast, IPs are inexpensive and have the advantages of small size and flexibility in the placement location and can be flush mounted causing minimal interference with the propagating wave. In this study, the detonation wave is tracked by high-resolution HSV imaging at framing rate of 200 kHz. At the same time, IPs are used to detect the rotating oblique shock wave inside the RDC, and different analysis techniques are explored to quantify the wave speed. IP voltage data are analyzed by differentiation, correlation and fast-Fourier transform methods to compute the wave speed (or rotation frequency), and the results are compared with those from the HSV image analysis. The uncertainty of different methods is discussed, and finally, the analysis techniques are applied to investigate the wave characteristics during an experiment.

Application of a Convolutional Neural Network for Wave Mode Identification in a Rotating Detonation Combustor Using High-Speed Imaging

2020 ◽  
Author(s):  
Kristyn B. Johnson ◽  
Donald H. Ferguson ◽  
Robert S. Tempke ◽  
Andrew C. Nix
Keyword(s):  
Neural Network ◽  
Detonation Wave ◽  
High Speed ◽  
Wave Mode ◽  
Classification Performance ◽  
Detonation Waves ◽  
Single Image ◽  
High Speed Imaging ◽  
Mode Identification ◽  
Rotating Detonation

Abstract Utilizing a neural network, individual down-axis images of combustion waves in a Rotating Detonation Engine (RDE) can be classified according to the number of detonation waves present and their directional behavior. While the ability to identify the number of waves present within individual images might be intuitive, the further classification of wave rotational direction is a result of the detonation wave’s profile, which suggests its angular direction of movement. The application of deep learning is highly adaptive and therefore can be trained for a variety of image collection methods across RDE study platforms. In this study, a supervised approach is employed where a series of manually classified images is provided to a neural network for the purpose of optimizing the classification performance of the network. These images, referred to as the training set, are individually labeled as one of ten modes present in an experimental RDE. Possible classifications include deflagration, clockwise and counterclockwise variants of co-rotational detonation waves with quantities ranging from one to three waves, as well as single, double and triple counter-rotating detonation waves. After training the network, a second set of manually classified images, referred to as the validation set, is used to evaluate the performance of the model. The ability to predict the detonation wave mode in a single image using a trained neural network substantially reduces computational complexity by circumnavigating the need to evaluate the temporal behavior of individual pixels throughout time. Results suggest that while image quality is critical, it is possible to accurately identify the modal behavior of the detonation wave based on only a single image rather than a sequence of images or signal processing. Successful identification of wave behavior using image classification serves as a stepping stone for further machine learning integration in RDE research and comprehensive real-time diagnostics.

OH* Chemiluminescence Imaging of the Combustion Products From a Methane-Fueled Rotating Detonation Engine

2018 ◽  
Author(s):  
J. Tobias ◽  
D. Depperschmidt ◽  
C. Welch ◽  
R. Miller ◽  
M. Uddi ◽  
...  
Keyword(s):  
Power Generation ◽  
Gas Turbines ◽  
Power Plants ◽  
Mechanical Energy ◽  
Combustion Products ◽  
Combined Cycle ◽  
Oblique Shock Wave ◽  
Continuous Detonation ◽  
Rotating Detonation ◽  
Probe Measurements

Pressure gain combustion (PGC) has been conceived to convert fuel’s chemical energy into thermal energy and mechanical energy, thereby reducing the entropy production in the process. Recent research has shown that the rotating detonation combustion or combustor (RDC) can provide excellent specific thrust, specific impulse, and pressure gain within a small volume through rapid energy release by continuous detonation in the circumferential direction. The RDC as a PGC system for power generating gas turbines in combined cycle power plants could provide significant efficiency gains. However, few past studies have employed fuels that are relevant to power generation turbines, since RDC research has focused mainly on propulsion applications. In this study, we present experimental results from RDC operated on methane and oxygen-enriched air to represent reactants used in land-based power generation. The RDC is operated at a high pressure by placing a back-pressure plate downstream of the annular combustor. Past studies have focused mainly on probe measurements inside the combustor, and thus, little information is known about the nature of the products exiting the RDC. In particular, it is unknown if chemical reactions persist outside the RDC annulus, especially if methane is used as the fuel. In this study, we apply two time-resolved optical techniques to simultaneously image the RDC products at framing rate of 30 kHz: (1) direct visual imaging to identify the overall size and extent of the plume, and (2) OH* chemiluminescence imaging to detect the reaction zones if any. Results show dynamic features of the combustion products that are consistent with the probe measurements inside the RDE. Moreover, presence of OH* in the products suggests that the oblique shock wave and reactions persist downstream of the detonation zone in the RDC.

Application of a Convolutional Neural Network for Wave Mode Identification in a Rotating Detonation Combustor Using High-Speed Imaging

2021 ◽  
pp. 1-22
Author(s):  
Kristyn B. Johnson ◽  
Donald H. Ferguson ◽  
Robert S. Tempke ◽  
Andrew C. Nix
Keyword(s):  
Neural Network ◽  
Detonation Wave ◽  
High Speed ◽  
Wave Mode ◽  
Classification Performance ◽  
Detonation Waves ◽  
Single Image ◽  
High Speed Imaging ◽  
Mode Identification ◽  
Rotating Detonation

Abstract Utilizing a neural network, individual down-axis images of combustion waves in a Rotating Detonation Engine (RDE) can be classified according to the number of detonation waves present and their directional behavior. While the ability to identify the number of waves present within individual images might be intuitive, the further classification of wave rotational direction is a result of the detonation wave's profile, which suggests its angular direction of movement. The application of deep learning is highly adaptive and therefore can be trained for a variety of image collection methods across RDE study platforms. In this study, a supervised approach is employed where a series of manually classified images is provided to a neural network for the purpose of optimizing the classification performance of the network. These images, referred to as the training set, are individually labeled as one of ten modes present in an experimental RDE. Possible classifications include deflagration, clockwise and counterclockwise variants of corotational detonation waves with quantities ranging from one to three waves, as well as single, double and triple counter-rotating detonation waves. The ability to predict the detonation wave mode in a single image using a trained neural network substantially reduces computational complexity by circumnavigating the need to evaluate the temporal behavior of individual pixels throughout time. Results suggest that while image quality is critical, it is possible to accurately identify the modal behavior of the detonation wave based on only a single image rather than a sequence of images or signal processing.

Developing an Application for Refractory Open Cell Metal Foams in Jet Engines

2004 ◽  
Vol 851 ◽  
Author(s):  
Wassim E. Azzi ◽  
William L. Roberts ◽  
Afsaneh Rabiei
Keyword(s):  
Pressure Drop ◽  
Gas Turbines ◽  
High Speed ◽  
Infrared Imaging ◽  
Metal Foam ◽  
Turbine Blades ◽  
Metal Foams ◽  
Thermodynamic Efficiency ◽  
Open Cell ◽  
The Difference

ABSTRACTThe thermodynamic efficiency of the Brayton cycle, upon which all gas turbines (aeropropulsion and power generation) are based on scales with the peak operating temperature. However, the peak temperature is limited by the turbine blades and the temperature they can withstand. The highest temperatures in the gas turbine occur in the combustor region but these temperatures are often too high for turbine blades. As a result, the combustion products must be diluted with relatively cooler air from the compressor to reduce the temperature to tolerable levels for the turbine blades. This research suggests placing a ring of high temperature open cell metal foam between the combustors and turbine sections of the jet engine to mix and average the difference in temperatures resulting from the cooling schemes in combustor cans. Temperature mixing effect was tested using a special setup with the application of an infrared camera and streams of hot and cold air passing through the foam. High speed flow pressure drop around Mach 1 (340 m/s) was done on the same foam samples to understand pressure drop in the compressible regime of air. Infrared imaging showed that open cell metal foams successfully mixed and averaged the difference in temperatures of the hot and cold gasses thus creating a more uniform temperature profile while pressure drop testing revealed that open cell metal foams result in minimal pressure drop at high flows especially when the increase in temperature in taken into consideration.

Effect of the multiphase composition in a premixed fuel–air stream on wedge-induced oblique detonation stabilisation

2018 ◽  
Vol 846 ◽  
pp. 411-427 ◽  
Author(s):  
Zhaoxin Ren ◽  
Bing Wang ◽  
Gaoming Xiang ◽  
Longxi Zheng
Keyword(s):  
Detonation Wave ◽  
Droplet Size ◽  
Oblique Shock ◽  
Smooth Transition ◽  
Oblique Shock Wave ◽  
Two Phase ◽  
Transition Pressure ◽  
Initial Droplet ◽  
Oblique Detonation Wave ◽  
Initial Droplet Size

An oblique detonation wave in two-phase kerosene–air mixtures over a wedge is numerically studied for the first time. The features of initiation and stabilisation of the two-phase oblique detonation are emphasised, and they are different from those in previous studies on single-phase gaseous detonation. The gas–droplet reacting flow system is solved by means of a hybrid Eulerian–Lagrangian method. The two-way coupling for the interphase interactions is carefully considered using a particle-in-cell model. For discretisation of the governing equations of the gas phase, a WENO-CU6 scheme (Hu et al., J. Comput. Phys., vol. 229 (23), 2010, pp. 8952–8965) and a sixth-order compact scheme are employed for the convective terms and the diffusive terms, respectively. The inflow parameters are chosen properly from real flight conditions. The fuel vapour, droplets and their mixture are taken as the fuel in homogeneous streams with a stoichiometric ratio, respectively. The effects of evaporating droplets and initial droplet size on the initiation, transition from oblique shock to detonation and stabilisation are elucidated. The two-phase oblique detonation wave is stabilised from the oblique shock wave induced by the wedge. As the mass flow rate of droplets increases, a shift from a smooth transition with a curved shock to an abrupt one with a multi-wave point is found, and the initiation length of the oblique detonation increases, which is associated with the increase of the transition pressure. By increasing the initial droplet size, a smooth transition pattern is observed, even if the equivalence ratio remains constant, and the transition pressure decreases. The factor responsible is incomplete evaporation before the detonation fronts, which results in a complicated flame structure, including regimes of formation of oblique detonation, evaporative cooling of droplets and post-detonation reaction.

Rotating Detonation Instabilities in Hydrogen-Oxygen Mixture

2014 ◽  
Vol 709 ◽  
pp. 56-62 ◽  
Author(s):  
Yu Hui Wang ◽  
Jian Ping Wang
Keyword(s):  
High Speed ◽  
Specific Impulse ◽  
Pressure Sensors ◽  
Intermediate Frequency ◽  
Oxygen Mixture ◽  
Detonation Waves ◽  
Thermodynamic Efficiency ◽  
Detonation Pressure ◽  
Acoustic Oscillations ◽  
Rotating Detonation

Rotating detonation engines are studied more and more widely because of high thermodynamic efficiency and high specific impulse. Rotating detonation of hydrogen and oxygen was achieved in this study. Rotating detonation waves were observed by high speed cameras and detonation pressure traces were recorded by PCB pressure sensors. The velocity of rotating detonation waves is fluctuating during the run. Low frequency detonation instabilities, intermediate frequency detonation instabilities and high frequency detonation instabilities were discovered. They are relevant to unsteady heat release, acoustic oscillations and rotating detonation waves.

Multiphase Rotating Detonation Engine

2020 ◽  
Author(s):  
Ian Dunn ◽  
Kareem Ahmed
Keyword(s):  
Detonation Wave ◽  
High Speed ◽  
Fourier Transforms ◽  
Operational Parameters ◽  
Discrete Fourier Transforms ◽  
Rotating Detonation Engine ◽  
Coal Particles ◽  
Detonation Engine ◽  
Rotating Detonation ◽  
Carbon Concentrations

Abstract The first experimental evidence of a solid-gas multiphase rotating detonation engine. Coal particles, carbon black with a volatility of 1% and a carbon concentration of 99%, were detonated successfully over many operational parameters. These operational parameters surrounding the various points of investigation are shown in multiple 2-D slices as well as plotted in one 3-D graph to show the effects of varying carbon concentrations. These parameters include: variation in total mass flux injected into the annulus ranging from (≅120–270 kg/(s*m2), variation in hydrogen-air equivalence ratio (0.65–1.0), and finally variation in total concentrations of carbon (0–42.5%). High-speed backend imaging allowed for the analysis of the detonation wave dynamics, where detonation velocities were deduced using Discrete Fourier Transforms. By varying the parameters mentioned above, detonation velocities experienced in the detonation channel allowed for an introduction of an optimal operational point. When carbon was injected into very lean hydrogen-air conditions, the detonation was over-driven, causing fluctuations in the detonation velocities upwards of ∼100 m/s. As carbon concentrations increased further, detonation wave velocities relative to Chapman-Jouguet detonation velocities decreased.

scholarly journals Numerical study of wedge supported oblique shock wave-oblique detonation wave transitions

2002 ◽  
Vol 24 (3) ◽  
pp. 149-157 ◽  
Author(s):  
C. A. R. Pimentel ◽  
J. L. F. Azevedo ◽  
L.F. Figueira da Silva ◽  
B. Deshaies
Keyword(s):  
Shock Wave ◽  
Detonation Wave ◽  
Numerical Study ◽  
Oblique Shock ◽  
Oblique Shock Wave ◽  
Oblique Detonation Wave
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