Combustion In Supersonic Flow Research Articles

Advances in Femtosecond Coherent Anti-Stokes Raman Scattering for Thermometry

The combustion process is complex and harsh, and the supersonic combustion flow field is also characterized by short duration and supersonic speed, which makes the real-time diagnostic technology for the transient environment extremely demanding. It is of great significance to realize high time-resolved accurate measurement of temperature, component concentration, and other parametric information of the combustion field to study the transient chemical reaction dynamics of the combustion field. Femtosecond CARS spectroscopy can effectively avoid the collision effect between particles in the measurement process and reduce the influence of the non-resonant background to improve the measurement accuracy and realize the time-resolved measurement on a millisecond scale. This paper introduces the development history of femtosecond CARS spectroscopy, points out its advantages and disadvantages, and looks forward to the future development trend to carry out high time-resolved measurements, establish a database of temperature changes in various complex combustion fields, and provide support for the study of engine mechanisms.

Experimental Investigation of Microwave-Assisted Kerosene Supersonic Combustion

ABSTRACT The microwave-assisted kerosene combustion in supersonic flow was invested experimentally using a novel microwave-flame coupling method. The experiment used a direct-connected system, with a horn antenna employed to introduce microwaves into the combustion chamber, generating a traveling wave within the cavity. The microwave field simulation results confirm this coupling method’s feasibility. The experimental results showed that with the influence of the microwave, the flame’s stable position moved upstream by 7.4 mm. The average velocity of flame propagation increased by 64% upstream of entering the cavity and by 61% upon exiting it. The specific impulse of the scramjet was increased by about 4% under a 700W continuous microwave. In the presence of hydrogen, there was a significant increase in the excitation of NO and N2. However, in hydrogen-free combustion processes, the enhancement of radicals was considerably less compared to ignition processes, suggesting a close correlation between microwave-assisted combustion and hydrogen. These experimental results validate the feasibility of the microwave-combustion coupling method, representing a novel exploration into microwave-assisted kerosene combustion that aligns more closely with the practical application scenarios of scramjet engines.

Supersonic combustion field evolution prediction in scramjet engine using a deblurring multi-scale attention network

Traditional deep learning technologies often overlook crucial spatiotemporal information when reconstructing supersonic combustion flow fields. These models can only reconstruct the current flow field, resulting in poor visual quality due to the atomization effect. This research introduces experimental studies on scramjet combustion flows with variable injection pressures at the inlet of a scramjet Mach 2.5, creating image datasets of flame evolution processes over different predicted time spans (5, 10, and 15 ms). It develops a multi-scale attention algorithm with deblurring (DB-MSAN) capabilities to predict the flame image after a certain period using the wall pressure signal from the previous moment. The algorithm employs two multi-head attention channels at different scales to extract timing information, encouraging the model to focus on the anisotropy of the input data and to identify more significant features. The DB module utilizes the adapted atmospheric scattering model to jointly estimate the transmission map and atmospheric light, achieving an exceptional defogging effect with a minimal computational expense. The model’s overall performance is assessed regarding efficiency and accuracy, comparing DB-MSAN’s performance differences with those of Chen’s and the ResNet16 models across multi-span, large-span, various test sets, and sparse wall measurement points. Experimental results indicated that, compared to other methods, DB-MSAN achieves a maximum peak signal-to-noise index improvement of 76.10 % and an SSIM index improvement of 155.26 % when predicting average-quality images. The prediction accuracy remains stable, even with sparse pressure input. In addition, DB-MSAN strikes an optimal balance between the number of parameters and model accuracy; it represents only 16.97 % of the volume compared to Chen’s model, which is 585 MB.

A Numerical Investigation of Supersonic Combustion Flow Control by Nanosecond-Pulsed Actuations

The efficiency of supersonic combustion is largely dependent on inlet and injection parameters. Additional energy input is required in some off-design conditions, and nanosecond discharge actuation can be a solution. In the present study, a phenomenological model of a nanosecond-pulsed surface dielectric barrier discharge (NS-SDBD) actuator was developed to analyze the combustion enhancement effect for a supersonic combustor with transverse H2 injection. A seven-reaction H2–air combustion model was adopted for the numerical simulation. Dynamic mode decomposition (DMD) was employed to acquire temperature perturbation in spatial and temporal domains. The results show that the actuator provides additional temperature-increment and species transportation through compression waves. The combustion enhancement effect is mainly attributed to the flow perturbation in the shear layer, which promotes the turbulent diffusion of fuel. Given the same power input, the combustion efficiency at the shockwave reflection point is increased by 17.5%, and the flame height is increased by 15.4% at its maximum.

Effects of ammonia combustion on skin friction characteristics for supersonic flow

Boundary layer combustion is an effective method to reduce friction in scramjet combustors. In existing research on drag-reducing fuels, hydrocarbons pose challenges related to carbon deposition and emissions. Meanwhile, hydrogen presents significant difficulties in storage and transportation. For the first time, this paper explores ammonia as a drag-reducing alternative. We employed the Reynolds-averaged Navier-Stokes (RANS) method to investigate the characteristics of drag reduction by ammonia combustion in supersonic flow. Numerical results indicate that the local drag reduction by ammonia combustion is better than hydrocarbon and worse than hydrogen compared to existing research. Ammonia exhibits superior potential for drag reduction. However, the overall drag reduction at room ammonia injection temperature is limited due to the significant distance between the ammonia self-ignition point and the injection port. To address this challenge, we proposed two optimization strategies: increasing the ammonia injection temperature and increasing the inlet ammonia decomposition ratio. As the ammonia injection temperature increases, the self-ignition position moves towards the inlet, and the combustion drag reduction region expands upstream. Interestingly, a higher ammonia inlet decomposition ratio does not necessarily lead to a better drag reduction effect. In fact, an excessively high decomposition ratio can inhibit the combustion drag reduction effect. The most effective drag reduction occurs when the ammonia inlet mass fraction is 50%, resulting in a 42.8% reduction in integrated drag compared to the case without NH3 injection. Overall, this paper offers critical insights into the utilization of ammonia combustion in scramjets to reduce drag.

Measurements of mixing layers and vortex structures of the strut-induced flow in a scramjet combustor with PIV and POD

The organization of the flow field in a scramjet is of great significance in achieving stable combustion in supersonic flow. Experimental investigation of the strut-induced flow in a scramjet is conducted with particle image velocimetry (PIV) measurement. The central wakes along with two outer free streams can be observed in the instantaneous velocity fields. Then the calculated vorticity shows a similar distribution with the mixing layers in the single-shot image, suggesting the mixing layers a preliminary assessment of the flow. Proper orthogonal decomposition (POD) of snapshots reveals several features beneficial for flame stabilization in the strut-induced flow, including the reverse flow, central large-scale vortex structures and the vortex structures in the mixing layers. Moreover, by comparison it is found that a significant asymmetry of strut-induced flow would compress the low-speed region and weaken the large-scale vortex structure which would present a challenge to achieve flame establishment. The research contributes to a profound understanding of strut-induced flow which may be useful for engineering design and optimization.

An improved flamelet/progress variable modeling in a hydrogen-fueled scramjet

The compressible nature of the supersonic combustion flow field results in significant temperature and pressure fluctuations. In the standard Flamelet/Progress Variable (FPV) model, not only is it difficult to specify the tabulation boundary conditions for the flamelet database, but using a single fixed flamelet database to describe the entire complex flow field will likely introduce significant errors. To account for this, an improved FPV model is proposed in this study. Dynamic adjustment of the tabulation pressure in the flamelet database is achieved by scaling the benchmark flamelet database to match the local pressure. Real-time calibration of the tabulation oxidant temperature and fuel temperature is also achieved by real-time statistics and interpolation between four flamelet databases. This allows the improved FPV model to adaptively match the target supersonic combustion flow field without the difficulty of specifying tabulation pressures and temperatures as in the standard FPV model, and it avoids the limitations imposed by the single flamelet database. An additional species transport equation is also incorporated into this model to improve species prediction. Based on the simulations of a hydrogen-fueled scramjet with low-and-high total temperature, the improved model is shown to better restore wall-pressure profiles, combustion mode predictions and OH (hydroxyl radical) distributions, compared to the standard FPV model and comparable studies. This indicates that the effects of compressibility on the chemical reaction rates have been considered.

A methodology for estimating hypersonic engine performance by coupling supersonic reactive flow simulations with machine learning techniques

We propose a methodology used to estimate the performance of hypersonic engines by coupling some machine learning methods with a generated CFD database and one-dimensional expansion equations. The present work also investigates the effects of fuel struts geometrical parameters on the supersonic combustion which takes place in a dual-mode ramjet/scramjet engine operating at stratospheric flight conditions with a cruise speed of Mach 8. We solved 2D compressible RANS flow equations coupled with the β-pdf method using Ansys Fluent commercial code, and built a CFD database with varying three design parameters which are strut V-settlement angle, strut location, and wedge angle. The numerical code was verified/validated using the data obtained in the DLR scramjet combustor. Three main objective functions in the combustor (combustion efficiency along 14 stations having 10 cm interval between each other, averaged flow variables at exit of combustor, and total pressure recovery factor in the combustor) were selected to evaluate the struts configuration parameters effects on supersonic combustion flow physics and engine performance. These objective functions, i.e. dependent variables were regressed with independent design parameters by three machine learning techniques which are Kernel regression, Gaussian process regression, and Artificial neural network. The machine learning models of the flow variables at the combustor throat provided initial conditions for a given fuel strut configuration to the expansion solutions for the nozzle component in order to calculate the engine performance. The Artificial neural network was found the most successful technique in overall regression of the objective functions. We also discovered that the most significant design variable is the strut wedge angle for all investigated phenomena in the supersonic reactive flow field.

Investigation on auto-ignition and chemical energy release characteristics of pilot hydrogen in supersonic combustion flow

This study investigates auto-ignition and heat release characteristics of pilot hydrogen chemical energy in a scramjet combustor equipped with a single cavity. Experiments are conducted in a direct-connected facility simulating Mach 6.0 flight conditions with a total temperature of 1350 K and total pressure of 1.75 MPa. Data are obtained from schlieren imaging, hydroxyl planar laser-induced fluorescence, flame emission, and 10-kHz static pressure transducers. The present investigation extends the pilot hydrogen ignition delay experimental dataset and clarifies the instabilities present in the ignition process. The results show that the supersonic internal flow of a confined cavity exhibits self-oscillating behavior with a dominant frequency of approximately 141.3 Hz. The primary chemical reaction occurs at mid-cavity, where the chemical energy of the pilot hydrogen begins to be converted into heat energy, then approaches the cavity ramp before finally being distributed across the whole cavity. The combustion mode is the cavity-stabilized scramjet mode. The distribution of hydroxyl radicals varies significantly because the combustion in the cavity is unsteady. The ignition delay time increases as the injection pressure rises. However, an injection pressure of 4.0 MPa produces an ignition delay of 24.7 ms, which is apparently shorter than the delay under an injection pressure of 3.5 MPa and similar to that under an injection pressure of 3.0 MPa. The injection of pilot hydrogen under high pressures induces greater heat release and more intense blockage effects, thus enhancing the probability of successful ignition and stable combustion.

Research on time series prediction of the flow field in supersonic combustor based on deep learning

The detection of supersonic combustion flow field provides valuable reference information for the efficient combustion of hypersonic vehicles. From the perspectives of scramjet operation during flight as well as experiment where the measured information is limited, flow field prediction using deep learning technology is a promising method that can provide future flow field evolution in scramjet combustors. This study proposes a convolutional neural network model of multi-temporal pressure information fusion to predict combustion flow field based on wall pressure. In addition, it analyzes the effect of various wall pressures on the flow field prediction. An experimental dataset of supersonic ground-pulse wind tunnel tests with different injection pressures is built through the combustion chamber wall under self-ignition conditions of a hydrogen-fueled scramjet. The results showed that the predicted flow field of the combustor agrees with the ground test, average correlation coefficient reached more than 90% and when the wall pressure number is 32, the average peak signal to noise ratio reaches about 23. and the main wave structure and turbulent boundary layer region are restored even if there is a shock boundary layer interaction.

Reconstructing the flame in supersonic combustion flow by using the distribution of the wall pressure based on deep learning

Two models based on the deep learning-based convolutional neural network (CNN) and the re-parameterized convolutional neural network (RepCNN) were designed to reconstruct the flame in the combustor. Experiments were performed on a ground-pulse combustion wind tunnel at a fixed inlet Mach number of 2.5 and different pressures to inject hydrogen to obtain the relevant datasets. The results showed that both models could reconstruct the image of the flame in the combustor based on pressures of the upper and lower walls as well as the pressure at which hydrogen was injected. The average structural similarity index between the reconstructed image of the flame and its actual/original image was 0.9553, the average peak signal-to-noise ratio was 34.201, and the average correlation coefficient was 0.9819. The speed of reconstruction of the image using the RepCNN model improved by 40.7% at the cost of a slightly lower accuracy compared with the CNN model, and it took only 2.85 ms to reconstruct the image of a single flame. The lightweight feature of the RepCNN provides an important foundation for monitoring the model to reconstruct the image of the flame in real time. The work here simplifies requirements on the hardware for ground wind tunnel tests and provides a new idea for examining the characteristics of the flame in small combustors.

Flame development prediction of supersonic combustion flow based on lightweight cascaded convolutional neural network

The flame development prediction of a scramjet combustor forecasts the combustion state and provides valuable information for active flow control. Experiments were performed on a hydrogen-fueled scramjet at different equivalence ratios in a ground pulse combustion wind tunnel with a Mach-2.5 incoming flow. Five image datasets of the flame evolution process were constructed at different predicted periods. The memory fusion cascade network (MFCN) was developed to predict flame images after a certain span using flame image sequences of the previous periods. A complete evaluation system was constructed to compare and analyze the performances of MFCN, Kongs, and ResNet16 models in multi- and long-span conditions. Experimental results show that MFCN achieves a maximum increase of 46.16% of the peak signal-to-noise ratio index, 69.14% of the structural correlation coefficient index, and 5.72% of the correlation coefficient index in the independent test set. Moreover, the volume of the model only reaches the KB level, which has the characteristics of being lightweight. MFCN outperforms other methods in terms of the prediction accuracy and maintains stable prediction results during multi- and long-span tasks.

A consistent scheme of the high-speed source term in probability density function methods for supersonic flows

To improve the particle energy accuracy of the probability density function (PDF) method in supersonic flows, a consistent numerical scheme for the high-speed source term in the particle energy equation is put forward. The proposed scheme is designed and computed based on the characteristic format, which shares the same right and left eigenvectors for the Jacobian of the convection term of the system. Therefore, this scheme is fully consistent with the spatial discretization of the inviscid term in the finite-difference solver of compressible flows. To show the advantages of the proposed scheme, a redundant energy equation is solved along with the Euler equation. The consistent scheme and the quasi scheme are numerically tested and compared in several canonical flows. The results show that the high-speed source term calculated by the consistent scheme generates much less numerical oscillation than the quasi scheme around discontinuities. Due to the accumulation of the numerical errors of the high-speed source term in every single iteration, the energy redundantly computed by the consistent scheme agrees better with the Euler results than the other scheme. Following this new high-speed source computation scheme, the large eddy simulation-PDF method is further developed and tested in a shock tube problem interacting with an isotropic turbulent flow and a supersonic temporally developing mixing layer. The results show that PDF with this consistent high-speed source scheme can improve the energy accuracy as well as turbulent combustion in supersonic flows.

Quasi-One-Dimensional Model of Hydrocarbon-Fueled Scramjet Combustor Coupled with Regenerative Cooling

In order to rapidly predict the performance of hydrocarbon-fueled regeneratively cooled scramjet engine in system design, a quasi-one-dimensional model has been developed. The model consists of a supersonic combustor model with finite-rate chemistry and a cooling channel model with real gas working medium, which are governed by two sets of ordinary differential equations separately. Additional models for wall friction, heat transfer, sonic fuel injection, and mixing efficiency are also included. The two sets of ordinary differential equations are coupled and iteratively solved. The SUNDIALS code is used since the equations for supersonic combustion flow are stiff mathematically. The cooling channel model was verified by electric heating tube tests, and the supersonic combustor model was verified by experimental results for both hydrogen and hydrocarbon-fueled scramjet combustors. Three cases were comparatively studied: (1) scramjet combustor with an isothermal wall, (2) scramjet combustor with an adiabatic wall, and (3) scramjet combustor with regenerative cooling. Results showed that the model could predict the axial distributions of flow parameters in the supersonic combustor and cooling channel. Differences on ignition delay time and combustion efficiency for the three cases were observed.

Evaluation of flamelet/progress variable model for the applications in supersonic combustion using hybrid RANS/LES approach

The Flamelet/Progress Variables (FPV) model coupled with large eddy simulation (LES) has been performed to appraise its applicability and performance for supersonic hydrogen combustion, based on the simulations of strut based scramjet and cavity based combustors. For the two typical schemes involved in the present work, the validation of the numerical solver compiled by in-house code is realized by the comparisons with the experimental measurements including temperature, velocity, and wall pressure. The methods for calculating mixture fraction variance in the framework of LES are also investigated and examined in both cases. It can be observed that the diffusion combustion mode is in the dominant state for the whole reactive zone in both cases, where the FPV model is physically compatible. Through the comparisons of the scale similarity method and the transport equation method for calculating mixture fraction variance, the importance of calculating this sub-grid turbulent scalar flux is emphasized. The results show that the mixture fraction variance calculated by the scale similarity model is locally high, but its diffusion is insufficient, which makes the local temperature of the combustion flow field overpredicted and concentrated. On the contrary, the transport equation of the mixture fraction variance can overcome this problem and improve the combustion prediction accuracy, thus, it is more recommended if the computing resources are guaranteed. Qualitatively, the Flamelet/Progress Variables (FPV) model with the large eddy simulation approach can accurately capture the structure and characteristics of the supersonic combustion flow field.

Effect of the micro vortex generator on the characteristics of vaporized RP-3 kerosene combustion in supersonic flows

Effect of the micro vortex generator on the characteristics of vaporized RP-3 kerosene combustion in supersonic flows

An investigation of hybrid CPU-GPU solvers for supersonic reacting flow simulation with detailed chemical kinetics

Accurate simulations of supersonic reacting flow require the use of detailed chemical kinetics to capture the complex phenomena such as auto-ignition and broken, thickened flamelets. However, the detailed chemical mechanisms for hydrocarbon fuels used in supersonic combustion typically have a great number of species and reactions. This paper reports on the implementation of a hybrid CPU-GPU solver by using the graphics processing unit (GPU) as a coprocessor to accelerate the computation of chemical source terms in modeling supersonic reacting flows with detailed chemical kinetics. The chemical kinetics are solved explicitly via a fully-coupled method with an implicit scheme. Three parallel strategies with different storage schemes were explored in implementing the highly parallel GPU algorithms for accelerating combustion modeling. Significant acceleration was obtained by using these parallel algorithms for chemical source terms evaluation. In order to verify the viability of the solver, two supersonic combustion flow test cases were conducted. The performance of these algorithms is evaluated by modeling four chemical reaction mechanisms on different grids compared with the CPU-only solver. The computation cost of these algorithms is basically proportional to the size of the grids. The performance gain of these parallel algorithms depends on the size of the reaction mechanism. A maximum speedup factor of over 80 was obtained by modeling the mechanism consisting of 348 species and 2163 reactions. The significant performance improvement provided by these parallel algorithms can provide a significant perspective for designing GPU-accelerated algorithms for applications in simulating supersonic reacting flows.

Design of a high-resolution optical measuring ring for supersonic combustion flow field

Design of a high-resolution optical measuring ring for supersonic combustion flow field

Flow and combustion mechanism of oblique detonation engines

<p indent="0mm">Oblique detonation engine is a novel type of ram propulsion system employed in air-breathing hypersonic flight vehicle. It utilizes oblique detonation waves to achieve the high-efficient combustion in supersonic flow. Benefiting from the scientific and technological advantages such as rapid energy release, high specific impulse, short combustor and fewer moving parts, research on the oblique detonation engines becomes the frontier of hypersonic propulsion technologies. To initiate and adjust the wave structures of the oblique detonations, it is critical to conduct systematic investigation on flow and combustion mechanism in the engine combustors. Due to the coupling of shock waves and combustion, the initiation zone of oblique detonations has the feature of complicated multi-wave structures, which are affected by the properties of the mixtures. Furthermore, these structures are constrained to the wedge by the high speed inflow, very sensitive to the change of inflow parameters. Hence, research on the related unsteady processes is also critical. Finally, the oblique detonation waves in confined spaces involve the interaction of the shock waves and the geometry structures, which is an unavoidable problem in the engineering application. In this paper, research progress of the above aspects has been summarized and commented, clarifying the underlying problems in the application and pointing out the future research trends.

Effects of Wall Emissivity on Aerodynamic Heating in Scramjets

The effects of the wall emissivity on aerodynamic heating in a scramjet are analyzed. The supersonic turbulent combustion flow including radiation is solved in the framework of a decoupled strategy where the flow field is d... | Find, read and cite all the research you need on Tech Science Press