We present EngineBench, the first machine learning (ML) oriented database to use high quality experimental data for the study of turbulent flows inside combustion machinery. Prior datasets for ML in fluid mechanics are synthetic or use overly simplistic geometries. EngineBench is comprised of real-world particle image velocimetry (PIV) data that captures the turbulent airflow patterns in a specially-designed optical engine. However, in PIV data from internal flows, such as from engines, it is often challenging to achieve a full field of view and large occlusions can be present. In order to design optimal combustion systems, insight into the turbulent flows in these obscured areas is needed, which can be provided via inpainting models. Here we propose a novel inpainting task using random edge gaps, a technique that emphasises realism by introducing occlusions at random sizes and orientations at the edges of the PIV images. We test five ML methods on random edge gaps using pixel-wise, vector-based, and multi-scale performance metrics. We find that UNet-based models are more accurate than the industry-norm non-parametric approach and the context encoder at this task on both small and large gap sizes. The dataset and inpainting task presented in this paper support the development of more general-purpose pre-trained ML models for engine design problems. The method comparisons allow for more informed selection of ML models for problems in experimental flow diagnostics. All data and code are publicly available at https://eng.ox.ac.uk/tpsrg/research/enginebench/.
The fuel injection system is the main process in supersonic vehicles. In this article, injection of fuel jet through a trapezoidal strut in the coaxial supersonic air stream is investigated. The numerical method is applied for the simulation of three-dimensional trapezoidal lobe strut in supersonic flow. Hydrogen gas is injected from the end of the trapezoidal strut injector to augment fuel mixing and diffusion downstream by intensifying vortices inside the domain. The power of the vortices varies by the injector velocity and free stream condition. To simulate our model, RANS equations with th…
A novel jet-stirred combustion chamber is designed to study turbulent premixed flames. In the new approach, multiple impinging turbulent jets are used to stir the mixture. It is well known that pair of counterflowing turbulent jets produces nearly a constant intensity along the jet axes. In this study, different numbers of impinging jets in various configurations are used to produce isotropic turbulence intensity. FLUENT simulations have been conducted to assess the viability of the proposed chamber. In order to be able to compare different configurations, three different non dimensional indic…
Predictions of thermoacoustic instabilities in annular combustors are essential but difficult. Axial variations of flow and thermal parameters increase the cost of numerical simulations and restrict the application of analytical solutions. This work aims to find approximate analytical solutions for the acoustic field in annular ducts with linear gradients of axially non-uniform cross-sectional area and mean temperature. These solutions can be applied in low-order acoustic network models and enhance the ability of analytical methods to solve thermoacoustic instability problems in real annular c…
Gas turbine combustion chambers contain numerous smallscale features that help to dampen acoustic waves and alter the acoustic mode shapes. This damping helps to alleviate problems such as thermoacoustic instabilities. During computational fluid dynamics simulations (CFD) of combustion chambers, these small-scale features are often neglected as the corresponding increase in the mesh cell count augments significantly the cost of simulation while the small physical size of these cells can present problems for the stability of the solver. In problems where acoustics are prevalent and critical to …
The combustion instability is investigated computationally for a multi-injector rocket engine using the flamelet progress variable (FPV) model. A C++ code is developed based on OpenFOAM 4.0 to apply the combustion model. Flamelet tables are generated for methane/oxygen combustion at the background pressure of $200$ bar using a 12-species chemical mechanism. A power law is determined for rescaling the reaction rate for the progress variable to address the pressure effect. The combustion is also simulated by the one-step-kinetics (OSK) method for comparison with the FPV approach. A study of comb…
We develop a theoretical framework that predicts and fully characterizes the diverse experimental observations of the nonlinear, combustion wave propagation in a rotating detonation engine (RDE), including the nucleation and formation of combustion pulses, the soliton-like interactions between these combustion fronts, and the fundamental, underlying Hopf bifurcation to time-periodic modulation of the waves. In this framework, the mode-locked structures are classified as autosolitons, or stably-propagating nonlinear waves where the local physics of nonlinearity, dispersion, gain, and dissipatio…
Distributed combustion, often associated with the low-oxygen condition, offers ultra-low NOX emission. However, it was recently achieved without combustion air dilution or internal flue gas recirculation, using a distinct approach called Mixture Temperature-Controlled combustion. Here, the fuel-air stream is cooled at the inlet to delay ignition and hence foster homogeneous mixture formation. The aim of this numerical study aims to understand the operation of this combustion concept better and present a robust framework for distributed combustion modeling in a parameter range where such operat…
To effectively simulate the combustion of hydrocarbon-fueled supersonic engines, such as rocket-based combined cycle (RBCC) engines, a detailed mechanism for chemistry is usually required but computationally prohibitive. In order to accelerate chemistry calculation, an artificial neural network (ANN) based methodology was introduced in this study. This methodology consists of two different layers: self-organizing map (SOM) and back-propagation neural network (BPNN). The SOM is for clustering the dataset into subsets to reduce the nonlinearity, while the BPNN is for regression for each subset. …
The present work details the analysis of the aerodynamics of an experimental swirl stabilized burner representative of gas turbine combustors. This analysis is carried out using High Frequency PIV (HFPIV) measurements in a reactive situation. While this information is usually available at a rather low rate, temporally resolved PIV measurements are necessary to better understand highly turbulent swirled flows, which are unsteady by nature. Thanks to recent technical improvements, a PIV system working at 12 kHz has been developed to study this experimental combustor flow field. Statistical quant…
This paper describes the numerical simulation of the NASA Langley Research Center supersonic H2 -Air combustion chamber performed using two approaches to model the presumed probability density function (PDF) in the flamelet progress variable (FPV) framework. The first one is a standard FPV model, built presuming the functional shape of the PDFs of the mixture fraction, Z, and of the progress parameter, Λ. In order to enhance the prediction capabilities of such a model in high-speed reacting flows, a second approach is proposed employing the statistically most likely distribution (SMLD) techcni…
A hybrid lattice Boltzmann/finite-difference solver for low Mach thermo-compressible flows developed in earlier works is extended to more realistic and challenging configurations involving turbulence and complex geometries in the present article. The major novelty here as compared to previous contributions is the application of a more robust collision operator, considerably extending the stability of the original single relaxation time model and facilitating larger Reynolds number flow simulations. Additionally, a subgrid model and the thickened flame approach have also been added allowing for…
The direct monitoring of a rotating detonation engine (RDE) combustion chamber has enabled the observation of combustion front dynamics that are composed of a number of co- and/or counter-rotating coherent traveling shock waves whose nonlinear mode-locking behavior exhibit bifurcations and instabilities which are not well understood. Computational fluid dynamics simulations are ubiquitous in characterizing the dynamics of RDE's reactive, compressible flow. Such simulations are prohibitively expensive when considering multiple engine geometries, different operating conditions, and the long-time…
The contribution of the "rapid" part of the pressure diffusion to the turbulent kinetic energy balance is analyzed, and a new model to describe its effect is suggested. A new transport equation for the turbulent kinetic energy is derived. The new k-equation does not require any modification in the standard epsilon-equation. A new k-epsilon model, which includes the new k-equation and the standard epsilon-equation, is validated in four separated flows: a planar diffuser, over a backstep, in a channel with wavy walls, and in an axisymmetric combustion chamber. It is shown that a new model reprod…
