Numerical study of flame stability, stabilization and noise in a swirl-stabilized combustor under choked conditions

Air transportation is an essential part of modern business and leisure needs, and the number of passengers carried per year is rapidly increasing worldwide. The International Civil Aviation Organization estimates that this number went from 2.2 billion in 2009 to 3.0 billion in 2013, due in part to rapid growth in emerging countries such as China. Many challenges for aircraft designers arise from this increase in air traffic, such as meeting pollutant and noise emission regulations. The engines play a major part in these emissions, and combustor technology has evolved towards high-pressure Lean Prevaporized Premixed (LPP) combustion to increase efficiency and decrease pollutant emissions. Unfortunately, this technology tends to reduce engine robustness, with a decrease in flame stability and stabilization margins. Recent studies suggest that combustion noise could also be increased in these systems. New methods are needed to describe and understand the mechanisms at hand for future design and optimization in order to operate these engines safely while still achieving emission targets. Large Eddy Simulation (LES) is a numerical approach to these problems which has shown excellent results in the past and is very promising for future design. The description of unsteady phenomena in these power-dense, confined and unsteady systems is essential to describe flame-turbulence interactions, acoustics and multiphysic couplings. As computing power grows, so does the amount of physics which can be modeled. Computational domains can be increased, and have gone from including only the reacting zone, to adding the fuel-air mixing areas, the heat liners and secondary flows, and the upstream and downstream elements. In this Ph.D., a compressible LES solver named AVBP is used to describe an academic test rig operated at the EM2C laboratory named CESAM-HP, a pressurized combustion chamber containing a swirl-stabilized partially-premixed flame and ended by a choked nozzle with high-speed flow. This leads to an accurate description of the chamber outlet acoustic behavior, and offers the possibility to investigate the dynamic behavior of the full system, and the occurrence of flame-acoustic coupling leading to combustion instabilities. It also gives insight into the combustion noise mechanisms, which are known to occur both in the reacting zone and in the nozzle. As shown in this study, this behavior also has an impact on flame stabilization in this system. This manuscript is organized as follows. In a first part, the context for chemistry, motion and acoustics of reacting multi-species flow is given. State of the art theories on reacting multi-species flow thermodynamics, thermoacoustics, combustion noise and flame stabilization in swirled burners are presented. Basic toy models and test cases are derived to validate the understanding of direct and indirect combustion noise, and numerical validations are performed. In a second part, the practical details about numerical investigation of such systems are reported. Finally, the third part describes the application of these tools and methods to the CESAM-HP4 test rig. The inclusion of the compressible nozzle in the LES computation yields results concerning three major issues for the burner: (1) flame stability, related to thermoacoustic instabilities; (2) flame stabilization, and the occurrence of flame flashback into the system’s injection duct; (3) combustion noise produced by the system, and identification of its separate contributions

Etude numerique de la stabilite, la stabilisation et le bruit de flamme dans un bruleur tourbillonnaire en conditions amorcees

Civil air traffic increase requires to decrease future aircraft emissions. Aeronauticengine combustor technology has evolved towards Lean Prevaporized Premixedcombustion to increase efficiency and reduce noxious emissions. Unfortunately, thistechnology tends to reduce engine robustness, with a decrease in flame stability andstabilization margins, and an increase in combustion noise. Compressible LargeEddy Simulation (LES), a promising numerical approach to describe full combustors,is used in this Ph.D on an academic test rig of a typical modern combustor flamein confined conditions. This investigation gives insight on the effects of full systemdynamics on combustion instabilities, flame flashback and combustion noise. Is showshow these tools can yield understanding of the phenomena controlling flame stabilityand stabilization, which is essential in order to operate future engines safely.Les chambres de combustion aéronautiques s’orientent vers la combustion pauvreprévaporisée prémélangée pour améliorer l’efficacité et réduire les émissions nuisiblesdes moteurs. Malheureusement, cette technologue tend à réduire les marges destabilité et de stabilisation des flammes, tout en augmentant le bruit de combustion.La Simulation aux Grandes Échelles compressible, une approche numériqueprometteuse pour décrire les chambres complètes, est utilisée dans cette thèse sur uncas académique de flamme typique des brûleurs modernes en conditions confinées.L’étude fournit des éléments clés sur l’effet de la dynamique du système completsur les instabilités de combustion, le retour de flamme et le bruit de combustion.Elle montre comment ces outils peuvent aider à comprendre les phénomènes quicontrôlent la stabilité et la stabilisation de flamme, ce qui est essentiel pour opérerles moteurs futurs en toute sécurité

Training convolutional neural networks to estimate turbulent sub-grid scale reaction rates

This work presents a new approach for premixed turbulent combustion modeling based on convolutional neural networks (CNN).1 We first propose a framework to reformulate the problem of subgrid flame surface density estimation as a machine learning task. Data needed to train the CNN is produced by direct numerical simulations (DNS) of a premixed turbulent flame stabilized in a slot-burner configuration. A CNN inspired from a U-Net architecture is designed and trained on the DNS fields to estimate subgrid-scale wrinkling. It is then tested on an unsteady turbulent flame where the mean inlet velocity is increased for a short time and the flame must react to a varying turbulent incoming flow. The CNN is found to efficiently extract the topological nature of the flame and predict subgrid-scale wrinkling, outperforming classical algebraic models

Detection of precursors of combustion instability using convolutional recurrent neural networks

Many combustors are prone to Thermoacoustic Instabilities (TAI). Being able to avoid TAI is mandatory to efficiently operate a system without sacrificing neither performance nor safety. Based on Deep Learning techniques, and more specifically Convolutional Recurrent Neural Networks (CRNN)1, this study presents a tool able to detect and translate precursors of TAI in a swirled combustor for different fuel injection strategies. The tool is trained to use only time-series recorded by a few sensors in stable conditions to predict the proximity of unstable operating points on a mass flow rate / equivalence ratio operating map, offering a real-time information on the margin of the system versus TAI. This allows to change operating conditions, and detect the directions to avoid in order to remain in the stable domain

Acoustically Induced Flashback in a Staged Swirl-Stabilized Combustor

This paper describes a joint experimental and numerical investigation of the inter- action between thermoacoustics and flashback mechanisms in a swirled turbulent burner. An academic air/propane combustor terminated by a choked nozzle is operated up to 2.5 bars. Experiments show that the flame can stabilize either within the combustion chamber or flashback inside the injection duct, intermittently or permanently. The present study focuses on the mechanisms leading to flashback: this phenomenon can occur naturally, depending on the swirl level which can be adjusted in the experiment by introducing axial flow through the upstream inlet. It can also be triggered by acoustic waves, either through acoustic forc- ing or self-excited thermoacoustic instability. Flashback is difficult to study experimentally, but it can be investigated numerically using LES: in a first configuration, the outlet of the chamber is treated as a non-reflecting surface through which harmonic waves can be intro- duced. In this case, a 20 kPa acoustic forcing is sufficient to trigger permanent flashback after a few cycles. When the LES computational domain includes the choked nozzle used experimentally, no forcing is needed for flashback to occur. Self-excited oscillations reach high levels rapidly, leading to flame flashback, as observed experimentally. These results also suggest a simple method to avoid flashback by using fuel staging, which is then tested successfully in both LES and experiments

Isolating strain and curvature effects in premixed flame/vortex interactions

This study focuses on the response of premixed flames to a transient hydrodynamic perturbation in an intermediate situation between laminar stretched flames and turbulent flames: an axisymmetric vortex interacting with a flame. The reasons motivating this choice are discussed in the framework of turbulent combustion models and flame response to the stretch rate. We experimentally quantify the dependence of the flame kinematic properties (displacement and consumption speeds) to geometrical scalars (stretch rate and curvature) in flames characterized by different effective Lewis numbers. Whilst the displacement speed can be readily measured using particle image velocimetry and tomographic diagnostics, providing a reliable estimate of the consumption speed from experiments remains particularly challenging. In the present work, a method based on a budget of fuel on a well chosen domain is proposed and validated both experimentally and numerically using two-dimensional direct numerical simulations of flame/vortex interactions. It is demonstrated that the Lewis number impact neither the geometrical nor the kinematic features of the flames, these quantities being much more influenced by the vortex intensity. While interacting with the vortex, the flame displacement (at an isotherm close to the leading edge) and consumption speeds are found to increase almost independently of the type of fuel. We show that the total stretch rate is not the only scalar quantity impacting the flame displacement and consumption speeds and that curvature has a significant influence. Experimental data are interpreted in the light of asymptotic theories revealing the existence of two distinct Markstein numbers, one characterizing the dependence of flame speed to curvature, the other to the total stretch rate. This theory appears to be well suited for representing the evolution of the displacement speed with respect to either the total stretch rate, curvature or strain rate. It also explains the limited dependence of the flame displacement speed to Lewis number and the strong correlation with curvature observed in the experiments. An explicit relationship between displacement and consumption speeds is also given, indicating that the fuel consumption rate is likely to be altered by both the total stretch rate and curvature

Etude numérique de la stabilité, la stabilisation et le bruit de flamme dans un brûleur tourbillonnaire en conditions amorcées

Le transport aérien est devenu un mode de déplacement primordial, et le nombre de passagers transportés chaque année est en rapide augmentation à travers le monde. La International Civil Aviation Organization estime que ce nombre est passé de 2.2 milliards en 2009 à 3.0 milliards en 2013, dû en partie à la croissance rapide de pays émergents comme la Chine. Les réglementations concernant les émissions polluantes et sonores s’adaptent et se durcissent, entraînant de nouveaux défis pour les constructeurs aéronautiques. Les chambres de combustion évoluent vers des technologies de combustion pauvre prémélangée prévaporisée pour améliorer l’efficacité et réduire la production de gaz néfastes. Malheureusement, cette technologie tend à réduire la robustesse des moteurs, en diminuant les marges de stabilité et de stabilisation de flamme. Des études récentes indiquent que cela pourrait aussi augmenter le bruit de combustion. Afin de poursuivre le design et l’optimisation des futurs moteurs, de nouvelles méthodes sont nécessaires pour décrire et comprendre les mécanismes en jeu, et d’opérer ces moteurs en toute sécurité tout en atteignant les objectifs de la réglementation. La Simulation aux Grandes Échelles (SGE) est une approche numérique de ces problèmes, qui a montré d’excellents résultats par le passé et qui est très prometteuse pour les designs futurs. La comprehension de ces systèmes énergétiquement denses, confinés et instationnaires passe par la description des interactions flamme-turbulence, de l’acoustique et des couplages multi-physiques. À mesure que la puissance de calcul augmente, la quantité de physique qui peut être modélisée croît également, tout comme la taille des domaines de calcul. Autrefois limités à la zone de fluide réactif, la zone de mélange entre l’air et le carburant a pu être incluse, puis des parois de la chambre et des contournement de flux secondaire, jusqu’à finalement les éléments en amont et en aval de la chambre de combustion. Dans cette thèse, un solveur SGE compressible nommé AVBP est utilisé pour décrire CESAM-HP, un banc d’essai académique situé au laboratoire EM2C: une chambre de combustion pressurisée, siège d’une flamme partiellement prémélangée stabilisée par un tourbillonneur, alimente une tuyère amorcée en fin de chambre. Ces calculs décrivent simultanément la chambre et la tuyère, tout en résolvant l’acoustique, ouvrant la voie à l’étude de la dynamique du système complet, et par là aux instabilités et au bruit de combustion. Cette étude montre enfin que la stabilisation de flamme est impactée par ce comportement dynamique, qui peut parfois entraîner des retours de flamme dans l’injecteur. Ce manuscrit est organisé de la manière suivante : dans une première partie, le contexte pour la chimie, le mouvement et l’acoustique dans un écoulement réactif multi-espèces est donné. L’état de l’art en matière de thermodynamique, de thermoacoustique, de bruit de combustion et de stabilisation de flamme dans les brûleurs tourbillonnaires est présenté. Des modèles simples et des cas test sont exposés pour valider la comprehension des phénomènes en jeu de manière isolée, et des confirmations numériques sont apportées. Dans une seconde partie, les détails pratiques de la mise en œuvre de tels calculs sont donnés. Enfin, la troisième partie décrit l’application de ces outils et méthodes au banc CESAM-HP. L’inclusion de la tuyère compressible dans le domaine fournit des résultats concernant trois sujets majeurs pour le brûleur: (1) la stabilité de la flamme, en lien avec les instabilités de combustion; (2) la stabilisation de la flamme, et l’apparition de retour de flamme dans l’injecteur; (3) le bruit de combustion produit par le brûleur, ainsi que l’identification de ses diverses contributions.Air transportation is an essential part of modern business and leisure needs, and the number of passengers carried per year is rapidly increasing worldwide. The International Civil Aviation Organization estimates that this number went from 2.2 billion in 2009 to 3.0 billion in 2013, due in part to rapid growth in emerging countries such as China. Many challenges for aircraft designers arise from this increase in air traffic, such as meeting pollutant and noise emission regulations. The engines play a major part in these emissions, and combustor technology has evolved towards high-pressure Lean Prevaporized Premixed (LPP) combustion to increase efficiency and decrease pollutant emissions. Unfortunately, this technology tends to reduce engine robustness, with a decrease in flame stability and stabilization margins. Recent studies suggest that combustion noise could also be increased in these systems. New methods are needed to describe and understand the mechanisms at hand for future design and optimization in order to operate these engines safely while still achieving emission targets. Large Eddy Simulation (LES) is a numerical approach to these problems which has shown excellent results in the past and is very promising for future design. The description of unsteady phenomena in these power-dense, confined and unsteady systems is essential to describe flame-turbulence interactions, acoustics and multiphysic couplings. As computing power grows, so does the amount of physics which can be modeled. Computational domains can be increased, and have gone from including only the reacting zone, to adding the fuel-air mixing areas, the heat liners and secondary flows, and the upstream and downstream elements. In this Ph.D., a compressible LES solver named AVBP is used to describe an academic test rig operated at the EM2C laboratory named CESAM-HP, a pressurized combustion chamber containing a swirl-stabilized partially-premixed flame and ended by a choked nozzle with high-speed flow. This leads to an accurate description of the chamber outlet acoustic behavior, and offers the possibility to investigate the dynamic behavior of the full system, and the occurrence of flame-acoustic coupling leading to combustion instabilities. It also gives insight into the combustion noise mechanisms, which are known to occur both in the reacting zone and in the nozzle. As shown in this study, this behavior also has an impact on flame stabilization in this system. This manuscript is organized as follows. In a first part, the context for chemistry, motion and acoustics of reacting multi-species flow is given. State of the art theories on reacting multi-species flow thermodynamics, thermoacoustics, combustion noise and flame stabilization in swirled burners are presented. Basic toy models and test cases are derived to validate the understanding of direct and indirect combustion noise, and numerical validations are performed. In a second part, the practical details about numerical investigation of such systems are reported. Finally, the third part describes the application of these tools and methods to the CESAM-HP4 test rig. The inclusion of the compressible nozzle in the LES computation yields results concerning three major issues for the burner: (1) flame stability, related to thermoacoustic instabilities; (2) flame stabilization, and the occurrence of flame flashback into the system’s injection duct; (3) combustion noise produced by the system, and identification of its separate contributions

Generalization Capability of Convolutional Neural Networks for Progress Variable Variance and Reaction Rate Subgrid-Scale Modeling

Deep learning has recently emerged as a successful approach to produce accurate subgrid-scale (SGS) models for Large Eddy Simulations (LES) in combustion. However, the ability of these models to generalize to configurations far from their training distribution is still mainly unexplored, thus impeding their application to practical configurations. In this work, a convolutional neural network (CNN) model for the progress-variable SGS variance field is trained on a canonical premixed turbulent flame and evaluated a priori on a significantly more complex slot burner jet flame. Despite the extensive differences between the two configurations, the CNN generalizes well and outperforms existing algebraic models. Conditions for this successful generalization are discussed, including the effect of the filter size and flame–turbulence interaction parameters. The CNN is then integrated into an analytical reaction rate closure relying on a single-step chemical source term formulation and a presumed beta PDF (probability density function) approach. The proposed closure is able to accurately recover filtered reaction rate values on both training and generalization flames

Deep-CRM: A New Deep Learning Approach For Capacitance Resistive Models

International audienceClassical reservoir simulators are built upon different underlying models: geological models integrating all the knowledge of the subsurface properties, fluid flow models integrating reservoir fluid physical properties, wells, and surface installations. The construction of such models however is very time and resources consuming. In the case of mature fields, where historical production data are available, data driven models can represent a suitable alternative or can be complementary to classical reservoir modelling as they require much less computation time and allocated resources. Among such models are Capacitance Resistive Models (CRMs), based on set of coupled ordinary differential equations representing material balance. These aim to predict flow rate in a reservoir using only dynamic data of production rates, water injections and Bottom Hole Pressure (BHP). In addition, CRMs can explain the underlying connectivity between several injectors and producers that could be a valuable information for dynamic synthesis and for better understanding of fluid flows in the reservoir. Most of the current work on CRMs optimizes a nonlinear multivariate regression of the CRM's parameters. Such optimization needs a closed form solution of the CRM ODEs. which is only possible under conditions: constant or linear variation in injection or in BHP. Once we have optimized the CRM's parameters, we can use the closed form solution to perform forecasting. The aim of this work is to propose a complete approach to optimize the CRM's parameters and forecast future production. This approach is not based on any assumptions on injections or on producers' BHP. To this end, we introduce a new approach based on a deep learning strategy: Physics-Informed Neural Networks (PINNs) for CRMs. This paper is organized as follows: first we introduce the related work on CRMs. Second, we detail the theory of CRMs and PINNs. Our approach, called Deep-CRMs, is presented in the third section. We focus on the mathematical description of Deep-CRMs and show experiments in order to compare our approach to the nonlinear multivariate regression of the closed form solution. These experiments are based on two datasets: the first is a synthetic dataset generated using ECLIPSE® and SISMAGE®, and the second is a real field dataset provided by one of our affiliates

Producing realistic climate data with generative adversarial networks

International audienceThis paper investigates the potential of a Wasserstein generative adversarial network to produce realistic weather situations when trained from the climate of a general circulation model (GCM). To do so, a convolutional neural network architecture is proposed for the generator and trained on a synthetic climate database, computed using a simple three dimensional climate model: PLASIM. The generator transforms a "latent space", defined by a 64-dimensional Gaussian distribution, into spatially defined anomalies on the same output grid as PLASIM. The analysis of the statistics in the leading empirical orthogonal functions shows that the generator is able to reproduce many aspects of the multivariate distribution of the synthetic climate. Moreover, generated states reproduce the leading geostrophic balance present in the atmosphere. The ability to represent the climate state in a compact, dense and potentially nonlinear latent space opens new perspectives in the analysis and handling of the climate. This contribution discusses the exploration of the extremes close to a given state and how to connect two realistic weather situations with this approach