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At least 37 records · Page 2

Markov Chain Monte Carlo Parameter Estimation of Deflagration Losses in a Rotating Detonation Engine

One of the practical challenges of the studies of rotating detonation engines (RDEs) is the direct estimation of losses from experimental measurements. This study attempts at resolving this limitation by combining a reduced order model (ROM) of the detonation wave characteristics with a Markov chain Monte Carlo parameter estimation framework. The model considers simple deflagration losses and the overall impact of deflagration on RDE performance. To evaluate this model, a Markov Chain Monte Carlo (MCMC) sampling technique was applied to estimate the loss parameters within the model for a set of conditions operated in hydrogen-air over a range of mass flow rates and equivalence ratios. The MCMC parameter estimation framework allowed for the determination of a posterior distribution of the loss parameters for each test condition, an examination of the correlation between the loss parameters and measured performance metrics of the RDE, and an uncertainty propagation of these parameters. The predicted model loss parameters were then compared to indirect experimental measurements of the deflagration combustion fractions to evaluating the validity of the approach, and shed light on the benefits and drawbacks of the model, measurement techniques, and the estimation framework.

33 ADVANCED PROPULSION SYSTEMS↗

Wave Detection and Tracking Within a Rotating Detonation Engine Through Object Detection

As the operational time window of experimental rotating detonation engines (RDEs) is expanded and the technology matures toward integration within gas turbines, monitoring techniques must evolve to offer computationally efficient and highly time-resolved diagnostics. In this study, computer vision object detection methodology that seeks to reduce data processing time and calculate wave velocity within drastically reduced time intervals as compared to traditional high-frame-rate RDE images analysis techniques is proposed. The adapted you-only-look-once object detection network is trained to detect individual detonation waves within single down-axis RDE images. The wave location and rotational direction detected within a frame are tracked through a series of high-speed images to calculate the frame-to-frame wave velocity with the time-step resolution of $\mathrm{20 μs}$ across a series of frames. The analysis of the annotation box size and image linearization effects is presented, demonstrating the lowest frame-to-frame velocity total uncertainty of $\mathrm{±3.8\%}$ and the highest classification speed of 9.5 frames per second using linearized images. Linearized images “unwrap” the RDE annulus pixel region to a reduced image size. Here, this new method offers great reductions in data processing times and unsteady detonation behavior insight at intervals more comparable to the timescales of detonation wave interactions via the application of machine learning to experimental RDE data.

33 ADVANCED PROPULSION SYSTEMS↗

Equivalence Ratio Scans in a Rotating Detonation Engine

Published data for run times exceeding a few seconds in rotating detonation engines (RDEs) is rare, but long duration tests are necessary to understand both transient and persistent phenomena in RDE operation. Previous work has noted different detonation wave modes at different equivalence ratios. In the current study, multiple long-duration runs with constant air flow rate and variable equivalence ratio are conducted in a hydrogen-fueled, water-cooled RDE. Analysis of the capillary tube averaged pressure (CTAP) data reveals a strong correlation with equivalence ratio as well as a small time dependency due to transient thermal processes. Ion probe measurements are used to analyze detonation wave frequencies and modes, both of which are strongly dependent on the equivalence ratio. Mode transitions are observed to occur consistently as the equivalence ratio is traversed between 0.55 and 0.60. These transitions are also found to be a function of the direction of changing equivalence ratio (ascending or descending) and time.

Boyette, Wesley R.↗

Equivalence Ratio Scans in a Rotating Detonation Engine

Published data for run times exceeding a few seconds in rotating detonation engines (RDEs) is rare, but long duration tests are necessary to understand both transient and persistent phenomena in RDE operation. Previous work has noted different detonation wave modes at different equivalence ratios. In the current study, multiple long-duration runs with constant air flow rate and variable equivalence ratio are conducted in a hydrogen-fueled, water-cooled RDE. Analysis of the capillary tube averaged pressure (CTAP) data reveals a strong correlation with equivalence ratio as well as a small time dependency due to transient thermal processes. Ion probe measurements are used to analyze detonation wave frequencies and modes, both of which are strongly dependent on the equivalence ratio. Mode transitions are observed to occur consistently as the equivalence ratio is traversed between 0.55 and 0.60. These transitions are also found to be a function of the direction of changing equivalence ratio (ascending or descending) and time.

Boyette, Wesley R.↗

Concept of Dynamic Heat Insulation for Rotating Detonation Engines

This work introduces a new class of materials concept to dynamically reduce instantaneous heat fluxes in Rotating Detonation Engine (RDE) combustor chamber walls. The high-frequency and high-amplitude surface heat fluxes observed in RDEs arise from large instantaneous temperature differences between the detonation shockwave and chamber wall surface. These temperature gradients drive substantial energy loss and reduce the chamber gas pressure, ultimately limiting the cycle’s thermodynamic efficiency. This work introduces a concept for dynamically insulating the combustion chamber surfaces using surface layers or coatings with low thermal time scale. With such coatings, the surface temperature may follow the fluctuations of the cyclic detonation wave temperature, thus reducing the instantaneous heat flux therefore cycle-mean heat flux. To analyze these cyclic thermal phenomena, a one-dimensional analytical conduction solver was utilized with the capability to handle multilayered structures. Parametric modeling was performed using transient heat flux boundary conditions representative of a hydrogen–air RDE across a broad range of coating thermal properties and engine conditions. The coating effectiveness scaled with the product of thermal time constant and detonation wave frequency and the results were non-dimensionalized to guide future materials development. This strategy may offer benefits in increasing material survivability, reducing cooling requirements, and enhancing pressure gain.

heat transfer↗

Multidimensional Numerical Modeling of Combustion Dynamics in a Non-Premixed Rotating Detonation Engine With Adaptive Mesh Refinement

In the present work, a novel computational fluid dynamics (CFD) methodology was developed to simulate full-scale non-premixed rotating detonation engines (RDEs). A unique feature of the modeling approach was the incorporation of adaptive mesh refinement (AMR) to achieve a good trade-off between model accuracy and computational expense. Here, unsteady Reynolds-averaged Navier–Stokes (RANS) simulations were performed for an Air Force Research Laboratory (AFRL) non-premixed RDE configuration with hydrogen as fuel and air as the oxidizer. The finite-rate chemistry model, along with a ten-species detailed kinetic mechanism, was employed to describe the H 2 -Air combustion chemistry. Three distinct operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel/air mass flowrates. For all conditions, the capability of the model to capture essential detonation wave dynamics was assessed. An exhaustive verification and validation study was performed against experimental data in terms of a number of waves, wave frequency, wave height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model was demonstrated to accurately predict the sensitivity of these wave characteristics to the operating conditions, both qualitatively and quantitatively. A comprehensive heat release analysis was also conducted to quantify detonative versus deflagrative burning for the three simulated cases. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

42 ENGINEERING↗

Flow Development in Radial Plane of Rotating Detonation Engine Integrated with Aerospike

In this study, axial and radial velocity components are measured downstream of a rotating detonation engine (RDE) integrated with an aerospike by using particle image velocimetry (PIV) at 100 kHz. The RDE is operated at high pressures obtained by restricting the RDE exit with a converging nozzle, which also directs the flow radially toward the aerospike. Reactants, methane fuel, and enriched air (67% oxygen and 33% nitrogen) are supplied from separate plenums at ambient temperature. PIV data are presented to investigate how pressure ratios within the RDE channel affect the flow evolution across the aerospike. The RDE is shown to operate stably and consistently in a single wave mode for all six test runs. The study highlights large temporal and spatial variations in both axial and radial flow velocities at the nozzle throat that persist downstream across the aerospike. Each point in the flowfield oscillates at the frequency recorded inside the RDE channel. Overall, the temporally and spatially varying aerospike flowfield is far from the ideal case of a uniform flow at its exit, and it points toward the need to condition the flow within the RDE channel to produce more uniform conditions at the nozzle throat.

Engineering↗

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗

Potassium carbonate decomposition modeling within rotating detonation engines for direct power extraction applications

We report that recently, there has been a significant interest in detonation-based combustion systems, such as rotating detonation engines (RDE), due to potential performance advantages in propulsion and energy applications. This includes improvements in thermodynamic efficiency, inherently high gas velocities, and the possibility of achieving an increase in total pressure (i.e. pressure gain) through the combustion process. Due to approximating a constant volume combustion process, these devices also tend to exhibit extremely high local gas temperatures relative to a comparable constant pressure combustor. These advantages overlap well with desirable performance characteristics of direct power extraction (DPE) technologies, such as a magnetohydrodynamic (MHD) generator. Typically, in DPE systems hot combustion products are seeded with an easily ionizable material such as potassium carbonate (K 2 CO 3 ) in order to boost the electrical conductivity. However, due to the short gas residence times within an RDE, it was unclear whether forming an electrically conductive combustion plasma would be feasible for integration with a downstream MHD generator. A model is presented which describes the heating, decomposition, and ionization of solid K 2 CO 3 particles and aqueous solutions of K 2 CO 3 in water, for a given initial particle diameter. This model was combined with available computational fluid dynamics (CFD) data for an oxygen-methane RDE in a one-way coupled Eulerian-Lagrangian framework to predict particle trajectories and the corresponding heating, decomposition, and ionization histories. Electrical conductivities were computed using a previously developed model, and a method was proposed to determine an equivalent average electrical conductivity. Results show that particle sizes below ~30 µm are able to fully decompose before reaching the exit of the RDE. While the one-way coupled nature of the simulations precluded rigorous evaluation of the effects of seed material on detonability, a substantial temperature reduction is expected at the detonation wave front due to heating and decomposition. A preliminary comparison is presented between the RDE and an equivalent constant pressure adiabatic combustor, showing a potential performance advantage for the RDE.

42 ENGINEERING↗

Computational Fluid Dynamics Combustion Modeling for Rotating Detonation Engines

This paper focuses on the development and validation of a combustion model for Computational Fluid Dynamics (CFD) modeling of Rotating Detonation Engines. A zero-dimensional Partially Stirred Reactor (PaSR) with a detailed chemical kinetic mechanism for hydrogen and air is used to model turbulent combustion. The model is computationally efficient and is based on the notion of partial mixing at the sub-grid level with turbulent exchange between mixed and unmixed regions. The ability of the PaSR model to accurately represent both detonative and deflagrative combustion is assessed by validating the results against experimental data. The effects of mesh resolution on the solution are also studied in order to determine if a mesh independent solution is obtainable with the Large Eddy Simulation (LES) approach to modeling turbulence. A comparison is made between the PaSR model and simply ignoring turbulence chemistry interactions which assumes that all species are perfectly mixed at the sub-grid level.

Strakey, Peter↗

Machine-Learning-Based Rotating Detonation Engine Diagnostics: Evaluation for Application in Experimental Facilities

Real-time monitoring of combustion behavior is a crucial step toward actively controlled rotating detonation engine (RDE) operation in laboratory and industrial environments. Various machine learning methods have been developed to advance diagnostic efficiencies from conventional postprocessing efforts to real-time methods. Here this work evaluates and compares conventional techniques alongside convolutional neural network (CNN) architectures trained in previous studies, including image classification, object detection, and time series classification, according to metrics affecting diagnostic feasibility, external applicability, and performance. Real-time, capable diagnostics are deployed and evaluated using an altered experimental setup. Image-based CNNs are applied to externally provided images to approximate dataset restrictions. Image classification using high-speed chemiluminescence images and time series classification using high-speed flame ionization and pressure measurements achieve classification speeds enabling real-time diagnostic capabilities, averaging laboratory-deployed diagnostic feedback rates of 4–5 Hz. Object detection achieves the most refined resolution of 20 μs in postprocessing. Image and time series classification require the additional correlation of sensor data, extending their time-step resolutions to 80 ms. Comparisons show that no single diagnostic approach outperforms its competitors across all metrics. This finding justifies the need for a machine learning portfolio containing a host of networks to address specific needs throughout the RDE research community.

33 ADVANCED PROPULSION SYSTEMS↗

Operability of a Natural Gas–Air Rotating Detonation Engine

A combustor was developed to operate with natural gas and air as the primary propellants at elevated chamber pressures and air preheat temperatures representative of land-based power generation gas turbine engines. Detonation dynamics were studied to characterize the operability of rotating detonation-based pressure gain combustion systems for this application. Measurements of chamber wave dynamics were performed using high-frequency pressure transducers and high-speed imaging of broadband combustion chemiluminescence. The rotating detonation engine was tested with two injector configurations across a broad range of mass flux (200–500 kg/m 2 /s), equivalence ratio (0.85–1.2), and oxygen mass fraction (23.2–35%) conditions to determine the effect of operating parameters on the propagation of detonation waves in the combustor. Wave propagation speeds of up to 70% of the mixture Chapman–Jouguet detonation velocity and chamber pressure fluctuations greater than 4 times the mean chamber pressure were observed. Supplementing the air with additional oxygen, varying the equivalence ratio, and enriching the fuel with hydrogen revealed that combustor operability is sensitive to the chemical kinetics of the propellant mixture. Comparing the operational trends of the two injector configurations suggests that one design mixes the incoming propellants more effectively. Although most test conditions exhibited counter-rotating detonation waves within the chamber, the injector design with superior mixing characteristics was able to support single-wave propagation.

20 FOSSIL-FUELED POWER PLANTS↗

Numerical Analysis of Wave Characteristics in a Methane-Oxygen Rotating Detonation Engine

Results from the simulation of the U.S. Air Force Research Laboratory methane–oxygen rotating detonation rocket engine from four independent research groups with different flow solvers underpredicted primary detonation wave speeds by a significant margin as compared to experimental values. In a simulation performed by the authors, the average calculated speed of the detonation waves was roughly [Formula: see text] as compared to the experimentally measured value of [Formula: see text]. This paper presents a detailed analysis of the wave characteristics in this simulation to provide a more quantitative understanding of the underlying factors leading to this discrepancy. The results show that weaker counter-rotating shock waves have a significant impact on the behavior of the primary detonation waves. The wave speed of the primary detonation wave is reduced by [Formula: see text] due to collisions with the counter-rotating waves. The presence of these counter-rotating waves also has a strong influence on the flow conditions upstream of the primary detonation waves, as well as the engine heat release rate. In addition, the flow properties upstream of the detonation wave vary significantly in the radial direction. Finally, the subfilter turbulent viscosity is shown to vary radially and with proximity to detonation waves.

Engineering↗

Individual Wave Detection and Tracking within a Rotating Detonation Engine through Computer Vision Object Detection applied to High-Speed Images

Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.

Johnson, Kristyn↗

Experimental and theoretical analysis of carbon driven detonation waves in a heterogeneously premixed Rotating Detonation Engine

Coal dust explosions can be hazardous; however, they can also generate a significant rise in stagnation pressure if adequately harnessed. Rotating detonation combustors seek to take advantage of the stagnation pressure rise phenomenon in a more sustained and controlled manner via confinement to a physical annulus, leading to increased overall thermodynamic efficiency. Here this investigation presents an analysis of detonations fueled by Carbon Black, a solid particulate consisting of virtually pure carbon molecules and lean Hydrogen-Air mixtures. It is realized that with the addition of Carbon Black, an increase of lean mixture detonability and detonation velocities extending the operating limit over that of a pure hydrogen-air mixture is experienced. For all testing conditions, the total equivalence ratio is held at φ = 1, while the fuel mixture's carbon mass fraction is increased from 0 to 0.7 while the hydrogen is decreased. Detonation wave velocities are extracted from high-speed imaging through applying a Discrete Fourier Transform algorithm to determine changes to the wave speed as Carbon Black particles are introduced. As a result, due to the addition of Carbon Black as an auxiliary fuel source, detonations were formed instead of deflagrations in operating conditions where one would expect deflagrations at the same hydrogen-air equivalence ratios without Carbon Black addition. The detonation formation provides evidence that the coal particles are reacting within the detonation wave in a large enough capacity to support a detonation wave within the annulus. Furthermore, the wave speed is shown to increase with the additional of carbon particles. At a constant global equivalence ratio, the detonation wave velocities were found to decrease with hydrogen's incremental replacement with coal particles. Whereby, through a theoretical comparison of the heat of combustion as computed from the experimentally derived detonation wave velocities, a linear relationship of the two was shown to exist. Therefore, the heat of combustion has the potential to describe an operational limit to sustaining a detonation wave.

42 ENGINEERING↗

Rotating Detonation Engine Introduction [Webinar]

Turning a constant pressure combustor into a constant volume combustor changes it from a Brayton Cycle into a Humphrey Cycle. This allows it to extract more work from the fuel, increasing efficiency and reducing emissions. One way to create a constant volume combustor is by using a rotation detonation engine that introduces air and fuel continuously.

30 DIRECT ENERGY CONVERSION↗