Devant la nécessité de diminuer les émissions polluantes du secteur du transport, les constructeurs de moteurs d'avion se sont tournés vers l'utilisation de régimes pauvres prémélangés. Ces régimes ont pour avantage de diminuer la production de NOx mais l'inconvénient de favoriser les instabilités de combustion dans les moteurs. La simulation numérique (LES (Large Eddy Simulation) et solveurs de Helmholtz par exemple) a fait ses preuves en matière de de prédiction des instabilités au stade de la conception des moteurs. Pour aller vers plus de précision, il est nécessaire de prendre en compte les détails géométriques des chambres. Les chambres de combustion sont équipées de plaques multiperforées dans le but d'assurer leur refroidissement. Ces plaques sont constituées d'orifices de diamètre inférieur au millimètre, il est donc impossible de les mailler. L'objectif de cette thèse est d'être capable de prendre en compte les plaques multiperforées dans le calcul des modes acoustiques d'une chambre de combustion. Les plaques sont donc remplacées par un modèle homogène développé par Howe en 1979. Ce modèle simule le comportement d'une plaque multiperforée soumise à une excitation acoustique sous certaines hypothèses. Ce modèle se présente sous la forme d'une impédance acoustique. Il est bien adapté pour être codé dans un solveur de Helmholtz. Le modèle de Howe a été développé dans le cas où les plaques multiperforées sont à l'interface entre deux fluides froids. Le modèle est adapté pour prendre en compte le saut de température entre le contournement et la chambre de combustion. Le codage est ensuite validé en comparant les résultats numériques obtenus avec une résolution analytique sur des configurations simples. Ces premiers résultats sur des cas simples permettent de mettre en évidence le comportement acoustique des plaques multiperforées. Elles ont pour effet d'amortir les modes acoustiques mais l'amortissement dépend des paramètres géométriques des plaques et de la vitesse de l'écoulement traversant les orifices. L'étude des instabilités est ensuite appréhendée par une approche de bilans énergétiques. Les chambres industrielles étant équipées de plusieurs paires de plaques multiperforées, il est intéressant de déterminer quelles plaques sont les plus efficaces. Un bilan d'énergie acoustique permet de calculer le pourcentage effectif d'amortissement auquel contribue chaque plaque. En présence d'une flamme, l'approche par bilans permet d'évaluer la contribution des plaques et de la flamme à l'amortissement ou l'amplification d'une instabilité. Une chambre industrielle équipant un hélicoptère de la société Turbomeca est calculée en utilisant les outils développés dans la thèse. Le calcul du bilan d'énergie en présence d'une flamme et des plaques multiperforées permet de déterminer la stabilité des modes de cette chambre et les éléments responsables de l'évolution de l'instabilité. L'ensemble de ces travaux a été financé par la SNECMA et le modèle pour les plaques multiperforées a été implémenté dans le solveur de Helmholtz AVSP, propriété CERFACS-SNECMA. / Aeronautical engine constructors are using lean premixed regimes to deal with the necessity to cut down pollutant emissions. These regimes indeed help to prevent the emission of NOx but trigger on the other hand combustion instabilities. Numerical simulation (which can consist of LES or Helmholtz solvers for example) has proven to be a usefool tool to predict these instabilities at the design stage. Acoustic modes can be well predicted only if geometrical details are taken into account. Multiperforated plates which equip combustion chambers with the purpose of cooling the inner walls must for instance be taken into account in a numerical calculation. These plates consist of several apertures with a diameter smaller than 1 millimeter, which makes their meshing impossible. The objective of this thesis is to take into account perforated plates in the numerical simulation of the acoustics of combustion chambers. The homogeneous model for the acoust ic behaviour of a perforated plate derived by Howe in 1979 is used. Provided some hypotheses, this model can predict the acoustic behaviour of a plate under an acoustic excitation. Howe's model, derived in an incompressible flow, is here adapted to be used in the case where the perforated plate in located between the casing (cold air) of a combustion chamber and the inner chamber (filled with a hot mixture). The model is well suited to be implemented in an existing 3D Helmholtz solver, because it appears under the form of an impedance. The coding is validated by comparing numerical results to analytical results on simple geometries. First results allow to show the damping behaviour of perforated plates and its dependance to geometric parameters or the speed of the incoming flow though the apertures.Acoustic instabilities can also be apprehended with an acoustic energy approach. Since industrial chambers are equipped with several pairs of multiperforated plates, it is interesting to show which of them are the most efficient at damping purposes. An acoustic energy budget allows to predict the percentage of the total damping a particular plate is responsible for. In the presence of a flame, the acoustic energy budget can also give information on the contribution of the flame on the triggering or damping of the instability.An industrial chamber designed by Turbomeca for a helicopter is computed. The acoustic energy budget on a computation taking into account the active flame and the multiperforated plates allows to predict the stability of the modes of the chamber. The elements responsible for the behaviour of the instability can be identified. This work has been funded by SNECMA and the code used to implement the model is AVSP, it co-belongs to CERFACS and SNECMA.

Lean premixed combustion is at present one of the most promising methods to reduce emissions and to maintain high efficiency in combustion systems. As the emission legislation becomes more stringent, modelling of turbulent premixed combustion has become an important tool for designing efficient and environmentally friendlier combustion systems. However, in order to predict these emissions reliable predictive models are required. One of the methods used for predicting pollutants is the conditional moment closure (CMC), which is suitable to predict pollutants with slow time scales. Despite the fact that CMC has been successfully applied to various non-premixed combustion systems, its application to premixed flames is not fully tested and validated. The main difficulty is associated with the modelling of the conditional scalar dissipation rate (CSDR) of the conditioning scalar, the progress variable. In premixed CMC, this term is an important quantity and represents the rate of mixing at small scales of relevance for combustion. The numerical accuracy of the CMC method depends on the accuracy of the CSDR model. In this study, two different models for CSDR, an algebraic model and an inverse problem model, are validated using two different DNS data sets. The algebraic model along with standard k-ε turbulence modelling is used in the computations of stoichiometric and very lean pilot stabilized Bunsen flames using the RANS-CMC method. A first order closure is used for the conditional mean reaction rate. The computed nonreacting and reacting scalars are in reasonable agreement with the experiments and are consistent with earlier computations using flamlets and transported PDF methods for the stoichiometric flames, and transported PDF methods for the very lean flames. Sensitivity to chemical kinetics mechanism is also assessed.

L’objectif final étant de développer des modèles d’ordre réduit pour les applications de combustion, des techniques d’apprentissage automatique non supervisées et supervisées ont été testées et combinées dans les travaux de la présente thèse pour l’extraction de caractéristiques et la construction de modèles d’ordre réduit. Ainsi, l’application de techniques pilotées par les données pour la détection des caractéristiques d’ensembles de données de combustion turbulente (simulation numérique directe) a été étudiée sur deux flammes H2 / CO: une évolution spatiale (DNS1) et une jet à évolution temporelle (DNS2). Des méthodes telles que l’analyse en composantes principales (ACP), l’analyse en composantes principales locales (LPCA), la factorisation matricielle non négative (NMF) et les autoencodeurs ont été explorées à cette fin. Il a été démontré que divers facteurs pouvaient affecter les performances de ces méthodes, tels que les critères utilisés pour le centrage et la mise à l’échelle des données d’origine ou le choix du nombre de dimensions dans les approximations de rang inférieur. Un ensemble de lignes directrices a été présenté qui peut aider le processus d’identification de caractéristiques physiques significatives à partir de données de flux réactifs turbulents. Des méthodes de compression de données telles que l’analyse en composantes principales (ACP) et les variations ont été combinées à des méthodes d’interpolation telles que le krigeage, pour la construction de modèles ordonnées à prix réduits et calculables pour la prédiction de l’état d’un système de combustion dans des conditions de fonctionnement inconnues ou des combinaisons de modèles valeurs de paramètre d’entrée. La méthodologie a d’abord été testée pour la prévision des flammes 1D avec un nombre croissant de paramètres d’entrée (rapport d’équivalence, composition du carburant et température d’entrée), avec des variantes de l’approche PCA classique, à savoir PCA contrainte et PCA locale, appliquée aux cas de combustion la première fois en combinaison avec une technique d’interpolation. Les résultats positifs de l’étude ont conduit à l’application de la méthodologie proposée aux flammes 2D avec deux paramètres d’entrée, à savoir la composition du combustible et la vitesse d’entrée, qui ont donné des résultats satisfaisants. Des alternatives aux méthodes non supervisées et supervisées choisies ont également été testées sur les mêmes données 2D. L’utilisation de la factorisation matricielle non négative (FNM) pour l’approximation de bas rang a été étudiée en raison de la capacité de la méthode à représenter des données à valeur positive, ce qui permet de ne pas enfreindre des lois physiques importantes telles que la positivité des fractions de masse d’espèces chimiques et comparée à la PCA. Comme méthodes supervisées alternatives, la combinaison de l’expansion du chaos polynomial (PCE) et du Kriging et l’utilisation de réseaux de neurones artificiels (RNA) ont été testées. Les résultats des travaux susmentionnés ont ouvert la voie au développement d’un jumeau numérique d’un four à combustion à partir d’un ensemble de simulations 3D. La combinaison de PCA et de Kriging a également été utilisée dans le contexte de la quantification de l’incertitude (UQ), en particulier dans le cadre de collaboration de données lié (B2B-DC), qui a conduit à l’introduction de la procédure B2B-DC à commande réduite. Comme pour la première fois, le centre de distribution B2B a été développé en termes de variables latentes et non en termes de variables physiques originales. / With the final objective being to developreduced-order models for combustion applications,unsupervised and supervised machine learningtechniques were tested and combined in the workof the present Thesis for feature extraction and theconstruction of reduced-order models. Thus, the applicationof data-driven techniques for the detection offeatures from turbulent combustion data sets (directnumerical simulation) was investigated on two H2/COflames: a spatially-evolving (DNS1) and a temporallyevolvingjet (DNS2). Methods such as Principal ComponentAnalysis (PCA), Local Principal ComponentAnalysis (LPCA), Non-negative Matrix Factorization(NMF) and Autoencoders were explored for this purpose.It was shown that various factors could affectthe performance of these methods, such as the criteriaemployed for the centering and the scaling of theoriginal data or the choice of the number of dimensionsin the low-rank approximations. A set of guidelineswas presented that can aid the process ofidentifying meaningful physical features from turbulentreactive flows data. Data compression methods suchas Principal Component Analysis (PCA) and variationswere combined with interpolation methods suchas Kriging, for the construction of computationally affordablereduced-order models for the prediction ofthe state of a combustion system for unseen operatingconditions or combinations of model input parametervalues. The methodology was first tested forthe prediction of 1D flames with an increasing numberof input parameters (equivalence ratio, fuel compositionand inlet temperature), with variations of the classicPCA approach, namely constrained PCA and localPCA, being applied to combustion cases for the firsttime in combination with an interpolation technique.The positive outcome of the study led to the applicationof the proposed methodology to 2D flames withtwo input parameters, namely fuel composition andinlet velocity, which produced satisfactory results. Alternativesto the chosen unsupervised and supervisedmethods were also tested on the same 2D data.The use of non-negative matrix factorization (NMF) forlow-rank approximation was investigated because ofthe ability of the method to represent positive-valueddata, which helps the non-violation of important physicallaws such as positivity of chemical species massfractions, and compared to PCA. As alternative supervisedmethods, the combination of polynomial chaosexpansion (PCE) and Kriging and the use of artificialneural networks (ANNs) were tested. Results from thementioned work paved the way for the developmentof a digital twin of a combustion furnace from a setof 3D simulations. The combination of PCA and Krigingwas also employed in the context of uncertaintyquantification (UQ), specifically in the bound-to-bounddata collaboration framework (B2B-DC), which led tothe introduction of the reduced-order B2B-DC procedureas for the first time the B2B-DC was developedin terms of latent variables and not in terms of originalphysical variables.

This work addresses the application of non-premixed filtered tabulated chemistry as a turbulent combustion modeling strategy in the LES framework. On the first part of this study the effects of the filtering operation on non-premixed flamelets are carefully appraised, considering an individual flamelet and the entire manifold. Subsequently, a systematic approach is followed where first the numerical implementation is verified. Afterwards validation is done on a coflow laminar diffusion flame, where promising results encourage the further model appraisal on a more complex turbulent configuration. This is finally achieved under turbulent conditions of Flames D and E, where the formalism including a SGS wrinkling modeling function adequately describes the wrinkled flame front features. The formalism assessment on a laminar coflow diffusion flame reveals a considerable sensitivity to the flame dimensionality. A flame sensor based on the mixture fraction gradient, with a tolerance to take into account the numerical grid resolution, is introduced and proves to deliver satisfactory results. The sensor-determined model activation allows to adequately represent the underlying physics behind flame filtering and so it endorses the consistency of the numerical procedure. The evaluation of the non-premixed FTACLES model on turbulent flames D and E demonstrates that the formalism coupling with a SGS wrinkling modeling function can adequately describe the wrinkled flame front condition. The model performs significantly well employing a three-dimensional tabulation strategy, where the numerical grid is coupled with the model by the third parameter, i.e. the computational cell size. The predictions for both the major stable species and the minor ones accurately correspond with the undergoing physics. The obtained results have a deep theoretical implication for the combustion research. First, they confirm the idea that SGS closure in diffusive combustion can be derived based on filtering arguments, and not only based on statistical approaches. Second, they demonstrate the enormous potential of the non-premixed FTACLES formalism once a sound flame sensor and a SGS wrinkling modeling function are included. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Gas turbine engines are an efficient and flexible way of power generation and aircraft propulsion. Even though different combustion systems can be implemented in these engines, more stringent regulations on pollutant emissions have been imposed throughout the years, especially in regard to nitrogen oxides (NOx). A very promising technology to reduce NOx emissions is lean premixed combustion (LPC), however, it is plagued by intense flame dynamics. Thermoacoustic instabilities, lean blow-off and lean instabilities are examples of dynamical phenomena that are detrimental to the gas turbines. In view of this, the present thesis presents the experimental investigation of the response of lean premixed swirl flames to acoustic perturbations at atmospheric and elevated pressures. The results of this investigation may be used to understand the thermoacoustic instabilities and further could be helpful in their prediction. Moreover, this work addresses the effects of non-thermal plasma discharges on the lean blow-off and stability limits of premixed swirl flames at elevated pressures. For the analysis of the flame response to acoustic fluctuations, the flame transfer functions, the flame dynamics, phase-locked velocity fields, and phase-locked measurements of flame curvature are collected through heat release and velocity fluctuations measurements, phase-locked images of the flame, particle image velocimetry, and planar laser-induced fluorescence, respectively. For the analysis of the effects of plasma discharges on the stability limits, electrical measurements and direct imaging of the flame are performed. The results include the development of an empirical relation based on the laminar burning velocity and on the circulation of the acoustically generated vortex to predict the response of the flame to acoustic fluctuations in different operating conditions. Moreover, the results show that the pressure has a strong impact on the response of lean premixed swirl flames to acoustic oscillations and on the flame-plasma interactions. Therefore, extrapolating results obtained at atmospheric conditions to elevated pressures may result in erroneous conclusions. Furthermore, it is shown that non-thermal plasma discharges can effectively extend the stability limits of lean premixed swirl flames at elevated pressures, underlining the potential of these discharges at conditions relevant for gas turbines.

Pre-Chamber combustion systems are gaining popularity in Internal Combustion Engines (ICE) with the increasing emissions regulations due to their advantages in improving fuel economy by increasing the lean limit and cutting emission, especially NOx. In pre-chamber Combustion, flame jets shoot out from the pre-chamber orifices into the main chamber and generates several ignition points that promote a rapid burn rate of the lean mixture (air-excess ratio (λ) >1) in the main chamber. This work focused on studying two different fuels in the main chamber, lean limit, combustion efficiency (ηc), and emissions. A single-cylinder heavy-duty engine equipped with a narrow throat active pre-chamber was used. Two fuels were tested in the main chamber, Methane (CH4) and Ethanol (C2H5OH), the first fuel is used as a baseline, while keeping the pre-chamber fueled by Methane only. The engine was operated at a fixed speed, intake pressure, and spark-timing. The amount of fuel injected was varied to attain different global λ, then at each global λ; the amount of fuel injected to the Pre-chamber was varied to observe the effect of the pre-chamber λ. Different air intake temperatures were tested to see the effect on combustion efficiency. Results from the study showed an increase in the lean-limit using Ethanol in the main chamber compared to using only Methane in both chambers. However, lower ηc than that of the Methane was reported; this is due to a combination of the narrow-throat feature and the high heat of vaporization of Ethanol, ηc showed improvement when the air intake temperature increased.

Packed bed combustors burn fairly large solid fuel particles within confining walls, with air supplied from below the grate. As combustion occurs and particles are consumed, fresh particles are fed onto the bed so the level is kept roughly constant. Packed bed combustion is used for wood and biomass combustion in small-scale power plants, wood waste combustion in pulp and paper plants, and trash incineration. The structure of a packed bed is very important to the combustion process and can be defined by particle shape and size, sphericity, particle overlap (decreasing area availability) and chiefly by void fraction. Void fraction has already been proven of great influence in packed beds – it is raised to the third power in the pressure loss equation, and it can also affect heat and mass transfer and surface reaction rates. This thesis presents results of several experimental combustion tests that were performed in a packed bed combustor, using commercial spruce lumber particles of parallelepipedal geometry as fuel. At the end of each test the bed contents were removed, taking care to preserve their structure, and fixed with liquefied wax. The solidified bed was then cut into circular cross sections at different heights of the bed, and photographs of the cross sections were taken so the local void fraction could be estimated using image analysis. The bed sampling led to the discovery that, surprisingly, the actual bulk void fraction in the combustor, which is the average of local void fraction measurements, is less than that of the unburnt particles, varying from 19% to 30% in decrease in void fraction depending on the particle type used. Local measurements allowed the development of an empirical linear equation model to represent the variation of void fraction with height above the grate. Each combustion test had measurements of gas volume fractions and temperatures at different heights above the bed grate to be compared with the results of a numerical model simulation. The numerical model used in this work is an existing numerical model of all the relevant processes in packed bed combustion. Previously, the numerical model had assumed the void fraction to be constant and equal to that of the unburnt fuel, since no information on local variation was available, and the packing geometry remained self-similar as particles are consumed. Three models for void fraction were then compared in the combustion model: a constant void equal to that of the unburnt particles, the empirical linear fit of void fraction with height, and a constant void equal to the measured bulk void fraction. Maximum temperatures were higher using the unburnt fuel void fraction because of a thicker oxidation zone, whereas the void fraction model iii based on experiments generated a thicker reduction zone and therefore higher CO concentrations. CO concentrations were experimentally measured and agreed quite well with the CO concentration from the model. Local void fraction differences had the most impact in the diffusion-controlled zone, as shown by comparing the empirical void model and the measured bulk void fraction. How lowering the void fraction can increase gas velocities, heat and mass transfer coefficients, and burning rates is also discussed in this work.

The gas turbine engine is an integral component of the global energy infrastructure and, through widespread use, contributes significantly to the emission of harmful pollutants and greenhouse gases. As such, the research and industrial community have a significant interest in improving the thermal efficiency of these devices. However, after nearly a century of development, modern gas turbine technology is nearing its realizable efficiency limit. Thus, using conventional approaches, including increased compression ratios and turbine inlet temperatures, only small future efficiency gains are available at a high cost. If a significant increase in gas turbine engine efficiency is to be realized, a deviation from this convention is necessary. Pressure gain combustion is a new combustion technology capable of delivering a step increase in gas turbine efficiency by replacing the isobaric combustor found in conventional engines with an isochoric combustor. This modification to the engine's thermodynamic cycle enables the loss in stagnation pressure typical of an isobaric combustor to be replaced with an overall net gain in stagnation pressure across the heat addition process. In this work, a pressure gain combustion technology known as the resonant pulse combustor is studied experimentally and numerically to bridge the gap between lab-scale experiments and practical implementations. First, a functional novel active valve resonant pulse combustor was designed and prototyped, thereby demonstrating naturally aspirated resonant operation with an air inlet valve-driven at a fixed frequency. Then, a series of experimental and numerical studies were carried out to increase the pressure gain performance of the combustor, and the performance and applicability of the active valve resonant pulse combustor concept were then experimental demonstrated in atmospheric conditions with both gaseous and liquid hydrocarbon fuels. Finally, the improved active valve resonant pulse combustor's pressure gain and NOX emissions performance was characterized within a high-pressure shroud in a configuration applicable to gas turbine applications and with varied inlet pressures extending up to 3 bar. This study demonstrates the low NOX capability of the pulse combustor concept and provides insight into how the device's performance may scale with increasing inlet pressure, as would exist in a practical application.

This thesis describes experimental investigation of thermal and combustion phenomena as well as structure for self- propagating combustion synthesis of porous Ni - Ti intermetallic aimed for structural biomedical application. The control parameters for the porosity distribution have been investigated experimentally through varying the preheat temperature, initial porosity, initial elemental particle size, and applied pressure during the fabrication process. Ni and Ti elemental powders are mixed using a 1:1 ratio. The mixture is compressed using several different compression forces to produce cylindrical samples of 1.1 cm diameter and 2-3cm length, with initial porosity ranging from 30% to 40%. The samples are preheated to various initial temperatures and ignited from the top surface such that the flame propagates axially downwards. The combustion reaction is recorded with a motion camera. An infrared sensor is used to record the temperature profile during the combustion process. The samples are then cut using a diamond saw in both longitudinal and transverse directions. Image analysis software is then used to analyze the porosity distribution in each sample.

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